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P53 regulated microRNAs in colorectal cancer
P53 regulierte MicroRNAs in Darmkrebs
Der Medizinischen Fakultät der Friedrich-Alexander-Universität
Erlangen-Nürnberg
zur
Erlangung des Doktorgrades Dr. med.
Vorgelegt von
Mariana Fernanda Cordoba Hansen
aus
Buenos Aires, Argentinien
Als Dissertation genehmigt
von der Medizinischen Fakultät
der Friedrich-Alexander-Universität Erlangen-Nürnberg
Tag der mündlichen Prüfung: 11.11.2014
Vorsitzender des Promotionsorgans:
Prof. Dr. med. Dr. h.c. Jürgen Schüttler
Gutachter/in:
Prof. Dr. rer. nat. Regine Schneider-Stock
Prof. Dr. med. Arndt Hartmann
Acknowledgements
First, I would like to thank Prof. Schneider-Stock for giving me the opportunity
to work at her lab. I appreciate all her contributions of time and ideas to make
my doctoral experience productive and stimulating.
Further, I would like to express my gratitude to Prof. Hartmann, for opening me
the doors to the Institute of Pathology and for always being willing to help me
and answer my questions.
My time at the Experimental Tumor Pathology Department was made
enjoyable in large part due to my nice colleagues. Special thanks to Jelena,
Chirine and Natalya, who have always been ready to orientate me with their
knowledge and shared with me their love for science. Big thanks to Bärbel for
her help with the translation. Hard times turned to be easier thanks to these
girls. I really appreciate their good humor and enthusiasm.
Most of all, I am eternally grateful to my family. To my parents and my sister,
for their love and support. To my three beautiful children: Máximo, Magdalena
and Laurens, for learning me every day the job of my dreams: being their
mother. And specially, thank you to Henrik, my husband. For believe in my
abilities and me. For his optimism and his way to make complicate things look
easier. For his encouragement, that made me try a completely new activity
after many years of exclusive formation and surgical work. For always, no
matter what, be unconditionally there for me.
Contents
List of abbreviations .........................................................................................
List of tables .....................................................................................................
List of figures....................................................................................................
Introduction .................................................................................................... 1
1. Introduction .......................................................................................... 1
1.1.
Colorectal cancer........................................................................... 1
1.2.
Tumor suppressor p53 .................................................................. 3
1.2.1.
Mutation status of p53 ................................................................ 5
1.2.2.
P53 mutations in CRC ................................................................ 7
1.2.3.
Polymorphisms in p53 gene ....................................................... 8
1.3.
K-ras .............................................................................................. 9
1.4.
BRAF ........................................................................................... 11
1.5.
MicroRNAs, novel gene regulatory molecules ............................. 11
1.5.1.
Biogenesis of miRNAs.............................................................. 12
1.5.2.
Oncogenic or tumor-suppressive miRNAs ............................... 14
1.5.3.
P53 and miRNAs ...................................................................... 15
2. Aims of the study................................................................................ 17
Materials and methods................................................................................. 18
3. Materials and methods ....................................................................... 18
3.1.
Samples....................................................................................... 18
3.2.
Equipment ................................................................................... 19
3.3.
Materials ...................................................................................... 19
3.4.
Methods ....................................................................................... 22
3.4.1.
DNA isolation from paraffin embedded sections ...................... 22
3.4.2.
Mutational analysis of p53 ........................................................ 24
3.4.3.
Mutational analysis of K-ras and BRAF .................................... 26
3.4.4.
RNA isolation from paraffin embedded sections ...................... 27
3.4.5.
Reverse transcription ............................................................... 27
3.4.6.
Real-Time Polymerase Chain Reaction (qRT-PCR)................. 28
3.4.7.
Immunohistochemical analysis of p53 (IHC) ............................ 29
Results ......................................................................................................... 30
4. Results ............................................................................................... 30
4.1.
P53 mutations.............................................................................. 30
4.2.
P53 polymorphisms ..................................................................... 33
4.3.
Analysis of p53 mutations in CRC cell lines................................. 34
4.4.
K-ras mutations ........................................................................... 35
4.5.
BRAF mutations .......................................................................... 39
4.6.
Associations with p53 gene mutations ......................................... 41
4.7.
Immunohistochemical staining patterns of p53 ............................ 41
4.8.
MiRNAs ....................................................................................... 45
4.8.1.
MiR-34a .................................................................................... 45
4.8.1.1.
MiR-34a gene mutation associations .................................... 48
4.8.2.
MiR-34b and miR-34c .............................................................. 48
4.8.3.
MiR-192, miR-215 and miR-200c ............................................. 48
Discussion ................................................................................................... 49
5. Discussion .......................................................................................... 49
5.1.
Role of p53 in CRC...................................................................... 49
5.2. The different genotypes of p53 codon 72 polymorphisms have
discrepancies in their biochemical and biological properties ................. 51
5.3.
Addressing the Cell Line Cross-contamination problem .............. 52
5.4.
K-ras gene is a marker of aggressive tumor phenotype .............. 52
5.5. V600E mutations are associated with higher risk of mortality in
CRC ......................................................................................................53
5.6. Simultaneous mutations of p53, K-ras and BRAF: rare but not
impossible ............................................................................................. 54
5.7.
Mutated p53 can be detected by immunostaining ....................... 55
5.8.
MiRNAs induced by p53 .............................................................. 58
5.8.1.
MiR-34 family ........................................................................... 58
5.8.1.1.
5.8.2.
MiR-34a is up-regulated in tumors with wt p53 ..................... 59
MiR-34b and miR-34c are not detectable in CRC samples ...... 61
5.8.3. Other components in the p53 network: miR-192, miR-215 and
miR-200c ............................................................................................... 61
5.8.4.
5.9.
MiRnas, K-ras and BRAF in CRC............................................. 63
Conclusion and outlook ............................................................... 64
6. References ......................................................................................... 67
Abstract ...................................................................................................... 105
Zusammenfassung .................................................................................... 107
Curriculum Vitae ........................................................................................ 109
List of abbreviations
5-FU
µl
µm
µM
ADR
Ago
APC
Arg
Bcl-2
CAC
CDC7
cDNA
CLCC
COX
CRC
Cte
Cth
CYP3A4
DBD
DCC
DNA
DTL
E2F1
EGFR
EMT
FAP
FFPE
Gadd45
GOF
H&E
HMGA2
HNPCC
HPV
IARC
IHC
iNOS
K-ras
MDM2
MDMX
Min
miRNA
Ml
mRNA
MSI
5-Fluoruracil
Microliter/s
Micrometer
micromol/es
Adriamycin
Argonaute
Adenomatous polyposis coli
Arginine
B-cell lymphoma 2
Colitis-associated cancer
Cell division cycle 7-related protein kinase
Complementary Deoxyribonucleic acid
Cell line cross-contamination
Cyclooxygenase
Colorectal cancer
Threshold cycle of the experimental gene
Threshold cycle of the housekeeping gene
Cytochrome p450 3A4
DNA-binding domain
Deleted in colorectal cancer
Deoxyribonucleic acid
Denticleless protein homolog
E2F transcription factor 1
Epidermal Growth Factor Receptor
Epithelial-mesenchymal transition
Familial adenomatous polyposis
Formalin-fixed paraffin-embedded
Growth arrest and DNA-damage inducible protein
Gain-of-function
Hematoxilin and eosin
High-mobility group AT-hook 2
Hereditary non-polyposis colorectal cancer
Human papilloma virus
International Agency for Research on Cancer, World Health
Organisation
Immunohistochemestry
Nitric oxide synthase
Kirsten rat sarcoma viral oncogene homolog
Murine double minute 2
Murine double minute X
Minute/s
Micro ribonucleic acid
Milliliter/s
Messenger ribonucleic acid
Microsatellite instability
MSS
Mut
Ng
P53
PCR
PIG3
Pro
PTEN
Puma
qRT-PCR
RAS
RE
RISC
RNA
RPM
RT
Sec
UTR
Wt
Microsatellite stability
Mutated
Nanogram/s
Tumor protein p53
Polymerase chain reaction
P53-inducible gene 3
Proline
Phosphatase and tensin homolog
P53 upregulated modulator of apoptosis
Real-Time-quantitative-PCR
Rat sarcoma viral oncogene homolog
Responsive element
RNA-induced silencing complex
Ribonucleic acid
Revolutions per minute
Reverse transcription
Second/s
Untranslated region
Wild-type
List of tables
Table 1. Patient clinical characteristics ........................................................ 18
Table 2. Equipment ..................................................................................... 19
Table 3. List of chemicals ............................................................................ 19
Table 4. List of consumables ....................................................................... 20
Table 5. List of commercial kits ................................................................... 20
Table 6. List of antibodies ............................................................................ 21
Table 7. List of primers ................................................................................ 21
Table 8. Detected p53 mutations ................................................................. 31
Table 9. P53 mutations in 5 CRC cell lines ................................................. 34
List of figures
Figure 1: Carcinogenic steps of four types of human colorectal cancer ........ 3
Figure 2: Tumor suppressor p53 and its signaling pathway .......................... 5
Figure 3. MiRNA biogenesis........................................................................ 13
Figure 4. P53 mutational spectrum in this project ....................................... 30
Figure 5. Distribution of the mutations......................................................... 31
Figure 6. Types of p53 mutations ................................................................ 32
Figure 7. Distribution of p53 codon 72 polymorphisms ............................... 33
Figure 8. 3 different genotypes of p53 codon 72 polymorphisms ................ 33
Figure 9. P53 mutations in CRC cell lines ................................................... 35
Figure 10. Percentage of K-ras mutations ................................................... 36
Figure 11. Distribution of K-ras mutations ................................................... 36
Figure 12. K-ras wt ...................................................................................... 37
Figure 13. G12D K-ras mutation ................................................................. 37
Figure 14. G12V K-ras mutation.................................................................. 38
Figure 15. G12S K-ras mutation.................................................................. 38
Figure 16. G12C K-ras mutation ................................................................. 38
Figure 17. G13D K-ras mutation ................................................................. 39
Figure 18. BRAF mutations ......................................................................... 39
Figure 19. BRAF wt ..................................................................................... 40
Figure 20. V600E BRAF mutation ............................................................... 40
Figure 21. Immunohistochemical staining of p53 non-mutated (wt) and
mutated samples.......................................................................................... 42
Figure 22. Relationship between p53 immunohistochemical expression in wt
and p53 mutated samples ............................................................................ 43
Figure 23. Relationship between p53 immunostaining and exon mutations 44
Figure 24. P53 staining patterns ................................................................. 45
Figure 25. Comparison of miR-34a levels in no tumor and tumor p53 wt
samples ....................................................................................................... 46
Figure 26. Comparison of miR-34a levels in no tumor and tumor p53
mutated samples.......................................................................................... 47
Figure 27. Comparison of miR-34a levels in wt and mutated p53 tumor
samples ....................................................................................................... 47
Introduction
1. Introduction
1.1. Colorectal cancer
Colorectal cancer (CRC) is one of the world´s leading cancer diseases and
third leading cause of cancer death worldwide (Erichsen et al. 2013; Karim and
Huso 2013; Lemos et al. 2013). It is considered the second most frequent
cause of cancer related mortality in the Western World (Nielsen et al. 2011).
An estimated 1.2 million new cases and 608.700 deaths have occurred in 2008
(Pamukcu et al. 2013; Seretis et al. 2014). Higher CRC incidence rate was
found in the New Zealand, certain countries in Europe and North America, but
the incidence has considerably increased in the last decades in regions
including Eastern Asia, Eastern Europe, and Spain (Chen et al. 2013). Only
about 5-10% of CRC cases have a defined hereditary background due to two
main diseases, familial adenomatous polyposis (FAP) and hereditary nonpolyposis colorectal cancer (HNPCC) (Jasperson et al. 2010). Most of the
cases seem to occur without a hereditary background, and are related to
environment factors such as smoking, alcohol drinking, physical inactivation,
red and processed meat consumption, high-fat diet and inadequate intake of
fiber (Stratmann et al. 2011). It has been hypothesized that obesity may also
lead to an increased CRC risk, being hyperinsulinemia the proposed
underlying biological mechanism for such association (Aleksandrova et al.,
2012). Other studies have proposed that hyperglycemia could also modulate
the association between obesity and CRC risk (Pais et al. 2009; Ramos-Nino
2013). Inflammatory bowel diseases represent a risk factor for developing
cancer as well (Farraye et al. 2010; Necela et al. 2011). CRC transforms
normal colonic epithelium cells to tumor cells (Lee and Yun 2010). This
transformation involves a multistep process, including genetic end epigenetic
changes, that leads to the activation of oncogenes and inactivation of tumor
suppressor genes in cancer cells (Choong and Tsafnat 2012). At least four
types of human colorectal carcinogenesis have been described: adenomacarcinoma sequence type, HNPCC type, “de novo” type, and colitis-associated
cancer (CAC) type (Okayama et al. 2012; Tanaka 2012). CAC arises from the
background of colitis and DNA injury, which is induced by production of free
1
radicals by the inducible nitric oxide synthase (iNOS) system in the colonic
mucosa with persistent inflammation, followed by p53 mutation and
development of a precancerous lesion, dysplasia (Shaked et al. 2012; Cooks
et al. 2013). The progression of dysplasia into invasive CRC is mediated by
cyclooxygenase- (COX-) 2, iNOS, and different cytokines produced in the
infiltrating inflammatory cells and accumulation of genetic abnormality, such
as a loss of the gene deleted in colorectal cancer (DCC) (Tanaka 2009;
Duman-Scheel 2012). On the other hand, in sporadic CRC (adenomacarcinoma sequence type), are the adenomatous polyposis coli (APC) and Kras genes and microsatellite instability that have been proposed to be hardly
involved in its development (Armaghany et al. 2012). Although it has been
important progress in the diagnosis and therapy of CRC in the last years,
patient’s prognosis is still poor (Li et al. 2013). The molecular mechanisms
underlying the development of cancer are complex and remain generally not
well understood (Kong et al. 2012; Muzes et al. 2012).
2
Figure 1: Carcinogenic steps of four types of human colorectal cancer (Tanaka
2012).
1.2. Tumor suppressor p53
P53, dubbed as the “guardian of the genome”, was the first tumor suppressor
gene to be identified in 1979 (Paskulin et al. 2012). The human p53 gene is
placed on chromosome 17p and consists of 11 exons and 10 introns (Saha et
al. 2013). P53 acts to eliminate and inhibit the proliferation of abnormal cells,
thereby preventing tumor development. Disruption of normal p53 functions is
often a prerequisite for the initiation and/or progression of tumors (Feng et al.
2011). Clinical studies reported that p53 is mutated in approximately 50% of
human cancers and it is estimated that more than 80% of tumors have
dysfunctional p53 signaling (Feng et al. 2011; Pei et al. 2012). MDM2 and
MDMX are two structurally related proteins that play a fundamental role in
down-regulating P53 activity under normal conditions (Gu et al. 2002).
