UALCAN: An update to the integrated cancer data analysis platform

• Type of Material: Article
• Authors: Darshan Shimoga Chandrashekar, University of Alabama Birmingham; Santhosh Kumar Karthikeyan, University of Alabama Birmingham; Praveen Kumar Korla, University of Alabama Birmingham; Henalben Patel, University of Alabama Birmingham; Ahmedur Rahman Shovon, University of Alabama Birmingham; Mohammad Athar, University of Alabama Birmingham; George J. Netto, University of Alabama Birmingham; Zhaohui Qin, Emory University; Sidharth Kumar, University of Alabama Birmingham; Upender Manne, University of Alabama Birmingham; Chad J. Creighton, Baylor College of Medicine; Sooryanarayana Varambally, University of Alabama Birmingham
• Language: English
• Date: 2022-03-01
• Publisher: Elsevier Science Inc.
• Publication Version: Final Published Version
• Copyright Statement: © 2022 The Authors. Published by Elsevier Inc.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.neo.2022.01.001
• Title of Journal or Parent Work: Neoplasia
• Volume: 25
• Start Page: 18
• End Page: 27
• Grant/Funding Information: S.V. and U.M were supported by the funding from U54 CA118948. S.V. is also supported by DOD funding, W81XWH-19-1-0588.; This study was supported by the UAB Department of Pathology, the UAB O'Neal Comprehensive Cancer Center, and the UAB Heersink School of Medicine.; C.J.C. is supported by grant CA125123.
• Keywords: Science & Technology; Transcriptomics; Life Sciences & Biomedicine; Gene expression; Differential expression; Correlation; Prostate; Cancer gene expression; Oncology; Proteomics; Bioinformatics; lncRNA; UALCAN; Patient survival
• Research Categories: Biology, Bioinformatics; Biology, Biostatistics; Health Sciences, Pathology; Health Sciences, Oncology

Abstract

Cancer genomic, transcriptomic, and proteomic profiling has generated extensive data that necessitate the development of tools for its analysis and dissemination. We developed UALCAN to provide a portal for easy exploring, analyzing, and visualizing these data, allowing users to integrate the data to better understand the gene, proteins, and pathways perturbed in cancer and make discoveries. UALCAN web portal enables analyzing and delivering cancer transcriptome, proteomics, and patient survival data to the cancer research community. With data obtained from The Cancer Genome Atlas (TCGA) project, UALCAN has enabled users to evaluate protein-coding gene expression and its impact on patient survival across 33 types of cancers. The web portal has been used extensively since its release and received immense popularity, underlined by its usage from cancer researchers in more than 100 countries. The present manuscript highlights the task we have undertaken and updates that we have made to UALCAN since its release in 2017. Extensive user feedback motivated us to expand the resource by including data on a) microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and promoter DNA methylation from TCGA and b) mass spectrometry-based proteomics from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). UALCAN provides easy access to pre-computed, tumor subgroup-based gene/protein expression, promoter DNA methylation status, and Kaplan-Meier survival analyses. It also provides new visualization features to comprehend and integrate observations and aids in generating hypotheses for testing. UALCAN is accessible at http://ualcan.path.uab.edu