epidemiology

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

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


-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

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500

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700

1975

1976

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1981

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1984

1985

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Both Sexes

Men

Women

Rate Per 100,000

0

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700

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1976

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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

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100

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1991

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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

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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


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

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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

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


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


-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


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

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0.8

1.0

Pow

er

AdditiveDominantRecessive

(a)

1.2 1.3 1.4 1.5 1.6 1.7 1.8


0.0

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0.4

0.6

0.8

1.0

Pow

er


(b)

1.2 1.3 1.4 1.5 1.6 1.7 1.8


0.0

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0.6

0.8

1.0

Pow

er


(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


Major difference in chr 5 SNP by histology

Outline


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.

epidemiology

Documents

causes of cancer

cancer incidence rates

cervical cancer

prevalence of cancer

women cancer death rates

national cancer institute

division of cancer control

psa screening men cancer