3
P53 responds to a big number of intrinsic and extrinsic stress signals, including
DNA damage, hypoxia, mitotic spindle damage, nutritional starvation and
activation of selected oncogenes (e.g. c-Myc, Ras and E2F-1) (Vogelstein et
al. 2000; Ha and Breuer 2012; Garritano et al. 2013; Liang et al. 2013). These
signals are detected and communicated to p53 via different enzymes that
mediate the modifications of p53 protein, such as phosphorylation, acetylation
and ubiquitination leading to an increase of p53 protein half-life and
consequently to p53 accumulation in cells (Levine et al. 2006). The activated
p53 protein in a stressed cell acquires the ability to bind to specific DNA
sequences, termed p53-responsive elements (RE) adjacent to genes and
enhances the rate of transcription of those genes (Feng et al. 2011; Wang and
Cui 2012). In this way, activated P53 selectively transcribes its target genes to
start various cellular responses (Bieging and Attardi 2012). Depending on the
cell type, environmental context, and the type and/or degree of stress, P53
promotes cell cycle arrest, senescence or apoptosis to prevent the propagation
of damaged or mutant cells that could potentially derive in cancerous cells
(Donehower 2009). For instance, in response to mild stress signals, P53
induces its target genes involved in cell cycle arrest (e.g. p21, Gadd45, and
14-3-3 sigma) and DNA repair (e.g. p48, and p53R2) to permit cells to survive
until the damage has been repaired or stress has been removed . In case of
severe or sustained stress signals, p53 induces genes involved in apoptosis
(e.g. Puma, Bax, Fas, PIG3, and Killer/DR5) and senescence (e.g. p21), and
in this way prevents the accumulation of damaged cells (Suzuki and
Matsubara 2011; Suppiah and Greenman 2013; Liu et al. 2014). Recent
investigation showed that p53 exert additional tumor suppressor functions like
energy metabolism (Puzio-Kuter 2011), antioxidant defense (Sablina et al.
2005) and anti-angiogenesis (Assadian et al. 2012). Moreover, a variety of
negative and positive feedback loops are activated, resulting in turning off p53
regulated functions or enhanced p53 activity (Harris and Levine 2005).
4
Figure 2: Tumor suppressor p53 and its signaling pathway (Liu et al. 2013b).
1.2.1. Mutation status of p53
P53 mutations are one of the most common genetic events in human cancer
(Olivier et al. 2010; Oren and Rotter 2010). As given above, 50% of all tumors
exhibit mutation of p53, but in those that retain wild-type p53, its activity can
be attenuated by several other mechanisms (Kim et al. 2009; Wang et al. 2011;
Zhao et al. 2013). The p53 gene encodes a 393 amino-acid, 53 kDa
phosphoprotein that is divided into 3 domains: an amino (-NH2) terminal
region, a central “core” domain which contains the DNA-binding regions and a
terminal carboxyl (-COOH) region (Brazdova et al. 2002). P53 mutations are
distributed in all coding exons of the gene, with a strong predominance in
exons 4-8, which encode the DNA-binding domain of the protein (Kucab et al.
2010; Rivlin et al. 2011; Suppiah and Greenman 2013). Of the mutations in
this domain, about 30% fall within 6 “hotspot” residues (residues R175, G245,
R248, R249, R273 and R282) (Goh et al. 2011; Rivlin et al. 2011; Eldar et al.
2013). Endogenous mutations frequently arise from spontaneous deamination
of methylated CpG dinucleotides, and interestingly, the codons at 4 of these
hotspot residues contain CpG dinucleotides (Yoon et al. 2001; Freed-Pastor
and Prives 2012). A transition (C to T or G to A) can take place following
deamination of the 5-methylcytosine, and not surprisingly this is exactly the
type of nucleotide change observed at these hotspots (Hussain et al. 2001;
5
Cao et al. 2009a). P53 mutations vary in the frequency with which they occur
in different tumor types, suggesting that environmental mutagens leave their
mark on p53 in a tumor- and tissue- selective manner (Kucab et al. 2010). A
good example of this is the finding that hepatocellular carcinomas in some
developing countries have a much higher frequency of p53-R249S mutations
than other tumor types or liver cancer in developed nations (Aguilar et al. 1993;
Liu and Wu 2010). This mutation has a strong association with exposure to
Aflatoxin B1, a carcinogenic agent present in fungal species (Aspergillus
flavus) and a common contaminant of food supply in areas of sub-Saharan
Africa and Asia (Pineau et al. 2008; Tillett 2010).
Types of p53 mutations
According to the IARC TP53 Database version R17, p53 mutations have the
following distribution: missense (73%), frameshift (9%), nonsense (8%), silent
(4%) and others (6%) (Petitjean et al. 2007; Suppiah and Greenman 2013).
P53 is frequently inactivated by a missense mutation, a single base-pair
substitution that results in the translation of a different amino acid at that
position (Brosh and Rotter 2009). The vast majority of missense mutations are
mapped to the DBD (DNA-binding domain) and usually abolish its sequencespecific DNA-binding activity (Jordan et al. 2010). As mentioned before, over
30% of all missense mutations arise in 1 of 6 “hotspot” codons (Goh et al.
2011).
P53 mutations can also be classified in “DNA contact” or “conformational”
mutants (Bullock and Fersht 2001; Brosh and Rotter 2009). The first group
includes missense mutations in the amino acid residues that normally make
direct contact with target DNA sequences, such as R273H. The second group,
typified by R175H, comprises those missense mutations that disrupt the
structure of the p53 on either a local or global level (Brosh and Rotter 2009;
Lanni et al. 2012). This distinction is important in order to avoid generalizations
about p53. Many mutant p53-binding partners bind with a higher affinity to a
group of tumor derived p53 mutants and it is also accepted that different kind
of p53 mutations are responsible for diverse cancer outcomes (Freed-Pastor
6
and Prives 2012). For example, mutant R248Q, but not R248W, enhances
invasiveness of human lung cancer (Yoshikawa et al. 2010). In breast cancer,
certain missense mutations (R248W and mutations at codon 179) correlate
with significantly poorer prognosis compared with other missense mutations
(Olivier et al. 2006). Thus, as p53 mutational status moves closer to the clinical
practice, it is fundamental to keep in mind that not all p53 mutations are
equivalent (Freed-Pastor and Prives 2012).
1.2.2. P53 mutations in CRC
P53 mutations have been described in about 40 to 50 % of colorectal
carcinomas and affect mainly 5 “hotspots” (Al-Kuraya 2009; Rivlin et al. 2011).
Mutation in codon 175 occurs at a higher frequency in tumors located in the
colon and mutation in codon 288 in exon 8 is more common in rectal tumors
(Naccarati et al. 2012). Mutations involving the most conserved regions of p53
(exons 5-8) are more frequent in tumors located at the distal compared to
proximal colon, suggesting differences in the aetiology of CRC (Iacopetta
2003; Russo et al. 2005b; Sorlie et al. 2005). Also transversion (purine to
pyrimidine) rather than transition (purine to purine, pyrimidine to pyrimidine)
mutations occur more frequently in distal colon tumors. Mutations in colorectal
adenomas are rare (16% versus 40-50% in CRC) meaning that alterations in
the gene represent a late event in adenocarcinoma progression (Naccarati et
al. 2012). Based on multinational data from approximately 9000 colorectal
tumors the most frequent mutations observed have been at codons 175 and
273 (Lea et al. 2009). However, the clinical significance of p53 status related
with survival and response to therapy still remains controversial (Iacopetta et
al. 2006). Up to date, the only reported significant predictors of poor prognosis
are G245 hotspot mutation and mutations in proximal colon tumors (Naccarati
et al. 2012). The effects of p53 status on the response of tumors to
chemotherapy are still being widely investigated. 5-fluorouracil (5-FU) is
commonly used in the treatment of a range of cancers, including CRC (Ju et
al. 2007). P53 can be activated by 5-FU through different mechanisms (Garcia
et al. 2011). Previous investigations reported that CRC patients with wt p53
7
tumors benefit from 5-FU based chemotherapy, while those with mutated gene
tumors do not (Naccarati et al. 2012).
1.2.3. Polymorphisms in p53 gene
In addition to somatic mutations, several polymorphisms in the wild-type p53
gene locus have been reported, which could alter its function and have impact
in the susceptibility to sporadic CRC (Dastjerdi 2011). Theoretically,
polymorphisms may affect p53 protein function through enhanced mutability
due to alter DNA sequence context, increased cryptic splicing events, altered
transcript stability or translation or tissue-specific expression (Petitjean et al.
2007). The most investigated polymorphism is rs1042522, a G to C
transversion in codon 72 of exon 4, which results in an amino acid change from
arginine to proline (Whibley et al. 2009). The TP53 Arg72Pro is located in a
proline-rich region of the protein, which is important for the growth suppression
and apoptotic functions (Naccarati et al. 2012). P53 genotype at codon 72 can
be heterozygous (Arg/Pro) or homozygous for either arginine (Arg/Arg) or
proline (Pro/Pro) (Schneider-Stock et al. 2004). The 2 isoforms of p53 due to
polymorphism at codon 72 have differences in their biochemical and biological
properties, and apparently the protein with Arg72 form induces apoptosis more
efficiently than the Pro72 form (Dumont et al. 2003). Several investigations
have examined the association between the Arg72Pro polymorphism and the
modulation of CRC risk, but results are controversial. Many investigations
reported a strong association of CRC risk with Pro72 allele (Goodman et al.
2006; Perfumo et al. 2006; Cao et al. 2009b; Sameer et al. 2010; Song et al.
2011) while others support an appreciable association between the Arg allele
and CRC (Dastjerdi 2011). In this context, the coexistence of Arg allele and
mutated p53 may be a predictor of increased tumor development due to
inactivation of the apoptosis pathway mediated by p73. Opposite to this,
Arg72allele association with wt p53 might potentially enhance apoptosis
(Godai et al. 2009; Naccarati et al. 2012).
Sharp ethnic differences in codon 72 allele frequencies have been detected
(Thurow et al. 2011). The frequency of Pro72 allele is approximately of 60% in
African Americans and 30-35% in Caucasian Americans (Naccarati et al.
8
2012). Interestingly, the Pro72 allele frequency increases in a North-South
gradient (Beckman et al. 1994). These latitude-dependent variations may be
related to winter temperature and not to UV radiation as suggested by previous
studies (Shi et al. 2009).
1.3. K-ras
K-ras is a proto-oncogene that encodes a small 21-kDA protein (p21Ras)
(Bissonnette et al. 2000; Tan and Du 2012). The Ras protein is activated by
extracellular signals such as growth factors, cytokines, and hormones, which
stimulate cell surface receptors (Adjei 2001). This protein has intrinsic GTPase
activity, permitting inactivation following signal transduction in the normal
cellular environment (Lin et al. 2000). Activating mutations of K-ras occurring
early in colorectal tumorigenesis might abolish GTPase activity, leading to
increased and unregulated cellular proliferation and malignant transformation
(Conlin et al. 2005; Jancik et al. 2010).
In human colorectal carcinomas, K-ras mutations are very common (20-50%)
and about 90% of the activating mutations are found in codons 12 (wild-type
GGT) and 13 (wild-type GGC) of exon 1 identifying these codons as hotspot
mutation points (Poehlmann et al. 2007). Codon 12 harbors circa 80% of these
mutations (Roa et al. 2013). G12D; G12V and G13D represent approximately
86% of the total number of mutations (Neumann et al. 2009; Yokota 2012; Roa
et al. 2013). The most common types of mutations are G->A transitions and
G->T transversions (Russo et al. 2005a).
Several publications have focused on K-ras mutations in CRC. In this context,
the RASCAL study has been conducted with the aim of investigating the
prognostic role of K-ras mutations in CRC progression (Arrington et al. 2012).
The Rascal study was made up on 2 principal collaborative studies. In the first
RASCAL study the mutational status of K-ras was analysed in 2721 patients
collected from 22 centres from 13 different nations. The authors showed that
mutations in the K-ras gene were important for the progression and outcome
of CRC, and that some specific mutations (glycine/valine at codon 12) seemed
to have a prognostic role more important than others (Andreyev et al. 1998).
9
The RASCAL II study analyzed data regarding 3439 cases of CRC collected
from 35 centers from 19 different nations with a follow up of 55 months. 35%
of the cases presented K-ras mutations, 26% of which were in codon 12 and
9% in codon 13. About 9% of the total mutation number showed the
replacement of the amino acid glycine with valine in codon 12. No association
was found between K-ras mutations and other clinicopathological variables like
age, sex, tumor site, type of growth, Dukes stage, histological type, vascular
invasion and, lymphocyte response (Andreyev et al. 2001). The results
obtained from the RASCAL studies express that K-ras mutations might have
an effect on the survival rate of CRC patients, predicting poor patient
prognosis. The specific codon 12 glycine/valine mutation could play a role in
the progression of this neoplasia, leading in this way to a higher risk of disease
relapse or death in 30%. Furthermore, when this mutation is present in Dukes
C tumors, the risk increases to 50% (Russo et al. 2005a).
In 2013 Phipps et al. demonstrated that CRC patients who have a K-ras
mutation have significantly poorer prognosis than those without mutation
(Phipps et al. 2013). Accumulated data suggest that K-ras mutation is a marker
of aggressive tumor phenotype, and therefore detecting this mutation at an
earlier disease may be of importance (Li et al. 2012). This could also have
significance for treatment, as patients with Dukes stage A and B tumors
undergo surgery with curative intent but are not routinely offered adjuvant
therapy. Thus, patients with early stage disease and K-ras mutation may
benefit from an alternative more aggressive treatment regimen (Conlin et al.
2005). On the other hand, knowing the mutational status of K-ras is also
relevant in order to identify those patients who will benefit from anti-EGFRtargeted therapies (Phipps et al. 2013). EGFR inhibitors such as cetuximab or
panitumumab are a successful strategy for the treatment of metastatic CRC in
addition to or after failure of conventional chemotherapy (Neumann et al.
2009). Only CRCs with wild-type K-ras respond to anti-EGFR treatment and
therefore mutation analysis is mandatory prior to the initiation of therapy (Kim
et al. 2014). It has also been suggested that wild-type BRAF is required for a
successful response to those drugs (Yokota 2012).
10
1.4. BRAF
BRAF is an oncogene that encodes a protein kinase involved in intracellular
signaling and cell growth (Hostein et al. 2010; Dienstmann and Tabernero
2011). Evidence suggests that BRAF mutations result in uncontrolled, nongrowth factor-dependent cellular proliferation (Kalady et al. 2012). Activating
mutations of BRAF are found in 10%-20% of CRCs with most (over 95%)
occurring in a hotspot of amino acid position 600 by a missense substitution of
valine by glutamic acid, known as the BRAF V600E mutation (Mao et al. 2012;
Prahallad et al. 2012; Yokota 2012; Kuan et al. 2014). The presence of BRAF
mutations is associated with significantly higher risk of mortality in CRC
patients (Safaee Ardekani et al. 2012). Patients with metastatic CRC with a
BRAF mutation have a very poor prognosis, with median survival of only 10
months, as compared with 35 months for patients with a wild-type BRAF (Mao
et al. 2012). There is a solid association between BRAF mutations and
deficient mismatch repair characterized by microsatellite instability (MSI)
(Calistri et al. 2005). BRAF mutations are found in 30% to 75% of MSI-positive
CRCs, in contrast to K-ras mutations that are more prevalent in MSI-negative
tumors (Vandrovcova et al. 2006; Kuan et al. 2014). Combined BRAF and MSI
subtyping analysis suggests that BRAF-mutated MSS tumor is an unfavorable
subtype, whereas BRAF wild-type MSI-high tumor is a favorable subtype, and
BRAF-mutated MSI-high and BRAF wild-type MSS tumors are intermediate
subtypes (Ogino et al. 2012; Lochhead et al. 2013). The presence of a BRAF
V600E mutation in CRC predicts resistance to anti-EGFR therapy in patients
with K-ras wild-type (Kalady et al. 2012; Kuan et al. 2014). BRAF-mutated CRC
patients do not respond to treatment with cetuximab or panitumumab (Yokota
2012). Finally, a number of inhibitors of the V600E mutant form of the BRAF
protein have been tested, for example vemurafenib (Safaee Ardekani et al.
2012). Vemurafenib achieved very good results in melanoma but
unfortunately, this high response rate have not extended to BRAF mutations
in CRC (Mao et al. 2013).
