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In The Name of God
Progress on Biomarkers of
Cancer Diagnosis and
Prognosis
Majid Kheirollahi
Ph.D, Medical Genetics
Department of Medical Genetics
Isfahan University of Medical Sciences
Biomarker
(Tumor marker / Mol marker / Signature marker)
Definitions:
National Cancer Institute: A biological molecule found in blood,
other body fluids or tissue that is sign of a normal or abnormal
process or disease.
NIH, “a characteristic that is objectively measured and evaluated
as an indicator of normal biological processes, pathogenic
processes, or pharmacologic responses to a therapeutic
intervention.
May be a molecule secreted by a tumor or a specific response of
the body to the presence of cancer
Expanding Interest in Biomarkers
Correlation: a biomarker vs a disease or status of a disease
Do not need understand functions
Detection: Detection of a particular marker is important
Validation: Build statistical correlation – large number of samples
Validation: sensitivity and specificity
Validation: Stand alone vs along with other markers
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History of Cancer Biomarker Discovery
The first cancer biomarker : the light chain of immunoglobulin in
urine (identified in 75% of patients with myeloma)
From 1930 to 1960, scientists identified numerous hormones,
enzymes and other proteins
The modern era of monitoring malignant disease, however, began in
the 1960s with the discovery of alfa-fetoprotein and
carcinoembryonic antigen (CEA).
In 1980, prostate-specific antigen (PSA), considered one of the best
cancer markers, was discovered
Biomarkers: Examples
 Metals & Minerals
 Gases
 Steroids & Hormones
 Viruses & Bacterias
 DNA
 RNA
 Proteins
An Ideal Biomarker Must be;
According to FDA an ideal biomarker should be specific, sensitive, simple and
inexpensive.
It should be used in standard biological sources such as serum and urine as
the basis of measurement.
 Minimally invasive, easily measurable
 Used in confirming the diagnosis
 Used in predicting the adverse events, and clinical outcomes that will appear
in the future
Biomarkers and Individualized Medicine
Correlation: a biomarker vs a disease or status of a disease
Do not need understand functions
Detection: Detection of a particular marker is important
Validation: Build statistical correlation – large number of samples
Validation: sensitivity and specificity
Validation: Stand alone vs along with other markers
Golden Time of Biomarkers Application
Detection of biomarker
Detection of biomarker
Quantitative
Qualitative
a link between exist of a marker and disease
Biomarkers with Clinical Application
70 prognosis genes are involved in all
aspects of tumor cell biology
proliferation
angiogenesis
intravasation, survival, extravasation
adhesion to extracellular matrix
local invasion
adhesion to extracellular matrix
proliferation
angiogenesis
Genes of unknown function (25)
Strategies for Biomarker Discovery
Hypothesis-driven
approach
Search for difference
approach
Mechanism based
((Grounds up))
((Top down))
Biomarker Development Pipeline
Should have great sensitivity, specificity, and accuracy in reflecting total
disease burden. A tumor marker should also be prognostic of outcome and
predictive of tumor recurrence and effectiveness of anti-cancer treatments.
Phases of Evaluation of Biomarkers
In 2002, the National Cancer Institute’s ‘Early Detection Research Network’
developed a five-phase approach to systematic discovery and evaluation of
biomarkers
Phase I refers to preclinical studies. Biomarkers are discovered through
knowledge-based gene selection, gene expression profiling or protein
profiling to distinguish cancer and normal samples
Phase II To document clinical usefulness, firstly, such assays need to be
validated for reproducibility and shown to be portable among different
laboratories.
Phases of Evaluation of Biomarkers
Phase III & Phase IV, an investigator evaluates the sensitivity and specificity of
the test for the detection of diseases that have yet to be detected clinically.
It is usually time-consuming and expensive to collect these samples with high
quality; therefore, phase III should consist of large cohort studies
Phase V evaluates the overall benefits and risks of the new diagnostic test on
the screened population. This again requires a large-scale study over a long
time period and could also be prohibitively expensive.
Phases IV is necessary to evaluate benefits and risks of the use of a
biomarker in screening and detection.
Risk Assessment
Some genetic mutations increase the risk of eventually
developing cancer. These biomarkers are said to predispose us
to cancer. Examples of biomarkers associated with an increased
risk of cancer are the BRCA1 and BRCA2 genes.
Harmful mutations in these genes can increase the chance of
developing breast and other cancers in both men and women.
Individuals with these mutations can obtain more frequent
screenings that may detect cancer in its early stages when it is
more readily treated.
