Survival gap by disease: Where are the disparities getting worse?

1. TRACO 2011Magnitude and Causes ofCancer Health DisparitiesStefan Ambs, PhD, MPHLaboratory of Human Carcinogenesis (LHC)Center for Cancer Research, NCIambss@mail.nih.gov

2. Excess Burden of Cancer in theAfrican-American Community. “African-Americans have the highest death rates from all cancer sites combined, and from malignancies of the lung, colon and rectum, breast, prostate, and the cervix of all racial groups in the United States”

3. Black-White Life Expectancy Gap. Major causes of death are heart disease and cancer. In men homicide and HIV is prevalent whereas in females diabetes and stroke are abundant

4. Survival gap by disease: Where are the disparities getting worse?

5. Health disparities in breast cancer Not all segments of the U.S. population have equally benefited from the advances of our knowledge and treatment of cancer.

6. Age-adjusted Incidence Rates among US Population Groups

7. Differences in Lung Cancer Susceptibility by Population Group

8. Age-adjusted Mortality Rates among US Population Groups

9. Cancer Health Disparity = Health Care Disparity • Income and education influence health insurance coverage and access to appropriate early detection, treatment and pallative care • Socioeconomic factors influence exposure to cancer risk factors: tobacco use, poor nutrition, physical activity, and obesity • Poor and minority communities are targeted by tobacco companies and fast food restaurants, and have fewer opportunities for healthy nutrition and physical activity • Cultural factors influence health behavior, attitudes toward disease, and choice of treatment • Racial discrimination in health care settings is delaying treatment

10. Comorbidity and Health Disparity • Post treatment quality of life – survival disparity • African American breast cancer patients are more likely to die from competing causes than European American patients (JAMA 2005, 14: 1765 – 1772) • Diabetes • Hypertension • African American renal cancer patients are less likely to receive surgical treatment (nephrectomy) and die more often from competing causes than European American patients (J Clin Oncol 2007, 25: 3589 – 3595) • Hazard ratio (HR): 1.2 (1.1 – 1.3) vs. adj. HR 1.0 (0.9 – 1.1)

11. Socioeconomic Factors and Access to Medical Care: The only Factors? • Socioeconomic factors account for stage differences at diagnosis for most cancers but not breast and prostate cancer (Cancer 2002, 94: 2844 - 2854; Cancer Causes and Control 2003, 14: 761 - 766) • Traditional socioeconomic, clinical, and pathologic factors do not account for the race-related stage difference at diagnosis for prostate cancer (JNCI 2001, 93: 388 - 395) • Breast cancer survival differs by race (AA versus EA) in an equal-access health care facility (Cancer 1998, 82: 1310 - 1318; Cancer 2003, 98: 894 - 899) • Accounting for traditional risk factors explains differences in breast cancer incidence and outcome for all race/ethnic groups except African Americans (JNCI 2005, 97: 439 - 448) • Being insured and having access to medical care does not eliminate the survival disparity for African American women with breast cancer (JNCI Monogr 2005, 35: 88 - 95)

12. The neighborhood Effect on Health. A low socioeconomic status (SES) neighborhood confers additional mortality risk beyond individual SES. (J. Epidemiol. Community Health 2003, 57:444-52) Can a neighbor effect health outcomes through physiological adaptations to the environment? Similar to the “Barker hypothesis” of the developmental origins of adult disease. Adaptations may include epigenetic modification of gene expression ●Population differences in gene-specific DNA methylation at birth(Birth Defects Res 2011, 91:738-36) Comparing 107 AA with 94 EA newborns Differences clustered in cancer-related pathway

13. Is Biology a Contributing Factor? “While data suggest that access to quality care is a factor in cancer disparities, other factors also play a major role, including tumor biology and genetics” Racial disparities in prostate and breast cancer survival between African-American and European-American persist in randomized clinical trials (JNCI 2009, 101: 984 – 92) Intrinsic differences in tumor biology influencing disease aggressiveness? Differences in response to therapy?

14. Population differences in tumor estrogen receptor status and disease grade Race/ethnic disparity in prevalence of basal-like/triple-negative breast tumors (JAMA 2006, 295: 2492 – 2502) Biology & Cancer Health Disparity: Example Breast Cancer

15. High proportion of breast cancer patients in West Africa present with high grade and triple-negative disease (J Clin Oncol 2009, 27: 4514 – 21) Caveat: Breast cancer survival desparity in US is irrespective of tumor ER status (JNCI 2009, 101: 993-1000) Race/ethnic differences in genome-wide methylation Hypermethylation in AA tumors (Clin Cancer Res 2004, 10:2052-7. Biology & Cancer Health Disparity: Example Breast Cancer