1.5. MicroRNAs, novel gene regulatory molecules
MicroRNAs (miRNAs) are short, (approximately 18-25 nucleotides), noncoding RNA molecules that regulate gene expression (Gao et al. 2013). They
11
act usually post-transcriptionally by binding to the 3´-untranslated region of
target mRNAs, leading to translational arrest, mRNA cleavage or a
combination of the two (Karaayvaz et al. 2013; Mallick and Ghosh 2012; Wang
et al. 2013a).
Each miRNA can target multiple mRNAs, and, conversely, a single mRNA can
be targeted by multiple miRNAs (Thomson et al. 2011). By targeting multiple
transcripts, miRNAs modulate a wide range of biological processes, including
apoptosis, differentiation and cell proliferation (Wang and Cui 2012).
Since the identification of the first miRNA, lin-4, in the nematode
Caenorhabditis elegans in 1993, thousands of miRNA genes have been
identified in animals and plants genomes (Lee et al. 1993; Raisch et al. 2013).
MiRNas are highly conserved in sequence between distantly related
organisms, indicating their participation in essential biological processes (Pillai
2005). According to the miRBase 2014, 1881 precursors and 2588 mature
miRNAs have been notated, but estimates suggest that their actual number
will keep on increasing (Kozomara and Griffiths-Jones 2014). Taking into
account the fact that each miRNA can regulate approximately the expression
of 100-200 target genes, the whole miRNA apparatus seem to participate in
the control of gene expression for an important proportion of the mammalian
gene complement (Gennarino et al. 2009).
MiRNA have such fundamental biological roles, that it is obvious that its
expression is tightly controlled and its deregulation may lead to various
diseases, including inflammatory disorders and cancer (Coskun et al. 2013; Li
et al. 2013).
1.5.1. Biogenesis of miRNAs
MiRNAs are clustered and located in either the introns of protein-coding genes
or between genes as intergenic miRNAs (Hackler et al. 2010). The miRNA
biogenesis starts in the nucleus, where 100-1000 nucleotides precursormolecules (pri-miRNAs) are synthesized from genomic DNA by the RNA
polymerase II (Ro et al. 2007). The long pri-miRNA is then cleaved by the
12
ribonuclease enzyme Drosha, into shorter, typically 70 nucleotides hairpin
structures known as pre-miRNAs (Felekkis et al. 2010). Pre-miRNAs are
transported into the cytoplasm by Exportin-5 and subsequently undergo further
processing by the endonuclease enzyme Dicer, to liberate a double stranded
mature miRNA, with approximately 22 nucleotides (Wang et al. 2013b; Zhuo
et al. 2013). One strand of the duplex is loaded onto Argonaute (Ago) protein
in order to produce RNA-induced silencing complex (RISC) (Doxakis 2013). It
has been suggested that, whereas all Ago proteins participate in the
stabilization of mature miRNA, only Ago2 (which has endonuclease activity)
cleaves the miRNA strand and activates RISC (Kang et al. 2013). This idea
led to the observation that Ago1 facilitated RISC-mediated translational
repression and Ago2-RISC led to target mRNA cleavage (Gu et al. 2011). The
mature miRNA assembled onto RISC interact through partial sequence
complementarity with the 3´untranslated regions (UTR) of target mRNAs to
bring about translational repression or mRNA degradation (Babalola et al.
2013). The final effect of the mature miRNA is then, the down-regulation of the
expression of the target gene by preventing the production of its protein
product (Mirnezami et al. 2009).
Figure 3. MiRNA biogenesis. MiRNA genes are transcribed into long transcripts
called primary miRNAs (Pri-miRNA) containing multiple stem-loop/hairpin structures.
Pri-miRNAs undergo cleavage by the endonuclease enzyme Drosha to form
approximately 70 nucleotide precursor miRNAs (Pre-miRNA). Pre-miRNAs are
13
actively exported to the cytoplasm by the nucleocytoplasmatic transport factor
Exportin 5, and there undergo further processing to give rise to mature single stranded
miRNAs of about 20-25 nucleotides in length. Mature miRNAs are assembled onto
the RNA-induced silencing complex (RISC) in association with other co-factors, and
interact with complementary sites in the 3’-UTR of target mRNAs to negatively
regulate gene expression through inhibition of translation (Mirnezami et al. 2009).
1.5.2. Oncogenic or tumor-suppressive miRNAs
Abnormal expression of cancer-related miRNAs is characterized by increased
or decreased expression levels compared with their levels in the
corresponding normal tissue (Davis-Dusenbery and Hata 2010). Accumulating
data suggest that some miRNAs may function as oncogenes or tumorsuppressor genes given their inhibition of a variety of tumor-suppressive and
oncogenic mRNAs, respectively (Kong et al. 2012). The miRNAs with
increased expression are thought to function as oncogenes and are called
oncomirs (Marsolier et al. 2013). These oncomirs negatively inhibit tumor
suppressor genes and/or genes controlling cell differentiation or apoptosis,
promoting in this way tumor development (Budhu et al. 2010). On the other
hand, some miRNAs show decreased expression in cancer cells and are
considered as tumor suppressor genes (Grammatikakis et al. 2013). They
usually prevent tumor development by negatively inhibiting oncogenes and/or
genes that regulate differentiation or apoptosis (Zhang et al. 2007).
There are a number of miRNAs that are overexpressed in one type of cancer
and down-regulated in another (Croce 2009). For example, miR-205 is upregulated in lung, bladder and endometrial cancers (Dip et al. 2012; Karaayvaz
et al. 2012; Jiang et al. 2013). Contrarily, it is significantly down-regulated in
prostate and breast cancers (Gandellini et al. 2012; Savad et al. 2012; Liu et
al. 2013; Verdoodt et al. 2013). The action of miRNAs is dependent on their
targets for mRNA, where they can have an oncogenic or a tumor suppressor
function (Hua et al. 2013).
Three distinct mechanisms have been proposed in order to explain how
miRNAs can function as oncogenes or tumor suppressor genes (Melo and
Esteller 2011).
14
1-First, oncogenic miRNAs can express a gain of function in tumors due to
genomic amplifications. This has been clearly demonstrated for the miR-17-92
cluster, whose amplification in B-cell lymphomas stimulates their development
(Olive et al. 2010).
2-Furthermore, tumor suppressive miRNAs could suffer loss of function in
tumors due to chromosomal rearrangements, deletions or mutations (Calin
and Croce 2006; Croce 2009). This has been shown for several miRNAs,
including the let-7 family, whose expression can diminish lung tumorigenesis
through inhibition of oncogenes like the RAS family and HMGA2 (Lambertz et
al. 2010). In particular, let-7 family members are in sites of frequent deletions
in human tumors, and their processing is inhibited by the oncogenic Lin28
proteins (Kumar et al. 2009; Wang et al. 2012). It has been observed that the
expression levels of let-7 were frequently reduced in both in vivo and in vitro
lung cancer studies and that this reduction was significantly associated with
shortened postoperative survival, independently of disease state (Takamizawa
et al. 2004; Esquela-Kerscher et al. 2008).
3-Finally, oncogenes can acquire mutations to remove miRNA-binding sites,
which alter the interaction between the miRNAs and the mRNA targets in
tumors (Ryan et al. 2010). This has been established for HMGA2, whose
translocation promotes lipoma development by releasing the transcript from
let-7-mediated tumor-suppression (Lee and Dutta 2007; Mayr et al. 2007).
1.5.3. P53 and miRNAs
Previous studies have demonstrated that p53 directly regulates some miRNAs,
and this mechanism turns out to be a critical aspect of the p53 function in
regulating cell cycle and cell proliferation (Karaayvaz et al. 2011). P53 induces
the transcription of several miRNAs and promotes the maturation of specific
miRNAs, both of which contribute to the function of p53 in tumor suppression
(Jones and Lal 2012). On the other hand, miRNAs can negatively regulate p53
protein levels and function by direct repressing the expression of p53, or
positively regulate p53 activity and function through the repression of negative
regulators of p53. These findings have shown that miRNAs are important
15
components in the p53 network (Xi et al. 2006; Feng et al. 2011). Among the
p53 induced miRNAs are the miR-34 family, miR-145, miR-107, miR-192, miR215 and miR-200c (Xi et al. 2006; Feng et al. 2011).
16
2. Aims of the study
The p53 signaling pathway is activated in response to many stress signals,
allowing p53 to coordinate programmes that contribute to tumor suppression
(Garritano et al. 2013). Activated p53 executes multiple functions, ranging from
repair of minor damage to cessation of cell-cycle progression, induction of
replicative senescence, and apoptosis (Raver-Shapira et al. 2007). Loss of
p53 function, through mutations in p53 itself or alterations in pathways
signaling to p53, is a common feature in most of human cancers (He et al.
2007). More than 75% of the mutations result in the expression of a p53 protein
that generally has lost the wild-type function (Chang et al. 2007). In addition,
mutant p53 also acquires oncogenic functions that are entirely independent of
wild-type p53 (Muller and Vousden 2013). As a transcription factor, p53
transactivates or represses many protein-encoding genes (Wang and Sun
2010). Recent reports have shown that p53 is also able to regulate the
expression of miRNAs and to promote the maturation of specific miRNAs, both
of which contribute to the function of p53 in tumor suppression (Xi et al. 2006).
On the contrary, miRNAs can negatively regulate p53 protein levels and
function through direct repression of p53 expression, or positively regulate p53
activity and function through the repression of different negative regulators of
p53 (Feng et al. 2011). Many miRNAs are up- or down-regulated, depending
on the existence of p53, what demonstrates that miRNAs are important
components in the p53 network (Shin et al. 2009).
The aim of this study was to address 3 issues:
1. Identification and characterization of the mutational status of p53 in colorectal
cancer and the co-existence of gene mutations in BRAF and K-ras.
2. Correlation between the mutation status and the immunohistochemical
expression pattern of p53 using two different p53 antibodies.
3. Identification and characterization of miRNAs that are regulated by p53, having
special focus on miR-34a.
17
Materials and methods
3. Materials and methods
3.1. Samples
The samples were obtained from the Institute of Pathology, University Hospital
Erlangen. They consisted in formalin-fixed paraffin-embedded (FFPE) tissue
specimens and hematoxylin and eosin (H&E)-stained sections from 55
patients with histologically proven colorectal adenocarcinoma, who had been
resected in 2012 and 2013. From the original 58 cases, 3 were not included in
the study because no tumor was present at the slides. All the sections had a
thickness of 5 µm. Material was obtained by recto-sigma resection,
hemicolectomy or other form of colon resection. Tumor localization within the
colon was defined as proximal (cecum through transverse colon), distal
(splenic flexure, descending, and sigmoid colon) or rectal (rectosigmoid
junction and rectum).
Table 1. Patient clinical characteristics.
Characteristic
No of patients
Age (median (range))
TNM stage
I
II
III
IV
Tumor localization
Proximal
Distal
Rectal
Tumor differentiation
Well
Moderate
Poor
Female
25
69 (35-91)
Male
30
70 (46-89)
Total
55
70 (35-91)
5
7
11
2
6
13
11
0
11
20
22
2
13
0
12
5
3
22
18
3
34
0
16
9
2
20
8
2
36
17
18
3.2. Equipment
Table 2. Equipment.
Product
C1000™ Thermal cycler, CFX96™ Real Time System
Freezer
Company
BioRad, Munich, Germany
Liebherr, Bulle, Switzerland; AEG, Frankfurt
Main, Germany
Fridges
Liebherr, Bulle, Switzerland; AEG, Frankfurt
Main, Germany
HERAEUS Megafuge 16 R
Thermo Scientific, Erlangen, Germany
Ice Machine AF 200
Scotsman, Milan, Italy
Microcentrifuge Galaxy MiniStar
VWR, Darstadt, Germany
HERAEUS Pico17 Centrifuge
Thermo Scientific, Erlangen, Germany
NanoDrop™ ND-1000 Spectrophotometer Peqlab Biotechnologie GmbH, Erlangen,
Germany
Pippetes (Eppendorf research 2,5; 10; 100; Eppendorf, Hamburg, Germany
200; 1000 µl)
Thermomixer comfort 1.5 ml
Eppendorf, Hamburg, Germany
Thermomixer comfort MTP
Eppendorf, Hamburg, Germany
Vortex-Genie 2
Scientific Industries, New York, USA
Savant DANN 120 SpeedVac®
Thermo Scientific, Erlangen, Germany
Concentrator
PCR-Chamber
Bäro Technology, Leichlingen, Germany
VWR Thermocycler
VWR, Darstadt, Germany
SensoQuest labcycler
SensoQuest, Göttingen, Germany
QIAxcel BioCalculator
QIAGEN, Hilden, Germany
PyroMark™ Q24 Vacuum Prep
QIAGEN, Hilden, Germany
Workstation
PyroMark Q24
QIAGEN, Hilden, Germany
3.3. Materials
Table 3. List of chemicals.
Product
TE buffer
Ethanol ≥95,5%
Xylol ROTIPURAN® ≥99%
Roticlear®
LiChrosolv® Water
PyroMark Annealing Buffer
PyroMark Binding Buffer
Streptavidin Sepharose™
High Performance
Company
Illumina, San Diego, USA
Roth, Karlsruhe, Germany
Roth, Karlsruhe, Germany
Roth, Karlsruhe, Germany
Merk, Darmstadt, Germany
Qiagen, Hilden, Germany
Qiagen, Hilden, Germany
GE Healthcare, Freiburg,
Germany
Catalog number
MTED970
5054.4
4436.1
A538.1
115333
979009
979006
17-5113-01
19
Table 4. List of consumables.
Product
0,5 ml Eppendorf safe-lock
reaction tube
1.0 ml Eppendorf safe-lock
reaction tube
2.0 ml Eppendorf safe-lock
reaction tube
1.5 ml Eppendorf DNA LoBind
tube
Filtertips 0.1-10 µL
Filtertips 0-20 µL
Filtertips 0-100 µL
Filtertips 0-200 µL
Filtertips 100-1000 µL
Gloves (SensiCare Ice,
powder free)
Individual PCR tubes™ Low
Tubes Strip; CLR
Multiplate™ PCR plates 96well, clear
Microseal® `B´ seal
24 PCR platte
Feather disposable scalpel
No. 11
Company
Eppendorf, Hamburg,
Germany
Eppendorf, Hamburg,
Germany
Eppendorf, Hamburg,
Germany
Eppendorf, Hamburg,
Germany
Nerbe plus, Winsel/Luhe,
Germany
Nerbe plus, Winsel/Luhe,
Germany
Nerbe plus, Winsel/Luhe,
Germany
Nerbe plus, Winsel/Luhe,
Germany
Nerbe plus, Winsel/Luhe,
Germany
Medline, Kleve, Germany
Catalog number
22363611
Bio-Rad Laboratories, Inc.,
Hercules, USA
Bio-Rad Laboratories, Inc.,
Hercules, USA
Bio-Rad Laboratories, Inc.,
Hercules, USA
Brand, Wertheim, Germany
pfm medical, Köln,
Germany
TLS0801
22363204
22363352
22431021
07-613-7300
07-622-7300
07-642-7300
07-662-7300
07-693-7300
486801
MLL9601
MSB1001
781411
200130011
Table 5. List of commercial kits.
Product
NucleoSpin® Tissue Kit
MinElute™ PCR Purification
Kit
Qiagen Multiplex PCR Kit
PyroMark Gold Q96 Reagent
Kit
RecoverAll™ Total Nucleic
Acid Isolation Kit
miScript II RT Kit
Company
Macherey- Nagel, Düren,
Germany
Qiagen, Hilden, Germany
Catalog number
740.952.250
28006
Qiagen, Hilden, Germany
Qiagen, Hilden, Germany
206143
972804
Ambion, Darmstadt,
Germany
Qiagen, Hilden, Germany
AM1975
218161
20
miScript SYBR Green PCR
Kit
ZytoChem-Plus AP PolymerKit
Qiagen, Hilden, Germany
218075
Zytomed, Berlin, Germany
POLAP-100
Table 6. List of antibodies.
