Abstract 6586: Updates to UALCAN, a comprehensive cancer proteogenomic data analysis platform for discovery research
Authors: Chandrashekar Darshan Shimoga , Varambally Sooryanarayana , Karthikeyan Santhosh Kumar , Korla Praveen Kumar , Patel Henalben , Athar Mohammad , Manne Upender , Netto George J. , Shovon Ahmedur Rahman , Kumar Sidharth , Qin Zhaohui S. , Crieghton Chad J. 
Published: April 2023

Background: Recent advances in high throughput technologies and initiation of multiple consortium driven projects have led to generation of high volume of molecular data related to thousands of cancer patients. These high throughput data are extremely useful for novel biomarker identification, therapeutic target identification in tumor subclasses and allows numerous hypothesis driven cancer research projects. However, the sheer volume of data and diverse data formats presents tremendous challenge for researchers with no programming experience to access and analyze comprehensively. These factors prompted us to develop UALCAN (University of ALabama CANcer portal, Yes! You All Can) for comprehensive cancer data analysis in a user-friendly manner. UALCAN enables cancer researchers/clinicians in tumor subgroup based gene expression, protein expression and survival analyses. UALCAN is extremely popular among cancer researchers round the world with well over a “MILLION” site visits and cited over 3400 times in research articles. UALCAN integrates The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), as well as gene expression data from Children Brain Tumor Tissue Consortium (CBTTC). Users can also analyze non-coding RNA (miRNA and lncRNA) expression data from The Cancer Genome Atlas (TCGA) and the epigenetic data though the promoter DNA methylation analysis form the TCGA data.

Results: UALCAN now enables user to study expression profile of ~10000 proteins in 14 CPTAC cancers and expression pattern and survival impact of 20,500 protein-coding, ~17,000 lncRNA and 1800 miRNA in 33 TCGA cancers. It also facilitates analysis of gene expression pattern in pediatric brain cancer. User-friendly graphical user interface of UALCAN facilitates a) analyzing protein/non-coding RNA expression in tumor subgroups based on race, stage, age and molecular types; b) identifying top differentially expressed lncRNA/miRNA in specific cancer subtype; c) listing potential gene targets of non-coding RNA; d) performing pan-cancer analysis and e) determining impact of gene expression on patient’s overall survival.

Conclusions: UALCAN is freely available at http://ualcan.path.uab.edu (Google: UALCAN) This dynamic data portal provides constant updates that empower cancer researchers in studying gene and protein level expression and identifying tumor subgroup specific non-coding RNA biomarkers. UALCAN serves a one-stop platform for access, study, analyze and leverage large cancer datasets.

Citation Format: Darshan Shimoga Chandrashekar, Sooryanarayana Varambally, Santhosh Kumar Karthikeyan, Praveen Kumar Korla, Henalben Patel, Mohammad Athar, Upender Manne, George J. Netto, Ahmedur Rahman Shovon, Sidharth Kumar, Zhaohui S. Qin, Chad J. Crieghton. Updates to UALCAN, a comprehensive cancer proteogenomic data analysis platform for discovery research [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 6586.