Abstract
Abstract The aim of the study is to conduct translational research of crucial breast cancer prognostic genes with functional proteomics. We have collected 61 breast cancer core biopsy samples, which were used for targeted sequencing for genetic variant analysis, mass-spectrometry analysis for protein expression and stain with H&E for whole slide image with Aperio Scanncer. After analysis of variant (ANOVA) of LC-MS/MS data, we found 17 proteins with highly differential expression between these 5 molecular subtypes from 61 patients. We then search for the protein-protein interaction (PPI) network from STRING database and found the strong network including 6 proteins namely Collagen Type II Alpha 1 Chain (COL2A1), Collagen alpha-1(XI) chain (COL11A1), Collagen alpha-1(VI) chain (COL6A1), Collagen alpha-2(VI) chain (COL6A2), Thrombospondin 1 (THBS1) and Lumican (LUM). To further investigate on the expression of these 6 target proteins in literature, we used Oncomine for data mining to query their mRNA expression profiles. Intriguingly, we discovered the mRNA expression of these targets are intensively distributed in many cancer types. This finding suggested the high potency of COL2A1, COL11A1, COL6A1, COL6A2, THBS1 and LUM as potential targets in breast cancer treatment. Our study has the potential contributing to the knowledge of breast cancer susceptibility, early detection, surveillance, and potential actionable targets, developing optimized screening programs and treatment protocols for distinct molecular subtypes. Citation Format: Chi-Cheng Huang, Wei-Chi Ku, Chi-Jung Huang, Ling-Ming Tseng. Identifying of potential therapeutic targets of Taiwanese breast cancer by functional proteomics [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 7098.
Published Version
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