Product
BD PharmigenTM purified Mouse
Anti-p53 clone, Pab 1801
Monoclonal Mouse Anti-Human
p53 Protein Clone DO-7
Company
BD Biosciences,
Heidelberg, Germany
Dako Denmark A/S,
Glostrup, Denmark
Catalog number
554169
M7001
Table 7. List of primers.
Product
P53 4A s_exon_4
P53 4B as_exon_4
P53-exon5 Fwd neu
P53-exon5 Rev neu
P53 6U1 s_exon_6
P53 6L1 as_exon_6
P53 in 6F s_exon_7
P53 7D as_exon_7
P53 8A s_exon_8
P53 8B as_exon_8
Pyro_BRAF_neu F
Pyro _BRAF_neu R
Pyro_BRAF-Seq
Pyro Kras_ s_D0456
Pyro Kras_as_D0457
Sequence
5'-ATC TAC AGT CCC CCT
TGC CG-3'
5'-GCA ACT GAC CGT GCA
AGT CA-3'
5'-CTG CCG TGT TCC AGT
TGC TT-3'
5'-AGC TGC TCA CCA TCG
CTA TCT-3'
5'-ACC ATG AGC GCT GCT
CAG AT-3'
5'-AGT TGC AAA CCA GAC
CTC AGG C-3'
5'-CCT CAT CTT GGG CCT
GTG TTA TC-3'
5'-GAG GCT GGG GCA CAG
CAG GCC AGT G-3'
5'-ACT GCC TCT TGC TTC
TCT TT-3'
5'-AAG TGA ATC TGA GGC
ATA AC-3'
5'-TGA AGA CCT CAC AGT
AAA AAT AGG-3'
5'-Biotin-AAA ATG GAT CCA
GAC AAC TGT TC-3'
5'-GGT GAT TTT GGT CTA
GC-3'
5'-GGC CTG CTG AAA ATG
ACT G-3'
5'-Biotin-AGC TGT ATC GTC
AAG GCA CTC T-3'
Company
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
Metabion, Martinsried,
Germany
21
Pyro Kras_Seq_ D0456
5'-CTT GTG GTA GTT GGA
GC-3'
Metabion, Martinsried,
Germany
3.4. Methods
3.4.1. DNA isolation from paraffin embedded sections
Deparaffination and xylene removing
The tissue corresponding to the area of interest in the slide was removed by
using a scalpel and put it in a tube containing 1,3 ml Roticlear. The tube was
incubated at 37°C for 30 min and then centrifugated for 10 min at 13.300 rpm.
The supernatant was removed and discharged. 1,3 ml ethanol 100% was
added. The tube was centrifugated for 3 min at 13,300 rpm and the
supernatant removed. Another 1,3 ml ethanol 100% were added. The tube was
centrifugated during additional 3 min and the supernatant was carefully
removed. The pellet was dryed in a Speed Vac (drying rate low) for 1,5 min.
Cell lysis and preparation of genomic DNA
The experiments were performed using the NucleoSpin® Tissue Kit
(Macherey-Nagel).
During this experiment, it was firstly performed lysis of the sample, releasing
the DNA from the tissue. The DNA was bounded to the silica membrane
under high salt/ethanolic conditions. The contaminants were washed away
keeping the DNA bounded to the membrane and in the end, the DNA was
eluted in low-salt buffer and was ready to be used for downstream
applications.
200 uL T1 Lysisbuffer was added to the pellet and afterwards, 10 uL
Proteinase K. The tube was incubated at 55°C for 18 hours. When the lysis
was not complete after this incubation time, additional 5 uL Proteinase K were
added and the tube was incubated at the same temperature during 2 hours.
210 uL B3 Lysisbuffer were added and incubated at 70°C for 10 min at 300
rpm. 220 uL ethanol 100% were added. The sample was transferred to the
NucleoSpin® Tissue Column and centrifugated for 2 min at 11,000 x g. The
eluate was discarded and 550 uL BW wash buffer was added to the column,
which was centrifugated for another 2 min at 11,000 x g and the eluate
22
discarded. 600 uL BW wash buffer were incorporated to the column. A
centrifugation of 2 min at 11,000 x g was performed and the eluate discarded.
In order to achieve a better drying, the sample was centrifuged again for 2 min
at 11,000 x g. The column was put in a new fresh tube and 40 uL hot BE elution
buffer (70°C) were added to the column and incubated for 3 min at room
temperature. The sample was centrifugated 2 min at 11,000 x g. Another 40
uL hot BE elution buffer (70°C) were added to the column, followed by an
incubation time of 3 min and a centrifugation of 2 min at 11,000 x g. The
genomic DNA concentration and purity were measured using a NanoDrop
spectrophotometer. The obtained DNA was stored at 4°C.
DNA isolation from cultured cells
The experiment were also performed using the NucleoSpin® Tissue Kit
(Macherey-Nagel).
The cells (up to 107) were resuspended in 200 uL T1 Lysisbuffer. 15 uL
Proteinase K were added and incubated at 56°C for 30 min at 350 rpm. In
order to obtain a better suspension, another 5 uL Proteinase K were added
and 30 minutes incubation at 56°C at 350 rpm performed.
210 uL B3
Lysisbuffer were added and incubated at 70°C for 20 min at 300 rpm. 220 uL
ethanol 100% were added. The sample was transferred to the NucleoSpin®
column and centrifuged for 2 min at 11,000 x g. The eluate was discarded and
550 uL BW wash buffer was added to the column, which was centrifugated for
another 2 min at 11,000 x g and the eluate discarded. 600 uL BW wash buffer
were incorporated to the column. A centrifugation of 2 min at 11,000 x g was
performed and the eluate discarded. In order to achieve a better drying, the
sample was centrifugated again for 2 min at 11,000 x g. The column was put
in a new collection tube and 50 uL hot BE elution buffer (70°C) were added to
the column and incubated for 3 min at room temperature. The sample was
centrifugated 2 min at 11,000 x g. Another 50 uL hot BE elution buffer (70°C)
were added to the column, followed by an incubation time of 3 min and a
centrifugation of 2 min at 11,000 x g. The DNA concentration was measured
by a NanoDrop and it was afterwards stored at 4°C.
23
3.4.2. Mutational analysis of p53
Polymerase Chain Reaction (PCR) amplification
PCR primer pairs (sense and antisense) were designed for the flanking site of
exons 4, 5, 6, 7 and 8 of the p53 gene, in which point mutations have been
reported frequently. The QIAGEN Multiplex PCR Kit (Qiagen) was used to
make the experiment. PCR amplification for each exon was performed in a
final volume of 25 uL containing 1 uL of template DNA and 24 uL of the bellow
described Master Mix.
The Master Mix:
Components
RNase-free water- 10,1
Qiagen Multiplex PCR Master Mix 2,0
Primer Sense 10 uM
Primer Antisense 10 uM- 0,7
Volume/Reaction in µL
10,1
12,5
0,7
0,7
PCR reaction was made in a VWR® Thermal Cycler and the used programs
are the following:
For p53 exon 4
Denaturation
Denaturation
Annealing
Elongation
Elongation
Store at
95°C
95°C
58°C
72°C
72°C
10°C
15 min
20 sec
60 sec
60 sec
7 min
∞
95°C
95°C
62°C
72°C
72°C
10°C
15 min
20 sec
60 sec
60 sec
7 min
∞
35 cycles
For p53 exon 5
Denaturation
Denaturation
Annealing
Elongation
Elongation
Store at
35 cycles
For p53 exon 6 Touchdown
24
Denaturation
Denaturation
Annealing
Elongation
Denaturation
Annealing
Elongation
Denaturation
Annealing
Elongation
Denaturation
Annealing
Elongation
Denaturation
Annealing
Elongation
Elongation
Store at
95°C
95°C
66°C
72°C
95°C
64°C
72°C
95°C
62°C
72°C
95°C
60°C
72°C
95°C
58°C
72°C
72°C
10°C
15 min
20 sec
60 sec
60 sec
20 sec
60 sec
60 sec
20 sec
60 sec
60 sec
20 sec
60 sec
60 sec
20 sec
60 sec
60 sec
7 min
∞
95°C
95°C
64°C
72°C
72°C
10°C
15 min
20 sec
60 sec
60 sec
7 min
∞
95°C
95°C
58°C
72°C
72°C
10°C
15 min
20 sec
60 sec
60 sec
7 min
∞
2 cycles
2 cycles
2 cycles
2 cycles
30 cycles
For p53 exon 7
Denaturation
Denaturation
Annealing
Elongation
Elongation
Store at
35 cycles
For p53 exon 8
Denaturation
Denaturation
Annealing
Elongation
Elongation
Store at
35 cycles
The success of the PCR was verified by capillary electrophoresis using the
QIAxcel system and QIAxcel BioCalculator Software (Qiagen).
DNA purification
The MinElute™ PCR Purification Kit (Qiagen) was used to purify doublestranded DNA fragments from PCR reactions resulting in high end
25
concentrations of DNA. Fragments from 70 bp to 4 kb were purified from
primers, nucleotides, polymerases and salts using MinElute spin columns in a
microcentrifuge.
25 uL of PCR product were used and treated following the instructions of the
MinElute Handbook, page 19-20 (03/2008). The DNA concentration was
measured by a NanoDrop.
DNA sequencing
Sanger sequencing was performed by to different companies: Seqlab and
Source BioScience. The instructions of both laboratories were precisely
followed in order to ship the purified PCR samples and primers in the correct
way.
3.4.3. Mutational analysis of K-ras and BRAF
Polymerase Chain Reaction (PCR) amplification
The experiments were done using the QIAGEN Multiplex PCR Kit (Qiagen) in
a final volume of 25 uL, where 20uL were Master Mix and 5 uL DNA. Negative
and positive controls were represented by HT-29 and HCT-116 samples
respectively, when analyzing K-ras mutations. For BRAF, HT-29 functioned as
the positive control and HCT-116 as the negative one.
The Master Mix:
Components
Volume/Reaction in µL
RNase-free water- 10,1
Qiagen Multiplex PCR Master
Mix 2,0
Primer Sense 10 uM
Primer Antisense 10 uM- 0,7
6,1
12,5
0,7
0,7
Cycling was performed in a VWR® Thermal Cycler as follows:
For K-ras
Denaturation
Denaturation
Annealing
Elongation
Denaturation
Annealing
95°C
94°C
60°C
72°C
72°C
4°C
15 min
60 sec
60 sec
60 sec
10 min
∞
35 cycles
26
For BRAF
Denaturation
Denaturation
Annealing
Elongation
Denaturation
Annealing
95°C
95°C
61°C
72°C
72°C
4°C
15 min
30 sec
30 sec
30 sec
5 min
∞
42 cycles
Successful amplification was verified by capillary electrophoresis using the
QIAxcel system and QIAxcel BioCalculator Software (Qiagen).
Pyrosequencing
Single-stranded DNA templates for pyrosequencing were obtained with the
assistance of the PyroMark Q24 Vacuum Prep Workstation (Qiagen)
according to manufacturer´s instructions. Briefly, 10 uL of the PCR product
were immobilized on streptavidin-coated Sepharose high-performance beads
(GE Healthcare) and processed to obtain single-stranded DNA. This DNA
template was then incubated with 25 uL sequencing primer mix on the heat
block at 80°C for 2 minutes. Pyrosequencing was performed on a PyroMark
Q24 system using software version 2.0.6, and PyroMark Gold Q96 Reagent
Kit (Qiagen) following the manufacturer´s guidelines.
3.4.4. RNA isolation from paraffin embedded sections
To extract FFPE-RNA, the RecoverAll™ Total Nucleic Acid Isolation Kit
(Ambion) was used following the RecoverAll™ Total Nucleic Acid Isolation
protocol, page 8-14 (02/2011). The samples were deparaffinized using a series
of xylene and ethanol washes. Next, they were subjected to an extensive
protease digestion (200 uL Digestion Buffer per sample was added) with an
incubation time of 60 min at 50°C and then 15 min at 80°C. RNA was then
purified using a rapid glass-filter method, and was eluted into Elution Solution.
The RNA was measured by a NanoDrop and stored at -20°C.
3.4.5. Reverse transcription
RNA was converted with the miScript II RT Kit (Qiagen) according to the
miScript PCR System Handbook, page 19-20 (10/2011). The 5x miScript
27
HiSpec Buffer was used (only mature miRNA quantification was executed).
0,25 ug RNA were used and filled up with nuclease free water up to 12 uL.
From the below described Master Mix, 8 uL were added to the diluted RNA.
The samples were mixed, briefly centrifugated and incubated at 37°C for 60
min. To inactivate the reverse transcriptase the samples were incubated at
95°C for 5 min. The obtained cDNA was stored at -20°C.
The Master Mix:
Components
5x miScript Buffer
10x miScript Nucleic Mix
miScript Reverse Transcriptase Mix
Volume/Reaction in µL
4
2
2
3.4.6. Real-Time Polymerase Chain Reaction (qRT-PCR)
The experiments were done according to the miScript PCR System Handbook,
page 22-24 (10/2011) using the miScript SYBR® Green PCR Kit (Qiagen). The
cDNA concentration was measured and afterwards diluted to a 3ng/uL
concentration by adding RNase-free water.
As housekeeping gene RNU6 was used. Triplicates of each sample were
made. The Master Mix was added to the cDNA (see below). Triplicates “not
template” controls were run. The plated was sealed and centrifuged for 1 min
at 1000g at 23°C.
Components
2x QuantiTect SYBR Green PCR Master Mix
10x miScript Universal Primer
10x miScript Primer Assay
RNase-free water
cDNA
Volume/Reaction in µL
12,5
2,5
2,5
6,5
1
The experiments were run on the C1000™ Thermal Cycler CFX96 realtime
PCR system (Bio-Rad).
The following program was used:
PCR initial activation
step
Denaturation
Annealing
95°C
94°C
55°C
15 min
15 sec
30 sec
40 cycles
28
Extension
70°C
30 sec
Melting curve: 65°C to 95°C. Increment 0,5°C.
Slow Ramp Rate: 1°C per sec.
The obtained data was analyzed with the help of the CFX Manager™ software
from Bio-Rad. The melting curve was observed and the fold induction was
calculated. The used formula is the following:
2(Cth / Cte) / 2(Cch / Cce)
Cth = threshold cycle of the housekeeping gene
Cte = threshold cycle of the experimental gene
3.4.7. Immunohistochemical analysis of p53 (IHC)
Immunohistochemistry was executed using 2 different p53 antibodies:
Monoclonal Mouse Anti-human p53 Protein Clone DO-7 from DAKO and BD
PharmigenTM purified Mouse Anti-p53 clone, PAb 1801. Staining with the
second p53 antibody was performed on FFPE representative tumor tissue
from all 55 carcinomas using the ZytoChem-Plus AP Polymer-Kit from
Zytomed. Briefly, slides were deparaffinised, rehydratet and heated in EDTA
buffer. Background staining caused by unspecific binding of the primary
antibody to the secondary antibody in the AP polymer was minimized by
incubation of the slides with a protein blocking solution. The sections were
afterwards incubated with a 1:2000 dilution of the p53 antibody at room
temperature overnight. After washing, enhancement reagent was applied and
incubated. A second washing was followed by the application of the APpolymer. After incubation and washing, chromogenic substrate was added in
order to start the enzymatic reaction of the alkaline phosphatase which leads
to colour precipitation where the primary antibody is bound.
