Abstract
Abstract Cutaneous squamous cell carcinoma (cSCC) is the second most common human malignancy in the United States. Chronic long-term ultraviolet (UV) exposure drives cSCC development. Early clonal mutation (CM) accumulation is the first step in photocarcinogenesis and is the first known manifestation of field cancerization. Understanding CM accumulation and development is expected to improve the prevention of field cancerization and cSCC. Nevertheless, CMs are poorly understood, and mutations in cSCC have yet to be systematically compared to CM in sun-exposed skin. Key steps for studies to detect and compare CMs are to design optimal targeted sequencing panels and compare mutational hotspot areas. The ideal panel should cover genomic regions containing maximum numbers of mutations within a given number of amplicons. Currently there is no computational tool to help optimize target area selection. Therefore, we aimed to create an algorithm to optimize sequencing target area design for capturing high mutation frequency hotspot areas. An R Shiny web application was created to identify an optimal sequencing target panel from an input mutation dataset and compare the distribution of mutational hotspots. The tool optimizes sequencing target areas based on preset amplicon length by identifying the best fitting panel of amplicons to capture mutations efficiently. Besides identifying optimal sequencing target areas, the developed software also efficiently identifies the most highly mutated genomic areas and compares target area overlaps. The developed algorithm was used to compare the mutational hotspots of cSCC and CM in clinically normal-appearing skin or cSCC from previous publications (cBioPortal, Martincorena et al, Hernando et al, Wei et al, Fowler et al). The current method was more efficient than tested previously available alternative methods by increasing target areas capture efficacy by 1.05 - 8.1-fold. Using the developed tool, we found that frequently mutated areas of CMs in normal skin significantly overlap (p < 0.005) with those of cSCC. Mutational hotspots of normal skin with a history of frequent UV exposure had 1.2-fold greater overlap with cSCC than skin with minimal UV exposure, suggesting the frequently UV-exposed skin carries a greater number of cSCC-related mutations. Although we found that normal skin CM hotspots better predict capture efficiency in sun-exposed normal skin than cSCC mutation hotspots, cSCC mutation hotspots can still design efficient sequencing targets in genomic areas where we do not have deep sequencing data on CM in normal skin. Our work provides a framework for helping design efficient, customized sequencing panels covering the genomic regions with the highest number of mutations. We expect the current algorithm to be a valuable tool for similar studies of other cancers. Citation Format: Sydney R. Grant, Megan E. Fitzgerald, Barbara A. Foster, Wendy J. Huss, Lei Wei, Gyorgy Paragh. Comparison of mutational burden hotspots in cutaneous squamous cell carcinoma and UV-exposed healthy skin for development of optimal targeted sequencing panels [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1909.
Published Version
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