Download post-surgery, after primary chemotherapy, at six

Supplementary data
Clinical data
Detailed clinical and follow-up data were obtained from medical records at predefined
intervals: post-surgery, after primary chemotherapy, at six-month intervals up to five years
and annually thereafter. Patients underwent primary surgery of the ovary and disseminated
disease for diagnosis, staging and debulking. Surgical staging was based on the FIGO
(Fédération Internationale des Gynaecologistes et Obstetristes) classification. Optimal
debulking was defined as less than 1 cm (diameter) residual disease, and sub-optimal
debulking as more than 1 cm. Patients were followed up with a physical examination,
including pelvic examination and serum CA-125 assay. When there were abnormal findings a
CT scan was done, and relapse was defined according to RECIST criteria (Response
Evaluation Criteria In Solid Tumors) (1) as tumor re-growth after a standard course of
platinum-based primary chemotherapy.
A complete clinical response (cCR) was defined as resolution of all clinical and radiographic
evidence of disease, and normal CA-125 after completion of first line chemotherapy, which
was considered the last treatment. Persistent disease was defined as lack of complete response
to first-line chemotherapy. For patients who achieved a cCR, progression-free survival (PFS)
was defined as the interval between the end of first-line chemotherapy and first confirmed
sign of disease recurrence. Overall survival (OS) was defined as the interval between the date
of diagnosis and the date of death from any cause.
Orthotopic implantation in the bursa of the ovary
Orthotopic implantation of EOC xenografts was as previously described with modifications
(2). Nude mice were anesthetized with isoflurane and a lateral midline incision was made to
allow access to the right ovary. Cancer cells from enzymatic digestion or ascites (1 × 106 cell
suspension in 10 μL HBSS) were injected orthotopically under the bursa of the ovary, using a
Hamilton syringe with a 26-gauge needle. The ovary was replaced in the peritoneal cavity and
the incision sutured with wound clips. Mice were checked twice a week for tumor formation
in the ovary and abdominal distension in the peritoneal cavity, and sacrified at the first sign of
discomfort; the time was recorded as survival.
Immuno-histochemistry
Tissue were formalin-fixed and paraffin-embedded, then sectioned (1 µm) onto slides. These
slides underwent incubation with EnVision FLEX Target retrieval Solution for 20-40min at
97° to obtained in a single passage dewaxing and antigen retrieval and autostaining with Dako
Autostainer Link 48. Exception was staining with CK7 antibody not requiring antigen
retrieval, where after dewaxuing slides were incubated for 7 min at 97° and stained with the
primary antobody. The sections were then mounted using an automated instrument and
visualized with a BX60 microscope (Olympus).
As for mucinous cases, appendix was always checked to exclude intestinal metastatic tumor.
In few cases of tumor- negative appendix and with not a clear cut histological diagnosis of
ovarian neoplasm, patients underwent gastroscopy
and colonscopy that were however
negative, suggesting a primary ovarian tumor. Negativity for specific markers of intestinal
neoplasm (CDX2) and positivity for ovarian epithelial markers (CDK7 and CDK20) were
also tested in all the mucinous cases.
Mutational analysis
Genomic DNA from EOC-xenografts and patient tumors was extracted using a Maxwell 16
Tissue DNA Purification Kit (Promega) or NucleoSpin Tissue Kit (Macherey-Nagel). Ten ng
were PCR amplified in 15 μL reaction, containing 200 μM dNTP solution, 200 nM specific
primers and 0.75 U FastStart Taq Polymerase (Roche). For each gene optimal primer pairs
were
chosen
using
PRIMER-3
software
(http://frodo.wi.mit.edu/cgi-
bin/primer3/primer3_www.cgi) or were modified from (3-5) for ARID1A; from (6) for
CTNNB1 and from (7) for PPP2R1A. Primer sequences are listed in Supplementary Table 1.
