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2023 North America Conference on Lung Cancer (NACL ...
PP01.96 (Poster) Characterization of DNA damage re ...
PP01.96 (Poster) Characterization of DNA damage repair mutations in lung cancer in an underserved urban patient population
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Pdf Summary
Lung cancer is the leading cause of cancer-related deaths worldwide. DNA-damage repair (DDR) mutations in lung cancer have shown potential as therapeutic targets and predictive biomarkers. However, the relationship between DDR mutations and socioeconomic, demographic, and environmental factors is not well-studied. <br />This study aims to characterize the distribution of DDR mutations in lung cancer patients at the University of Illinois Chicago (UIC) and identify correlations with demographic data. The study population consisted of underserved and underinsured patients, with a high percentage of Medicaid recipients and Black individuals. <br />The frequency and distribution of DDR mutations in lung cancer at UIC were found to be similar to what has been previously reported. Lung cancers with DDR mutations had a higher tumor mutational burden, indicating a potential susceptibility to immunotherapy. There was no significant difference in sex or race between the DDR positive and DDR negative groups. However, there may be differences in lung cancer type, insurance category, and geographic distribution between the two groups. <br />Future work includes obtaining further clinical data such as tobacco history, family history, and survival time for the study population. The geographic distribution will be studied in more detail, taking into account factors such as income, environmental burden, crime rate, cigarette smoking rate, obesity, and pollution. Overall, this study provides valuable insight into the characteristics of DDR mutations in an underserved urban patient population with lung cancer, which could contribute to the development of targeted therapies and personalized treatment approaches.
Asset Subtitle
Jeremy Kao
Keywords
lung cancer
DDR mutations
therapeutic targets
predictive biomarkers
underserved patients
Medicaid recipients
tumor mutational burden
immunotherapy susceptibility
geographic distribution
targeted therapies
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