Epidemiology and OncologyEpidemiology and OncologyTranslational Research in Translational Research in
Clinical OncologyClinical Oncology 2009 2009
Neil Caporaso, MDGenetic Epidemiology Branch,
Division of Cancer Epidemiology and Genetics, National Cancer Institute
DCEG
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
Domain of epidemiology
Epidemiology Epidemiology = causes of health and disease in human = causes of health and disease in human populationspopulations
= = epi epi (upon) + (upon) + demosdemos (the people) + (the people) + logia logia (talk about)(talk about)
An An OBSERVATIONALOBSERVATIONAL science (like astronomy, science (like astronomy, evolutionary biology)evolutionary biology)Contrast with Contrast with experimentalexperimentalInvestigator does NOT get to pick who is exposed or Investigator does NOT get to pick who is exposed or unexposed unexposed Free-living people make choices about participating…Free-living people make choices about participating…possible possible BIASBIASStudy of individuals with and without disease (unlike Study of individuals with and without disease (unlike Clinical Research)Clinical Research)
What are the goals of epidemiology ?1. Identify the 1. Identify the causescauses of cancer of cancer
2. Quantify risks2. Quantify risks
3. Identify risk groups3. Identify risk groups
4. Understand mechanisms4. Understand mechanisms
Public health and health servicesPublic health and health services
6. Identify syndromes6. Identify syndromes
Prevention
Primary Primary = directed to susceptibility stage= directed to susceptibility stageExample: Needle exchange to prevent AIDS, HPV vaccineExample: Needle exchange to prevent AIDS, HPV vaccine
Secondary Secondary = directed to subclinical stage= directed to subclinical stageExample: Screen for cervical cancer with Pap SmearExample: Screen for cervical cancer with Pap Smear
Tertiary Tertiary = directed to clinical stage= directed to clinical stageExample: Treat diabetic retinopathy to prevent blindnessExample: Treat diabetic retinopathy to prevent blindness
Epidemiologist as a “crusher of dreams”
Question you want the epidemiologist to answer:Question you want the epidemiologist to answer:= What is the p value?= What is the p value?
What the epidemiologist is thinking…..What the epidemiologist is thinking…..Your study design is what?Your study design is what?Your controls came from where?Your controls came from where?Did you consider bias?Did you consider bias?Did you consider confounding?Did you consider confounding?What was your original hypothesis?What was your original hypothesis?Did you consider the power of your study?Did you consider the power of your study?etc.etc.
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
SEER
-SEER Surveillance, Epidemiology, and End Results (SEER) Program
26% of US population26% of US population
incidence and survival, incidence and survival, patient demographics, primary patient demographics, primary tumor site, tumor morphology and stage at diagnosis, first tumor site, tumor morphology and stage at diagnosis, first course of treatment, and follow-up for vital status course of treatment, and follow-up for vital status
comprehensive source of population-based informationcomprehensive source of population-based information
CANCER RATESThese are RATES not numbers of events
KEY DIFFERENCERates take into account age and size of population
0
100
200
300
400
500
600
700
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Both Sexes
Men
Women
Rate Per 100,000
0
100
200
300
400
500
600
700
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Cancer Incidence Rates*, All Sites Combined, All Races, 1975-2000
75% increase dueto PSA screening
Men cancer rates
Cancer Incidence Rates* for Women, US, 1975-2000
*Age-adjusted to the 1970 US standard population.Source: Surveillance, Epidemiology, and End Results Program, 1973-1998, Division of Cancer Control and Population Sciences, National Cancer Institute, 2001.
0
50
100
150
200
250
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Breast
Lung
Uterine corpus
Ovary
Rate Per 100,000
Colon & rectum
561.2
392.0
259.0
444.4406.3
306.9
229.2
312.2
696.8
419.3
0
100
200
300
400
500
600
700
800
White African American Asian/Pacific Islander American Indian/Alaskan Native
Hispanic†
Men Women
Rate Per 100,000
Cancer Incidence Rates* by Race and Ethnicity, 1996-2000
Cancer incidence rates
Why are cancer deathrates leveling off?