PCR amplification of genomic DNA was done in a thermocycler (TC-510, Techne) by
denaturation at 94-96°C for 2-10 min and cycling condition as follows: ARID1A exon 1: three
cycles at 94°C for 15s, 62°C for 30s, 72°C for 30s; three cycles at 94°C for 15s, 59°C for
30s, 72°C for 30s; three cycles at 94°C for 15s, 56°C for 30s, 72°C for 30s; 41 cycles at 94°C
for 15s, 55°C for 30s, 72°C for 30s. ARID 1A exons 2-20, PPP2R1A exons 5 and 6: three
cycles at 94°C for 15s, 64°C for 30s, 72°C for 30s; three cycles at 94°C for 15s, 61°C for 30s,
72°C for 30s; three cycles at 94°C for 15s, 58°C for 30s, 72°C for 30s; 41 cycles (30 cycles
for PPP2R1A) at 94°C for 15s, 57°C for 30s, 72°C for 30s. CTNNB1 exon 3: 30 cycles at
96°C for 15s, 55°C for 30s, 72°C for 30s. BRAF exons 11 and 15, KRAS exon 2, PI3KA exon
21, TP53 exons 5-6, 7 and 8-9: 35 cycles at 94°C for 15s, 60°C for 30s, 72°C for 45s. PI3KA
exon 10: 35 cycles at 94°C for 15s, 57°C for 30s, 72°C for 45s. The primer specificity and
optimal cycling conditions were verified by detecting single-band amplicons of the PCR
products by human DNA and none by murine DNA.
PCR products were purified using Illustra ExoStar (GE Healthcare Life Sciences) and
sequenced using a Big Dye Terminator Kit v.3.1 (Applied Biosystems) in presence of the
universal
primers
M13F
and
M13R
(5’-GTAAAACGACGGCCAGT,
5’-
CAGGAAACAGCTATGACC), following the manufacturer’s instructions. Reactions were
purified using the BigDye-XTerminator Purification kit and run on the 3730 DNA Analyzer
(Applied Biosystem).
Genome-wide gene expression analysis
RNA isolation and assessment of human and mouse proportions
Qiazol and the miRNeasy Mini Kit together with a DNase I digestion step (Qiagen) were used
according to the manufacturer’s recommendations to isolate total RNA from EOC-xenografts
and patient tumor specimens. Total RNA quality was checked for integrity using RNA Nano
Chips on an Agilent Bioanalyzer 2100 (Agilent Technologies). Xenograft tumors are
composed of a mixture of human- and mouse-derived cells; to assess their respective amounts,
total RNA was evaluated by species-specific TaqMan Prime Time qPCR assays for beta actin
(ACTB). Briefly, 200 ng tot RNA were reverse-transcribed with random hexamers in a 20 L
reaction volume by the High Capacity cDNA Reverse Transcription kit (Applied Biosystems);
cDNA (2 L of the 1:20 dilution) was PCR amplified in 10 L reaction, with 500 nM primers,
250 nM probe (Hs PT39a22214847, MmPT53a.31778008, IDT) and the TaqMan gene
expression master mix 1x (Applied Biosystem) on the Applied Biosystems 7900HT Fast Real
Time PCR system (40 cycles at 94°C for 15 s, 60°C for 60s). Standard curves generated with
the following formula: [CtmouseACTB – CthumanACTB = (m-h Ct)] using known human and mouse
total RNA mixtures (100, 95, 90 ,80, 75, 70, 60, 50%), were used to determine the proportions
of human and mouse ACTB RNA in EOC-xenograft. The value (m-h Ct) obtained for each
sample (analyzed in triplicate) was plotted against the standard curve to extrapolate the
percentage of human RNA. Only samples with a human RNA content over 75% were
considered for analysis.
One-color microarray-based hybridization
Labeled cRNA target was prepared starting from 100 ng of input RNA [RNA integrity number
(RIN) > 7.0] by a Low Input Quick Amp Labelling Kit and One-Color Spike-In Kit (Agilent
Technologies) and purified with RNeasy Mini Kit (Qiagen) according to the manufacturer’s
recommendation and protocols. Cyanine3 CTP-labeled cRNA was quantified on a NanoDrop
ND1000 Spectrophotometer using microarray/RNA-40 measurement and the specific activity
of cyanine 3 was calculated for each reaction. We set a minimum of 2 μg for yield and 7
pmol/μg for the specific activity. Labeled cRNA (600ng) was fragmented by incubation with
5 L of 10× blocking reagent and 1 L of 25× fragmentation buffer in a 25 L reaction
volume for 30 minutes at 60°C. 25 L of 2× GE Hybridization Buffer Hi-RPM were added to
fragmented cRNA; 40 μL of this “hybridization mix” were placed on SurePrint G3 Human
GE V2 8x60K microarrays (50,599 Biological Features/array; Agilent Technologies).
