Dataset Information

Lung Cancer Screening and Epigenetics in African Americans: The Role of the Socioecological Framework.

ABSTRACT: Lung cancer is the leading cause of cancer morbidity and mortality in the U.S. and racial/ethnic minorities carry the greatest burden of lung cancer disparities with African Americans (AAs) impacted disproportionately. Inequities in lung cancer health disparities are often associated with multiple bio-behavioral and socio-cultural factors among racial/ethnic minorities. Epigenetic research has advanced the understanding of the intersectionality between biological and socio-cultural factors in lung cancer disparities among AAs. However, gaps exist in the engagement of diverse populations in epigenetic lung cancer research, which poses a challenge in ensuring the generalizability and implementation of epigenetic research in populations that carry an unequal cancer burden. Grounding epigenetic lung cancer research within a socio-ecological framework may prove promising in implementing a multi-level approach to community engagement, screening, navigation, and research participation among AAs. The University of Illinois Cancer Center (UI Cancer Center) is employing an evidence-based (EB) model of community/patient engagement utilizing the socio-ecological model (SEM) to develop a culturally sensitive epigenetic lung cancer research program that addresses multiple factors that impact lung cancer outcomes in AAs. By implementing epigenetic research within a group of Federally Qualified Health Centers (FQHCs) guided by the SEM, the UI Cancer Center is proposing a new pathway in mitigating lung cancer disparities in underserved communities. At the individual level, the framework examines tobacco use among patients at FQHCs (the organizational level) and also tailors epigenetic research to explore innovative biomarkers in high risk populations. Interpersonal interventions use Patient Navigators to support navigation to EB tobacco cessation resources and lung cancer screening. Community level support within the SEM is developed by ongoing partnerships with local and national partners such as the American Lung Association (ALA) and the American Cancer Society (ACS). Lastly, at the policy level, the UI Cancer Center acknowledges the role of policy implications in lung cancer screening and advocates for policies and screening recommendations that examine the current guidelines from the United States Preventive Services Task Force (USPTF).

SUBMITTER: Watson KS

PROVIDER: S-EPMC6423082 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Lung Cancer Screening and Epigenetics in African Americans: The Role of the Socioecological Framework.

Watson Karriem Sadot KS Hulbert Alicia A Henderson Vida V Chukwudozie Ifeanyi Beverly IB Aponte-Soto Lisa L Lerner Lane L Martinez Erica E Kim Sage S Winn Robert A RA

Frontiers in oncology 20190312

Lung cancer is the leading cause of cancer morbidity and mortality in the U.S. and racial/ethnic minorities carry the greatest burden of lung cancer disparities with African Americans (AAs) impacted disproportionately. Inequities in lung cancer health disparities are often associated with multiple bio-behavioral and socio-cultural factors among racial/ethnic minorities. Epigenetic research has advanced the understanding of the intersectionality between biological and socio-cultural factors in lu ...[more]

PMID: 30915271

Similar Datasets

Project description:Translational Relevance Historically, African Americans have been underrepresented in clinical cancer research. Diversity helps to ensure equal access to new cancer therapies and better treatment for everyone. Cancer research is increasingly focused on classifying patients according to molecular profiles for particular groups. We provide a detailed molecular analysis from paired NSCLC tissues that identified differential coding and noncoding RNA expression in NSCLC from African Americans (AA) and European Americans (EA). Similar to other tumor types, we determined that race-enriched gene and microRNA expression signatures suggest a more aggressive disease in African Americans. Based on predicted drug resistance to adjuvant chemotherapies, AA may not equally benefit from the same range of clinical drugs as EA. Our findings provide a rationale for integrating coding and noncoding transcriptome profiles, along with clinical, demographic, and genomic data, when determining treatment options. Abstract Purpose: To determine if racial differences in gene and microRNA expression translates to differences in lung tumor biology with clinical relevance in African Americans (AA) and European Americans (EA). Experimental Design: The NCI-Maryland Case Control Study includes seven Baltimore City hospitals and is overrepresented with AA patients (~40%). Patients that underwent curative NSCLC surgery between 1998 and 2014 were enrolled. Comparative molecular profiling used mRNA (n = 22 AAs and n = 19 EAs) and microRNA (n = 42 AAs and n = 55 EAs) expression arrays to track differences in paired fresh frozen normal tissues and lung tumor specimens from AA and EA. Pathway enrichment, predicted drug response, tumor microenvironment infiltration, cancer immunotherapy antigen profiling, and microRNA target enrichment were assessed. Results: AA-enriched differential gene expression was characterized by stem-cell and invasion pathways. Differential gene expression in lung tumors from EA were primarily characterized by cell proliferation pathways. Population-specific gene expression was partly driven by population-specific miRNA expression profiles. Drug susceptibility predictions revealed a strong inverse correlation between AA resistance and EA sensitivity to the same panel of drugs. Statistically significant differences in M1 and M2 macrophage infiltration was observed in AA (P <0.05), however, PD-L1, PD-L2 expression was similar between both. Conclusions: Comparative transcriptomic profiling revealed clear differences in lung tumor biology between AA and EA. Increased participation by AA in lung cancer clinical trials are needed to integrate, and leverage, transcriptomic differences with other clinical information to maximize therapeutic benefit in both AA and EA. GSEA, Connectivity Map, CIBERSORT, cancer immunotherapy antigen profiling, and hypergeometric testing for overlapping miRNA targets were performed.

Project description:Because existing risk prediction models for lung cancer were developed in white populations, they may not be appropriate for predicting risk among African-Americans. Therefore, a need exists to construct and validate a risk prediction model for lung cancer that is specific to African-Americans. We analyzed data from 491 African-Americans with lung cancer and 497 matched African-American controls to identify specific risks and incorporate them into a multivariable risk model for lung cancer and estimate the 5-year absolute risk of lung cancer. We performed internal and external validations of the risk model using data on additional cases and controls from the same ongoing multiracial/ethnic lung cancer case-control study from which the model-building data were obtained as well as data from two different lung cancer studies in metropolitan Detroit, respectively. We also compared our African-American model with our previously developed risk prediction model for whites. The final risk model included smoking-related variables [smoking status, pack-years smoked, age at smoking cessation (former smokers), and number of years since smoking cessation (former smokers)], self-reported physician diagnoses of chronic obstructive pulmonary disease or hay fever, and exposures to asbestos or wood dusts. Our risk prediction model for African-Americans exhibited good discrimination [75% (95% confidence interval, 0.67-0.82)] for our internal data and moderate discrimination [63% (95% confidence interval, 0.57-0.69)] for the external data group, which is an improvement over the Spitz model for white subjects. Existing lung cancer prediction models may not be appropriate for predicting risk for African-Americans because (a) they were developed using white populations, (b) level of risk is different for risk factors that African-American share with whites, and (c) unique group-specific risk factors exist for African-Americans. This study developed and validated a risk prediction model for lung cancer that is specific to African-Americans and thus more precise in predicting their risks. These findings highlight the importance of conducting further ethnic-specific analyses of disease risk.

Dataset Information

Lung Cancer Screening and Epigenetics in African Americans: The Role of the Socioecological Framework.

Publications

Lung Cancer Screening and Epigenetics in African Americans: The Role of the Socioecological Framework.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets