Abstract
Abstract Background: Pancreatic adenocarcinoma (PDAC) is an aggressive cancer predicted to be the second leading cause of cancer mortality in the next decade. Significant disparities in the incidence rate and outcomes of Black patients with PDAC have recently been reported. Efforts to characterize the molecular landscape of PDAC are ongoing; however, the molecular mechanisms driving cancer in PDAC patients remain largely unexplored with respect to sociocultural race. In this study, we utilized the Cancer Genome Atlas (TCGA) dataset to describe the somatic mutation, DNA methylation and gene expression profiles of PDAC patients with respect to sociocultural race in an effort to elucidate the racial heterogeneity in pancreatic carcinogenesis. Methods: This study involved accessing the public TCGA dataset for all patients with diagnosed PDACs. We filtered this cohort to include only patients with available racial information and matched DNA methylation, mRNA expression and simple somatic mutation data (n = 150). We analyzed the frequency and nature of non-silent simple somatic mutations for our cohort, both combined and separated by sociocultural race, and calculated the top differentially-methylated and differentially-expressed genes, using a maximum p-value of 0.01 for the Benjamini-Hochberg adjustment method as our cut-off. Results: We observed the four previously reported pancreatic adenocarcinoma driver genes (KRAS, TP53, SMAD4, and CDKN2A) to be the genes most frequently mutated in White (n = 132) and Asian (n = 9) PDAC samples. In Black (n = 5) samples, PDAC appears to be only partially driven by mutation of these driver genes. We found Black PDAC samples have a distinct mutational landscape and harbor somatic mutations in additional genes, including: CSMD2 (42.9%), RYR1 (28.6%), CBLL2 (28.6%), ANKRD24 (28.6%), SAMD7 (28.6%). The DNA methylation landscape of PDAC patients is also distinct with respect to sociocultural race, with the majority of differentially-methylated loci present to a greater degree in Black (53.8%) or Asian samples (28.2%), compared to White (17.9%) samples. Gene expression data also follow this trend, with the majority of genes showing the highest degree of differential expression in Black (82.4%) versus Asian (14.7%) or White (2.9%) patients. Conclusion: Our preliminary analyses suggest racial heterogeneity exists at the level of DNA methylation, gene expression and somatic mutation. We discovered that reporting on PDAC driver mutations is likely biased by the overrepresentation of White patient samples in the TCGA dataset – the largest publicly available dataset with data on sociocultural race. Given our preliminary results, further work to describe the DNA methylation and gene expression landscape in PDAC with respect to sociocultural race is imperative. However, until minority representation is improved in such biobanking efforts – the ability to perform molecular profiling of PDAC within those populations experiencing disparate incidence and outcomes remains underpowered. Citation Format: Haleigh Tianna Larson, Ankit Chhoda, Astrid Hengartner, Nesrin Hasan, Nensi Ruzgar, Sri Yalamanchi, John W. Kunstman, James J. Farrell, Anup Sharma, Nita Ahuja. Racial heterogeneity in the molecular landscape of pancreatic adenocarcinoma: A call for action [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-155.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.