GEO series

Photoproximity labeling of c-Myc reveals SLK as a cancer-specific co-regulator [RNA-Seq]

GSE330346 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/05/17 Platform GPL34284

At a glance

RNA-seq (gene expression) · human · 12 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: 12 samples: 12 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.

Summary (written by the submitters)

Transcription factors (TFs) have long been aspirational therapeutic targets for the treatment of diseases, as their dysregulation is a common mechanism for altered cell states. Despite this, many TFs implicated in disease havedisordered structures and lack canonical binding pockets, rendering them non-trivial targets for small moleculebased therapies.

Read the full summary ↓

Directly inhibiting TF function has proven difficult, but indirect inhibition by targeting the effector molecules that modulate TF function is a promising, yet underexplored, alternative approach. Here we report a strategy for capturing cancer-specific protein-protein interactions using context-dependent µMap photoproximity labeling. Using an intein-based method for catalyst conjugation in biochemically intact nuclei, we demonstrate that we can capture unique protein interactomes of c-Myc in healthy and cancerous prostate cell lines, and that these unique interactors can be mined to identify druggable vulnerabilities. We find that a cancerspecific c-Myc interactor, STE20 like kinase (SLK), selectively promotes c-Myc stabilization at the protein level, drives epithelial morphology, and is essential for tumorigenesis, validating it as a viable therapeutic target. Mechanistically, this stabilization is driven by SLK-mediated phosphorylation of c-Myc at serine 329, which antagonizes GSK3β-dependent phosphorylation of the c-Myc phosphodegron and effectively increases the stability of c-Myc. This cancer-selective interaction is enabled by a change in SLK splicing that promotes nuclear localization of the long isoform, rather than changes at the protein or total RNA level. Furthermore, analysis of cancer patient data shows a strong correlation between the SLK long splice isoform and expression of c-Myc targets across multiple tumor types. Importantly, the SLK-c-Myc interaction is validated in cancer cell lines from diverse tissues, suggesting this novel regulatory axis is broadly operative across human cancer.

This dataset

Open GSE330346 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 GSE330346_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 PRJNA1463691 and SRA study SRP698650. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

12 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 12 sample titles: 12 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

GSM9724246 PC3 cells, replicate A
GSM9724247 PC3 cells, replicate B
GSM9724248 PC3 cells, replicate C
GSM9724249 PC3 cells, replicate D
GSM9724250 PC3 SLK-KO cells, replicate A
GSM9724251 PC3 SLK-KO cells, replicate B
GSM9724252 PC3 SLK-KO cells, replicate C
GSM9724253 PC3 SLK-KO cells, replicate D
GSM9724254 PC3 SLK-KO cells + MYC, replicate A
GSM9724255 PC3 SLK-KO cells + MYC, replicate B
GSM9724256 PC3 SLK-KO cells + MYC, replicate C
GSM9724257 PC3 SLK-KO cells + MYC, replicate D

Datasets on a similar topic

GSE307813 Photoproximity labeling of c-Myc reveals SLK as a cancer-specific co-regulator [total RNA-seq] 15 samples shares slk, cancer-specific, photoproximity, co-regulator, labeling, rna-seq, c-myc
GSE331167 Photoproximity labeling of c-Myc reveals SLK as a cancer-specific co-regulator 47 samples shares slk, cancer-specific, photoproximity, co-regulator, labeling, c-myc
GSE330345 Photoproximity labeling of c-Myc reveals SLK as a cancer-specific co-regulator [ChIP-Seq] 20 samples shares slk, cancer-specific, photoproximity, co-regulator, labeling, c-myc
GSE94277 Cancer-specific retargeting of BAF complexes by a prion-like domain [RNA-Seq] 29 samples shares cancer-specific, rna-seq
GSE328503 CBFA2T3-GLIS2 fusion-mediated mSWI/SNF chromatin remodeler disruption generates cancer-specific dependencies in AMKL [RNA-Seq fhd286] 24 samples shares cancer-specific, rna-seq
GSE274688 The lineage master transcription factor, p63 recruits a cancer-specific cofactor, FOXK1 to mediate oncogenic 3D chromatin dynamics in squamous cell carcinoma [RNA-seq] 22 samples shares cancer-specific, rna-seq
GSE312017 A FOXA1/SPDEF Co-regulatory Axis Maintains Luminal Identity in HER2-Positive Breast Cancer by Driving ERBB2 Expression and Suppressing a TEAD/YAP-Driven EMT Program [RNA-Seq] 16 samples shares co-regulator, rna-seq
GSE328421 CBFA2T3-GLIS2 fusion-mediated mSWI/SNF chromatin remodeler disruption generates cancer-specific dependencies in AMKL [RNA-Seq] 9 samples shares cancer-specific, rna-seq

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