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Targeting YES1 Disrupts Mitotic Fidelity and Potentiates the Response to Taxanes in Triple-Negative Breast Cancer

GSE232632 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2024/07/16 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 4 × MDA-MB-231, sgNTS, 48 hrs, vs 4 × MDA-MB-231, sgYES1, 48 hrs, vs 4 × SUM159PT, sgNTS, 48 hrs, vs 4 × SUM159PT, sgYES1, 48 hrs,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.
Paper
Targeting YES1 Disrupts Mitotic Fidelity and Potentiates the Response to Taxanes in Triple-Negative Breast CancerCancer research · 2024
Summary (written by the submitters)
Triple negative breast cancer (TNBC) is a heterogeneous disease with limited therapeutic options. Two commonalities of TNBCs are a failure to express receptors for hormone or HER2-targeted therapies and high levels of chromosomal instability (CIN), both of which generate considerable therapeutic challenges. Focusing on the Src Family Kinases (SFKs), we found that treatment of TNBC cells with pan-SFK inhibitors causes abnormal nuclear phenotypes and DNA double strand breaks that are characteristic of excessive CIN, suggesting that SFKs may provide a vulnerability for treating TNBC.
Read the full summary ↓
While prior clinical studies found that pan-SFK inhibition causes dose-limiting toxicities and minimal efficacy, we asked whether targeting individual family members may provide more specificity and hence, greater impact. Analysis of public datasets revealed that YES1 is one of the most highly expressed SFKs in basal/TNBC breast cancer and that its expression is associated with poor patient outcomes. Genomic and pharmacologic targeting of YES1 in TNBC cells further demonstrated that its sustained activity is essential for normal mitoses, including centrosome composition and bipolar spindle formation, as well as chromosome stability. We then determined if the ability of YES1 inhibition to induce mitotic defects and profound CIN could be leveraged to potentiate the efficacy of taxanes, cornerstone drugs for TNBC that also induce CIN. Combining paclitaxel with the selective YES1 inhibitor, CH695355, synergistically inhibited growth of several TNBC models both in vitro and in vivo. Moreover, YES1 inhibition re-sensitized taxane-resistant TNBC cells to paclitaxel. Elevated tumor expression of YES1 was also associated with worse overall survival of TNBC patients treated with combined taxanes/anthracyclines. Mechanistically, YES1 suppression leads to a loss of FOXM1 expression, a transcription factor whose disruption has also been reported to induce CIN, but has not yet been effectively therapeutically targeted. Together, these studies demonstrate that the SFK family member, YES1, is a novel and essential regulator of genome stability in TNBC. More broadly, these results suggest that YES1 may be a therapeutically targetable vulnerability that could potentiate the efficacy of mitotic inhibitors to induce maladaptive CIN and improve the treatment of TNBC.
Published in
Targeting YES1 Disrupts Mitotic Fidelity and Potentiates the Response to Taxanes in Triple-Negative Breast Cancer
Piemonte KM, Ingles NN, Weber-Bonk KL et al. · Cancer research 2024 · PMID 39037997 · doi:10.1158/0008-5472.CAN-23-2558
This dataset
Open GSE232632 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 GSE232632_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 PRJNA973063 and SRA study SRP438052. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39037997) ↗
Study design
4 × MDA-MB-231, sgNTS, 48 hrs, vs 4 × MDA-MB-231, sgYES1, 48 hrs, vs 4 × SUM159PT, sgNTS, 48 hrs, vs 4 × SUM159PT, sgYES1, 48 hrs,

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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
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