Cancer death rates
…..because the most common cause of cancer death is declining……
Lung cancer death rates
Men cancer death rates
Women cancer death rates
Per-Capita Consumption of Different Forms of Tobacco in The U.S. 1880-2003
CigarettesCigars
Pipe/roll your own
Chewing
Snuff
0
2
4
6
8
10
12
14
1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000Year
Pou
nds
of T
obac
co P
er-C
apita
Cigarettes Cigars Pipe/roll your own Chewing Snuff
Data Source USDA
Prevalence of cancer
# of people diagnosed with cancer# of people diagnosed with cancer
Includes those ‘cured’ and those Includes those ‘cured’ and those living with the diseaseliving with the disease
> 10 million Americans> 10 million Americans
Men lifetime mortality
Women lifetime mortality
Childhood cancer
Childhood Cancers (< 14 ys)Childhood Cancers (< 14 ys)
Incidence 8,600 new cases/yr 12,400 (0 – 19 ys)
Mortality 1,500 deaths/yr 2,300 (0 – 19 ys)
rates 50% since 1973
Etiology -- poorly understood
Trends in Survival, Children 0-14 Years, All Sites Combined, 1974-19991. For children of age 0-4 the 5 year survival rate was 56.5% in 1975 and 77.3% in 1995.2. For children of age 5-9 the 5 year survival rate was 55.3% in 1975 and 77.6% in 1995.3. For children 10-14 years of age, the 5 year survival rate was 55.2% in 1975 and 77.6% in 1995.
What are the general risk factors for cancer?
Increasing ageIncreasing age
Environmental factorsEnvironmental factors
Genetic factorsGenetic factors
Combinations of the above!Combinations of the above!
Relative risk
A measure of the strength of the relationship A measure of the strength of the relationship between the risk factor and the cancerbetween the risk factor and the cancer
So, if tobacco has a RR=10 for lung cancer,So, if tobacco has a RR=10 for lung cancer,smokers are 10-fold more likely to get lung cancer smokers are 10-fold more likely to get lung cancer
than non-smokers. than non-smokers. Contrast with: odds ratio absolute risk
DietDiet
~ 30-35%~ 30-35%
TobaccoTobacco
~30-35%~30-35%
Other*Other*
~30-35%~30-35%
Causes of Cancer DeathsCauses of Cancer Deaths* * Environmental pollution, Infectious agents, Lifestyle,
Alcohol use, Occupational factors, Medicine, Radiation, Genetic susceptibility, other & unknown causes
Skull With Skull With CigaretteCigarette
van Goghvan Gogh
Diet and cancer
1.00
1.31
1.79
1.00
1.211.51
1
10
T1 T2 T3 T1 T2 T3
OR
& 9
5%
CI
Tertile (freq. per day)
Highest-versus-lowest tertile of frequency intake
Higher frequency of fresh red and processed meat intake increased lung cancer risks
p-trend: <0.001
Fresh red meat Processed meat
What are some dietary risk factors?
High fatHigh fat Colon, breastColon, breastHigh caloriesHigh calories UterineUterineLow fiberLow fiber ColonColonMicronutrientsMicronutrients Lung (?)Lung (?)Diet contaminentsDiet contaminents LiverLiver
What are alcohol-associated cancers?