Diagnosis
Prostate Cancer Diagnosis with PSA
Cancer of the prostate does not cause any symptoms until it is
locally advanced or metastatic. PSA is also found in the
cytoplasm of benign prostate cells.
There is a correlation between elevated PSA and prostate
cancer.
Diagnosis of PSA for prostate cancer in the most time means
measurement of the PSA in serum samples.
Based on these data, PSA testing was approved by the US FDA
for the screening and early detection of prostate cancer.
Diagnosis
Cancer biomarkers can also be useful in establishing a specific
diagnosis. This is particularly the case when there is a need to
determine whether tumors are of primary or metastatic origin.
To make this distinction, researchers can screen the chromosomal
alterations found on cells located in the primary tumor site against
those found in the secondary site.
If the alterations match, the secondary tumor can be identified as
metastatic; whereas if the alterations differ, the secondary tumor can
be identified as a distinct primary tumor.
Prognosis
Prognosis refers to the natural course of the disease in the absence of
treatment. Some cancers are more aggressive than others and knowing
this can help guide treatment.
If a biomarker can help distinguish a cancer that is likely to grow rapidly
from one that is likely to grow slowly, then patients with these two types
of cancers might receive different treatments.
An example of a potential prognostic biomarker is Telomerase in brain
tumors.
Prediction of Treatment Response
Approximately one fourth of all breast cancers have too many copies of the
HER2 gene, which go on to produce too much HER2 protein.
Another aspect of HER2/neu overexpression is that it causes breast cancers
to grow and divide more quickly.
For this reason, over-expression of this gene is
also used as a prognostic biomarker whose
presence indicates a more aggressive cancer.
HER-2/neu is an example of a biomarker with
more than one use.
20
Therapy Target Her-2
HER2-positive metastatic breast cancer have a more aggressive disease, greater
likelihood of recurrence, poorer prognosis and decreased survival.
Herceptin
Herceptin binds to HER2-positive cancer cells and may block them
from dividing and growing.
Herceptin attaches to the HER2-positive cancer cells and may
signal the body's immune system to destroy the cell.
Herceptin can also conjugated with chemotherapy (paclitaxel)
to destroy HER2-positive cancer cells.
Pharmacokinetics or Predicting Drug Doses
Decreased metabolism of a certain drug causes high levels
of the drug to accumulate in the body.
This may cause the drug’s effects to be more intense and
prolonged than expected, and may lead to more toxic side
effects.
In other words, if we have mutations that affect drug
metabolism, we may experience worse side effects than
people without these mutations
Example of Pharmacokinetics
In 2008, three drugs (insulin, digoxin and warfarin) in the US
were responsible for one in three emergency department
visits related to medication among older adults.
For warfarin alone, overdoses resulted in 40/000 visits to US
emergency rooms at an annual cost of USD 2 billion.
Mutations in two genes (VKORC1 and CYP2C9) account for
30-50% of individual response to warfarin.
Monitoring treatment response
Biomarkers can also be used to monitor how well a
treatment is working.
An example of this is the use of a protein biomarker called
S100-beta in monitoring the response of malignant
melanoma.
Response to treatment is associated with reduced levels of
S100-beta in the blood of individuals with melanoma.
Recurrence
Oncotype DX® is an example of a test used to predict the
likelihood of breast cancer recurrence.
This test is specified for use in women with early-stage
(Stage I or II), node-negative breast cancer who will be
treated with hormone therapy.
26
Oncotype DX ®
Oncotype DX ® evaluates a panel of 21 genes in cells
taken from a tumor biopsy.
The results of the test are given in the form of a recurrence
score that indicates the likelihood of distant recurrence at
10 years: the higher the score, the more likely the tumor is
to recur.
This test can also be used to help predict who will benefit
from chemotherapy.
26
How Do We Assess Risk
in Breast Cancer Patients?
Classic Pathological
Criteria
Lymph Node
Status
Tumor
Size
Oncotype DX®
Age
Tumor
Grade
New tools in the
Genomic Era…
ER/PR
HER2
Oncotype DX 21-gene recurrence score
16 cancer genes and 5 reference genes make up the Oncotype DX
gene panel. The expression of these genes is used to calculate the
recurrence score:
PROLIFERATION
Ki-67
STK15
Survivin
Cyclin B1
MYBL2
REFERENCE
Beta-actin
GAPDH
RPLPO
GUS
TFRC
ESTROGEN
ER
PR
Bcl2
SCUBE2
RS =
BAG1
GSTM1
CD68
HER2
GRB7
HER2
INVASION
Stromelysin 3
Cathepsin L2
+ 0.47 x HER2 Group Score
- 0.34 x ER Group Score
+ 1.04 x Proliferation Group Score
+ 0.10 x Invasion Group Score
+ 0.05 x CD68
- 0.08 x GSTM1
- 0.07 x BAG1
Paik et al. N Engl J Med.
