DNA Methylation DNA Methylation
and Cancerand CancerShen-Chih Chang, Ph.DShen-Chih Chang, Ph.D
Epi 243Epi 243May 14, 2009May 14, 2009
Presentation OutlinePresentation Outline
Epigenetics and DNA methylationEpigenetics and DNA methylation DNA methylation and CancerDNA methylation and Cancer Techniques of measuring DNA methylationTechniques of measuring DNA methylation
Methylation-Specific PCR (MSP)Methylation-Specific PCR (MSP) Selected results on lung and head and neck cancerSelected results on lung and head and neck cancer
MethyLight Taqman real-time Methylation AssaMethyLight Taqman real-time Methylation Assayy Selected results on bladder cancerSelected results on bladder cancer Selected results on liver cancerSelected results on liver cancer
EpigeneticsEpigenetics The study of heritable changes of DNA, not involving cThe study of heritable changes of DNA, not involving c
hanges in DNA sequence, that regulate gene expressiohanges in DNA sequence, that regulate gene expression. n. Classic genetics alone cannot explain the diversity of phenotyClassic genetics alone cannot explain the diversity of phenoty
pes within a population.pes within a population. Identical twins or cloned animals have different phenotypes aIdentical twins or cloned animals have different phenotypes a
nd susceptibilities to diseases.nd susceptibilities to diseases.
Epigenetics provides additional instructions on how, wEpigenetics provides additional instructions on how, where, and when the genetic information should be usehere, and when the genetic information should be used. d.
Epigenetics controls gene expression in two main ways:Epigenetics controls gene expression in two main ways: Chemically alteration of DNA: DNA methylationChemically alteration of DNA: DNA methylation Modification of histones: chromatin structure modulationModification of histones: chromatin structure modulation
Epigenetic MechanismsEpigenetic Mechanisms
Qiu J, 2006
Mapping chromosomal regions with differential DNA methylation in Monozygous twins by using comparative genomic hybridization for methylated DNA
Fraga M. F. et.al. PNAS 2005;102:10604-10609
©2005 by National Academy of Sciences
DNA MethylationDNA Methylation
Chemical modification of DNAChemical modification of DNA Addition of a methyl group to the number 5 Addition of a methyl group to the number 5
carbon of the cytosine, to convert cytosine to carbon of the cytosine, to convert cytosine to 5-methylcytosine.5-methylcytosine.
In humans, DNA methylation occurs in a cytIn humans, DNA methylation occurs in a cytosine which is immediately followed by a guosine which is immediately followed by a guanine (dinucleotide CpGs).anine (dinucleotide CpGs).
CpG Sites and CpG CpG Sites and CpG islandsislands
CpG sites are not randomly distributed in the CpG sites are not randomly distributed in the genome - the frequency of CpG sites in human genome - the frequency of CpG sites in human genomes is 1%, which is less than the expectegenomes is 1%, which is less than the expected (~4-6%). d (~4-6%).
Around 60-90% of CpGs are methylated in maAround 60-90% of CpGs are methylated in mammals. DNA methylation frequently occurs in mmals. DNA methylation frequently occurs in repeated sequences, and may help to suppress repeated sequences, and may help to suppress junk DNA and prevent chromosomal instabilitjunk DNA and prevent chromosomal instability. y.
Unmethylated CpGs are grouped in clusters caUnmethylated CpGs are grouped in clusters called “CpG islands” which tend to be located lled “CpG islands” which tend to be located in the promoter regions of many genes.in the promoter regions of many genes.
Function of DNA Function of DNA MethylationMethylation
In humans, DNA is methylated by three enzymes, DNA In humans, DNA is methylated by three enzymes, DNA methyltransferase 1, 3a, and 3b (DNMT1, DNMT3a, DNmethyltransferase 1, 3a, and 3b (DNMT1, DNMT3a, DNMT3b).MT3b).
DNMT3a and 3b are the DNMT3a and 3b are the de novode novo methyltransferases th methyltransferases that set up DNA methylation patterns early in developmeat set up DNA methylation patterns early in development. nt.
DNMT1 is the maintenance methyltransferase that is rDNMT1 is the maintenance methyltransferase that is responsible for copying DNA methylation patterns to thesponsible for copying DNA methylation patterns to the daughter strands during DNA replication. e daughter strands during DNA replication.
DNA methylation is important in:DNA methylation is important in: Transcriptional gene silencingTranscriptional gene silencing Maintain genome stabilityMaintain genome stability Embryonic developmentEmbryonic development Genomic imprintingGenomic imprinting X chromosome inactivationX chromosome inactivation
DNA Methylation and DNA Methylation and CancerCancer
Hypomethylation – decreased methylation Hypomethylation – decreased methylation levelslevels A lower level of DNA methylation in tumors as A lower level of DNA methylation in tumors as
compared to their normal-tissue counterparts was compared to their normal-tissue counterparts was one of the first epigenetic alterations to be found one of the first epigenetic alterations to be found in human cancer. (Feinberg AP, et al., 1983). in human cancer. (Feinberg AP, et al., 1983).
