Abstract 6564: Biomarker discovery in triple negative breast cancer using RNA-sequencing analysis

Abstract

Abstract Breast cancer is the most common form of cancer, and afflicted over 2.2 million people in 2020. The sheer volume of patients who suffer from breast cancer warrants continued research and discovery efforts to improve treatment options. Triple negative breast cancer (TNBC) affects 10-15% of breast cancer patients. Unlike other forms of breast cancer, TNBC does not have estrogen or progesterone receptors and makes little to none of the HER2 protein. Due to the lack of these biomarkers that are typical treatment targets for other kinds of breast cancers, the hormone therapies and drugs that target other breast cancers are often ineffective against TNBC. This leaves chemotherapy and radiation therapy as the main treatment options. Although chemotherapy and radiation have treatment benefits, the recurrence rate after treatment is around 40%. Furthermore, these treatment options are very detrimental to the body, resulting in a weaker patient and a necessary recovery time between treatments. In this study, we analyzed publicly available RNA-sequencing (RNA-seq) data to identify the upregulated and downregulated transcriptional mechanism(s) that play a role in TNBC compared to healthy breast tissue. The analysis of the RNA-seq data was completed with the Automated Reproducible Modular Workflow for Preprocessing and Differential Analysis of RNA-seq Data (ARMOR), which trims, maps, and quantifies the mRNA sequencing reads to the human transcriptome for each read. The ARMOR program identified more than 12,000 differentially expressed genes between TNBC and healthy breast tissue samples. We then applied an artificial intelligence-based classification method, a random forest algorithm, to identify new biomarkers that best differentiate TNBC cells from healthy cells. These specific transcriptional biomarkers for TNBC could potentially be used as diagnostic biomarkers or as therapeutic targets. We anticipate that this data may expand the treatment options for TNBC. Citation Format: Jenna B. Poulsen, Mauri E. Dobbs, Naomi Rapier-Sharman, Brett E. Pickett. Biomarker discovery in triple negative breast cancer using RNA-sequencing analysis [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 6564.