29
Results
4. Results
This project can be divided in 2 principal parts. Basically, in the first part,
mutations in p53 protein, in K-ras and BRAF were analyzed. In the second
part, miRNAs induced by P53 were evaluated. The statistical analysis was
performed using IBM SPSS Statistics 19v (SPSS Inc., Chicago, IL, USA).
4.1. P53 mutations
From a total of 55 cases, 23 presented mutations in exons 4,5,6,7 or 8 (41,8%).
mutated
41,8%
wt
58,2%
Figure 4. P53 mutational spectrum in this project.
3 mutations were found in exon 4 (13%), 6 in exon 5 (26,1%), 4 in exon 6
(17,4%), 6 in exon 7 (26,1%), and 4 in exon 8 (17,4%).
30
exon 8
17,4%
exon 4
13%
exon 5
26,1%
exon 7
26,1%
exon 6
17,4%
Figure 5. Distribution of the mutations.
There were 18 missense mutations, 3 frameshift mutations and 2 nonsense
mutations (stop mutations). 7 mutations occurred at known hot-spot codons (1
at codon 175, 2 at codon 245, 3 at codon 248 and 1 at codon 273). One sample
presented a double mutation (R273H and R213stop) and was obtained from a
46 year old male patient, who had a moderately differentiated sigma
adenocarcinoma, TNM stage II.
The location and the frequency of p53 are reported in Table 1. Representative
DNA sequences are shown in Figure 2.
Table 8. Detected p53 mutations.
Nr. of
Mutations
Exon
1
4
1
4
1
4
3
5
1
5
1
5
1
5
1
6
1
6
Detail
P89L
R110L
A83Frameshift
A159V
G154S
R175H
C176S
R196stop
N200K
31
1
1
1
2
1
2
1
1
1
1
A
6
6
7
7
7
7
8
8
8
8
Y205S
R213stop
S240R
G245S
R248Q
R248W
L264Frameshift
G266E
R273Frameshift
G281Y
B
32
C
Figure 6. Types of p53 mutations. A-Example of missense mutation. Exon 5 codon
175, sense sequencing, CGC (Arg) to CAC (His). B- Example of stop mutation.
Exon 6 codon 213, sense sequencing, CGA (Arg) to TGA (Stop). C- Example of
frameshift mutation. Exon 4 codon 83, sense sequencing, 11 bp deletion. In the box
below, representative parts of the normal and mutated sequences are described.
Normal sequence
Mutated sequence
CCG GCG GCC CCT GCA CCA GCC
CCG ACC AGC CCC CTC CTG GCC
No significant associations between P53 mutations and clinicopathological
features like age, sex, TNM stage, tumor localization and tumor differentiation
were observed.
32
4.2. P53 polymorphisms
The genotype distribution of p53 codon 72 polymorphisms showed 65,4% (36
cases), 27,3% (15 cases) and 7,3% (4 cases) for the Arg/Arg (R), Arg/Pro (RP)
and Pro/Pro (P) genotypes respectively.
RP
27,3%
R
65,4%
P
7,3%
Figure 7. Distribution of p53 codon 72 polymorphisms.
A
B
C
Figure 8. 3 different genotypes of p53 codon 72 polymorphisms. A- Arg/Arg (R)
genotype. Sense sequencing, CGC (Arg)/CGC (Arg); B- Arg/Pro (RP) genotype.
33
Antisense sequencing, CGC (Arg)/CCC (Pro); C- Pro/Pro (P) genotype. Antisense
sequencing, CCC (Pro)/CCC (Pro).
4.3. Analysis of p53 mutations in CRC cell lines
In this project, the p53 status of 5 CRC cell lines used at the lab was tested by
DNA sequencing. All of them showed the expected mutation for each cell line.
Table 9. P53 mutations in 5 CRC cell lines.
Mutation
type
Point
mutation
Point
mutation
Point
mutation
Point
mutation
Point
mutation
Cell
line
Location
Exon 6 codon
204
Exon 7 codon
SW837
248
Exon 7 codon
DLD1
241
Exon 8 codon
SW480
273
Exon 8 codon
HT29
273
CACO2
Mutation
effect
Glu to Stop
Arg to Trp
Ser to Phe
Arg to His
Arg to His
34
A
B
C
D
E
Figure 9. P53 mutations in CRC cell lines. A- CACO2 cell line, sense sequencing.
Exon 6 codon 204, GAG (Glu) to TAG (Stop). B- SW837 cell line, antisense
sequencing. Exon 7 codon 248, CGG (Arg) to TGG (Trp). C- DLD1 cell line,
antisense sequencing. Exon 7 codon 241, TCC (Ser) to TTC (Phe). D- SW480 cell
line, antisense sequencing. Exon 8 codon 273, CGT (Arg) to CAT (His). E- HT29
cell line, antisense sequencing. Exon 8 codon 273, CGT (Arg) to CAT (His).
4.4. K-ras mutations
The results revealed that 16 cases had K-ras mutations (29,1%). There were
11 cases of codon 12 mutation (68,8%) and 5 cases of codon 13 mutation
(31,3%).
35
mutated
29,1%
wt
70,9%
Figure 10. Percentage of K-ras mutations.
The most common mutation was glycine to aspartate on codon 12 (G12D)
(31,3%). Other founded mutations of codon 12 were glycine to valine (G12V)
(18,8%), glycine to serine (G12S) (12,5%) and glycine to cysteine (G12C)
(6,3%). On codon 13, only glycine to aspartate mutations were detected
(G13D) (31,3%).
G13D
31,3%
G12C
6,3%
G12S
12,5%
G12D
31,3%
G12V
18,8%
Figure 11. Distribution of K-ras mutations.
36
Examples of K-ras wt and different types of mutations.
Figure 12. K-ras wt, GGT (Gly).
Figure 13. G12D K-ras mutation, GGT (Gly)/GAT (Asp).
37
Figure 14. G12V K-ras mutation, GGT (Gly)/GTT (Val).
Figure 15. G12S K-ras mutation, GTT (Gly)/AGT (Ser).
Figure 16. G12C K-ras mutation, GGT (Gly)/TGT (Cys).
38
Figure 17. G13D K-ras mutation, GGC (Gly)/GAC (Asp).
K-ras mutations were not significantly associated with clinicopathological
factors like age, sex, TNM stage, tumor localization and tumor differentiation.
4.5. BRAF mutations
8 BRAF mutations have been identified (14,5%), being all of them a
substitution of glutamic acid for valine at amino acid 600 (V600E).
mutated
14,5%
wt
85,5%
Figure 18. BRAF mutations.
39
Examples of BRAF wt and mutated.
Figure 19. BRAF wt, GTG (Val).
Figure 20. V600E BRAF mutation, GTG (Val)/GAG (Glu).
The BRAF mutation status was correlated with patients’ clinicopathological
data using the Chi-squared test. P <0,05 was considered to be statistically
significant. Significant associations were found between BRAF mutations and
sex (P=0,022) and tumor localization (P=0,006). 7 from the 8 patients
presenting BRAF mutations were women (87,5%). The majority of the BRAF
mutations (87,5%) had proximal localization and 12,5% had rectal localization.
No one presented distal localization.
40
BRAF mutated samples corresponded in most of the cases to old patients (55,
59, 68, 73, 74, 88, 89 and 90 years old). No correlation was found between
BRAF mutations and TNM stage and tumor grade.
4.6. Associations with p53 gene mutations
From the total 55 cases, P53 mutation associated with K-ras mutation was
present in 3 patients (5,5%) distributed in exon 4, 7 and 8, and with BRAF also
in 3 cases (5,5%) located in exon 5, 6 and 7.
K-ras and BRAF were found simultaneously mutated in 1 case (1,8%).
Interestingly, this patient presented also a silent mutation in exon 8 of p53
(L264L).
Simultaneous
association
between
p53
mutations
and
p53
R72P
polymorphisms were seen in 16 cases (44,4%) presenting R72, 4 cases
(26,7%) with R72P and 3 cases (75%) with P72.
The Arg/Arg homozygous genotype was associated with K-ras mutations in 10
cases (27,8%) and with BRAF mutations in 4 (11,1%). The Pro/Pro
homozygous was related with K-ras mutations in 1 case (25%) and with BRAF
mutations in 2 (50%). Finally, the p53 Pro/Arg heterozygous genotype was
found 5 times (33,3%) in combination with K-ras and 2 times with BRAF
(13,3%).
4.7. Immunohistochemical staining patterns of p53
Immunochemistry was performed using 2 different p53 antibodies: Monoclonal
Mouse Anti-human p53 Protein Clone DO-7 from DAKO and, BD PharmigenTM
purified Mouse Anti-p53 clone, PAb 1801.
With the first antibody (DAKO), positive p53 staining patterns were seen in
60% of the mutated p53 samples and in 58,3% of the wt p53 specimens.
With the second antibody (BD PharmigenTM), positive p53 immunostaining was
observed in 18 from the 23 samples presenting p53 mutations (78,3%). Only
5 mutated cases (21,7%) presented negative staining, corresponding to 1
frameshift mutations in exon 4, 2 frameshift mutations in exon 8, 1 stop
41
mutation in exon 6 and a D281Y mutation in exon 8. In the wild type group,
negative p53 staining was seen in 71,9% of the samples. The results
presented from this point on, refer to the second p53 antibody.
Figure 21. Immunohistochemical staining of p53 non-mutated (wt) and mutated
samples. Localization and details of the mutation in mutated samples with negative
staining pattern: sample A (exon 8 D281Y); sample B (exon 6 R196 stop); sample
C (exon 4 frameshift); sample D (exon 8 frameshift); sample E (exon 8 frameshift).
The association between p53 mutations and the immunohistochemical p53
protein expression was analysed performing the T-test. P <0,05 was
considered to be statistically significant. A significant correlation between them
was found (P=0,001).
42
Figure 22. Relationship between p53 immunohistochemical expression in wt and
p53 mutated samples (p53 wt samples: (,00), p53 mutated samples: (1,00)).
The analysis of the grade of expression of p53 related to the mutated exon
revealed that the highest percentage of positive tumor cell nuclei were found
in samples that harboured mutations in exon 5 and 7.
43
Figure 23. Relationship between p53 immunostaining and exon mutations (wt:
(,00), mutated exons: (4,00, 5,00, 6,00, 7,00 and 8,00).
44
Figure 24. P53 staining patterns. Positive (A and B), and negative (C and D)
immunohistochemical p53 staining patterns. Pictures A (magnification x50) and B
(magnification x400) correspond to a sample harbouring a G245S mutation in exon
7 of p53. The grade of immunostaining was estimated to be 90%. Pictures C
(magnification x50) and D (magnification x400) represent a sample with wt p53. The
staining grade is 0 (there are no p53 positive tumor nuclei).
In all the positive stainings the intensity was high, distributed between 54 cases
(98,2%) with strong staining (3+) and only one case (1,8%) of moderate
staining (2+).
No correlation was found between p53 immunohistochemistry and Kras/BRAF mutations. In the same way, no correlation has been seen between
p53 IHC and the patients’ clinical data including sex, TNM stage, tumor
localization and tumor differentiation.
4.8. MiRNAs
4.8.1. MiR-34a
The levels of miR-34a in 10 histologically normal and 10 colorectal cancer
samples with p53 wt, as determined by qRT-PCR revealed that miR-34a was
45
significantly up regulated in the colon cancer group. Only 1 sample did not
present up-regulation.
Figure 25. Comparison of miR-34a levels in no tumor and tumor p53 wt samples.
In addition, miR-34a levels were analyzed comparing 2 groups of 15 samples
each: one composed by histological normal (no tumor) tissues, and the other
one represented by their counterpart tumors harbouring mutations in p53
protein. Many of the samples in the p53 mutated tumor group presented downregulation of miR-34a or the same expression level as in the no tumor group,
what leads to the conclusion that in the cancer group the regulation is lost.
46
Figure 26. Comparison of miR-34a levels in no tumor and tumor p53 mutated
samples.
The expression of miR-34a in the whole set of tumor samples was evaluated
by dividing them in wt p53 and mutated p53. The comparison showed no
significant differences in the expression level of miR-34a between the 2
groups.
Figure 27. Comparison of miR-34a levels in wt and mutated p53 tumor samples.
47
4.8.1.1. MiR-34a gene mutation associations
The correlation between the expression of miR-34a and the p53 codon 72
polymorphisms was analyzed in the 55 samples, and there was found that the
highest expression level of the miRNA was present in association with the
Arg/Arg genotype.
No association was observed between miR-34a and K-ras/BRAF mutations.
No relationship was found between miR-34a and the immunohistochemical
staining patterns of p53, as well as no correlation was observed between miR34a and the clinical data.
4.8.2. MiR-34b and miR-34c
MiR-34b and miR-34c were also tested using qRT-PCR but no expression was
observed.
4.8.3. MiR-192, miR-215 and miR-200c
The samples were amplifiable but no differences in the expression of miR-192,
miR-215 and miR-200c between samples with wt p53 and mutated p53 were
found.
48
Discussion
5. Discussion
5.1. Role of p53 in CRC
In somatic cells, p53 has a fundamental role in translating stress signals into
classical processes such as apoptosis, cell cycle arrest, DNA repair and
senescense, contributing to its main role as the “guardian of the genome”
(Lane 1992; Aloni-Grinstein et al. 2014). P53 eliminates and inhibits the
proliferation of abnormal cells, preventing tumor development and progression
(Kim et al. 2009; Feng et al. 2011). Mutations or deletions in p53 are seen in
approximately half of all human cancers. (Touqan et al. 2013). In this study,
one of the principal aims has been to analyze the incidence of mutations of
p53 protein in patients with colorectal cancer. In this connection, 41,8% of the
studied tumors exhibited p53 mutations. This value is in concordance with the
average percentage presented in the literature, described to be between 40
and 50 % (Naccarati et al. 2012).
Research showed that p53 mutations are distributed in all coding exons of the
gene, with a strong predominance in exons 4, 5, 6, 7, 8, and 9. About 30% of
the mutations in these exons fall within 6 hotspot codons (175, 245,248,
249,273, and 282) (Rivlin et al. 2011). The general distribution of p53
mutational hotspots in exons 4-8 in this study showed the most common
hotspots at codons 159 (13%), 248 (13%) and 245 (8,7%). The high frequency
of mutations in codons 248 and 245 is comparable to the distribution pattern
of p53 mutation hotspots in CRC in the International Agency for Research on
Cancer TP53 mutation database (IARC TP53, version R17, November 2013).
3 mutations were present at codon 159. This codon is not described as a hotspot codon in the up-to-date published literature. Among the detected p53
mutations, 2 fall within other known hot-spots: 1 in codon 175 and 1 in codon
273 (Petitjean et al. 2007).
Unlike most tumor suppressor genes, which are basically inactivated as a
result of deletion or truncation, most of cancer-associated mutations in p53 are
missense mutations, single base-pair substitutions that result in the translation
of a different amino acid (Freed-Pastor and Prives 2012). Concordantly with
49
this, the majority of the p53 mutations identified in this work were missense
(78,3%) but also 3 frameshift (13%) and 2 nonsense mutations (8,7%) were
observed. While wild-type p53 under normal conditions is a very short-lived
protein, missense mutations lead to the production of a protein with a
prolonged half-life (Strano et al. 2007). Many of these stable mutant forms of
p53 can exert a dominant-negative effect on the remaining wild-type allele,
serving to annul the ability of wild-type p53 to inhibit cellular transformation.
