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Abstract 6080: Comprehensive profiling of pathogenic/likely pathogenic large genomic rearrangements in pan cancer samples

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Background: Correlations between large genomic rearrangements (LGRs) and cancer types beyond breast or ovarian cancer have not been sufficiently profiled, likely due to the highly inefficient methods of detecting these… Click to show full abstract

Background: Correlations between large genomic rearrangements (LGRs) and cancer types beyond breast or ovarian cancer have not been sufficiently profiled, likely due to the highly inefficient methods of detecting these types of mutations. Methods: This study utilized next-generation sequencing (NGS) to analyze and classify the germline LGR mutation profile in 17,025 cancer patients across 22 cancer types. We characterize novel LGRs based on predicted pathogenicity and take a closer look at genes that acquire both germline and somatic mutations within our samples. Detection method was validated using ddPCR assay of commonly investigated LGR genes. Results: In total, 15,659 samples from across 22 cancer types were retained for analysis after filtering. We observed that, in our cohort, the cancer type with the highest proportion of LGRs are ovarian cancer (4.7%), renal cell carcinoma (2.5%), breast cancer (2%), glioma (1.8%), and thyroid carcinoma (1.8%). Annotation of detected germline variants revealed several genes containing novel LGRs including MSH2, FANCA, and PMS2. We observed co-mutational events between LGR in MSH2 and somatic mutations in BRCA2, KTM2B, KDM5A, CHD8, and HNF1A. Furthermore, our analysis shows that samples with pathogenic and likely pathogenic germline LGR mutations tended to also have higher mutational burden, chromosomal instability, and microsatellite instability ratio compared to other samples with non-LGR germline mutations. Conclusion: In this study, we demonstrated the prevalence of LGRs beyond that of BRCA1/2 and RB1 in breast and ovarian cancer. Our profiles of these pathogenic/likely pathogenic alterations can potentially fuel further investigations and highlight new understanding of LGRs in multiple cancer types. Proportion of samples with large genomic rearrangements in each cancer type Cancer Typess Germline Non-LRG P/LP proportion (%) Germline Non-LRG P/LP proportion (%) Ovarian cancer (OC) 22.4 22.4 Breast cancer (BC) 16.2 16.2 Prostate (PRAD) 13 13 Endometrial 13.4 13.4 Glioma 11.7 11.7 Pancreatic (PC) 11.3 11.3 Neuroendocrine (NEN) 8.5 8.5 Sarcoma 9.5 9.5 Colorectal cancer (CRC) 9.7 9.7 Thyroid (THCA) 8 8 Hepatocellular carcinoma (HPC) 9.1 9.1 Gastrointestinal stromal tumor (GIST) 9.5 9.5 Gastric cancer (GC) 8.2 8.2 Renal cell carcinoma (RCC) 9.3 9.3 Cervical cancer 10.2 10.2 Lung cancer 8.2 8.2 Esophageal cancer 9.2 9.2 Bladder cancer (BLCA) 8.8 8.8 Leukemia 3.9 3.9 Head and neck cancers (HNC) 6.7 6.7 Lymphoma 1.2 4.8 Melanoma 0.5 4.8 Pan-Cancer 1 9.1 P/LP: Pathogenic/Likely pathogenic LGR: Large genomic rearrangement Citation Format: Haimeng Tang, Hua Bao, Xue Wu, Yang Shao. Comprehensive profiling of pathogenic/likely pathogenic large genomic rearrangements in pan cancer samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6080.

Keywords: pathogenic likely; pan cancer; large genomic; genomic rearrangements; likely pathogenic; cancer

Journal Title: Cancer Research
Year Published: 2023

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