GEO series

SNX10 deficiency confers resistance to anti-HER2 antibody-drug conjugates via regulating endosomal trafficking

GSE269495 Homo sapiens (human) RNA-seq (gene expression) 13 samples Submitted 2025/03/31 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 13 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: 13 samples: 9 × PDO sample, # vs 4 × resistant cell line, #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)

Antibody-drug conjugates (ADCs) are a rapidly developing therapeutic approach in cancer treatment that has shown remarkable efficacy in breast cancer. Despite the promising efficacy of anti-HER2 ADCs, many patients are still experiencing disease progression under treatment. Here, by analyzing the transcriptome data from patient-derived organoid models, I-SPY2 trial, and resistant cell lines, we identified that SNX10 deficiency conferred anti-HER2 ADCs resistance.

Read the full summary ↓

Low levels of SNX10 attenuated HER2 recycling and promoted HER2 trafficking into lysosomes. We also noticed that the lack of interaction between SNX10 and the transcription factor STAT1 inhibited its activation, while STAT1 binds to the promoter region of RAB11A and regulates its transcription. Thus, the lack of SNX10 inhibited HER2 recycling by downregulating RAB11A, decreased cell-surface HER2, and caused anti-HER2 ADC resistance.

This dataset

Open GSE269495 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 GSE269495_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 PRJNA1120434 and SRA study SRP512694. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 × PDO sample, # vs 4 × resistant cell line, #

Supports a between-group comparison across 13 samples.

How we read this: 2 replicated groups read from 13 sample titles; they account for 13 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

GSM8316731 resistant cell line, #1 resistant cell line, #
GSM8316732 resistant cell line, #2 resistant cell line, #
GSM8316733 resistant cell line, #3 resistant cell line, #
GSM8316734 resistant cell line, #4 resistant cell line, #
GSM8316735 PDO sample, #2122097 PDO sample, #
GSM8316736 PDO sample, #2140962 PDO sample, #
GSM8316737 PDO sample, #2122418 PDO sample, #
GSM8316738 PDO sample, #471561 PDO sample, #
GSM8316739 PDO sample, #2134420 PDO sample, #
GSM8316740 PDO sample, #2141570 PDO sample, #
GSM8316741 PDO sample, #2143454 PDO sample, #
GSM8316742 PDO sample, #2134353 PDO sample, #
GSM8316743 PDO sample, #2136650 PDO sample, #

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.