Global hypomethylation of DNA sequences that Global hypomethylation of DNA sequences that are normally heavily methylated may result inare normally heavily methylated may result in
Chromosomal instability Chromosomal instability Increased transcription from transposable elements Increased transcription from transposable elements An elevated mutation rate due to mitotic recombinationAn elevated mutation rate due to mitotic recombination
Promoter hypomethylation of proto-oncogenes will Promoter hypomethylation of proto-oncogenes will activate the repressed gene expressionactivate the repressed gene expression
DNA Methylation and DNA Methylation and CancerCancer
Hypermethylation – increased methylation lHypermethylation – increased methylation levelsevels Promoter hypermethylation can suppress gene Promoter hypermethylation can suppress gene
expression in two ways:expression in two ways: Methylated DNA may itself impede the binding of traMethylated DNA may itself impede the binding of tra
nscriptional proteins to the gene nscriptional proteins to the gene Methylated DNA may be bound by proteins which can Methylated DNA may be bound by proteins which can
modify histones to form compact, inactive chromatin.modify histones to form compact, inactive chromatin. Promoter hypermethylation of tumor-suppressoPromoter hypermethylation of tumor-suppresso
r genes is a major event in the origin of many car genes is a major event in the origin of many cancers.ncers.
The profiles of hypermethylation of the CpG islaThe profiles of hypermethylation of the CpG islands are specific to the cancer type.nds are specific to the cancer type.
Baylin et al. 2001; Jones et al. 2002
Laird PW, 1997
Das PM 2004
Das PM 2004
Factors associated with Factors associated with DNA MethylationDNA Methylation
AgingAging Nutrient intakeNutrient intake Genetic Genetic
polymorphismspolymorphisms Metal exposureMetal exposure Tobacco SmokingTobacco Smoking Alcohol DrinkingAlcohol Drinking
Application of DNA Methylation Application of DNA Methylation MeasurementMeasurement
Early diagnosis –Early diagnosis – Detection of CpG-island hypermethylation in Detection of CpG-island hypermethylation in
biological fluids (serum/plasma)biological fluids (serum/plasma) Prognosis –Prognosis –
Hypemethylation of specific genesHypemethylation of specific genes Whole DNA methylation profilesWhole DNA methylation profiles
Prediction –Prediction – CpG island hypermethylation as a marker of CpG island hypermethylation as a marker of
response to chemotherapyresponse to chemotherapy Prevention –Prevention –
Developing DNMTs inhibitors as Developing DNMTs inhibitors as chemopreventive drugs to reactive silenced chemopreventive drugs to reactive silenced genes genes
Techniques of Measuring Techniques of Measuring Gene-Specific Gene-Specific
HypermethylationHypermethylation Methylation Specific PCR (MSP)Methylation Specific PCR (MSP) MethyLight Taqman Real-Time MethyLight Taqman Real-Time
Methylation AssayMethylation Assay
Methylation Specific PCR Methylation Specific PCR (MSP)(MSP)
•DNA ModificationDNA Modification• C UC U• CCMM C C
•Two set of primersTwo set of primers•MethylatedMethylated•UnmethylatedUnmethylated
•Positive control Positive control (Universal (Universal Methylated DNA)Methylated DNA)
•Negative control Negative control (H(H22O)O)
Results from the MSPResults from the MSP•p1p1
66
•MGMTMGMT •GSTP1GSTP1
Selected Results on Lung Selected Results on Lung and and
Head and Neck CancerHead and Neck CancerShu-Chun Chuang, Ph.D
Aim:Aim:To evaluate the associations between lunTo evaluate the associations between lung and head and neck cancer and promoteg and head and neck cancer and promoter-region methylation of selected genes, inr-region methylation of selected genes, including P16INK4a, MGMT , and GSTP1 gecluding P16INK4a, MGMT , and GSTP1 genes in buccal cell DNA in a population-banes in buccal cell DNA in a population-based case-control study in Los Angeles coused case-control study in Los Angeles county.nty.
Materials and MethodsMaterials and Methods Study design: population-based case-control studyStudy design: population-based case-control study
Subject selection criteria: Cases were newly diagnosed Subject selection criteria: Cases were newly diagnosed and pathologically confirmed. Controls were matched and pathologically confirmed. Controls were matched to cases on age, gender, and neighborhood.to cases on age, gender, and neighborhood.
