Abstract 4972: Bioinformatic analysis of an annotated genomic database is clinically useful in a private cancer center

Abstract

Abstract Background: Sequencing of patient solid tumor tissue is not a common service provided by community cancer centers. Our community cancer center has collected and sequenced over 5,000 tumor tissue samples from patients with various types of cancer. Since April 2019, we have conducted whole-exome and whole-transcriptome sequencing and stored this data in an internal genomics database. To analyze large patient cohorts, we must first optimize bioinformatic workflows on a smaller scale, which can then be applied to studies of larger populations. Previous studies have shown BRAF mutations are associated with an increased activation of the mitogen-activated protein kinase (MAPK) pathway. We analyzed transcriptomes of a cohort of 30 patients with thyroid cancer, 15 with V600E BRAF mutations and 15 wild-type for BRAF, for MAPK Pathway Activation Scores (MPAS). MPAS serves as a transcriptomic measure of the activation state of the MAPK pathway and has been shown to be a reliable prognostic biomarker of MAPK activity. Method: We conducted a retrospective analysis of data from FFPE tumor samples sent to a commercial CLIA-certified laboratory from April 2019 to October 2023. Samples were profiled by whole exome, whole transcriptome sequencing and immunohistochemistry (IHC). Whole transcriptome sequencing (WTS) was executed using Illumina NovaSeq along with the Agilent SureSelect Human All Exon V7 bait panel. Resulting data were reported in transcripts per million (TPM) using the Salmon expression pipeline. MPAS was calculated using the expression profile of 10 MAPK-associated genes. Results: There was no significant difference in BRAF expression levels or MAPK activation between patients with BRAF mutant and BRAF wild-type thyroid cancer (median MPAS scores: -0.09 vs. 0.11, p=0.9). This analysis workflow will be repeated with a larger patient population of patients with melanoma in the future; however, the consistency of expression between the groups, the rank-order, and the low variability per group suggest that expression changes related to this BRAF mutation may occur upstream or via differential regulation of an indirect pathway. Rank-order statistics and percentiles become more precise as data per tumor type grows. Conclusions: Our community cancer center began building an internal genomics database including whole-exome and whole-transcriptome sequencing since 2019. This resource facilitates analysis of patient samples for tumor mutational burden, gene fusions, transcriptomic data, and other important characteristics which could reveal patterns or trends that inform cancer diagnosis and prognosis of other patients. Analysis of expression data for patients with advanced solid tumors who have mutations in genes of interest could inform on potential targeted treatments in the future. This study represents a single example of the potential of our internal clinically annotated genomics database. Citation Format: Carlos E. Zuazo, Sourat Darabi, David R. Braxton, Phillip Stafford, Michael J. Demeure. Bioinformatic analysis of an annotated genomic database is clinically useful in a private cancer center [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4972.