Abstract 6571: Mammonc-DB: A web based user-friendly tool for comprehensive multi-omics data analysis in breast cancer

Abstract

Breast cancer (BC) accounted for 15% cancer related death among women, in the United States last year. It is a highly heterogeneous and complex diseases with multiple molecular events occurring during cancer initiation and progression. It is important to unravel the heterogeneity of breast cancer and the molecular events to develop diagnostic biomarkers and targeted therapies. There is need for comprehensive and user-friendly tool for the utilization of available breast cancer data including metastatic and treatment response data. We have earlier created a highly used pan-cancer proteogenomic portal called UALCAN (ualcan.path.uab.edu). Based on the current unmet need for comprehensive BC data analysis and visualization resource, we developed an integrated proteo-genomicbreast cancer data analysis portal, called Mammonc-DB (http://resource.path.uab.edu/MammOnc-ge.html). For Mammonc-DB, we collected data from public repositories like NCBI Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) for collecting and analysis of genomics and epigenetics data, and, PRIDE, and, ProteomeXchange for proteomics data. We procured and processed multi-omics studies related to normal, primary, and metastatic human breast cancer data with other clinical information available, for different clinical models. We also collected and analyzed different therapy, and treatment studies that are currently employed in treating BC patients. Mammonc-DB has user friendly interface that aid breast cancer researchers and clinicians in, a) allows users to identify potential biomarkers in breast cancer, b) accessing publicly available breast cancer multi-omics data, c) Visualizing the expression pattern of gene or protein of interest with clinical feature stratification in each dataset among others This resource serves as a one-stop resource to study gene expression (protein-coding and non-coding) analysis along with epigenetic regulation, and protein expression patterns in BC. With this platform, we tend to create global user base that will accelerate discovery of biomarkers in BC that might be involved in diagnosis, therapeutic target identification and treatments of breast cancer. Citation Format: Santhosh Kumar Karthikeyan, Darshan S. Chandrashekar, Upender Manne, Chad Creighton, Zhaohui S. Qin, Sidharth Kumar, Sooryanaraya Varambally. Mammonc-DB: A web based user-friendly tool for comprehensive multi-omics data analysis in breast cancer [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 6571.