Eligibility:Eligibility: Current resident of Los Angeles CountyCurrent resident of Los Angeles County 18-65 during the observation period, 1999-200418-65 during the observation period, 1999-2004 either speak English or Spanish or have translators either speak English or Spanish or have translators
availableavailable have no other primary cancers (cases)have no other primary cancers (cases) have no history of lung or head and neck cancers have no history of lung or head and neck cancers
(controls)(controls)
Biological samples: buccal cell samples were collected Biological samples: buccal cell samples were collected during the interviewduring the interview
Response RateResponse Rate
Eligible Interviewed (%) Buccal Biospecimen (%)
Control 1540 1040 (67.5) 928 (89.2)
Lung 1577 611 (38.7) 544 (89.0)
Oral 584 303 (51.9) 195 (64.4)
Pharynx 238 100 (42.0) 77 (77.0)
Larynx 226 90 (39.8) 79 (87.8)
Esophagus 316 108 (34.2) 97 (89.8)
Cancer Cases Reason of non-participation
Lung H & N (1) The patients died before we contacted them. 25% 10% (2) Incorrect addresses. 14% 18% (3) The patients were too ill to get interviewed. 5% 4% (4) The patients were not willing to participate. 16% 21% (5) Physicians refused our requests. 1% 1%
Main Effect of p16 Main Effect of p16 HypermethylationHypermethylation
P16P16HypermethylaHypermethyla
tiontion
ControControlsls
N (%)N (%)
LungLung Head and NeckHead and Neck
N (%)N (%) Crude ORCrude OR(95% CI)(95% CI)
Adjusted Adjusted OROR11
(95% CI)(95% CI)
N (%)N (%) Crude ORCrude OR(95% CI)(95% CI)
Adjusted Adjusted OROR22
(95% CI)(95% CI)
NoNo 769 769 (8(84)4)
433 433 ((8811))
1.001.00 1.001.00 293 293 (8(84)4)
1.001.00 1.001.00
YesYes 146 146 (1(16)6)
100 100 ((1199))
1.22 (0.92-1.22 (0.92-1.61)1.61)
1.31 (0.94-1.31 (0.94-1.83)1.83)
57 57 (1(16)6)
1.03 (0.73-1.03 (0.73-1.43)1.43)
1.03 (0.72-1.03 (0.72-1.48)1.48)
1. Adjusted for age, sex, race, and pack-years of smoking.
2. Adjusted for age, sex, race, pack-years of smoking, and drink-years of alcohol consumption
Main Effect of GSTP1 Main Effect of GSTP1 HypermethylationHypermethylation
GSTP1GSTP1HypermethylatHypermethylat
ionion
ControControlsls
N (%)N (%)
LungLung Head and NeckHead and Neck
N (%)N (%) Crude ORCrude OR(95% CI)(95% CI)
Adjusted ORAdjusted OR11
(95% CI)(95% CI)N (%)N (%) Crude ORCrude OR
(95% CI)(95% CI)Adjusted ORAdjusted OR22
(95% CI)(95% CI)
NoNo 675 675 (88)(88)
354 354 (85)(85)
1.001.00 1.001.00 254 254 (86)(86)
1.001.00 1.001.00
YesYes 96 (12)96 (12) 61 (15)61 (15) 1.21 (0.86-1.21 (0.86-1.71)1.71)
1.17 (0.78-1.17 (0.78-1.75)1.75)
40 (14)40 (14) 1.11 (0.75-1.11 (0.75-1.65)1.65)
1.04 (0.67-1.04 (0.67-1.62)1.62)
1.Adjusted for age, sex, race, and pack-years of smoking.2.Adjusted for age, sex, race, pack-years of smoking, and drink-years of alcohol consumption
Main Effect of MGMT Main Effect of MGMT HypermethylationHypermethylation
MGMTMGMTHypermethylatHypermethylat
ionion
ControControlsls
N (%)N (%)
LungLung Head and NeckHead and Neck
N (%)N (%) Crude ORCrude OR(95% CI)(95% CI)
Adjusted ORAdjusted OR11
(95% CI)(95% CI)N (%)N (%) Crude ORCrude OR
(95% CI)(95% CI)Adjusted ORAdjusted OR22
(95% CI)(95% CI)
NoNo 721 721 (82)(82)
380 380 (77)(77)
1.001.00 1.001.00 250 250 (76)(76)
1.001.00 1.001.00
YesYes 157 157 (18)(18)
112 112 (23)(23)
1.35 (1.03-1.35 (1.03-1.78)1.78)
1.19 (0.86-1.19 (0.86-1.65)1.65)
78 (24)78 (24) 1.43 (1.05-1.43 (1.05-1.95)1.95)
1.34 (0.96-1.34 (0.96-1.88)1.88)
1.Adjusted for age, sex, race, and pack-years of smoking.2.Adjusted for age, sex, race, pack-years of smoking, and drink-years of alcohol consumption
MGMTMGMTHypermethylatHypermethylat
ionion
ControControlsls
N (%)N (%)
PharynxPharynx
N (%)N (%) Crude ORCrude OR(95% CI)(95% CI)
Adjusted ORAdjusted OR(95% CI)(95% CI)
NoNo 721 721 (82)(82)
38 38 (68)(68)
1.001.00 1.001.00
YesYes 157 157 (18)(18)
18 18 (32)(32)
2.18 (1.21-2.18 (1.21-3.91)3.91)
2.00 (1.09-2.00 (1.09-3.68)3.68)
Adjusted for age, sex, race, pack-years of smoking, and drink-years of alcohol consumption
Stratified by Site
MethyLight Taqman Methylation MethyLight Taqman Methylation AssayAssay
Real-Time PCRReal-Time PCR Real-time PCR is a PCR-based method
using fluorescent molecules to directly measure the reaction while amplification is taking place.
Data are collected throughout the PCR process rather than the end of the process.
It measures the point in time when amplification of a target is first detected during cycling rather than by the amount of target accumulated at the end of PCR.
Can be used to achieve both qualitative and quantitative measurements.
DenaturationPrimer Annealing
Elongation
5’ 3’
5’3’5’ 3’
5’3’
5’ 3’
5’3’5’
5’
Taq
Taq
Repeat
Traditional Standard Traditional Standard PCRPCR
In theory, product accumulation is proportional to 2n, where n is the number of amplification cycle repeats
However, in reality...However, in reality...
