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Overcoming ADC resistance in advanced colorectal cancer by dual targeting of TROP2 and PERK to suppress Wnt/β-catenin signaling

GSE311016 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/12/18 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples: 10 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
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
Overcoming ADC resistance in advanced colorectal cancer by dual targeting of TROP2 and PERK to suppress Wnt/β-catenin signalingCell reports. Medicine · 2026
Summary (written by the submitters)
Targeted therapy for advanced colorectal cancer (CRC) remains a significant clinical challenge. In this study, we systematically examined the anti-tumor efficacy and underlying mechanisms of IMMU132, an FDA-approved anti-TROP2 antibody conjugate linked to the topoisomerase I inhibitor SN-38, both as a standalone treatment and in combination with the PERK inhibitor GSK2606414 in TROP2-positive advanced CRC.
Read the full summary ↓
We first established that TROP2 expression was markedly elevated in CRC cohorts and correlated with poor patient prognosis. In vitro experiments demonstrated that IMMU132 inhibited CRC cell proliferation and viability in a dose-dependent manner. In patient-derived xenograft (PDX) models, IMMU132 monotherapy significantly inhibited tumor growth. Mechanistically, transcriptomic analysis indicated that PERK, a key factor in endoplasmic reticulum stress (ERS), may serve as a critical synergistic target for IMMU132’s anti-tumour activity. Subsequent screening of various ERS inhibitors revealed that the specific PERK inhibitor GSK2606414 significantly enhanced the effects of IMMU132. In diverse experimental models, including cell lines, organoids, and PDX models, combination therapy exhibited superior anti-tumor effects compared to monotherapy, highlighting a pronounced synergistic effect. Furthermore, transcriptomic analysis showed that combination therapy notably inhibited the Wnt/β-catenin signaling pathway. Gene set enrichment analysis confirmed significant upregulation of Wnt pathway-related genes, while Western blot analysis showed downregulation of key molecules in the Wnt pathway, including β-catenin, GSK3B, JUN, and WNT2B, following combination therapy. These findings suggest that the synergistic anti-tumour effects of IMMU132 and GSK2606414 may arise from their dual modulation of ERS and Wnt signalling pathways, offering novel insights for targeted therapy in advanced CRC and informing strategies for combining antibody-drug conjugates (ADCs).
Published in
Overcoming ADC resistance in advanced colorectal cancer by dual targeting of TROP2 and PERK to suppress Wnt/β-catenin signaling
Liu J, Li M, Huang J et al. · Cell reports. Medicine 2026 · PMID 42030933 · doi:10.1016/j.xcrm.2026.102769
This dataset
Open GSE311016 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE311016_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1368476 and SRA study SRP647971. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42030933) ↗
Study design
10 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 10 sample titles: 10 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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