16. A mutation in the p53 tumor suppressor gene negatively affects response to cancer therapy p53 mutation frequency in breast tumors is highest in patients from deprived communities in Great Britain (Br J Cancer 2010, 102: 719 – 726) which is consistent with previous observations by the Harris lab at NCI that the p53 mutation status of tumors appears to be related to specific exogenous or endogenous carcinogens (Mutation Res 1999, 428: 23 – 32) and the observation of differences in p53 alterations in breast tumors between AA and EA patients (Cancer 2004, 101: 1293 – 1301; PLoS One 2009, 4: e4531) Tumor p53 mutation status is associated with SES in Breast Cancer

17. Biology & Cancer Health Disparity: Example Prostate CancerFaster growth rate/earlier transformation in African American than European American tumors (J Urology 2010, 183: 1792 – 7)Inflammation in non-cancerous prostate biopsies is more prevalent among African American than European American men (JNCI 1998, 90: 756 – 60)Distinct genetic alterations in prostate tumors in ChinaInfrequent PTEN loss and TMPRSS2:ERG fusionDifferent pathway to cancer? (Cancer Res 2010, 70: 5207 – 12)

18. Race differences in prevalence of 8q24 cancer susceptibility variants Admixture mapping identified 8q24 as a locus of increased risk for African-American men when compared to European-American men (PNAS 2006, 103: 14068-73) Risk alleles are more common among African-American men, leading to the highest population attributable risk conferred by 8q24 in this population (Nat Genet 2007, 39: 638 – 44 & 954 – 6) Genetics & Cancer Health Disparity: Example Prostate Cancer

19. Health Disparity Research at LHCNCI Maryland Case Control StudiesExamine the contribution of environmental and inherited factors to the excess cancer burden among African AmericansCancer SitesProstate PI: AmbsBreastLung PI: HarrisColon

20. Research Aims Examine the tumor biology of prostate and breast cancer comparing African-American patients with European-American patients Identify factors that may either influence the presentation of the disease (e.g., causing a more aggressive disease among African-American patients), or influence the response to therapy (e.g., causing an inferior response among African-American patients)

21. HypothesisDifferences in gene expression will reveal differences in tumor biology between African American and European American patients

22. Gene Expression Profiling Study of Prostate Cancer • Gene expression analysis • 33 African-American (AA) patients • 36 European-American (EA) patients • Tumors were matched for clinical parameters • Analysis at gene and pathway level

23. Differentially Expressed Genes(Cancer Res 2008, 68: 927– 36) • 162 genes differently expressed (FDR  5%) • Several metastasis-related genes, e.g., CXCR4, MMP9, AMFR • Differently expressed genes were not shared with the published list(s) of marker genes for prostate tumorsMarker genes in prostate cancer • Meta-analysis by Rhodes et al. • Cancer Res. 2002, 62, 4427–33 • 80 marker genes – no overlap

24. First Finding Expression of previously identified marker genes for prostate cancer is not significantly different between tumors from African-American and European-American patients

25. Pathway Analysis:Differences in Immune ResponseDifferently expressed genes Significance of enrichment for genes in a pathway

26. DNA Copy Number Alterations Affect Loci Regulating Immune Response in AA N = 21 N = 20 Confirmed in independent validation set

27. Rose et al. J Translational Medicine 2010, 8:70 (continued) Functional annotation of genes in the 4 genomic areas3q26.1, 5p15.33, 14q32.33, 16p11.2

28. An interferon Signature in AA TumorsUp-regulated genes include:IFN, INDO, PTPN22, STAT1CCL4, CCL5, CCL8, CCL19, CXCL9 CXCL11, CXCR4, CCR7IL-15 & 16ISG15, ISG20, IFI16, IFI27, IFI44 & 44L IFIT1, IFIT3, IFITM(1/2/3), IRF1 & 8MX1 & 2, OAS2TAP1 & 2

29. Interferon Signature Predicts Survival Homolog to “Interferon-related Gene Signature for DNA Damage Resistance” (IDRS) (PNAS 2008, 105: 18490 – 95) and an EMT-related “Interferon Response Gene Signature” (IRG) (Genome Biol 2007, 8: R191) associated with poor outcome in breast cancer IRDS is a predictive marker for resistance to chemotherapy and radiation and poor survival. Key signature genes mediate experimental resistance to therapy.