• A linear increase follows exponential
•
Eventually plateaus
Cycle #
Theoretical
Real Life
Log
Targ
et
DN
A
Limitation in standard PCRLimitation in standard PCR
Amplification is exponential, but the Amplification is exponential, but the exponential increase is limited:exponential increase is limited:
Geometric
linear
plateau
Standard PCR as Standard PCR as endpointendpoint
Standard PCR as Standard PCR as endpointendpoint
Identical reactions will have very different final amounts of fluorescence at endpoint
•The point at which the fluorescence rises appreciably above threshold is called CT
•Identical reactions will have identical CT values
Real-Time PCRReal-Time PCR
CT
Threshold
How to measure DNA How to measure DNA concentration?concentration?
How to measure DNA How to measure DNA concentration?concentration?
Setup for MethyLight MSPSetup for MethyLight MSP Modified DNA as templatesModified DNA as templates Methylation sequence specific forward Methylation sequence specific forward
and backward primersand backward primers Taqman Probes: 5’-FAM---------TEMRA-3’Taqman Probes: 5’-FAM---------TEMRA-3’ Taqman Universal PCR Master MixTaqman Universal PCR Master Mix Negative control contains PCR reagents Negative control contains PCR reagents
but without DNA – ddHbut without DNA – ddH22OO Replicate wells -- using two or more Replicate wells -- using two or more
replicate reactions per sample to ensure replicate reactions per sample to ensure statistical significance.statistical significance.
A calibrator -- The sample used as the basis A calibrator -- The sample used as the basis for comparative results. for comparative results. A universal methylated positive control was A universal methylated positive control was
used in this study as a calibrator. used in this study as a calibrator. An endogenous control gene -- A gene An endogenous control gene -- A gene
present at a consistent expression level in present at a consistent expression level in all experimental samples. An endogenous all experimental samples. An endogenous gene is used as an internal control of the gene is used as an internal control of the difference amount of input DNA.difference amount of input DNA. ACTB gene without CpG dinucleotides was used ACTB gene without CpG dinucleotides was used
as endogenous control gene in this study.as endogenous control gene in this study.
Setup for MethyLight MSPSetup for MethyLight MSP
Calibrator
Negative control
Endogenous control gene; others are all target genes
Setup for MethyLight MSPSetup for MethyLight MSP
Analyzing Relative Analyzing Relative Quantification DataQuantification Data
∆∆∆∆CCTT Method Method
∆∆CCT T (sample) = C(sample) = CT T (marker)- C(marker)- CT T (ACTB)(ACTB)
∆∆CCT T (calibrator) = C(calibrator) = CT T (marker)- C(marker)- CT T (ACTB)(ACTB)
∆∆∆∆CCTT = ∆C = ∆CT T (sample) - ∆C(sample) - ∆CT T (calibrator) (calibrator) Relative quantification of methylated 5’-Relative quantification of methylated 5’-
cytosine = Ecytosine = E(-∆∆CT)(-∆∆CT) E: efficiency of amplificationE: efficiency of amplification Assumption: E = 2 for both marker and Assumption: E = 2 for both marker and
endogenous geneendogenous gene
Analyzing Relative Quantification Analyzing Relative Quantification DataData
-- Amplification Plot (linear plot of reporter signal vs cycle nu-- Amplification Plot (linear plot of reporter signal vs cycle number) --mber) --
negative control ACTB gene
Analyzing Relative Analyzing Relative Quantification DataQuantification Data
-- Amplification plot of positive control---- Amplification plot of positive control--
linear plot of reporter signal vs cycle numberlinear plot of reporter signal vs cycle number logarithmic plot of baseline-corrected reporter signal vs. cycle number
Analyzing Relative Analyzing Relative Quantification DataQuantification Data
-- Amplification plot of p16 gene hypermethylation---- Amplification plot of p16 gene hypermethylation--
logarithmic plot of baseline-corrected reporter signal vs. cycle number
After adjusting baseline and threshold, software automatically calculates relative quantity (RQ) of the sample compared to the calibrator
Selected Results on Bladder Selected Results on Bladder CancerCancer
Aim:Aim:
To evaluate the associations To evaluate the associations between between promoter hypermethylation status of promoter hypermethylation status of genes involved in bladder tumorigenesis genes involved in bladder tumorigenesis (including P16INK4a, P14ARF, APC, (including P16INK4a, P14ARF, APC, CDH1, RASSF1A, MGMT, and GSTP1) in CDH1, RASSF1A, MGMT, and GSTP1) in WBC, NBC, CIS, and, cancer tissues from WBC, NBC, CIS, and, cancer tissues from 73 bladder cancer patients.73 bladder cancer patients.
