TCGEx: a powerful visual interface for exploring and analyzing cancer gene expression data

被引：0

作者：

Kus, M. Emre ^{[1
]}

Sahin, Cagatay ^{[1
]}

Kilic, Emre ^{[1
]}

Askin, Arda ^{[1
]}

Ozgur, M. Mert ^{[2
]}

Karahanogullari, Gokhan ^{[3
]}

Aksit, Ahmet ^{[4
]}

O'Connell, Ryan M. ^{[5
]}

Ekiz, H. Atakan ^{[1
]}

机构：

[1] Izmir Inst Technol, Dept Mol Biol & Genet, TR-35430 Izmir, Turkiye

[2] Bilkent Univ, Dept Mol Biol & Genet, TR-06800 Cankaya, Ankara, Turkiye

[3] Izmir Inst Technol, Dept Math, TR-35430 Izmir, Turkiye

[4] Izmir Inst Technol, Dept Informat Technol, TR-35430 Izmir, Turkiye

[5] Univ Utah, Dept Pathol, Salt Lake City, UT 84112 USA

来源：

EMBO REPORTS | 2025年 / 26卷 / 07期

关键词：

TCGA; Functional Genomics; Machine Learning; Interactive Analysis; Gene Expression; REPRODUCIBLY PREDICT RESPONSE; CHECKPOINT BLOCKADE THERAPY; CELL; SIGNATURES; LANDSCAPE; MELANOMA; PROGRAM; IMPRES;

D O I：

10.1038/s44319-025-00407-7

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Analyzing gene expression data from the Cancer Genome Atlas (TCGA) and similar repositories often requires advanced coding skills, creating a barrier for many researchers. To address this challenge, we developed The Cancer Genome Explorer (TCGEx), a user-friendly, web-based platform for conducting sophisticated analyses such as survival modeling, gene set enrichment analysis, unsupervised clustering, and linear regression-based machine learning. TCGEx provides access to preprocessed TCGA data and immune checkpoint inhibition studies while allowing integration of user-uploaded data sets. Using TCGEx, we explore molecular subsets of human melanoma and identify microRNAs associated with intratumoral immunity. These findings are validated with independent clinical trial data on immune checkpoint inhibitors for melanoma and other cancers. In addition, we identify cytokine genes that can be used to predict treatment responses to various immune checkpoint inhibitors prior to treatment. Built on the R/Shiny framework, TCGEx offers customizable features to adapt analyses for diverse research contexts and generate publication-ready visualizations. TCGEx is freely available at https://tcgex.iyte.edu.tr, providing an accessible tool to extract insights from cancer transcriptomics data.

引用

页码：1863 / 1890

页数：28

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