30. IFNgamma/STAT1 Signaling selects for aggressive cancer phenotype & resistance ●Constitutive overexpression of IFNγ/STAT1 pathway genes is selected for by lung microenvironment (B16F1 lung metastasis model)● IFNγ/STAT1 pathway activation leads to resistance to IFNγ, ionizing radiation & doxorubicin toxicity

31. Breast Tumor Microenvironment Differs between AA and EA Women Validation Study Immunohistochemistry: AA =143; EA =105 Pilot Study LCM dissected tumors: AA =18; EA =17 In African-American tumors (independent of disease stage and ER status) Interferon signature Macrophage infiltration (CD68) Microvessel density (CD31) Differences by Pathway

32. Conclusions • Indication of distinct tumor microenvironments by race/ethnicity • Differences in tumor immunobiology and chemotaxis • Presence of an interferon signature in AA tumors • Immune-related differences could be predisposing to tumor progression and may affect therapy outcome

33. Potential Implications resulting in AA resistance to therapy and increased tumor metastasisThe Immune Signature in African-American Tumors results from chronic inflammation leading to:1. Suppression of T cell cytotoxicity2. Angiogenesis3. Infiltration of monocytes and4. Tissue remodeling.

34. Intrinsic Signature or Environmental ExposureInterferons (α,β,γ) in tumors increase from:1. viral infections2 germline differences e.g. SNPs by ancestry3. stress4. reactivation of endogenous retroviruses e.g. HERV-K and 5. acquired genetic alterations in tumors.

35. Role of Chronic Stress in Cancer ProgressionEpidemiology connects stressful life events to immune dysfunction and poorer cancer survival, but not to increased incidence (Nat Rev Immunol 2005, 5: 243 – 251; Nat Clin Pract 2008, 5: 466 – 475; JCO 2010, 28: 4094 – 4099)

36. Stress Impacts Tumor Biology Chronic stress promotes tumor vascularization and growth by beta-adrenergic signaling in a mouse model of ovarian cancer (Nat Medicine 2006, 12: 939 – 944) Stress-induced beta-adrenergic signaling induces breast cancer metastasis and involves tumor-associated macrophages (Cancer Res 2010, 70: 7042 – 7052) Noradrenaline induces migration and metastasis of human breast, colon, and prostate cancer cells (Cancer Res 2001, 61: 2866 – 2869; BCRT 2003, 80: 63 – 70; Int J Cancer 2006, 118: 2744 – 2749)

37. Beta-Blocker Use Improves Breast Cancer Survival Beta blocker use reduces disease recurrence and improves breast cancer-specific survival (Oncotarget 2010, 1: 628 – 638) Propranolol users are significantly less likely to develop advanced breast cancer and have a reduced breast cancer-specific mortality (OR = 0.19, 95% CI: 0.06 to 0.60) (JCO 2011, 29: 2635 – 2644) Beta blocker use is associated with improved RFS in breast cancer in general and in the triple-negative disease (JCO 2011, 29: 2645 – 2652)

38. A Pilot Study - Design Collect fresh-frozen tumor tissue and adjacent non-tumor tissue (as available) and a blood sample (for plasma/serum, PBMCs) from consented 100 breast cancer patients African-Americans and European-Americans Patients will complete a short interviewer-administered questionnaire (trained personnel through NCI contract) evaluates perceived stress and discrimination, use of beta blockers, education and income, martial status, and body mass index

39. Study Design (continued) Determine tumor adrenaline, noradrenaline and dopamine, and cAMP concentrations Perform gene expression profiling of tumor and adjacent normal tissue Stratify patients by self-reported perceived stress and discrimination and identify gene signatures associated with stress/discrimination and catecholamines

40. Study Design (continued) Evaluate gene signature(s) as predictor of disease survival and/or response to therapy Select candidate markers for testing as blood-based markers of stress-induced tumor progression Test in UMD and Georgetown U patient cohorts Examine differences between AA and EA patients and by tumor subtype

41. Analysis Plan Examine relationship between perceived stress/discrimination and tumor biology Self-reported perceived stress and discrimination Gene expression profile and protein markers (IHC, ELISA) Examine relationship between perceived stress/discrimination and tumor catecholamine levels Generate tumor gene signature for catecholamines Compare with stress/discrimination signature Evaluate gene signature(s) as predictor of disease outcome and response to therapy (e.g., beta blocker use) In-house and publically available datasets

42. Evaluate prevalence of stress signature in breast tumors from AA and EA patients and by tumor subtype Is there a disparity consistent with disease outcome data? Identify candidate blood-based marker(s) for stress-induced tumor progression using the obtained gene expression profiles for guidance Evaluate these marker(s) in the current study and a patient cohort of 383 AA and 383 EA breast cancer patients at Georgetown University previously evaluated for discrimination-based stress (PI Vanessa Sheppard) Analysis Plan (continued)

43. Gene Expression Profiling Studies A Collaboration • Contributors • LHC: Wallace TW, Martin DN, Boersma BJ, Prueitt RL, Howe TM, Williams EH, Ambs S • Intramural: Yi M, Stephens RM, Gillespie JW, Caporaso NE, Tsai YC, Weissman AM • Extramural: Yfantis HG, Lee DH (both Baltimore VA Hospital), Reimers M (VCU), Loffredo CA (Georgetown University) • NCI Cooperative Prostate Cancer Tissue Resource