Biological Markers for Exposures Epidemiology 243 Molecular Epidemiology of Cancer.

Biological Markers for Exposures

Epidemiology 243

Molecular Epidemiology of Cancer

Early Studies

• MacMahon: Geographical correlation of urinary estrogen concentrations with cancer of the breast (1974)

• Cole & MacMahon: Urinary and blood estrogens and breast cancer in case-control studies (1969,1982, 1983)

• McMichael: The relationship between cancer mortality and serum cholesterol concentrations (1984)

Recent Studies

• Aflatoxins and hepatitis B on liver cancer in a cohort study, including measurements of urinary metabolites and nucleic acid adducts of aflatoxin (Ross, 1992, 1994)

• The relationship between HPV and cervical cancer (Munoz, 1992, Bosch, 1995)

Application of biomarkers in Epidemiology

Molecular markers can be applied to increase the accuracy of measurements

• of genetic and other acquired susceptibility to disease;

• of exposures that may cause or prevent disease;• of exposures that confound or modify the

associations between risk and other exposures• of disease itself• of factors that may determine the outcome of the

disease such as precursors and stages

Application of biomarkers in Epidemiology

Biomarkers may also be used • to reduce the time interval between the relevant

exposure and measurement of the putative effect• To increase the yield of information on disease

pathogenesis• To increase the cost-effectiveness of

epidemiological studies. More information is gained per unit cost.

Biomarker in Epidemiology: Biomarkers of Biological Agents

• Biological agents associated with chronic infection and subsequent development of cancer are measured using serological or nucleic acid markers.

Biomarker in Epidemiology: Biomarkers of Biological Agents• HPV DNA by PCR-based assays

HPV infection is often transient, especially in young women so that repeated sampling is required to assess persistent HPV infections

Classification of Cervical Squamous Neoplasia

Dysplasia PapS. CIN scale Bethesda

Normal 1 Normal Normal

Infla. Atypia 2a Infla. atypia Normal

Koilocyt.Atypia 2b Koilocyto a. LG SIL

Mild dysplasia 3 CIN1 LG SIL

Moderate dysp. 3 CIN2 HG SIL

Severe dysp. 3 CIN3 HG SIL

Ca. in situ 4 CIN3 HG SIL

Invasive ca. 5 Invasive ca Invasive ca

HPV Testing and Typing

• HPV infection is the main cause of cervical cancer. Transient in women. Only 10-20% persistent infections are at risk of neoplasia

• About 70 subtypes, of which 25 are tropic for genital tract. Those are subdivided into three categories:

HPV Testing and Typing

• HPV can be tested and typed by dot blot hybridization, southern blot hybridization, Hybrid Capture and PCR

• High sensitivity but relatively low specificity, particular among young women

• HPV typing has great potential as a primary screening tool for cervical cancer.

Biomarker in Epidemiology: Biomarkers of Biological Agents

HBV infection by serological assays.

• There are serological markers that distinguish between past and persistent infections. HBV DNA detection in sera further refines the assessment of exposure.

HBV

Gender Case

N %

Control

N %

P Value

Male 159 (77.94 )

287(69.16) 0.0221

Female 45 (22.06) 128(30.84)

204 415

Gender distribution among cases and controls

Self-reported hepatitis virus infection type

Hepatitis History Case

N %

Control

N %

Crude OR (95%CI)

Adjusted OR (95% CI)

No 108(60.34) 354(90.08) 1 1

HAV 16(8.94) 19(4.84) 2.77(1.38~5.57) 2.67(1.27~5.60)

HBV 55(30.73) 19(4.40) 11.30(6.22~20.5) 14.52(7.38~28.6)

HDV 0 (0) 1(0.26)

The relationship between liver cirrhosis and liver cancer

Liver cirrhosis Case

N %

Control

N %

Crude OR (95%CI)

Adjusted OR (95% CI)

No 149(86.6) 355(99.2)

Yes 23 (13.4) 3 (0.8) 18.3(5.40~61.8) 22.1(6.11~79.9)

The relationship between HBV vaccine and liver cancer

HBV vaccine Case

N %

Control

N %

Crude OR (95%CI)

Adjusted OR (95% CI)

No 157(96.32)

293(86.14) 1 1

Yes 6(3.68) 47(13.9) 0.24(0.10~0.57) 0.24(0.10~0.60)

The distribution of HBsAg among cases and controls

HBsAg Case

N %

Control

N %

Crude OR (95%CI)

Adjusted OR (95% CI)

Negative 72(35.29) 312(75.36) 1 1

Positive 132(64.71) 102(24.64) 5.59(3.95~8.18) 5.06(3.45~7.43)

HBsAg Case

N %

Control

N %

Crude OR (95%CI)

Adjusted OR (95% CI)

Negative 183(91.04) 403(97.11) 1 1

Positive 18 (8.96) 12 (2.89) 3.49(1.66~7.33) 3.21(1.46~7.06)

The distribution of anti-HCV among cases and controls

TYPE HBsAg HBsAb HBeAg HBeAb HBcAb Crude OR

(95%CI)

Adjusteda

(95%CI)