While inactivating missense mutations in p53 may be selected for during tumor
progression due to their ability to act as dominant-negative inhibitors of wildtype p53, there is also strong evidence that mutant p53 can exert oncogenic
or gain-of-function (GOF) activity independent of its effects on wild-type p53
(Freed-Pastor and Prives 2012). Mutp53 GOF is expressed through several
biological manifestations. In this regard, mutp53 has the ability to disrupt
mechanisms that maintain cellular genome integrity, for example, mutated p53
can disrupt normal spindle checkpoint control, leading to accumulation of cells
with polyploid genomes (Oren and Rotter 2010). Mutp53 has also the ability to
confer on cells an elevated resistance to a variety of pro-apoptotic signals,
which may not only accelerate tumor progression but also hinder the response
of cancer patients to anticancer therapy (Kim et al. 2009). Increased tumor
aggressiveness and higher metastatic potential are also hallmarks of mutp53
GOF. These advanced stages in tumor progression are characterized by
acquisition of an ability of the cancer cells to invade adjacent tissue, migrate
to distant sites, and seed metastases (Kang et al. 2013). P53 missense
mutations display different patterns and strengths of GOF activity in human
cancers. Previous research have demonstrated that mice carrying mutations
equivalent to human R175H and R273H showed no difference in survival time
as compared with null mutation, although a broader tumor spectrum was
observed (Lang et al. 2004; Olive et al. 2004). Recently, Xu et al. demonstrated
that p53 mutations on R248 and R282 could regulate the expression of
CYP3A4, which is one of the most important enzymes involved in the
metabolism of chemotherapeutic drugs. Cancer cells bearing p53 R248/R282
mutations
displayed
resistance
to
multiple
CYP3A4-metabolized
antineoplastic drugs. These findings show that R248/R282 mutations may lead
to chemoresistance, suggesting that certain types of p53 mutations have
50
unequal prognostic significance in human cancers (Xu et al. 2014). Some CRC
studies have reported that somatic mutations in p53 are associated with poor
prognosis, while other studies failed to show such a relationship (Naccarati et
al. 2012). Until today, only mutation in the G245 hotspot and mutations in
proximal tumors are related to significantly worse survival (Samowitz et al.
2002). In this project, 3 mutations of codon 248 and 2 mutation of codon 245
were found. The 3 patients carrying mutations of codon 248 were old women
(70, 73 and 79 year old) with TNM stage III. The first and second woman had
a proximal tumor and the third one, a distal tumor. The tumor differentiation
was described as moderate, poor and moderate respectively. The 2 patients
with codon 245 mutations were a 86 year old woman and a 45 year old man,
with distal, moderately differentiated tumors. The TNM stage was II and III
respectively.
5.2. The different genotypes of p53 codon 72 polymorphisms have
discrepancies in their biochemical and biological properties
P53 polymorphisms at codon 72 (Arg72Pro) have been associated with
increased risk for many human cancers (Whibley et al. 2009). This
polymorphism produces 2 different proteins because of a single base change
modifying CGC to CCC in exon 4 of the p53 gene, altering amino acid residue
72 from Arg to Pro (Schneider-Stock et al. 2004). In this study, the genotype
distribution of p53 codon 72 polymorphisms showed 65,4%, 27,3% and 7,3%
for the Arg/Arg, Arg/Pro and Pro/Pro genotypes respectively. It is now
accepted, that Arg/Arg genotype induces apoptosis with faster kinetics and
suppresses transformation in a more efficient way than Pro/Pro (Dumont et al.
2003). During the last years, the role of the Arg/Pro polymorphism in CRC
susceptibility has been examined in several investigations, which reported
controversial results (Perez et al. 2006). Although this lack of consensus
between studies, the majority of them support an appreciable association
between the Arg allele and colorectal cancer (Dastjerdi 2011). The
simultaneous presence of Arg allele in mutated form of p53 may serve as a
predictor of increased tumor development due to inactivation of the apoptosis
pathway mediated by p73. On the other hand, Arg72 allele over wild type p53
background might potentially enhance apoptotic ability (Godai et al. 2009;
51
Naccarati et al. 2012). In this project, a concomitant presence of p53 mutation
and Arg allele has been seen in 16 cases (69,6%).
5.3. Addressing the Cell Line Cross-contamination problem
During this study, the p53 mutation status of 5 different CRC cell lines used
frequently at the laboratory was checked. After DNA sequencing, it was
possible to infer that all of them presented the expected mutation for each cell
line (Liu and Bodmer 2006). Cancer cell lines are essential tools used in many
areas of biomedical research (Kniss and Summerfield 2014). They can be
used for drug screening, for production of various macromolecules, for
modelling human tumors or as biological test tubes for a variety of experiments
(Ahmed et al. 2013). Existing data show that cross-contaminated and
misidentified cell lines are still a silent and neglected danger and that extreme
care should be taken as a wrong p53 status could lead to disastrous
experimental interpretations (Berglind et al. 2008; Ahmed et al. 2013). A recent
study indicates a CLCC of 18% at a German cell line repository (Berglind et al.
2008). To reduce this risk, the identity of each individual cell line used in the
experiments should be verified and matched to external resources (CapesDavis et al. 2013; Somaschini et al. 2013).
5.4. K-ras gene is a marker of aggressive tumor phenotype
K-ras is an oncogene that regulates cell proliferation, differentiation, and
apoptosis and it is one of the first genes proposed to be involved in CRC
development (Kosmidou et al. 2014). Mutations in K-ras are found mostly in
codons 12 and 13 of exon 1, and its frequency in CRC ranges from 20-50%
depending on the study and the sample source (Poehlmann et al. 2007).
Additional more rare mutations occur at smaller frequencies, ranging from 1%
to 4% in CRC and involve codons 61, 117 and 146 (de Macedo et al. 2014). In
the present study, K-ras mutation status was evaluated by performing PCR
and subsequent pyrosequencing. This analysis revealed that 16 of the 55
tested tumors, carried a K-ras mutation (29,1%). The frequencies of mutations
at codon 12 and 13 were 68,8% and 31,3% respectively, which support
findings previously reported in the literature (Andreyev et al. 2001; Roa et al.
52
2013; Wangefjord et al. 2013; Tong et al. 2014). No sample harboured double
mutations involving both codons 12 and 13. Mutations in other codons were
not analyzed. The most abundant mutation of codon 12 was G12D, followed
by G12V, G12S and G12C while G13D was the predominant mutation in codon
13. Also these results are in concordance with several previous studies
(Neumann et al. 2009; Yokota 2012).
No significant associations were found between K-ras mutation status and
clinicopathological variables like sex, age, TNM stage, tumor site and
differentiation grad, which agrees with the results presented in other
investigations (Andreyev et al. 2001; Wangefjord et al. 2013).
K-ras mutations in CRC are associated with significantly poorer prognosis, like
Phipps et al. demonstrated in their research in 2013. Accumulated data
suggest that mutation of the K-ras gene is a marker of aggressive tumor
phenotype, and therefore detecting this mutation at an earlier disease may be
of relevance in planning individual cancer therapies (Li et al. 2012). Generally,
patients with CRC Dukes A or B undergo surgery with curative intent but are
not routinely offered adjuvant therapy. If these patients with early stage
disease carry a K-ras mutation, they might benefit from an alternative more
aggressive treatment regime (Conlin et al. 2005). On the contrary, in patients
with advanced, metastatic CRC, the mutational status of K-ras serves to
identify which patients in this group would be offered anti-EGFR treatment,
because only CRCs with wild-type may benefit from it (Kim et al. 2014b). As
exposed, both patients with early disease and the ones with advanced CRC
seem to be good candidates for the routine analysis of the K-ras mutation
status.
5.5. V600E mutations are associated with higher risk of mortality in
CRC
BRAF is another oncogene and it is mutated in up to 70 % of cancer cell lines
(Safaee Ardekani et al. 2012). Activating mutations of BRAF are found in 10%20% of CRCs, with most (over 95%) occurring in a hotspot of amino acid
position 600 by a missense substitution of valine by glutamic acid, what is
known as BRAF V600E mutation (Mao et al. 2012; Prahallad et al. 2012;
53
Yokota 2012; Kuan et al. 2014). In this study, 14,5% of BRAF mutations have
been identified and all of them were V600E. As exposed above, these findings
correspond well with previously reported literature.
BRAF mutations are associated with female sex, older age, proximal tumor
localization, low differentiation grade and locally advanced characteristics (Li
et al. 2006; Clancy et al. 2013; Wangefjord et al. 2013; Kim et al. 2014a). This
investigation revealed that 87,5% of the BRAF mutations were present in
women. In 2013, Clancy et al. reported that BRAF mutation was not associated
with young age. This suggest that BRAF mutations are acquired mutations
occurring mainly in sporadic colorectal cancers and thus, not common in
younger patients. The same group informed that there is a solid association
between proximal tumor location and BRAF mutations (Clancy et al. 2013).
Same results were observed in this work, where 75% of the BRAF mutations
corresponded to samples from patients older than 65 years old. 7 from the 8
patients with BRAF mutations were women. In 87,5% of the cases the tumor
localization was proximal.
The presence of BRAF mutations is associated with notably higher risk of
mortality in CRC (Safaee Ardekani et al. 2012). In addition to prognosis, BRAF
mutation might have clinical treatment implications. Similar to patients with Kras mutations, those patients with metastatic tumors that are being consider
for anti-EGFR therapies should be tested for BRAF mutations as well (Pu et
al. 2013). The presence of BRAF V600E mutation in CRC predicts resistance
to anti-EGFR therapy in patients with K-ras wild-type (Kuan et al. 2014).
Because K-ras is mutated more often than BRAF, first-line testing should be
done for K-ras. If the tumor presents K-ras wild-type, then genotyping BRAF
should be considered (Kalady et al. 2012).
5.6. Simultaneous mutations of p53, K-ras and BRAF: rare but not
impossible
Several research groups have studied the simultaneous expression of p53, Kras and BRAF in CRC, concluding that synchronic mutations in these genes
rarely occur (Calistri et al. 2005; Chang et al. 2013). This could suggest that
p53 and K-ras mutations are on separate pathways to CRC development and
54
are not part of a common pathway of accumulating genetic change (Conlin et
al. 2005; Berg et al. 2010). In this study, p53 mutation associated with K-ras
mutation was only present in 3 from the 55 tested patients (5,5%). In the same
way, co-presence of mutations in BRAF and p53 is quite rare (Calistri et al.
2005). BRAF mutations are more frequently found in premalignant colon
polyps and in early, rather than advanced, CRC (Monticone et al. 2008).
Combination of mutp53 and mutBRAF was in this project, also seen in 3
patients (5,5%).
As concomitant K-ras and BRAF mutations are uncommon in premalignant
colon polyps and early stages of CRC, they are considered as alternative or
mutually exclusive mutations (Yokota 2012). In recent studies, however, it was
found that the number of simultaneous K-ras and BRAF mutations increased
along with the depth of the wall invasion of sporadic MSS (microsatellite stable)
CRC, suggesting that activation of both genes is likely to harbor a synergistic
effect and that K-ras could give the tumor an invasive behavior (Oliveira et al.
2007; Monticone et al. 2008). In this work, the co-existence of K-ras and BRAF
mutations was found in only 1 patient (1,8%), that interestingly also harboured
a silent p53 mutation in exon 8 (L264L). This patient was a 55 year old woman
with a proximal, moderately differentiated tumor, TNM stage I.
Due to the infrequent observation of this phenomena, it is not clear whether
or not tumors carrying coincident K-ras and BRAF mutations have a different
biology and natural history than K-ras or BRAF mutant tumors, or which of the
2 mutations is the dominant oncogene driving tumor proliferation. Further
studies are necessary to understand the true frequency and the role of
concomitant K-ras and BRAF mutations.
5.7. Mutated p53 can be detected by immunostaining
The application of nucleotide sequencing of p53 is the most reliable technique
to detect gene mutation, but its application in pathology practice is limited.
Thus, immunohistochemical analysis of p53 expression is commonly used as
a substitute for mutational analysis (Yemelyanova et al. 2011). The
relationship between p53 overexpression and mutation is still being
55
controversially discussed (Gao et al. 2000). A number of investigations have
shown that a positive p53 expression status often equates with p53 mutation,
but not always (Kruschewski et al. 2011). In this work, 2 different p53
antibodies were proved. The antibody from DAKO showed a high rate of
negative stainings in samples harbouring p53 mutations (40%) and a low
percentage of negative stainings in the wt group (41,7%). Not satisfied with
these results, a new antibody (BD PharmigenTM) was used, obtaining staining
patterns which are in concordance with the published literature. Thus, 73,8%
of the mutated cases detected with sequencing presented positive
immunostaining, which is in agreement with previous investigations that
revealed that the positivity range of p53 expression in CRC is between 40 and
81% (Kruschewski et al. 2011). This wide range is a result of interstudy
variations, including different antibodies, scoring systems, cutoff values, and
study populations (Kruschewski et al. 2011; Nyiraneza et al. 2011).
Wild-type p53 protein is relatively unstable and has a short half-life, which
makes it undetectable by immunohistochemistry. In contrast, mutated p53 has
a much longer half-life, and therefore, accumulates in the nucleus creating a
stable target for immunohistochemical detection (Yu et al. 1993; Yang et al.
2013). Antibodies used for IHC can detect both wild-type and mutant p53
protein (Tabyaoui et al. 2013). P53 overexpression is generally regarded as
indicative of missense mutations, but nuclear p53 overexpression could
sometimes occur in the absence of mutation and vice versa (Cripps et al. 1994;
Dix et al. 1994; Rossner et al. 2009). This work showed 5 mutated cases with
negative staining, corresponding to 1 frameshift mutations in exon 4,
2
frameshift mutations in exon 8, 1 stop codon mutation in exon 6 and a D281Y
mutation
in
exon
8.
It
is
now accepted
that
complete
lack
of
immunohistochemical expression may be result of mutations generating
premature stop codon or frameshift mutations leading to formation of a
truncated, non-immunoreactive protein (Iacopetta 2003; Yemelyanova et al.
2011). The lack of p53 immunoexpression associated with nonsense (or null)
mutation is very important to recognize because some studies demonstrated
worse prognosis for patients with this finding compared with patients whose
tumor had a missense mutation (Hashimoto et al. 1999). Interestingly, tumors
with wild-type p53 display a wide range of immunolabeling patterns, with the
56
most common pattern showing <10% of positive cells, but presenting other
times overexpression. In the wild-type group of this project, positive expression
of p53 was seen in 28,1% of the samples. Apart from the kind of mutation,
there are several other possible explanations for the lack of perfect correlation
between TP53 mutation and immunohistochemical expression. First, the
number of the codons included in the analysis; the present study evaluated
exons 4-8, which would identify most, but not all possible mutated loci. Second,
post-translational alteration; cellular stress could result in delayed degradation
of wt p53 making it detectable by IHC. Third, discrepancy of the samples used
on mutational analysis and staining. Fourth, factors affecting immunolabeling,
especially under-fixation (Yemelyanova et al. 2011). For these cases without
detectable mutation showing positive immunohistochemical expression, the
execution of microdissection could be recommended. In this technique,
sections of formalin-fixed, paraffin-embedded tumor samples are mounted on
slides and stained immunohistochemically with the p53 antibody. Single p53positive cells are separated from the surrounding tissue with the use of laser
and they are picked up using a micromanipulator-guided needle. From these
cells, DNA extraction and sequencing is carried, increasing the chance of
detecting mutations (Kaserer et al. 2000).
In this study, the analysis of the positivity range of expression of p53 showed
the highest expression in samples with mutations in exon 5 and exon 7. The
significance of this result could not have been correlated with other studies due
to the lack of previous published literature addressing this issue.