Yu-Ching Kelly Yang, Ph.D
Materials and MethodsMaterials and Methods Hospital-based case-only studyHospital-based case-only study Memorial Sloan-Kettering Cancer CenterMemorial Sloan-Kettering Cancer Center Recruitment period: Oct 1993 to June 1997Recruitment period: Oct 1993 to June 1997 Cases selection criteria:Cases selection criteria:
Newly diagnosed and pathologically confirmed blNewly diagnosed and pathologically confirmed bladder cancer casesadder cancer cases
In stable medical conditionIn stable medical condition Have lived in the US for at least one yearHave lived in the US for at least one year
Fresh bladder tissues were obtained from radFresh bladder tissues were obtained from radical cystectomy ical cystectomy
Study PopulationStudy PopulationPatients with tissue blocks
N = 152
Only have cancerous tissuesN = 33
Did not conform to pathological criteria
N = 46
Patients with cancerous tissue andnon-cancerous tissue (NBC)
N = 73
Proportion of methylation detected in seven tumor-related genes in white blood cells (WBC), in situ (CIS), non-cancerous (NBC), and cancerous tissue specimens of the bladder cancer patients. WBC CIS NBC Cancer
Gene analyzedMethylation
detected
analyzedMethylation
detected
analyzedMethylation
detected
analyzedMethylation
detected
P16 0/11 0.00 0/6 0.00 0/73 0.00 21/73 0.29
APC 0/11 0.00 3/6 0.5 21/73 0.29 42/73 0.58
MGMT 0/11 0.00 0/6 0.00 0/73 0.00 3/73 0.04
RASSF1A 1/11 0.09 2/6 0.33 10/73 0.14 28/73 0.38
CDH1 2/11 0.18 4/6 0.67 22/73 0.30 45/73 0.62
GSTP1 0/11 0.00 0/6 0.00 1/73 0.01 2/73 0.03
ARF 0/11 0.00 0/6 0.00 0/73 0.00 0/73 0.00
WBC:white blood cell; CIS: carcinoma in situ; NBC: epithelium showing no remarkable histological change
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
WBC NBC CIS Cancer
Av
era
ge
nu
mb
er
of
me
thy
late
d g
en
e
The mean and standard deviation of average number of The mean and standard deviation of average number of methylated genes in white blood cells (WBC), carcinoma in situ methylated genes in white blood cells (WBC), carcinoma in situ (CIS), epithelium showing no remarkable histological change (CIS), epithelium showing no remarkable histological change
(NBC) and cancer tissues of bladder cancer patients (NBC) and cancer tissues of bladder cancer patients
age
(>=65 vs. <65 years)
Gender
(male vs. female)
Cigarette smoking
(ever vs. never)
Alcohol drinking
(ever vs. never) Gene
Y (%) N (%) P-value Y (%) N (%) P-value Y (%) N (%) P-value Y (%) N (%) P-value
Promoter hypermethylation
P16
normal 31 66 21 81 37 71 12 67 43 74 3 38 33 73 11 58
hypermethylation 16 34 5 19 0.186 15 29 6 33 0.721 15 26 5 63 0.048 12 27 8 42 0.227
APC
normal 28 60 19 73 35 67 10 56 39 67 5 63 28 62 14 74
hypermethylation 19 40 7 27 0.252 17 33 8 44 0.372 19 33 3 38 0.790 17 38 5 26 0.381
MGMT
normal 45 96 25 96 49 94 18 100 56 97 8 100 43 96 19 100
hypermethylation 2 4 1 4 0.933 3 6 0 0.980 2 3 0 0.983 2 4 0 0.983
RASSF1A
normal 34 72 19 73 36 69 15 83 44 76 5 63 34 76 14 74
hypermethylation 13 28 7 27 0.946 16 31 3 17 0.254 14 24 3 38 0.423 11 24 5 26 0.875
CDH1
normal 26 55 17 65 30 58 11 61 35 60 3 38 27 60 10 53
hypermethylation 21 45 9 35 0.404 22 42 7 39 0.800 23 40 5 63 0.232 18 40 9 47 0.586
No. of methylated genes
none 19 40 13 50 21 40 9 50 27 47 1 13 21 47 6 32
at least one 28 60 13 50 0.431 31 60 9 50 0.479 31 53 7 88 0.101 24 53 13 68 0.268
The association between hypermethylation in promoter-region of The association between hypermethylation in promoter-region of tumor-related genes and environmental exposures, including tumor-related genes and environmental exposures, including
cigarette smoking and alcohol drinkingcigarette smoking and alcohol drinking
Stage
(>=3a vs. <3a)
Lymph node metastatsis
(yes vs. no)
Vascular invasion
(yes vs. no)
TP53 mutation
(mutated vs. normal) Characteristics
Y (%) N (%) P-value Y (%) N (%) P-value Y (%) N (%) P-value Y (%) N (%) P-value
Promoter hypermethylation
P16
normal 34 69 15 71 22 71 27 69 23 62 25 78 23 66 24 75