Hybridization was carried out for 17 hours at 65°C, rotating at 10 rpm. Microarray slides were
washed in GE Wash Buffer-1 for 2 minutes and pre-warmed GE Wash Buffer-2 for 2 minutes
at room temperature. Microarray slides were scanned in an Agilent Scanner version C
(G2505C, Agilent Technologies).
Data analysis
Images were analyzed using the Feature Extraction software v10.7. Raw data elaboration was
processed with Bioconductor (www.bioconductor.org) (8), using R statistical language.
Background correction was done with the normexp method with an offset of 50 and quantile
algorithm was used for between-array normalization. The LIMMA (LInear Models for
Microarray Analysis) package was then used to identify genes differently expressed in EOCxenografts and the corresponding patient tumors. The empirical Bayes method was used to
compute moderated t-statistics (9). Transcripts with a log base two-fold change (logFC)
greater than 1 or lower than -1 and p-value less than 0.01 were considered differently
expressed. MeV version 4.8 (10) was used for unsupervised hierarchical clustering, on the
global expression profiles of EOC-xenografts, patient tumors and external datasets, as well as
on subsets of genes according to their ontological classification. Pearson correlation as
similarity metrics and average/complete linkages as linkage method were used. To look for
any overrepresented biological feature at process level ALL (BPALL) of the Gene ontology
(GO), we used the functional annotation tool available within DAVID Website
(http://david.abcc.ncifcrf.gov/), using the lists of differently expressed genes in EOCxenograft models versus their corresponding patient tumors.
External datasets (we chose datasets of tissues and cell lines profiled on the same commercial
platform as the one we used herein) were retrieved from public repositories such as
ArrayExpress (European Bioinformatic Institute - EBI) and Gene Expression Omnibus (GEO
at the National Center for Biotechnology Information – NCBI) and from ongoing experiments
in G.C. laboratory. The prostate cancer tissue data derive from the hybridization on Agilent
SurePrint G3 Human GE 8x60K microarrays of the same totRNA already profiled on Agilent
22K (GEO series GSE14206) and published in Kunderfranco P. et al., PLoS One 2010 (11).
Legends to Supplementary Figures
Supplementary Figure 1
Histologic characteristics of the original patient tumors and corresponding EOCxenografts. Sections from the patient tumor and the corresponding xenograft are shown
(H&E). The EOC-xenograft identification number and the original clinical diagnosis are
indicated.
Supplementary Figure 2
Comparative immuno-histologic analysis of patient tumor and the corresponding
xenograft. Images show the staining of representative patient tumors (pt) and the related
EOC-xenograft (xeno) with H/E, pool of Cytokeratin (Cyto pool), and CA125.
Supplementary Figure 3
Comparative immunohistochemical analysis of xenografts at different passages.
Immunohistochemical analysis were performed on xenografts at early and late passages.
Hematoxilin/Eosin (H/E) staining and Cytocheratin Pool, Ca125 and Estrogen Receptor (ER)
markers were evaluated as described in Material and Methods.
Supplementary Figure 4
Copy number in patient (■) and xenograft ( ) matched tumors for cMet, cMyc, PI3K, PTEN,
FGFR1, ERBB2, RB1 and NF1 genes.
Spearman coefficient as correlation coefficient
between patient and xenograft copy number was calculated.
Supplementary Figure 5
Pearson’s correlation coefficient across all EOCs. Correlation coefficient was calculated
based on 50,599 probes (SurePrint G3 Human GE V2 8x60K microarrays; Agilent
Technologies) from nine patient tumors and 29 EOC-xenograft models (represented by 62
tumor replicates). The Pearson’s correlation coefficient between patient tumors and the
corresponding EOC-xenografts (nine cases) ranged from 0.99 to 0.84, and from 0.92 to 0.84
between the patient tumors and the 20 not-paired EOC-xenograft models.
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