OralOralPharynxPharynxEsophagusEsophagusLarynxLarynxLiverLiver
RadiationRadiation• Ionizing
• Non Ionizing– Ultraviolet– Electromagnetic
Ionizing Radiation
Leukemia (AML, but not CLL)Leukemia (AML, but not CLL)BreastBreastLungLungThyroidThyroidHead and neck cancerHead and neck cancer
Partial list: studies implicating cancer and Ionizing Radiation
Type of XRT Study Cancer ImplicatedA-Bomb Japan Breast, Leuk, Gastric, ThyA-Bomb Marshall Island ThyroidMedical Breast/Mastitis BreastMedical Hemangioma Breast, ThyroidMedical Hodgkin’s Breast, lung, ThyroidMedical TB-Flouroscopy BreastRadionuclides Thorotrast Leukemia, Liver (Th-232)Radionuclides Spondylytis Bones (Ra-224)Occupation Radium Dial painters BoneOccupation Rad Technicians LeukemiaOccupation Chernobyl Cleanup ?Environmental Indoor radon Lung
Excessive sun tanning
Non-Ionizing Radiation (UV/sun)
Basal cellBasal cellSquamous cellSquamous cellMelanomaMelanoma
Melanoma map
Indoor air pollution in China
4-Aminobiphenyl Bladder Arsenic Lung, skin Asbestos Lung, pleura,
peritoneum Benzene Leukemia Benzidine Bladder beta-Naphthylamine Bladder Coal tars and pitches Lung, skin Mineral oils Skin Mustard gas Pharynx, lung Radon Lung Soot, tars, and oils (polycyclic hydrocarbons) Lung, skin Vinyl chloride Liver Wood dusts (furniture) Nasal sinuses
OCCUPATIONAL EXPOSURES -- HUMAN OCCUPATIONAL EXPOSURES -- HUMAN CARCINOGENSCARCINOGENS
EXPOSUREEXPOSURE SITE OF SITE OF CANCERCANCER
Viruses and cancer
Bacteria and Stomach Cancer
• Helicobacter pylori increases risk of stomach cancer
HP-associated Disease (US)
Genetic EpidemiologyGenetic Epidemiology
• Etiology, distribution, and control of disease in families and with inherited causes of disease in populations
• Includes – family studies– molecular epi studies w/ genetic
components – traditional cohort + case-control studies w/
family history components
CDKN2ACDKN2A Mutations in Mutations in Familial MelanomaFamilial Melanoma
• CDKN2A -- major melanoma susceptibility gene
• Frequency of mutations varies in families– 2 cases <5%– 3 – 5 cases 20 – 24%– >6 cases 50%
Cloned Familial Tumor Suppressor Genes Retinoblastoma RB1 13q14 1986Wilms’ tumor WT1 11p13 1990Li-Fraumeni syndrome p53 17p13 1990Neurofibromatosis 1 NF1 17q11 1990Neurofibromatosis 2 NF2 22q12 1993von Hippel-Lindau VHL 3p25 1993Familial melanoma 1 p16 9p21 1994Familial breast 1 BRCA1 17q21 1994Familial breast 2 BRCA2 13q12 1995Basal cell nevus PTC 9q22 1996
Environment- +
Gen
es+
- Spontaneous
Smoking 1950’s Microbes –- 1960s Chemicals – 1970s Lifestyle – 1980s
Hereditary syndromes Low-penetrant variants
Interactions
Categories of Cancer Causation
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
3 big gaps on the ENVIRONMENT sideFor many cancers, risk factors are unknown?For cancers where general ‘cause’, is understood, individual susceptibility is poorly understoodHow G and E work in concert is
poorly understood Epidemiologists have responded byExpanding the tools of epidemiologyEnhancing investigation of causation.
Cancer statastics 2000; CA J Clin 2000; 50:7-33
Chronic Lymphocytic Leukemia
• Most common leukemia of Western world.• 30% of adult leukemia in USA• Less frequent in Asia and Latin America.• Male to female ratio is 2:1.• Median age at diagnosis is 65-70 years.• No extrinsic environmental causes known• Family history is the most important risk
factor
Traditional epidemiologyExposure to tobacco leads to lung
cancer
Molecular epidemiologyUsing biomarkers for both E and D Historic rationale for molecular epidemiology:We enter the black box orGain mechanistic insightTobacco thru an unknown mechanism leads to lung cancer
Molecular epidemiologyMeasure smoking exposure urine cotinine
Molecular epidemiology exposureinternal doseearly biological effectaltered structure or functionearly diseasedisease
seme
Traditional clinical trialEvaluate new treatment
.
Translational medicineUnderstand molecular pathology
biomarker of disease e.g., p53 mutations, P16 methylation, telomere alterations, etc
Integrative epidemiologyBehavior leads to outcomeexposureinternal doseearly biological effectaltered structure or functionearly diseasedisease
Exposure disease outcome
A premise…………..
Translational medicine and molecular Translational medicine and molecular epidemiology are natural partners.epidemiology are natural partners.
We need both to meaningfully advance We need both to meaningfully advance prevention and treatment of major cancers.prevention and treatment of major cancers.