Expression of p53 is evaluated according to the percentage of positive tumor
cell nuclei (the number of positive tumor cells over the total number of cells)
(Kruschewski et al. 2011). Research groups use different cutoff values making
data from different studies difficult to compare and interpret (Zlobec et al. 2007;
Sarasqueta et al. 2013). In this study a cut-off of 10% was assumed as
indicative of p53 overexpression. Scoring systems for p53 in CRC are in many
cases based on a measure of the proportion of positive tumor cells often
combined with a degree of staining intensity. Staining intensity is evaluated as
0=negative, 1=weak, 2=moderate, and 3=strong (Zlobec et al. 2007). In all the
positive stainings of this investigation the intensity was high, distributed
57
between 54 cases with strong staining (3+) and only one case of moderate
staining (2+). Anyway, it is recognized that the interpretation of staining
intensity is not only highly subjective but may also be affected by storage time,
variation in protocols, and fixation procedures (Zlobec et al. 2007).
Several studies have reported that p53 overexpression is more frequently
associated with right-sided colon cancers and with mucinous or poor
differentiated tumors (Nyiraneza et al. 2011). In the present study, from the
total 27 cases with positive immunostaining, 66,7% had rectal localization,
33,3% proximal and 11,1% distal localization. The tumor differentiation grade
was moderate (77,8%), poor (18,5%) and well (3,7%). From the 5 cases with
mutated p53 and negative expression in immunohistochemistry explained
before, 40% had proximal localization and 80% were poorly differentiated.
Included in this group, there was a 59 year old woman, who was the only one
in the whole set of cases with a mucinous tumor (poorly differentiated, localized
in the colon ascendens). Sanger sequencing showed a R196stop mutation in
p53 protein.
From the above exposed, it can be concluded that immunohistochemistry is a
robust method for inferring the presence of p53 mutations; not isolated but as
a complement of other techniques like sequencing.
5.8. MiRNAs induced by p53
5.8.1. MiR-34 family
Several groups have reported that p53 can directly regulate the expression of
the miR-34 family members (Chang et al. 2007; Raver-Shapira et al. 2007;
Shin et al. 2009). The precursors of these miRNAs are transcribed from two
distinct loci: the miR-34a locus on chromosome 1p36 and the miR-34b and
miR-34c locus on chromosome 11q23 (Wang et al. 2009). Canonical p53binding sites are placed in the promoter regions of miR-34a, b and c.
Consistent with a possible tumor-suppressor role, loss of expression of
members of the miR-34 family has been reported in human cancers (Chang et
al. 2007; Roy et al. 2012). Expression of miR-34a is increased by p53 in
response to genotoxic stress, both in vitro and in vivo (Raver-Shapira et al.
2007). Ectopic expression of miR-34a promotes p53-mediated apoptosis, cell
58
cycle arrest and senescence, while inactivation of endogenous miR-34a
strongly inhibits p53-dependent apoptosis in cells (Chang et al. 2007; He et al.
2007; Raver-Shapira et al. 2007). Recent investigations have shown that miR34 family members directly repress the expression of several targets involved
in the regulation of cell cycle and in the promotion of cell proliferation and
survival. Among these targets are cyclin E2, cyclin-dependent kinases 4 and
6 (CDK4 and CDK6), and BCL2 (Feng et al. 2011; Okada et al. 2014). Thus,
the phenotypic output of miR-34 activation may vary by cell type depending on
the spectrum of its targets that are available for repression. In accordance with
their regulation by p53, comparatively low levels of miR-34s are seen in human
tumors and cancer cell lines, which have a high frequency of functional p53
deficiency (He et al. 2007).
5.8.1.1. MiR-34a is up-regulated in tumors with wt p53
Recently, abnormal up- and down-regulation of several miRNAs in human
CRC has been reported. However, which miRNA species are actually
implicated in the development of this cancer is a question that remains open
(Wang et al. 2014). Tazawa et al. revealed that the expression level of miR34a was reduced in 36 % of human CRC specimens. Using quantitative qRTPCR analysis, they demonstrated that miR-34a was highly up-regulated in a
human colon cancer cell line harbouring wild-type p53, HCT 116, treated with
a DNA-damaging agent, adriamycin (ADR). In this experiment, they compared
the miRNA responses after ADR treatment between HCT 116 and HCT 116
p53 knockout (HCT 116 p53-/-) cell lines, and they identified miR-34a as an
ADR-responsive miRNA in a p53-dependent manner. To confirm that the
induction of miR-34a depends on p53, other human colon cancer cell lines,
either with wild-type p53 genes (LoVo and RKO) or mutated p53 genes (DLD1
and HT29) were studied. LoVo and RKO cells, as well as HCT 116 cells,
exhibited increased expression of miR-34a, but DLD1 and HT29 cells showed
no change, like the HCT 116 p53 -/- cells (Tazawa et al. 2007).
In this doctoral work, the level of miR-34a was compared between 2 groups of
FFPE samples: one group of p53 wt tumor tissues and the other group
represented by their counterpart normal tissues. The results showed a notable
59
up-regulation in the first group, which is in concordance with previous studies
(Chang et al. 2007; Tazawa et al. 2007).
Assuming that the expression of miR-34a is p53 dependent, this miRNA is
expected to be down-regulated in specimens with mutated p53. Tazawa et al.
analyzed the levels of miR-34a in human colon cancer and paired counterpart
normal tissue. Nine of 25 colon cancer tissues (36%) showed decreased
expression of miR-34a, suggesting that down-regulation of miR-34a may be,
at least in part, involved in the development of colon cancer. They also
observed that one-third of colon cancer cases presented up-regulation of miR34a, which express that there may be alternative mechanisms that remain to
be identified in the regulation of miR-34a (Tazawa et al. 2007).
In this study, the comparison of the expression levels of miR-34a in
histologically normal samples and tumor samples harbouring p53 mutations
showed that many of the specimens in the second group presented downregulation or no changes in the expression level, what suggests that in the
cancer group the regulation is lost.
Overall comparison between the 55 samples (including samples with wt and
tumor samples with mutated p53) showed no significant differences in the
expression level of mir34a. Here it would have also been expected a downregulation in the miR-34a levels in the group presenting p53 mutations.
The expression of miR-34a related to p53 codon 72 polymorphisms was
analyzed, concluding that the highest expression of miR-34a was associated
with the Arg/Arg genotype.
The association between miRNAs and K-ras/BRAF still remains undefined
(Kent et al. 2010; Ito et al. 2014). Research revealed that 6 miRNAs (miR-23a,
miR-125b, miR-191, miR-200c, miR-221 and miR-222) were up-regulated and
2 (let-7b and let 7i) were down-regulated under the control of oncogenic K-ras
in 3D culture (Tsunoda et al. 2011). Other investigations showed that the
expression of miR-31 is notable up-regulated in CRCs that present BRAF
mutations. In this doctoral work, no association was observed between miR34a and K-ras/BRAF mutations.
60
5.8.2. MiR-34b and miR-34c are not detectable in CRC samples
No expression of miR-34b and miR-34c in the samples was detected in the
qRT-PCR experiments. Under unstressed conditions, the expression of miR34a and miR-34b/c is particularly intense in the testis, brain, and lung. MiR34b/c expression seems largely restricted to these three tissues, while miR34a is detectable, albeit at lower levels, also in several other organs including
colon, liver and kidney (Concepcion et al. 2012). In 2007, 2 independent
investigations working with HCT 116 cells reported that while substantial
expression of miR-34a was observed, the expression levels of the miR-34b
and -34c were very low or not even detectable (Chang et al. 2007; Tazawa et
al. 2007).
5.8.3. Other components in the p53 network: miR-192, miR-215
and miR-200c
In addition to the miR-34 family, 3 other p53 induced miRNAs were studied in
this project: miR-192, miR-215 and miR-200c. No differences in the expression
of these miRNAs were seen when comparing wt and mutated p53 tumor
samples. A brief description of these miRNAs can be found below.
MiR-192 and miR-215
MiR-215 clusters on chromosome 1 (1q41) and miR-192 on chromosome 11
(11q13.1). Both miRNAs are highly homologues to each other and share the
same seed sequences (Khella et al. 2013). Previous studies demonstrated that
miR-192 and -215 express at high levels in colon and liver (Barad et al. 2004;
Lu et al. 2005). In the same way than miR-34a, miR-192 and -215 are among
the p53 regulated miRNAs and show reduced expression levels in CRC
(Karaayvaz et al. 2011; Zhai and Ju 2011). In an effort to obtain a more
complete set of p53-responsive microRNAs, Braun et al. hybridized
microarrays with small RNA from Nutlin3-treated cells and found that clusters
encoding miR-192 and miR-215 were p53 responsive, in addition to miR-34a.
The same clusters were down-regulated in colon cancer relative to normal
colon tissue, supporting the idea that they might be part of a tumor-suppressing
61
program (Braun et al. 2008). In 2012, Chiang et al. studied the expression
levels of miR-192 and -215 in a large number of CRC tissues, relative to their
non-tumor counterparts, by real-time PCR assay. Significantly lower
expression of these miRNAs was found in cancer tissues compared to nontumor counterparts. Similar significant results were obtained in CRC cell lines
(Chiang et al. 2012). Functional analysis revealed that miR-192 and -215 were
capable of inducing p21 expression and cell cycle arrest in a p53-dependent
manner, suggesting that they may be able to activate p53 (Georges et al. 2008;
Song et al. 2008). In this context, the expression of p21 was increased by miR192 and miR-215 only in cells that carried wt p53, but not in cells with p53-/status (Braun et al. 2008). Among the targets of miR-192 and -215 are a
number of regulators of DNA synthesis and the G1 and G2 cell cycle
checkpoints in cells, such as CDC7, MAD2L1 and CUL5 (Feng et al. 2011).
Recent investigations studied the regulating mechanism of p53 level by miR192 and -215 and discovered a key target, denticleless protein homolog (DTL)
(Zhai and Ju 2011). The suppression of DTL by these miRNAs generates an
up-regulation of p53 and p21 (Georges et al. 2008; Song et al. 2010;
Karaayvaz et al. 2011). DTL is thought to play an essential role in DNA
synthesis, cell cycle progression, proliferation, and differentiation (Pan et al.
2006).
MiR-200c
MiR-200c has been widely reported to be elevated in tumor tissues and sera
of CRC patients and has been found to correlate with poor prognosis (Chen et
al. 2014). Xi et al. study demonstrated that miR-200c expression was strongly
associated with the mutation status of p53 in CRC (Xi et al. 2006). In March
2014, Chen et al. published that the expression of miR-200c was significantly
higher in tumor tissues than in peritumoral tissues of patients with colon
cancer. They conclude, that miR-200c functions as an oncogene in colon
cancer cells through regulating tumor cell apoptosis, survival, invasion, and
metastasis as well as xenograft tumor growth through inhibition of PTEN
expression and p53 phosphorylation (Chen et al. 2014). Previous studies
reported controversial roles of miR-200c in the metastasis of colon cancer
62
such as that overexpression of miR-200c inhibited the metastatic ability of
colon cancer cells in one study, whereas a positive association between miR200c expression and metastasis of CRC was observed in another (Chen et al.
2012; Hur et al. 2013). In this context, 2 independent research groups have
investigated the function of miR-200c in epithelial-mesenchymal transition
(EMT), a key process in tumor progression and metastasis. MiR-200c upregulated by p53, repress the expression of 2 EMT promoters (ZEB1 and
ZEB2) decreasing, in this way, the activation of the EMT program. This data
reveals a potential therapeutic implication to suppress EMT through activation
of p53-miR-200c pathway (Chang et al. 2011; Kim et al. 2011).
5.8.4. MiRnas, K-ras and BRAF in CRC
Although activating mutations in RAS oncogenes are known to result in
aberrant signaling through multiple pathways, the role of miRNAs in the Ras
oncogenic program still remains unclear (Kent et al. 2010). Mosakhani et al.
compared miRNA profiles between 2 groups of CRC patients, one with mutant
K-ras and the other one with wild-type K-ras, founding a significant differential
expression between them. One of these differential expressed miRNAs was
miR-92a, which showed up-regulation in CRC samples with mutated K-ras
(Mosakhani et al. 2012). MiR-92 is up-regulated in several types of cancers
including CRC (Ng et al. 2009). Expression of the miR-92 promotes cell
proliferation, suppresses apoptosis of cancer cells and induces tumor
angiogenesis (Mendell 2008). Chen et al. had experimentally validated K-ras
oncogene as target of miR-143. MiR-143 is significant in suppressing CRC cell
growth through inhibition of K-ras translation (Chen et al. 2009; Pichler et al.
2012). Tsunoda et al. analyzed also the relationship between miRNAs and Kras in CRC cells. In this study, they found 6 miRNAs (miR-23a, miR-125b, miR191, miR-200c, miR-221 and miR-222) to be up-regulated and 2 (let-7b and
let-7i) to be down-regulated under the control of oncogenic K-ras in 3D culture
(Tsunoda et al. 2011).
The association between miRNAs and BRAF in CRC is also undefined. Recent
studies using miRNA array analysis revealed that miR-31 expression is
significantly up-regulated in CRCs with mutated BRAF (V600E), compared
63
with CRCs possessing wild-type BRAF. High miR-31 expression has been
associated with BRAF and K-ras mutations and proximal location. Functional
analysis showed that miR-31 inhibitor decreased cell invasion and proliferation
(Ito et al. 2014; Nosho et al. 2014).
5.9. Conclusion and outlook
Colorectal cancer is a leading cause of cancer-related mortality worldwide
(Wang et al. 2014). Colon carcinogenesis is a multistep process, involving
oncogene activation and tumor suppressor gene inactivation as well as
complex interactions between tumor and host tissues, leading finally to an
aggressive metastatic phenotype (Wang and Sun 2010). Among many genetic
lesions, mutational inactivation of p53 tumor suppressor is the most frequent
event, found in 50% of human cancers. P53 plays a critical role in tumor
suppression principally by inducing growth arrest, apoptosis, and senescence,
and
by
blocking
angiogenesis.
Additionally,
p53
confers
chemo-
radiosensitivity. Thus, it is not surprising that p53 has become the most
appealing target in anti-cancer drug discovery. This project aimed to increase
the current knowledge concerning the role of p53 in CRC, its interaction with
the oncogenes K-ras and BRAF, and its association with miRNAs.
In this study, 41,8% of the tested samples presented p53 mutations; 29,1%
had K-ras mutations and 14,5% showed BRAF mutations. Mutation
frequencies were found to be within previously reported range supporting the
representativeness of the results in this work (Andreyev et al. 2001; Naccarati
et al. 2012; Yokota 2012; Kuan et al. 2014; Tong et al. 2014).
Simultaneous expression of p53, K-ras and BRAF rarely occur (Chang et al.
2013). Even though, the association p53 mutation/K-ras mutation was seen in
5,5% of the samples (3 patients), and the association p53 mutation/BRAF
mutation was found in other 5,5% (3 patients). The co-existence of K-ras and
BRAF mutations was found in only 1 patient (2,6%). It remains unclear if
tumors with coincident K-ras and BRAF mutations have a different biology and
natural history than K-ras or BRAF tumors, or which of the 2 mutations acts as
dominant in tumor development.
64
Mutations in p53 were detected in this project by Sanger sequencing and
immunohistochemical staining. Mutated p53 has a longer half-life than the wt
p53 and this is the reason why it can be detected immunohistochemically (Yu
et al. 1993). Negative p53 immunostaining in association with p53 mutations
was seen in 5 cases corresponding to 3 frameshift mutations, 1 stop mutation
and a D281Y mutation in exon 8. The complete lack of immunohistochemical
expression may be the result of mutations generating premature stop codon
or frameshift mutations leading to formation of a truncated, nonimmunoreactive protein (Iacopetta 2003; Yemelyanova et al. 2011). Nuclear
p53 overexpression was found in this investigation in the presence of p53
mutations using 2 different antibodies.