2004;351:2817-26.
Non-coding RNA: the NA formerly known as “junk”
RNA Transcripts
Protein-coding mRNA
Non-coding RNA Transcripts
Regulatory RNA
miRNA
siRNA
piRNA
Anti-sense RNA
•
•
•
•
Transcription/chromatin structure regulators
Translational regulators
Protein function modulators
RNA/Protein localization regulators
snoRNAs
Housekeeping RNAs
•tRNA
•rRNA
•snRNA
•tmRNA
•Rnase P RNA
•vRNAs
•gRNAs
•MRP RNA
•SRP RNAs
•Telomerase RNA
NC-RNAs compose majority of transcription in complex genomes
Unique MicroRNA Profile in Lung Cancer
Diagnosis and Prognosis
• miRNAs are small non-coding RNAs which
play key roles in regulating the translation
and degradation of mRNAs
• Genetic and epigenetic alteration may
affect miRNA expression, thereby
leading to aberrant target gene(s)
expression in cancers
• Yanaihara et al, Cancer Cell, 2006:
- miRNA profiles of 104 pairs of primary
lung cancers and corresponding noncancerous lung tissues were analyzed by
miRNA microarrays
- 43 miRNAs showed statistical differences
The role of microRNAs in cancer diagnosis
● Aberrant miRNA expression offered new clues to pancreatic
tumorigenesis and might provide diagnostic biomarkers for
pancreatic cancer.
● With the application of RT-PCR, it was shown that the aberrantly
expressed miR-221, miR-301 and miR-376a were localized to
pancreatic cancer cells but not to stroma or normal acini or ducts.
Lee EJ, et al. Expression profiling identifies microRNA signature in pancreatic cancer.
Int J Cancer 2007, 120:1046-1054.
Cho WC. MicroRNAs: potential biomarkers for cancer diagnosis, prognosis and targets for
therapy. Int J Biochem Cell Biol 2010.
Cho WC. MicroRNAs in cancer - from research to therapy. Biochim Biophys Acta - Rev Cancer
2010;1805(2):209-217.
The role of microRNAs in cancer prognosis
●Reduced let-7 miRNA expression in lung cancer was
significantly associated with shorter postoperative survival.
●Overexpression of let-7 miRNA in A549 lung adenocarcinoma
cell line inhibited lung cancer cell growth in vitro.
Takamizawa J, et al. Reduced expression of the let-7 microRNAs in human lung
cancers in association with shortened postoperative survival. Cancer Res 2004,
64:3753-3756.
The role of microRNAs in cancer prognosis
● The expression pattern of miRNAs in pancreatic cancer were
compared with those of normal pancreas and chronic
pancreatitis using miRNA microarrays.
● Differentially expressed miRNAs were identified which could
differentiate pancreatic cancer from normal pancreas,
chronic pancreatitis, or both.
● High expression of miR-196a-2 was found to predict poor
survival of more than 24 months.
Bloomston M, et al. MicroRNA expression patterns to differentiate pancreatic
adenocarcinoma from normal pancreas and chronic pancreatitis. JAMA 2007,
297:1901-1908.
microRNAs
Tumorigenesis
miR-9
Neuroblastoma
miR-10b
Breast cancer
miR-15, miR-15a
Leukemia, pituitary adenoma
miR-16, miR-16-1
Leukemia, pituitary adenoma
miR-17-5p, miR-17-92
Lung cancer, lymphoma
miR-20a
Lymphoma, lung cancer
miR-21
Breast cancer, cholangiocarcinoma, head & neck
cancer, leukemia
miR-29, miR-29b
Leukemia, cholangiocarcinoma
miR-31
Colorectal cancer
miR-34a
Pancreatic cancer
miR-96
Colorectal cancer
miR-98
Head & neck cancer
miR-103
Pancreatic cancer
miR-107
Leukemia, pancreatic cancer
miR-125a, miR-125b
Neuroblastoma, breast cancer
miR-128
Glioblastoma
miR-133b
Colorectal cancer
miR-135b
Colorectal cancer
miR-143
Colon cancer
miR-145
Breast cancer, colorectal cancer
miR-146
Thyroid carcinoma
Diagnosis
Prognosis
Pancreatic
cancer
Neuroblastoma
microRNAs
Tumorigenesis
miR-155, has-miR-155
Breast cancer, leukemia, pancreatic cancer
miR-181, imR-181a, imR-181b, imR-181c
Leukemia, glioblastoma, thyroid carcinoma
miR-183
Colorectal cancer
miR-184
Neuroblastoma
miR-193
Gastric cancer
Diagnosis
Lung cancer
miR-196a-2
Pancreatic cancer
miR-221
Glioblastoma, thyroid carcinoma
miR-222
Thyroid carcinoma
miR-223
Leukemia
Pancreatic cancer
miR-301
Pancreatic cancer
miR-376
Pancreatic cancer
let-7, let-7a, let-7a-1, has-let-7a-2, let-7a-3
Prognosis
Lung cancer, colon cancer
Lung cancer
Cho WC. MicroRNAs: potential biomarkers for cancer diagnosis, prognosis and targets for therapy.