Definitions: Molecular Epidemiology using biomarkers in population
studies
Translational Medicine optimizing information flow between basic and clinical science (bench-bedside)
Epidemiologists use 5 criteriato support causal relations…..tobacco and lung cancer
High relative risk (odds ratio)ConsistencyDose-responseTemporal relationshipPlausible mechanism
Lung cancer deaths occur 2 decades after smoking incidence
Lung cancer correlates with cigarette consumption
Basal cell proliferation
Squamous carcinoma
Relative Risks of Lung Cancer According to Years Since Quitting Smoking among Males in Three Cohort Studies of Smokers
0
2
4
6
8
10
12
14
16
18
20
0 1-4 5-9 10-14 15-19 20+
Years Since Quitting Smoking
Re
lati
ve
Ris
k
British Physicians U.S. Veterans American Cancer Society
Smoking cessation
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know
The lung cancer challenge….1- Drives overall cancer mortality n the US and worldwide2- Treatment and screening pose challenges3- Lung cancer is paradigm for genetics of complex disease4- Clearest example of environment and gene in cancer5- The clearest example of a genetically influenced behavior associated with the leading public health problem in the
world
Tobacco and public health tobacco is the major cause of preventable morbidity and mortality in the Western world 1 in 5 US deaths (450,000 USA, 3M worldwide/yr) 10 million tobacco related deaths/annum by 2030 (WHO estimate) 30% of all cancer, 8 major sites, all difficult to treat- tobacco related disease costs Medicare $10B/yr and Medicaid $13B/yr In spite of widespread knowledge of the health consequences of smoking
- rates in US adolescents are stable or increasing- declines in adults have leveled off- individual smoking cessation difficult
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know
Seven questions in lung cancerWhy begin to smoke?Why persist in smoking?Why can’t people quit smoking?What determines who gets lung cancer?What genetic lesions characterize LC?Can we effectively screen LC?Can we effectively treat LC?
Chain of events that must occur to result in death from lung cancer (population perspective)1. Start smoking2. Persist in smoking/can’t quit3.Host susceptibility/molecular lesions4.Can’t detect early5. Can’t treat
Chain of events that must occur to result in death from lung cancer (population perspective) Traditional discipline that addresses the area1. Economics/politics2. Behavioral scientists3. Genetics, Epidemiology, Molecular biologists4. Prevention trials5. Clinical Trials
It costs less to intervene early in the process………..
It takes longer for interventions early in the process to influence cancer
rates….…
It is politically easier to fund treatment then public health…
Molecular epidemiology starting point
3. Host susceptibility
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know
-Evidence: hereditary variation in lung cancer- Lung cancer kindreds exist Tomizawa 1997 Case–control studies identify increased risks in case relativesTokuhata 1963, Ooi 1986, Shaw 1991, Bromen 2000, Lynch 1986 Segregation analysisSellers 1990 Population databasesCannon-Albright 1994 Twin studies (note- results mixed)Morison 1994, Paul 1987, Braun 1994,95 Animal Models Manenti 1997, 1999; Dragani 1995 Many plausible polymorphic candidate genes Rare lung cancer susceptibility gene identified in lung cancer families
Lung cancer risk and Family HistoryNo rel.w/LC Cont Cases * OR(95% CI)
0 466 393 1.01 78 119 1.7 (1.2- 2.4)
2+ 8 20 2.9 (1.2- 6.6)
* Adjusted for gender, smoking, passive smoking,
and the # of 1st degree relatives
Genes that contribute to cancer fall in 2 categories
Single SusceptibilityStudy design family populationType linkage associationAllele freq rare common# of genes one/few manyD and G freq rare commonRisk high lowRole of E low highAttrib risk low highConcept deterministic probabilisticType Search anonymous directedexample: BRCA1 TERT/CHRN
To look for first category of genes you need families……….
High risk kindreds like this likely harbor rare genes that confer
high risk- if we knew what were they would be clinically important….
