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Integrative Assessment of RNA-seq and IHC: Linking Tumor Biomarkers and Microenvironment

GSE293591 Homo sapiens (human) RNA-seq (gene expression) 365 samples Submitted 2025/08/06 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 365 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
365 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
RNA sequencing and immunohistochemistry jointly improve tumor biomarker interpretationScientific reports · 2025
Summary (written by the submitters)
This study aimed to assess the correlation between RNA sequencing (RNA-seq) and immunohistochemistry (IHC) in detecting key cancer biomarkers across solid tumors, and then, to establish RNA-seq thresholds that accurately reflect clinical IHC classifications. Expression levels of nine biomarkers—ESR1, PGR, AR, MKI67, ERBB2, CD274, CDX2, KRT7, and KRT20—were analyzed in 365 formalin-fixed, paraffin-embedded samples from breast, lung, gastrointestinal, and other solid carcinomas.
Read the full summary ↓
Correlations between RNA-seq data and IHC scores were determined using Spearman’s correlation coefficients, with RNA-seq cut-offs established to distinguish positive from negative IHC scores. The results revealed strong correlations for most biomarkers, with coefficients ranging from 0.53 to 0.89. RNA-seq thresholds were confirmed across internal and external cohorts, demonstrating high diagnostic accuracy (up to 98%) and precision in identifying biomarker expression levels. The analysis also highlighted the influence of tumor microenvironment and purity, particularly in the moderate correlation 0.63 observed for PD-L1. Our study demonstrates that RNA-seq can serve as a robust complementary tool to IHC, offering objective and high-throughput biomarker assessment. The RNA-seq thresholds established provide a reliable method for determining biomarker positivity, supporting the integration of RNA-seq in clinical diagnostics to enhance precision, especially where tumor purity and microenvironment factors are significant.
Published in
RNA sequencing and immunohistochemistry jointly improve tumor biomarker interpretation
Kushnarev V, Stupichev D, Davitavyan S et al. · Scientific reports 2025 · PMID 40753302 · doi:10.1038/s41598-025-12780-3
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE293591_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1245330. Searching any of these in the dataset finder brings you back here.

Samples in this study

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