PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 21, 2026British Journal of Pharmacology9 citationsOpen Access

TNMplot: An enhanced platform for pharmacological target identification through cross‐stage and pan‐cancer gene expression analysis

View Full Paper
ÁBÁron BarthaBGBalázs Győrffy

Key Points

  • The central aim is to enhance pharmacological target identification through comprehensive gene expression analysis across various cancer stages.
  • Integration of RNA-Seq and gene-chip data from 56,938 samples.
  • Stage-based expression comparisons across 22 tumor types including key cancers like breast and lung.
  • Introduction of advanced visualization tools for multi-gene and multi-tissue analysis.
  • Identification of progression-related genes from 4470 cancer samples.
  • Enhanced visual analytics support druggable pathway investigations.
  • Robust cross-platform validation of pharmacological targets through RNA-Seq and gene chip datasets.

Abstract

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.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Bartha et al. (2026) studied this question.

synapsesocial.com/papers/69be37aa6e48c4981c677848https://doi.org/10.1111/bph.70390
Ask AI
Helpful
Bookmark
Share
View Full Paper