To search for the 2nd (common) category of genes you need large populations
CLL CLL
CLL, NHL,HL
NHL
Until recently you also needed some idea of what kinds of genes to look
for….. Starter paradigm for identifying candidate
genes in lung cancer
Smoking causes most lung cancer
Carcinogens in tobacco must be metabolically activated
Metabolic alteration is under geneticcontrol
Processing is often under hereditary control
examples: tobacconicotine (CYP2A6)aryl amines (NAT2)
PAH (CYP1A1, GSTM1, others)nitrosamines (CYP2A6/13, CYP2E1)
Metanalyses: Lung cancerGene studiesOR (95% CI) author
CYP1A1 22 1.2 (0.9-1.5) Houlson 2000 4 MspI 1.7 (1.3-2.3) d’Errico 1999 3 exon7 2.3 (1.4-3.7) d’Errico 1999
CYP2D6 16 1.3 (1.0-1.6) d’Errico 199913 1.3 (0.9-2.0) Christensen 1997
MPO * 6 0.7 (0.4-0.8) Kantarci 2002
GSTM1 23 1.1 (1.0-1.3) Houlson 199913(C) 1.2 (1.1-1.4) d’Errico 1999
Genetic Association StudiesHirschhorn et al Genetic Medicine
2002- 600 reported associations (133 diseases and 268 genes)
166 studied 3 or more times
only 6 consistently reproducedDVT and F5 (arg506Gln)
Graves Disease and CTLA4 (Thr17Ala)Type 1 Diabetes and INS (5’ VNTR)HIV/AIDS and CCR5 (32bp ins/del)
Alzheimers and APOE (e 2/3/4)Creutfeldt-Jacob and PRNP (met129val)
None involving cancer
Some observations
- In general candidate genes studies to identify the precise genes that account for the hereditary risks
in complex disease have been disappointing
Situation NOT unique to lung cancer
An improved approach was needed to examine the genome in a systematic manner…
What were some challenges in finding genes involved in common cancers using candidate approach (pre-2007)?
- type 1 error (false positives)- population stratification - multiple comparisons- inadequate power (type 2 error)- design issues- failure to consider gene-environmentfailure to consider pathwaysfailure to consider genetic architecture
Where genes might operate to influence disease risk...
1 PAHCYP1A1, AHR, GSTM1, GSTP1, EH, NQO1, MPO
2 nitrosaminesCYP2E1, CYP2D6, CYP2A6
3 aromatic aminesCYP1A2, NAT1, NAT2
4 nicotineCYP2A6, CYP2A13, CYP2D6
Where genes might operate to influence disease risk.
1 dopamineDRD2, DRD4, SLC6A3, TH, DBH
2 serotonin5HTT, CYP2D6, receptors
3 nicotineCYP2A6, CYP2A13, nicotinic receptors..
Multiple Comparisons The problem:
1. Many gene families and many genes within each family
2. Many SNPs within each geneTechnical capacity to test 1000s of genes
Low prior probability that any given SNPis truly associated with the cancer……..
Therefore because the number of true associations is limited………………
Multiple ComparisonsThe vast majority of observed ‘significant’
associations will be FALSE POSITIVE
Suppose we test 5 SNPs for each of 20,000 genes or 100,000 SNPs….assume that 100 SNPs have a
true ‘disease’ relation…..
only 100/5100 or 2% of nominally significant associations will be ‘true positives’.
A problem.What we investigate:
One gene leads to one disease.The biological reality is tha one gene has many effects (pleiotropy). Many
genes cause one disease.
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
WISH LIST in 2005 to identifygenes in lung cancer
MUCH MUCH larger study
Technology to look at all genes in an ‘agnostic’ screen
EAGLE website
Study Design
Population-basedCatchment's area: 5 cities and 216 municipalitiesCases: from 13
hospitals Controls: randomly sampled from the
areaMatched by age,
sex, and residence
Study description2348 incident lung cancer cases2012 population-based controlsParticipation rate, Cases = 85%; Controls = 73%; 1. QuestionnairesCAPI, Demographics, Smoking, Family history, Medical history, Reproductive history, Occupational exposures, Self-administered, Behavior, Diet,2. Clinical Data Path reports, Diagnostic procedures, Imaging,
3. Biospecimens Blood/buccal, WB, PBMC, RBC, Serum, Plasma, Buffy coat, DNA, RNA, Blood cards, Tissue Fresh frozen, Paraffin blocks, Paraffin slides4. caBIG
Participation rate, Cases=85%; Controls=73%
• •
Pilot studies: participation rate
A 30% participation rate was obtained by
Survey and Phone A 49% participation rate was obtained by Invitation letter, Follow-up by phone, In hospital, Advertisements, Cash award, Physicians’ letter and Home/hospital.
