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posted on 2024-01-26, 14:20 authored by Shreya M. Shah, Elena V. Demidova, Salena Ringenbach, Bulat Faezov, Mark Andrake, Arjun Gandhi, Pilar Mur, Julen Viana-Errasti, Joanne Xiu, Jeffrey Swensen, Laura Valle, Roland L. Dunbrack, Michael J. Hall, Sanjeevani Arora Characterization of POLE mutations in the CLS and TCGA dataset. A, Flowchart and analysis tree for colorectal cancer (CRC), endometrial cancer (EC), and ovarian cancer (OC) tumors by POLE mutations, TMB, and MSI/MSS status. Among 1,870 colorectal cancer, 4,481 endometrial cancers, and 8,910 ovarian cancer tumor genomic profiles, a total of 447 carried POLE mutations. Clinically relevant TMB cut-off points were used to define the TMB-H (≥10 mut/Mb) and TMB-L (<10 mut/Mb) cohorts. POLE mutation cohorts along with TMB and MSI/MSS status were defined. TMB-L tumors with POLE variants but no established POLE ExoD driver are referred to as “POLE Variants TMB-L” (Group 1, MSS or MSI). TMB-H tumors with known POLE ExoD driver only were referred to as “POLE ExoD Driver” (Group 2, MSS or MSI). TMB-H tumors with co-occurring POLE ExoD driver and POLE variant(s) were referred to as “POLE ExoD Driver + POLE ExoD Variant” (Group 3, MSS or MSI). TMB-H tumors with only POLE variant(s) and no POLE ExoD driver were referred to as “POLE Variant TMB-H” (Group 4, MSS or MSI). B, Age distribution of patients in the CLS cohort with POLE-mutated tumors (n = 447) designated as Group 1 (green), Group 2 (red), Group 3 (purple), and Group 4 (blue). mTMB comparisons between Group 2 and 3 colorectal cancers (C), endometrial cancers (D), and ovarian cancers (E). mTMB comparisons between Group 2 and 3 genomic profiles of colorectal cancer (F), endometrial cancer (G), and ovarian cancer (H). MSI-H tumor profiles were removed from this analysis. TCGA cohort mTMB comparisons between Group 2 and 3 tumors, in I MSI-H or MSS tumor profiles were included and in J only MSS tumor profiles were included. Because of smaller sample size per tumor type, analyses were pooled. A Mann–Whitney test was performed and ***, P < 0.001; *, P < 0.05; NS, nonsignificant.
Funding
HHS | National Institutes of Health (NIH)
American Cancer Society (ACS)
U.S. Department of Defense (DOD)
Spanish Ministry of Science and Innovation
MEC | Instituto de Salud Carlos III (ISCIII)
Generalitat de Catalunya (Government of Catalonia)
History
ARTICLE ABSTRACT
POLE driver mutations in the exonuclease domain (ExoD driver) are prevalent in several cancers, including colorectal cancer and endometrial cancer, leading to dramatically ultra-high tumor mutation burden (TMB). To understand whether POLE mutations that are not classified as drivers (POLE Variant) contribute to mutagenesis, we assessed TMB in 447 POLE-mutated colorectal cancers, endometrial cancers, and ovarian cancers classified as TMB-high ≥10 mutations/Mb (mut/Mb) or TMB-low <10 mut/Mb. TMB was significantly highest in tumors with “POLE ExoD driver plus POLE Variant” (colorectal cancer and endometrial cancer, P < 0.001; ovarian cancer, P < 0.05). TMB increased with additional POLE variants (P < 0.001), but plateaued at 2, suggesting an association between the presence of these variants and TMB. Integrated analysis of AlphaFold2 POLE models and quantitative stability estimates predicted the impact of multiple POLE variants on POLE functionality. The prevalence of immunogenic neoepitopes was notably higher in the “POLE ExoD driver plus POLE Variant” tumors. Overall, this study reveals a novel correlation between POLE variants in POLE ExoD-driven tumors, and ultra-high TMB. Currently, only select pathogenic ExoD mutations with a reliable association with ultra-high TMB inform clinical practice. Thus, these findings are hypothesis-generating, require functional validation, and could potentially inform tumor classification, treatment responses, and clinical outcomes.
Somatic POLE ExoD driver mutations cause proofreading deficiency that induces high TMB. This study suggests a novel modifier role for POLE variants in POLE ExoD-driven tumors, associated with ultra-high TMB. These data, in addition to future functional studies, may inform tumor classification, therapeutic response, and patient outcomes.