hypermethylation 15 31 6 29 0.864 9 29 12 31 0.875 14 38 7 22 0.155 12 34 8 25 0.408
APC
normal 30 61 15 71 22 71 23 59 26 70 19 59 27 77 17 53
hypermethylation 19 39 6 29 0.416 9 29 16 41 0.300 11 30 13 41 0.345 8 23 15 47 0.042
MGMT
normal 46 94 21 100 30 97 37 95 35 95 31 97 34 97 30 94
hypermethylation 3 6 0 0.979 1 3 2 5 0.699 2 5 1 3 0.647 1 3 2 6 0.513
RASSF1A
normal 34 69 17 81 24 77 27 69 27 73 24 75 23 66 28 88
hypermethylation 15 31 4 19 0.323 7 23 12 31 0.446 10 27 8 25 0.849 12 34 4 13 0.044
CDH1
normal 25 51 16 76 18 58 23 59 17 46 23 72 22 63 18 56
hypermethylation 24 49 5 24 0.056 13 42 16 41 0.939 20 54 9 28 0.032 13 37 14 44 0.582
No. of methylated genes
none 18 37 12 57 14 45 16 41 10 27 19 59 15 43 14 44
at least one 31 63 9 43 0.118 17 55 23 59 0.728 27 73 13 41 0.008 20 57 18 56 0.941
The association between hypermethylation in promoter-region of The association between hypermethylation in promoter-region of six tumor-related gene and clinicopathological factors six tumor-related gene and clinicopathological factors
Overall survival Disease-specific survival Progression-free survival
No. D HRa 95%CI D HRa 95%CI D HRa 95%CI
P16 hypermethylation
Yes 49 38 1.00 ref 30 1.00 ref 13 1.00 ref
No 21 17 1.18 ( 0.66- 2.12) 13 1.07 ( 0.55- 2.07) 5 0.97 ( 0.34- 2.77)
P-chisq 0.580 0.847 0.953
APC hypermethylation
Yes 45 35 1.00 ref 26 1.00 ref 12 1.00 ref
No 25 20 0.84 ( 0.47- 1.49) 17 0.93 ( 0.49- 1.78) 6 0.73 ( 0.26- 2.02)
P-chisq 0.547 0.836 0.540
MGMT hypermethylation
Yes 67 52 1.00 ref 40 1.00 ref 17 1.00 ref
No 3 3 1.34 ( 0.41- 4.42) 3 1.64 ( 0.49- 5.46) 1 1.18 ( 0.15- 9.20)
P-chisq 0.627 0.421 0.871
RASSF1A hypermethylation
Yes 51 40 1.00 ref 31 1.00 ref 12 1.00 ref
No 19 15 1.10 ( 0.59- 2.04) 12 1.19 ( 0.59- 2.39) 6 1.37 ( 0.49- 3.84)
P-chisq 0.774 0.630 0.552
CDH1 hypermethylation
Yes 41 33 1.00 ref 26 1.00 ref 8 1.00 ref
No 29 22 0.89 ( 0.50- 1.59) 17 0.82 ( 0.43- 1.58) 10 1.41 ( 0.52- 3.85)
P-chisq 0.693 0.552 0.503
No. of methylated genes
none 30 23 1.00 ref 18 1.00 ref 6 1.00 ref
at least one 40 32 1.19 ( 0.67- 2.11) 25 1.12 ( 0.59- 2.13) 12 1.41 ( 0.50- 3.99)
P-chisq 0.545 0.731 0.512
HRa: hazard ratio adjusted for age, gender, and stage
The association between hypermethylation in six tumor-related The association between hypermethylation in six tumor-related genes and survival time genes and survival time
Selected Results on Liver Selected Results on Liver CancerCancer
Aim:Aim: To evaluate the associations between HCC To evaluate the associations between HCC
and promoter-region methylation of and promoter-region methylation of selected genes, including APC, CDH1, selected genes, including APC, CDH1, P16INK4a, and MGMT genes in peripheral P16INK4a, and MGMT genes in peripheral blood DNA in a Chinese population. Also, to blood DNA in a Chinese population. Also, to examine the associations of examine the associations of hypermethylation with age, gender, tobacco hypermethylation with age, gender, tobacco smoking, and alcohol consumption. smoking, and alcohol consumption.
Shen-Chih Chang, Ph.D
Materials and MethodsMaterials and Methods Population-based case-control study Population-based case-control study Taixing, ChinaTaixing, China Recruitment period: Jan 1, 2000 to Jun 30, 2000Recruitment period: Jan 1, 2000 to Jun 30, 2000 Cases selection criteria:Cases selection criteria:
Newly diagnosed liver cancer casesNewly diagnosed liver cancer cases Age 25-70Age 25-70 Have no history of any previous diagnosis of cancerHave no history of any previous diagnosis of cancer Have lived in Taixing for at least 10 yearsHave lived in Taixing for at least 10 years
A group of healthy population controls were A group of healthy population controls were frequency-matched (on age and gender) to cases frequency-matched (on age and gender) to cases with a control-to-case ratio of 2:3 from the general with a control-to-case ratio of 2:3 from the general population in Taixing (one common control group population in Taixing (one common control group to three case groups)to three case groups)