A 73% participation rate was obtained by New interviewers, Physicians’ call, Gas coupon, TV ads, New invitation letter,
Mayor’s letter, Toll-free phone lineTotal number of subjects in pilot
investigations:
156 Cases - 212 Controls Clinical data: 99%
Questionnaires: 87% Biospecimens: 97%
Why Population Controls ? Gold standard
Representative of the population from which cases
deriveCan calculate absolute rates
Reduces selection bias
IMPLIES
Defined population in time and spaceSpecified eligibility and exclusion
criteriaDefined and high response rate
Study design: controls35% never smokers 30% former 35% currentn=700 n=600 n=700Test for Test for Test forsmoking initiation smoking initiation
smoking persistence smoking persistence
Lung Cancer Case Control
GENEVA OverviewGENEVA OverviewGene Environment Association Studies.
Part of NIH-wide Genes, Environment and Health Initiative (GEI).
GENEVA aims: use whole genome technology:Identify genetic variants related to common, complex diseases.
Identify variations in gene-trait associations related to environmental exposures.
Address potential pathways to outcomes in various populations.
Study Investigators – Phase IStudy Investigators – Phase IThe first round of GENEVA grants funded eight Study Investigators in 2007.PI Institution TitleFrank Hu, MD, PhD Harvard University Type 2 DiabetesWilliam Lowe, MD Northwestern University Maternal Metabolism-Birth Weight InteractionsMary Marazita, PhD1 University of Pittsburgh Dental CariesJeffrey Murray, MD University of Iowa Prematurity and its ComplicationsTerri Beaty, PhD1 Johns Hopkins University Oral CleftsLaura Bierut, MD2 Washington University AddictionEric Boerwinkle, PhD3 The University of Texas Health Science Center at Houston
CHDNeil Caporaso, MD National Cancer Institute Lung Cancer Study
Our AimsFind genes related to:
Lung CancerSmokingSurvival
EAGLEEnvironment And Genetics in Lung Cancer Etiology
PLCO Cancer Screening TrialProstate, Lung, Colon, Ovary
Initial design included ~5800 subjects but we sought collaborators from other
lung cancer studies to have additional power to find genes…..
1.2 1.3 1.4 1.5 1.6 1.7 1.8
Genotype Relative Risk
0.0
0.2
0.4
0.6
0.8
1.0
Pow
er
AdditiveDominantRecessive
(a)
1.2 1.3 1.4 1.5 1.6 1.7 1.8
Genotype Relative Risk
0.0
0.2
0.4
0.6
0.8
1.0
Pow
er
AdditiveDominantRecessive
(b)
1.2 1.3 1.4 1.5 1.6 1.7 1.8
Genotype Relative Risk
0.0
0.2
0.4
0.6
0.8
1.0
Pow
er
AdditiveDominantRecessive
(c)
Power Calculation _ Lung Cancer Revision= Phase 1: EAGLE + PLCO (n=~5,500)
Data SharingFor EAGLE, PLCO, ATBC
Lung cancer• Age• Gender• Family history of lung cancer• Case/control status• Histology• Stage
Smoking phenotype• Smoking status (never/ever/former)• Pack years• Fagerstrom (available in EAGLE only)
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
Major difference in chr 5 SNP by histology
Outline
1. What is the point of epidemiology?2. What causes cancer?3. Why don’t we know what causes cancer? 4. How have epidemiology investigations evolved?5. Why lung cancer?6. 7 questions about lung cancer I can’t answer7. Why bother studying genetics in a disease caused by smoking?8. Where are the missing genes? 9. Tell me something I don’t know10. What next?
WISH LIST in 2009 to identifygenes (in lung cancer and other
cancer)
MUCH MUCH larger study
Technology to look at more genes in an ‘agnostic’ screen
Go from 500,000 SNPs>>>millionsInclude CNVs
Include rare genesEventually need sequencing
Next PrioritiesRole of chr 15 in lung
Cancer/Smoking
Genomics: Outcome
Key subgroups
Large studies provide key advantages:
- incorporate new technologies and disciplines test diverse hypotheses lower marginal costs bring interdisciplinary expertise to bear use resources efficiently get full scientific value from large study ‘platforms’
Large studies should do everything possible to incorporate multiple ‘domains’ to createa setting for the best science.