Int J Biochem Cell Biol 2010.
Cho WC. OncomiRs: the discovery and progress of microRNAs in cancers. Mol Cancer. 2007;6:60.
Characterizing proteins and DNA at the molecular
level is the key to understanding their function
Functional genomics
t-RNA
mRNA
t-RNA
Ribosome
t-RNA
(....)
Protein
t-RNA
DNA
Genomics
Post Translational
Modifications
X
(....)
X
Proteomics
Active Protein
CHO
PO4
Proteomics: leading biological
science in the 21st century
● Proteomics represents the effort
to establish the identities,
quantities, structures,
biochemical and cellular
functions of all proteins in an
organism, organ, or organelle
● and how these properties vary in
space, time, or physiological
state.
Cho WC. Proteomics – Leading biological science in the 21st century. Science J,
2004; 56(5):14-17.
Cho WC, Cheng CH. Oncoproteomics: current trends and future perspectives.
Expert Rev Proteomics 2007;4(3):401-410.
Traditional vs High-throughput approach
The emergence of proteomics and its
application
DNA
static genome
Transcriptional control
RNA
message variable: transcriptome
Translational control
Protein
product variable: proteome
Post-translational modification
Genome Era
Post-genome Era
Intrinsic factors:
physiological &
pathological
status, …
Sample
preparation
& processing
Cho WC, Cheng CH.
Oncoproteomics:
current trends and
future perspectives.
Expert Rev Proteomics
2007;4(3):401-410.
Extrinsic factors:
environment, pathogens, drug, …
Functional protein
expressed
Automation sample application
ESI-TOF MS
MALDI-TOF MS
Low-throughput
High-throughput
Peptide ions
(MS)
Peptide fragment ions
(MS-MS)
Protein chip,
e.g. SELDITOF MS
ESI: Electrospray ionization
MALDI: Matrix-assisted
laser desorption ionization
Bioinformatics
Experimental or
clinical results
Database interrogation
Protein identification
SELDI: Surface-enhanced
laser desorption ionization
TOF: Time of flight
Validation and application
Biomarker discovery
● Markers can be easily
found by comparing
protein maps.
● SELDI is faster and
more reproducible than
2D PAGE.
● Has been being used to
discover protein
biomarkers of diseases
such as ovarian cancer,
breast cancer, prostate
and bladder cancers.
(Normal)
(Cancer)
Cho WC. Contribution of oncoproteomics to cancer biomarker discovery. Mol
Cancer 2007;6:25.
Measurements
● The digested proteins were measured by Nano LC ESI-Orbitrap
mass spectrometry.
● Fifty centimeter (C18) columns in combination with three hours
time were used to obtain the best possible separation
Analysis of data
Not normally distributed
Progenesis
Clustering
(Partek Genomics Suite 6.5)
+
Parametric
statistic (SPSS)
p<0.01
DATA
Discrete values
Non-parametric
statistic (SPSS)
Mann-Whitney
p<0.01
Un-Supervised Clustering of Samples
(Partek Genomics Suite 6.5)
Proteins as biomarkers
The protein composition may be associated with disease
processes in the organism and thus have potential utility as
diagnostic markers.
• Proteins are closer to the actual disease process,
in most cases, than parent genes
• Proteins are ultimate regulators of cellular function
• Most cancer markers are proteins
• The vast majority of drug targets are proteins
Cho WC. Cancer biomarkers (an overview). In Hayat MA (ed): Methods of cancer
diagnosis, therapy and prognosis. Volume 7. New York, NY: Springer, 5 Jan 2010.
Thanks