Epidemiology data collectionEpidemiology data collection Face-to-face interviewFace-to-face interview Blood samples collected during interviewBlood samples collected during interview
Study PopulationStudy Population
358 incident liver 358 incident liver cancer cases were cancer cases were diagnoseddiagnosed 204 (57%) 204 (57%)
recruited recruited 199 blood 199 blood
samplessamples 194 DNA 194 DNA
extractedextracted
464 potential 464 potential controls were controls were identified identified 415 (90%) 415 (90%)
recruited recruited 410 blood 410 blood
samplessamples 393 DNA 393 DNA
extractedextracted
Case (%)
Control (%)
Crude OR (95% CI)
Adjusted OR1
(95% CI)Adjusted OR2
(95% CI)APC
- 181 (95.6) 332 (94.1) 1.00 1.00 1.00+ 8 (4.2) 21 (6.0) 0.70 (0.30, 1.61) 0.52 (0.19, 1.41) 0.70 (0.24, 2.08)
p-value0.3998 0.1981 0.5233
CDH1
- 100 (52.9) 173 (49.4) 1.00 1.00 1.00+ 89 (47.1) 177 (50.6) 0.87 (0.61, 1.24) 0.93 (0.61, 1.42) 1.05 (0.65, 1.68)
p-value0.4406 0.7287 0.8548
MGMT
- 190 (100.0) 351 (100.0)
+ 0 (0.0) 0 (0.0)
p-value
P16
- 190 (100.0) 348 (99.4)
+ 0 (0.0) 2 (0.6)
p-value
No. of methylated genes
None 99 (52.4) 171 (48.9) 1.00 1.00 1.001 83 (43.9) 160 (45.7) 0.90 (0.62, 1.29) 0.98 (0.63, 1.51) 1.04 (0.64, 1.69)2 7 (3.7) 19 (5.4) 0.64 (0.26, 1.57) 0.50 (0.17, 1.47) 0.78 (0.24, 2.59)
Associations between promoter hypermethylation of APC, Associations between promoter hypermethylation of APC, CDH1, MGMT, and P16 gene and HCCCDH1, MGMT, and P16 gene and HCC
1: Adjusted on age, gender, BMI, education, smoking pack-years, alcohol drinking, HBsAg, and plasma AFB1-albumin adducts2: Further adjusted on plasma levels of folate, vitamin B12, and homocysteine
≦12.76 nM >12.76 nM
Case/Control
Crude OR (95% CI)
Adjusted OR*
(95% CI)Case/
ControlCrude OR (95% CI)
Adjusted OR* (95% CI)
APC
- 93/169 1.00 1.00 84/159 1.00 1.00
+ 2/10 0.36 (0.08, 1.69)
0.20 (0.04, 1.06) 6/11 1.03 (0.37, 2.89)
1.01 (0.26, 3.86)
p-value 0.1974 0.0583 0.9513 0.9920
CDH1
- 48/82 1.00 1.00 49/89 1.00 1.00
+ 47/96 0.84 (0.51, 1.38)
0.98 (0.54, 1.77) 41/79 0.94 (0.56, 1.58)
0.82 (0.43, 1.59)
p-value 0.4825 0.9412 0.8218 0.5653
APC+CDH1 (continuous)
0.78 (0.50, 1.22)
0.81 (0.48, 1.34) 0.96 (0.63, 1.47)
0.87 (0.50, 1.51)
p-value 0.2727 0.4084 0.8646 0.6294
Associations between promoter hypermethylation of APC and Associations between promoter hypermethylation of APC and CDH1 gene and HCC, stratified on plasma folate levelsCDH1 gene and HCC, stratified on plasma folate levels
*Adjusted on age, gender, BMI, education, smoking pack-years, alcohol drinking, HBsAg, and plasma AFB1-albumin adducts
≦228.88 pM >228.88 pM
Case/Control
Crude OR (95% CI)
Adjusted OR*
(95% CI)Case/
ControlCrude OR (95% CI)
Adjusted OR* (95% CI)
APC
- 33/160 1.00 1.00 145/166 1.00 1.00
+ 1/15 0.32 (0.04, 2.53) 0.24 (0.03, 2.04) 7/6 1.34 (0.44, 4.07)
1.62 (0.39, 6.69)
p-value 0.2824 0.1922 0.6096 0.5060
CDH1
- 19/79 1.00 1.00 80/92 1.00 1.00
+ 15/94 0.66 (0.32, 1.39) 0.78 (0.33, 1.82) 72/79 1.05 (0.68, 1.62)
1.05 (0.59, 1.85)
p-value 0.2773 0.5628 0.8334 0.8726
APC+CDH1 (continuous)
0.64 (0.34, 1.21) 0.68 (0.34, 1.36) 1.07 (0.73, 1.58)
1.10 (0.67, 1.83)
p-value 0.1728 0.2781 0.7185 0.7060
Associations between promoter hypermethylation of APC and Associations between promoter hypermethylation of APC and CDH1 gene and HCC, stratified on plasma vitamin B12 levelsCDH1 gene and HCC, stratified on plasma vitamin B12 levels
*Adjusted on age, gender, BMI, education, smoking pack-years, alcohol drinking, HBsAg, and plasma AFB1-albumin adducts
≦9.50 µM >9.50 µM
Case/Control
Crude OR (95% CI)
Adjusted OR*
(95% CI)Case/
ControlCrude OR (95% CI)
Adjusted OR* (95% CI)
APC
- 79/168 1.00 1.00 100/161 1.00 1.00
+ 4/10 0.85 (0.26, 2.80) 0.95 (0.24, 3.81) 4/11 0.59 (0.18, 1.89)
0.26 (0.05, 1.23)
p-value 0.7899 0.9468 0.3706 0.0890
CDH1
- 44/92 1.00 1.00 55/79 1.00 1.00
+ 39/84 0.97 (0.58, 1.64) 1.00 (0.52, 1.92) 49/92 0.77 (0.47, 1.25)
0.75 (0.41, 1.39)