2 - - - - - 1.00 1.00

1 - + - - - 0.24 (0.09~0.63)* 0.23 (0.09~0.61)*

3 - - - - + 1.00 (0.49~2.03) 1.02 (0.49~2.11)

1 + - - + + 4.74 (2.48~9.06)* 3.91 (1.99~7.66)*

2 + - - - + 8.9 (4.00~19.73)* 7.68 (3.23~18.31)*

3 + - + - + 12.50 (4.78~32.73)* 11.55 (4.18~31.90)*

Most frequent HBV infection spectrum in cases and controls

Mildewed food intake

GSTM1 Case

N %

Controls

N %

Crude OR(95% CI)

Adjusted OR(95%CI)

Further adjusted OR(95%CI)

No Normal 45(25.6) 126(32.9) 1 1 1

Yes Normal 17(9.7) 29(7.6) 1.64(0.82~3.27) 1.81(0.87~3.76)

2.69(1.15~6.30)

No Null 86(48.9) 193(50.4) 1.25(0.82~1.91) 1.20(0.77~1.87)

1.38(0.84~2.25)

Yes Null 28(15.9) 35(9.1) 2.24(1.23~4.09) 2.67(1.36~5.23)

4.13(1.85~9.24)

The possible interaction between GSTM1 and mildewed food

The possible interaction between GSTT1 and HBV

HBsAg GSTT1 Case

N %

Control

N %

Crude OR

(95% CI)

Adjusted

OR (95%CI)

Further adjusted OR(95%CI)

No Normal 36(19.0) 146(37.1) 1

1 1

Yes Normal 67(35.3) 54(13.7) 5.03(3.02~8.39) 4.49(2.63~7.67) 4.48(2.62~7.67)

No Null 27(14.2) 150(38.1) 0.73(0.42~1.26) 0.73(0.41~1.29) 0.68(0.38~1.22)

Yes Null 60(31.6) 44(11.2) 5.53(3.25~9.43) 4.91(2.81~8.60) 5.04(2.85~13.9)

Raw water drinking

HBsAg Case

N %

Control

N %

Crude OR

(95% CI)

Adjusted

OR (95%CI)

No Negative 32(17.30) 184(51.40) 1 1

Yes Negative 30(16.22) 83(23.18) 2.08(1.19~3.64) 1.84(1.03~3.28)

No Positive 63(34.05) 63(17.60) 5.75(3.44~9.60) 5.25(3.04~9.06)

Yes Positive 60(32.43) 28(7.82) 12.32(6.86~22.11) 9.66(5.22~17.89)

The interaction between HBsAg and raw water drinking

Mildew food intake

HBsAg Case

N %

Control

N %

Crude OR

(95% CI)

Adjusted

OR (95%CI)

No Negative 46(24.08) 151(62.13) 1 1

Yes Negative 21(10.99) 52(12.87) 2.20(1.21~4.00) 2.47(1.32~4.63)

No Positive 97(21.53) 87(21.53) 6.08(3.97~9.33) 5.41(3.46~8.45)

Yes Positive 27(14.14) 14(3.47) 10.52(5.13~21.58) 10.82(5.09~22.98)

The interaction between HBsAg and mildewed food intake

Alcohol drinking

HBsAg Case

N %

Control

N %

Crude OR

(95% CI)

Adjusted

OR (95%CI)

No Negative 34(17.71) 157(38.20) 1 1

Yes Negative 35(18.23) 153(37.23) 1.06(0.63~1.78) 1.06(0.56~2.00)

No Positive 53(27.60) 70(36.46) 5.00(2.92~8.54) 4.36(2.47~7.68)

Yes Positive 49(11.92) 52(12.65) 6.22(3.71~10.41) 6.19(3.13~12.25).

The interaction between HBsAg and alcohol drinking

Anti-HCV HBsAg Case

N %

Control

N %

Crude OR

(95% CI)

Adjusted

OR (95%CI)

No Negative 63(31.19) 304(73.08) 1 1

Yes Negative 6(2.97) 10(2.40) 2.90(1.02~8.26) 2.63(0.88~7.85)

No Positive 120(59.41) 100(24.04) 5.79(3.96~8.46) 5.20(3.49~7.76)

Yes Positive 13(6.44) 2(0.48) 31.37(6.91~ 42.44)

23.99(5.09~ 13.12)

The interaction between HBsAg and anti-HCV

The interaction between HBsAg and family history of liver cancer

Anti-HCV HBsAg Case

N %

Control

N %

Crude OR

(95% CI)

Adjusted

OR (95%CI)

No Negative 58(28.29) 284(68.27) 1 1

Yes Negative 14(6.83) 30(7.21) 2.285(1.41~4.58) 2.33(1.13~4.81)

No Positive 94(45.85) 93(22.36) 4.95(3.31~7.40) 4.52(2.96~6.92)

Yes Positive 39(19.02) 9(2.16) 21.22(9.75~46.19) 24.14(10.34~ 6.35)

Selected Variables OR ( 95%CI )

Age 0.95 (0.93~0.98)

Gender 1.71 (0.80~3.65)

Education 0.56 (0.38~0.82)