The expression level of several p53-induced miRNAs was also evaluated. For
miR-34a, using paired analysis, 2 groups of samples with wt p53 were
compared: one represented by CRC tissues and the other one by normal
tissues. A notable up-regulation in the levels of miR-34a was found in the first
group showing that the expression of miR-34a is increased by p53 in wild-type
form, in response to cellular stress. The comparison of the expression levels
of miR-34a in histologically matched normal samples and tumor samples
harbouring p53 mutations revealed, in most of the cases, down-regulation or
no changes in the expression level of the second group, suggesting that in p53
mutated cancer the regulation is lost. No expression of miR-34b and miR-34c
was detected in the samples and no significant differences in the expression
of miR-34a, miR-192, miR-215 and miR-200c were found when comparing the
whole tumor group with wt and with mutated p53.
Some of the experiments of this work should be repeated and several other
experiments could also be conducted to supplement the above exposed data.
Due to time limitations the comparison between the expression of miRNAs in
matched normal and tumor samples was only performed for miR-34a. It could
be very interesting to investigate the behavior of the other miRNAs in the 15
paired normal/tumor samples.
A DNA and RNA bank derived from the samples used in the research has been
created. This represents a unique possibility for further investigations, such as
65
the study of other genes or miRNAs of interest and mutations not included in
this project.
Recent investigations suggest that maybe p53 is not sufficient and other
proteins may be required as co-activators along with p53 to induce miRNA
expression. In this context, the employement of Chip Assays could be useful
tools in future investigations. More sensitive methods such as RNA-seq could
also be used to assay for miRNA transcripts undetectable by conventional RTPCR.
The current ability to understand the genetics of individual cancers is changing
the way the disease is treated. Research centers worldwide investigate tools
to study cancer’s genetic features and try to determine how best to apply the
new knowledge in the clinic. This is part of a larger movement toward
personalized medicine, which aims to tailor disease prevention and treatment
as much as possible to the individual patient. It has been the purpose of this
study to make a simple contribution in this development.
66
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Abstract
Colorectal cancer is one of the leading causes of cancer death worldwide and
it is associated with aberrant cycle progression and defective apoptosis
induction due to the activation of proto-oncogenes and/or inactivation of tumor
suppressor genes. Mutational inactivation of p53 tumor suppressor, the
“guardian of the genome”, is the most frequent event found in 50% of human
cancers. The aim of this study was to extend the present knowledge about the
role of p53 in CRC, its interactions with the oncogenes K-ras and BRAF, the
correlation between the mutation status and the immunohistochemical
expression patterns of p53, and the association of protein p53 with certain
miRNAs.
This study was based on the analysis of formalin-fixed paraffin-embedded
tissues from 55 patients with histological proven colorectal adenocarcinoma.
41,8% of the samples presented p53 mutations, which is in concordance with
previous published data, that estimate the p53 mutation incidence in CRC to
be between 40 and 50%. The incidence of K-ras mutations was 29,1% and of
BRAF 14,5%. Simultaneous expression of p53, K-ras and BRAF are not
frequently reported in the literature, suggesting that they are on separate
pathways to colorectal tumorigenesis and not part of a common pathway of
accumulating genetic change. In this study, 3 patients presented co-existence
of p53/K-ras mutations and 3 others harboured a double mutation p53/BRAF.
Only 1 patient had simultaneous mutation of K-ras and BRAF.
The mutant forms of p53 are stable and have longer half-life than the wild-type
forms, making it possible to detect them immunohistochemically. In this work,
73,8% of the mutated p53 cases presented positive immunostaining, which is
in agreement with previous investigations.
Recent studies have demonstrated that miRNAs interact with p53 and its
network at several levels. P53 controls the transcription expression and
maturation of a group of miRNAs, which in turn, can regulate the activity of p53
through direct repression of p53 or its regulators cells. MiR-34 showed upregulation in the wt p53 cancer group compared with the normal tissue group,
showing that the expression level of miR-34a is increased by p53 in the wildtype form, in response to cellular stress, like genotoxic damages, oncogene
105
activation and hypoxia. The comparison of the expression levels of miR-34a in
normal samples and tumor samples that harboured p53 mutations showed that
many of the specimens in the second group presented down-regulation or no
changes in the expression level, suggesting that in the cancer group the
regulation is lost. No difference in the expression of this miRNA was seen
between tumor samples with wt p53 and mut p53 in the whole tumor group.
Other p53 regulated miRNAs included in this study were miR-34b, miR-34c,
miR-192, miR-215 and, miR-200c.
P53 is a fundamental component of the colorectal carcinogenesis. Further
research will contribute to a better understanding of its function, taking us a
step forward in the process of developing personalized cancer treatment.
106
Zusammenfassung
Das Kolorektale Karzinom ist weltweit eine der Hauptursachen für den
Krebstod und ist verbunden mit einem abnormen Zellzyklus und einer defekten
Apoptoseinduktion infolge der Aktivierung von Proto-Onkogenen und/oder der
Inaktivierung von Tumorsupressorgenen. In 50% der Krebsfälle ist das p53
Tumorsupressorgen, auch Wächter des Genoms genannt, durch eine
Mutation deaktiviert. Ziel dieser Studie war die Ausdehnung der bisherigen
Kenntnisse über die Rolle von p53 in CRC, die Prüfung einer Korrelation
zwischen
dem
Mutationsstatus
und
dem
immunohistochemisch
nachweisbaren Expressions-Muster von p53 sowie dessen Wechselwirkung
mit verschiedenen miRNAs.
Diese Studie basiert auf der Analyse der in Paraffin eingebetteten
Gewebeschnitte von 55 Patienten mit einem histologisch gesicherten
kolorektalen
Adenokarzinom.
In
Übereinstimmung
mit
bisherigen
veröffentlichen Daten, welche eine Häufigkeit der p53-Mutation bei CRC auf
40-50% schätzen, wiesen 41,8% der hier untersuchten Proben eine p53Mutation auf. Die Häufigkeit einer K-ras Mutation lag bei 29,1%, die einer
BRAF Mutation bei 14,5%. Eine gleichzeitige Expression von p53, K-ras und
BRAF wird in der Literatur kaum erwähnt, was zu der Annahme führt, dass sie
nicht Teil eines gemeinsamen Signalweges mit einer Ansammlung
genetischer Veränderungen sind, sondern über verschiedene Signalwege
Einfluss auf die Tumorgenese nehmen. In dieser Studie trat bei 3 Patienten
eine Koexistenz von p53/K-ras Mutationen auf, 3 weitere hatten eine
Doppelmutation von p53/BRAF. Bei einem Patienten trat eine gleichzeitige
Mutation von K-ras und BRAF auf.
Die mutierten Formen des p53 Proteins zeigten eine hohe Stabilität und hatten
eine längere Halbwertszeit als der p53 Wildtyp, wodurch es möglich war, diese
immunohistochemisch nachzuweisen. In dieser Arbeit zeigten 73,8% aller
Fälle mit einer p53 Mutation eine positiv p53 Immunfärbung, was mit früheren
Untersuchungen übereinstimmt.
Jüngste Studien haben gezeigt, dass miRNAs mit p53 und seinem Netzwerk
auf mehreren Ebenen interagieren. P53 kontrolliert die Transkription,
Expression und Reifung einer Gruppe von miRNAs, welche ihrerseits die p53
107
Aktivität regulieren entweder durch direkte Suppression oder über seine
Regulatoren. Bei dem Vergleich der p53 Wildtyp Tumoren mit dem
korrespondierenden Normalgewebe zeigte die miR-34 eine Hochregulierung.
Der Vergleich der Expressionsmenge der miR-34a in gepaarten Normalproben
und Tumorproben mit einer p53 Mutation zeigt in den Tumorproben eine
Herunterregulation oder keine Veränderung im Expressionslevel. Dies führt zu
der Annahme, dass die Regulation in der Tumorgruppe mit mutiertem p53
verloren geht. Es gab keinen Unterschied im Expressionslevel dieser miRNA
im Gesamtkollektiv bei Vergleich von Wildtyp p53 und p53 mutierten Tumoren.
Weitere durch p53 regulierte miRNAs wie miR-34b, miR-34c, miR-192, miR215 und miR-200c wurden in dieser Studie untersucht und zeigten keinerlei
Korrelation zum p53 Status.
P53 ist ein wesentlicher Bestandteil der kolorektalen Karzinogenese. Die
weitere Erforschung dieses wichtigen proteins wird uns ein besseres
Verständnis seiner Funktion liefern und uns somit einen Schritt in der
Entwicklung einer personalisierten Krebstherapie weiterbringen.
108
Curriculum Vitae
Mariana Fernanda Cordoba Hansen
Date of birth: June 28 1976
Place of birth: Buenos Aires, Argentina
Address: Hirtenbachstrasse 4A, 91353, Hausen, Germany
Telephone: 091917362872 Mobile: 01712837681
E-mail: [email protected]
Education
06/13 – 07/14
Universitätsklinikum Erlangen, Erlangen, Germany
Doctoral candidate at the Experimental Tumor Pathology
Department, Institute of Pathology
02/13 - 02/13
Universitätsklinikum Erlangen, Erlangen, Germany
Assistenzärztin at the Department of Surgery
04/11 - 04/12
Hillerød Hospital, Hillerød, Denmark
Senior resident at the Department of Surgery
01/10 - 03/11
Rigshospitalet, Copenhagen, Denmark
Senior resident at the Department of Surgical
Gastroenterology (12 months at the Department of Surgery
and Liver Transplants and 3 month at the Department of
Paediatric Surgery)
08/08 - 12/09
Herlev Hospital, Herlev, Denmark
Senior resident at the Department of Surgical
Gastroenterology (started as mid level resident)
05/08 -07/08
Ringsted Hospital, Ringsted, Denmark
Mid level resident at the Department of Breast Surgery
11/07- 05/08
Herlev Hospital, Herlev, Denmark
Mid level resident at the Department of Surgical
Gastroenterology
11/05 – 10/07
Gentofte Hospital, Gentofte, Denmark
Mid level resident at the Department of Surgical
Gastroenterology
05/05 – 10/05
Gentofte Hospital, Gentofte, Denmark
Mid level resident at the Department of Cardiothoracic
Surgery
06/04 – 04/05
Gentofte Hospital, Gentofte, Denmark
Started out as junior resident and advanced to mid level
resident at the Department of Surgical Gastroenterology
07/01 - 07/05
Hospital Prof. Dr. Luis Güemes, Haedo, Argentina
109
4 years Residence within General Surgery (the education
was financed by a scholarship from the Argentinean
Ministry of Health)
07/00 – 03/01
Hospital Dr. Carlos G. Durand, Buenos Aires, Argentina
Rotation round
03/95 – 07/00
Universidad de Buenos Aires, The Faculty of Medicine,
Buenos Aires, Argentina
Medical education
Average grade: 8.69 on the 1- 10 scale
03/94 - 12/94
Universidad de Buenos Aires, CBC, Buenos Aires, Argentina
Two semesters of preparation and admission study for
Medical School
03/89 – 12/93
The Institute of Abate José Rey, Caseros, Argentina
High school student
References
Christian Ross, Education responsible and Consultant, the Department of Surgical
Gastroenterology, Rigshospitalet, telephone: +45 35 45 96 45
Jesper Vilandt, Consultant, the Department of Surgery (specialised in colon), Hillerød
Hospital, telephone: +45 48 29 71 55
Claus Anders Bertelsen, Consultant, the Department of Surgery (specialised in colon),
Hillerød Hospital, telephone: +45 48 29 59 72
Anders Ulrich Neuenschwander, Consultant, the Department of Surgery (specialised in
colon), Hillerød Hospital, telephone: +45 48 29 59 42
Anders Fischer, Consultant, the Department of Surgical Gastroenterology, Herlev Hospital,
telephone: +45 44 88 44 88, DECT: 82-563
Jens G. Hillingsø, Clinic Director and Consultant, the Department of Surgical
Gastroenterology, Rigshospitalet, telephone: +45 35 45 87 80
Practical experience during medical school
03/98 – 07/00
Hospital Dr. Carlos G. Durand, Buenos Aires, Argentina
Intern as a part of the obligatory training at medical school
03/96 – 03/98
Hospital Zonal Prof. Dr. Ramón Carrillo, Buenos Aires,
Argentina
Intern at the hospitals emergency room
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08/97 – 11/97
The Argentinean Social and Health Ministry, Buenos Aires,
Argentina
Vaccination Campaign against influenza
Courses, congresses, seminars and research
06/11
Research training Statistic and database
05/11
Endoscopy course
05/11
Gastroenterology and Hepatology I
04/11
Management and Administration II
03/11
Gastroenterology and Hepatology II
02/11
The acute surgery patient
12/10
Basic resuscitation in paediatric
09/10
Management and Administration I
09/10
Danish association of surgery, annual congress
03/10
Ultrasound
03/06
23rd course in open and laparoscopic surgical technique, Davos,
Switzerland
11/03
74th Argentinean Surgical Congress
Seminar for surgeons and surgical workshops
Coordinator and participant at the round table Management of
choledocolithiasis
11/03 XVIII
Argentinean Congress of Emergentologi
11/03
Update in treatment of the venous system
11/03
International course in outpatient-surgery
11/03
International course in mini invasive surgery
10/03
Workshop: Treatment of pancreas, gallbladder and biliary tract cancer.
Organised by the Asociación Argentina de Oncología Clinica
10/03
Regional seminar for doctors in Buenos Aires
08/03
Percutaneous treatment of piogenic abscesses
Presented for the Asociación Argentina de Cirugía
08/03
PROACI: Development program in surgery
Organised by the Argentinean Surgical Association
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The program dealt with new trends in treatment of surgical pathologies
06/03
Seminar for surgeons 2003
Trauma course
05/03
XVI Argentinian and Latin American congress for young surgeons
Seminar for young surgeons under education
Author and lector of Ambulant treatment of haemorrhoids
05/03
Update in treatment of the venous system
Organised by the Sociedad de Flebologia y Linfologia del Oeste Provincia de
Buenos Aires
12/02
A.T.L.S (Advanced trauma life support)
Organised by The committee on trauma - American College of Surgeons
11/02
XIV Workshop for young surgeons in Buenos Aires
Workshops of general surgery
Organiser and speaker
10/02
73rd Argentinian Surgical Congress
Seminar for surgeons: Surgical workshops
Coordinator and participant at the round the table Treatment of the acute
thoracic trauma
10/02
4th Latin American Congress of Endoscopic Surgery
10/02
International course of cancer and laparoscopic surgery
09/02
1st Workshop for doctors Hospital Dr. Luis Güemes
09/02
XIV Workshop for young doctors under surgical education
04/02
XV Argentinian and Latin American congress for young surgeons
Seminar for young surgeons under education
Author of Penetrating trauma in duodenum and pancreas
11/01
72nd Argentinean Surgical Congress
Seminar for surgeons: Surgical workshops
Coordinator and participant at the round table
11/01
3rd Latin American Congress of Endoscopic Surgery
11/01
Regional seminar for doctors in Buenos Aires
Seminar for young doctors under education
Assistant in connection with the presentations of several subjects within
surgery
11/00
XXXVI Annual Scientific Seminar of the Hospital Dr. Carlos Durand
112
Further information
Languages
Spanish (mother tongue), English (fluent) and Danish (fluent), German
(good communication skills)
First Certificate in English: Issued by the University of Cambridge.
IT
Windows, Microsoft Office Professional, Internet
Personal
interests
Fitness and running, reading, travelling and cooking
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