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Methylation of the epigenetic regulator KMT2D by SMYD2 contributes to therapeutic response in hormone-dependent breast cancer [SMYD2_KD_RNA]

GSE253957 Homo sapiens (human) DNA methylation 12 samples Submitted 2024/05/04 Platform GPL20301
At a glance

DNA methylation · human · 12 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
12 samples: 3 × MCF7 shSMYD2 +DOX -Alpelisib vs 2 × MCF7 shSMYD2 -DOX -Alpelisib vs 2 × MCF7 shSMYD2 -DOX +Alpelisib vs 2 × MCF7 shSMYD2 +DOX +AlpelisibGroups 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
Methylation of the chromatin modifier KMT2D by SMYD2 contributes to therapeutic response in hormone-dependent breast cancerCell reports · 2024
Summary (written by the submitters)
Activating mutations in PIK3CA, the gene encoding PI3Kα, are frequently found in estrogen receptor (ER+) breast cancer and the combination of the PI3K inhibitor alpelisib with the anti-ER agent fulvestrant is approved for therapy. We have uncovered a key role for the chromatin modifier KMT2D in regulating the ER-PI3K crosstalk. PI3Kα effectors, AKT and SGK, negatively regulate KMT2D through S1331 phosphorylation.
Read the full summary ↓
When PI3K is inhibited, this regulatory event is lost, leading to increased chromatin recruitment of KMT2D and an upregulation of ER-dependent transcription. Here we discovered a previously undescribed methylation site on KMT2D, at K1330 directly adjacent to S1331, catalyzed by the lysine methyltransferase SMYD2. SMYD2 loss attenuates alpelisib-induced KMT2D chromatin binding. Accordingly, loss of SMYD2 abrogates alpelisib-induced changes in gene expression, including ER-dependent transcription. Knockdown or pharmacological inhibition of SMYD2 sensitizes breast cancer cells, patient-derived organoids, and tumors to PI3K/AKT inhibition and endocrine therapy in part through KMT2D K1330 methylation. Methyl dead knock-in clones of KMT2D phenocopy many of the effects of SMYD2 inhibition on cell and tumor growth, drug response, and transcriptional output. Together, our findings uncover a regulatory cross-talk between posttranslational modifications that plays an important role in fine-tuning the functions of KMT2D at the chromatin. This provides a rationale for epigenetic therapy using SMYD2 inhibitors in combination with PI3Kα/AKT inhibitors for the treatment of ER+/PIK3CA mutant breast cancer.
Published in
Methylation of the chromatin modifier KMT2D by SMYD2 contributes to therapeutic response in hormone-dependent breast cancer
Blawski R, Vokshi BH, Guo X et al. · Cell reports 2024 · PMID 38700982 · doi:10.1016/j.celrep.2024.114174
This dataset
Open GSE253957 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 GSE253957_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1068001 and SRA study SRP485400. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38700982) ↗
Study design
3 × MCF7 shSMYD2 +DOX -Alpelisib vs 2 × MCF7 shSMYD2 -DOX -Alpelisib vs 2 × MCF7 shSMYD2 -DOX +Alpelisib vs 2 × MCF7 shSMYD2 +DOX +Alpelisib

Supports a between-group comparison across 9 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 9 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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