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Updated: Mar 21, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
TNMplot: An enhanced platform for pharmacological target identification through cross-stage and pan-cancer gene
Áron Bartha1, Balázs Győrffy1,2,3
1Department of Bioinformatics, Pediatric Center, Semmelweis University, Budapest, Hungary.
None:
TNMplot.com, a web-based platform integrating RNA-Seq and gene-chip data from 56,938 samples, enables differential gene expression analysis across normal, primary tumour and metastatic tissues, facilitating large-scale transcriptomic profiling across 22 tumour types. We introduced an updated version of the TNMplot database with novel features that support pharmacological and translational oncology research. A key addition is the stage-based expression comparison, which allows the identification of progression-related genes from 4470 cancer samples, including breast (n = 2331), colorectal (n = 648), lung (n = 1399), skin (n = 31) and prostate (n = 61) tumours. These progression markers can inform drug target discovery and the timing of therapeutic intervention. The platform now includes enhanced visualisation tools, such as a pan-cancer dot matrix enabling simultaneous multi-tissue and multi-gene comparison, and new multi-gene analytics including density plots, gene-gene correlation, correlation matrices, correlation profile analysis, gene signature evaluation and targetgram analysis. These tools support the investigation of druggable pathways, co-expression networks and pharmacogenomic biomarker panels. A unique feature of TNMplot remains the parallel analysis of RNA-seq and gene chip datasets, enabling robust cross-platform validation of candidate pharmacological targets in diverse patient populations. In conclusion, the updated TNMplot platform offers a comprehensive and versatile environment for transcriptomic analysis in support of pharmacological hypothesis generation, biomarker discovery and preclinical target validation in oncology.
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