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A TROP2-targeting ADC synergizes with oxidative phosphorylation inhibitor to enhance apoptosis in ESCC by suppressing the PI3K-AKT-mTOR signaling pathway

GSE304294 Homo sapiens (human) RNA-seq (gene expression) 11 samples Submitted 2026/08/06 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 11 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)
Topic
Esophageal cancerThis series is part of our curated briefing on it.
Samples
11 samples: 3 × KYSE30 cells, Control, 1Day, vs 3 × KYSE30 cells, IACS010759, 1Day, vs 3 × KYSE30 cells, Combination, 1Day, vs 2 × KYSE30 cells, IMMU132, 1Day,Groups 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.
Summary (written by the submitters)
Currently, there are no effective targeted therapies for advanced esophageal squamous cell carcinoma (ESCC). Trophoblast cell surface antigen-2 (TROP2) are considered robust therapeutic targets which leverages antibody-drug conjugates (ADCs) to control solid tumors. Mitochondrial oxidative phosphorylation (OXPHOS) influences the growth of cancer cells, metastasis and drug resistance.
Read the full summary ↓
However, whether inhibiting OXPHOS can potentiate the efficacy of TROP2-targeting ADCs is not well understood. Here, we investigated the therapeutic efficacy of IMMU132 (IMMU), an ADC targeting TROP2, either alone or in combination with IACS010759 (IACS), a selective OXPHOS inhibitor, through clinically ESCC models. Immunohistochemical analysis was performed on a cohort of 222 patients, which revealed that 94.6% of all specimens tested positive for TROP2. Among them, moderate and strong staining were observed in 29.3% and 27.0% of cases, respectively. Co-administration of IMMU and IACS synergistically inhibited the growth of tumors in human ESCC cell lines, PDXO and PDX models. Mechanistically, we found that the combination treatment achieved tumor suppression in ESCC cells via inducing apoptosis and oxidative stress, as well as preventing cell motility. Results of the RNA-seq analysis demonstrated that the combined treatment of IMMU and IACS downregulated the expression level of several cancer-related pathways, such as the PI3K-AKT-mTOR pathway, OXPHOS and apoptosis. Moreover, the data confirmed that inhibition of the PI3K-AKT-mTOR pathway significantly suppressed ESCC tumor growth following administration of the combination therapy. Based on these findings, we present a novel therapeutic strategy that enhances the efficacy of TROP2-targeting ADCs via concurrent inhibition of OXPHOS, which is likely to improve clinical outcomes of patients with TROP2-positive ESCC.
This dataset
Open GSE304294 in finder → Find more human RNA-seq datasets → Esophageal cancer landscape →
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 GSE304294_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 PRJNA1300296 and SRA study SRP605775. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × KYSE30 cells, Control, 1Day, vs 3 × KYSE30 cells, IACS010759, 1Day, vs 3 × KYSE30 cells, Combination, 1Day, vs 2 × KYSE30 cells, IMMU132, 1Day,

Supports a between-group comparison across 11 samples.

How we read this: 4 replicated groups read from 11 sample titles; they account for 11 of them. 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
More Esophageal cancer datasets

Search all human RNA-seq datasets in GEO →

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