Mildewed food intake 2.64 (1.39~4.99)

Refrigerator using at home 0.30 (0.13~0.68)

Raw water drinking 1.19 (0.65~2.19)

Pack-year of smoking 1.00 (0.98~1.03)

Alcohol drinking 1.38 (0.72~2.62)

Characteristics

optimistic 0.40 (0.23~0.69)

Depressed 4.35 (1.41~13.45)

Family history of liver cancer 4.81 (2.41~9.60)

HBsAg 6.93 (4.07~11.78)

Anti-HCV 3.49(1.10~11.07)

GSTM1 1.87 (1.09~3.21)

GSTT1 0.72 (0.43~1.21)

Multivariate Logistic Regression Analysis

Major Risk Factors for Stomach Cancer in Chinese Population

• Helicobacter pylori was the first bacterium to be officially recognized as a cancer-causing agent.

Major Risk Factors for Stomach Cancer in Chinese Population

• Helicobacter pylori Infection. Nitrates and nitrites are substances commonly found in cured meats, some drinking water, and certain vegetables, that can be converted by Helicobacter pylori, into compounds that have been found to cause stomach cancer in animals.

Figure 1a: H.pylori and gastric cancer - Prospective studies: meta-analysis of non cardia cancer

cases.

Figure 1b: H.pylori and gastric cancer - Prospective studies: meta-analysis of cardia cancer cases.

H. Pylori Infection and Stomach Cancer in Whites at MSKCC

H. Pylori case/control OR

no 69/54 1.00

yes 67/15 3.50 (1.80-6.79)

Infection rates:

21.7% in controls

49.3% in cases

Biomarker in Epidemiology: Biomarkers of Internal Dose

• Biomarker of internal dose of external chemical exposures are measurements of a parent compound or its metabolites in an accessible biological matrix, such as serum or urine

Biomarker in Epidemiology: Biomarkers of Internal Dose

• The half-life of the external agent or its metabolites in the body

• The pattern of the exposure it is measuring (regular exposure or infrequent exposure)

• Whether the secular trends have occurred in that exposure (e.g., smoking cessation)

• Direct or indirect influence of the disease

Urine Test Kit for Tobacco Use

Marker for Internal Dose

Fat-soluble substance such as DDT metabolites

• Persist over time

• Will not be affected by disease status

DDT

• DDT (dichlorodiphenyltrichloroethane) is a commercial organochlorine insecticide that has been used in countries around the world. It has been used widely on agricultural crops as well as for "vector control" - the control of insects that carry such diseases as malaria and typhus

DDT

DDT

• This organochlorine insecticide can be considered as the pesticide of the greatest historical significance, due to its effect on the environment, agriculture, and human health.

• First synthesized by a German graduate student in 1873, it was rediscovered by Dr. Paul Mueller, a Swiss entomologist, in 1939 while searching for a long-lasting insecticide for the clothes moth.

DDT

• DDT subsequently proved to be extremely effective against flies and mosquitoes, ultimately leading to the award of the Nobel Prize in medicine for Dr. Mueller in 1948.

• Effective January 1, 1973 the Environmental Protection Agency (EPA) officially canceled all uses of DDT, but not before more than 1 billion kilograms of DDT had been introduced into the United States.

Biomarker of Dietary Intake

• Whether it is a good indicator of intake

• Whether it is a long- or short-term marker

• Whether there is a need for multiple measurements

• Whether it is acceptable for researcher and the subject

• Whether it is compatible with study design

Main component of green Tea Catechins:  (-)-Epigallocatechin gallate ((-)EGCg)

Adduct as Biomarker

• Chemicals can bind covalently to cellular macromolecules such as nucleic acids and protein. The product of this addition of a chemical moiety to a macromolecule is termed an “adduct”

Adduct as Biomarker

• Adduct may be highly specific for carcinogen of interest, but not necessarily specific for a given exposure because of multiple sources of carcinogen with environment

• Adduct formation normally occurs after the metabolic activation of the carcinogen; DNA repair may follow adduct formation

Adduct as Biomarker

The persistent of the adducts is determined by

• Chemical stability of the adduct itself

• The turnover of macromolecule to which the chemical is bound

Adduct as Biomarker

• A half-life of adducts on proteins (HB and albumin): a few weeks to months

• A half-life of DNA adducts: a few hours to several years depending on cell type concerned

Adduct as Biomarker

• Adducts can be measured at

• Blood

• Exfoliated cells

• Tissue

• Urine (metabolites of adducts)

Group 1: Carcinogenic to Humans

• Tobacco Smoking• Tobacco Products, Smokeless• 4-Aminobiphenyl (4-ABP)• Benzene• Carmium• Chromium• 2-Naphthylamine (2-NA)• Nickel• Polonium-210 (Radon)• Vinyl Chloride

Group 2A: Probably Carcinogenic to Humans

• Acrylonitrile• Benzo[a]pyrene• Benzo[a]anthracene• 1,3-Butadiene• Dibenz(a,h)anthracene• Formaldehyde• N-Nitrosodiethylamine• N-Nitrosodimethylamine

PHIP DNA Adducts

P32 postlabeling