p-value 0.9115 0.9938 0.2825 0.3625
APC+CDH1 (continuous)
0.96 (0.61, 1.49) 1.00 (0.58, 1.70) 0.76 (0.50, 1.16)
0.67 (0.39, 1.15)
p-value 0.8393 0.9842 0.2020 0.1427
Associations between promoter hypermethylation of APC and Associations between promoter hypermethylation of APC and CDH1 gene and HCC, stratified on plasma homocysteine levelsCDH1 gene and HCC, stratified on plasma homocysteine levels
*Adjusted on age, gender, BMI, education, smoking pack-years, alcohol drinking, HBsAg, and plasma AFB1-albumin adducts
Hypermethylation
APC CDH1 No. of methylated genes
No(N, %)
Yes(N, %) P*
No(N, %)
Yes(N, %) P*
0 (N, %)
1 (N, %)
2 (N, %) P*
Age
< 55 124 (37.4)
8 (38.1)
0.95
70 (40.5) 60 (33.9)
0.20
69 (40.4) 54 (33.8) 7 (36.8)
0.46≥ 55 208
(62.7)13 (61.9) 103
(59.5)117
(66.1)102 (59.7) 106 (66.3) 12
(63.2)
Gender
Female 104 (31.3)
6 (28.6)
0.79
54 (31.2) 54 (30.5)
0.89
53 (31.0) 50 (31.3) 5 (26.3)
0.91Male 228
(68.7)15 (71.4) 119
(68.8)123
(69.5)118 (69.0) 110 (68.8)
14 (73.7)
Smoking
Never 173 (52.3)
12 (57.1)
0.66
99 (57.6) 84 (47.5)
0.06
97 (57.1) 76 (47.5)10
(52.6)0.22
Ever 158 (47.7)
9 (42.9) 73 (42.4) 93 (52.5)73 (42.9) 84 (52.5) 9 (47.4)
Alcohol Drinking
Never 168 (51.1)
9 (42.9)
0.47
90 (52.6) 85 (48.0)
0.39
88 (52.1) 80 (50.0) 7 (36.8)
0.45Ever 161
(48.9)12 (57.1) 81 (47.4) 92 (52.0)
81 (47.9) 80 (50.0)12
(63.2)
Associations between promoter hypermethylation of APC and Associations between promoter hypermethylation of APC and CDH1 gene and age, gender, smoking, and alcohol drinking CDH1 gene and age, gender, smoking, and alcohol drinking
habits in the control grouphabits in the control group
*P-value from χ2 tests or Fisher’s exact test
Compare MSP and MethyLightCompare MSP and MethyLightMethylation Specific PCRMethylation Specific PCR MethyLight Methylation assayMethyLight Methylation assay
AdvantageAdvantage
•Inexpensive Inexpensive •Easy to performEasy to perform•Less prone to human errorLess prone to human error•Faster, more efficient than MSPFaster, more efficient than MSP•More specific by adding Taqman More specific by adding Taqman probe probe
DisadvantageDisadvantage
•Prone to human errorProne to human error•Easily get contaminatedEasily get contaminated•Labor-intensiveLabor-intensive
•Higher expenses for equipment Higher expenses for equipment maintenancemaintenance
Other TechniquesOther Techniques
Gene-Specific DNA MethylationGene-Specific DNA Methylation SequencingSequencing MicroarrayMicroarray High-resolution Melting Method (Roche)High-resolution Melting Method (Roche) BeadChip Technology (Illumina)BeadChip Technology (Illumina)
Global DNA MethylationGlobal DNA Methylation Liquid Chromatography-Mass SpectrometLiquid Chromatography-Mass Spectromet
ryry ELISA-based global methylation analysis aELISA-based global methylation analysis a
ssay (Sigma Aldrich)ssay (Sigma Aldrich)
ReferencesReferences
http://www.appliedbiosystems.comhttp://www.appliedbiosystems.com http://pathmicro.med.sc.edu/pcr/realtime-home.htmhttp://pathmicro.med.sc.edu/pcr/realtime-home.htm http://www.biorad.comhttp://www.biorad.com Eads CA., et al. MethyLight: a high-throughput assay to mEads CA., et al. MethyLight: a high-throughput assay to m
easure DNA methylation. Nucleic Acids Res., 28: e32, 200easure DNA methylation. Nucleic Acids Res., 28: e32, 2000.0.
Esteller M. Epigenetics in cancer. New England Journal oEsteller M. Epigenetics in cancer. New England Journal of Medicine, 358: 1148-59, 2008f Medicine, 358: 1148-59, 2008
Qiu J. Epigenetics: unfinished symphony. Nature, 441: 14Qiu J. Epigenetics: unfinished symphony. Nature, 441: 143-145, 2006.3-145, 2006.
Zeschniqk M., et al. Zeschniqk M., et al. A novel real-time PCR assay for quanA novel real-time PCR assay for quantitative analysis of methylated alleles (QAMA): analysis of titative analysis of methylated alleles (QAMA): analysis of the retinoblastoma locus. Nucleic Acids Res., 7: 3125, 200the retinoblastoma locus. Nucleic Acids Res., 7: 3125, 2004.4.
Thank you!Thank you!