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Targeting Fatty Acid Oxidation Enhances Response to HER2-targeted Therapy

GSE254622 Mus musculus (mouse) RNA-seq (gene expression) 11 samples Submitted 2024/07/08 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
11 samples: 11 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.
Paper
Targeting fatty acid oxidation enhances response to HER2-targeted therapyNature communications · 2024
Summary (written by the submitters)
Metabolic reprogramming is a hallmark of tumorigenesis and includes alterations in glucose and fatty acid metabolism. In this study, we investigated the role of Carnitine palmitoyl transferase 1A (CPT1A), a key enzyme in fatty acid oxidation (FAO), in the induction of HER2+ (Human Epidermal growth factor 2, ErbB2) breast cancer. Using an ErbB2+ genetically engineered mouse models, we found that ablation of CPT1A delayed tumor onset and reduced tumor growth, angiogenesis, and metastatic capacity.
Read the full summary ↓
CPT1A-deficient ErbB2+ cells exhibited impaired mitochondrial function, leading to a reliance on the tricarboxylic acid cycle to reduce NAD+/FAD for energy production. Consequently, loss of CPT1A resulted in glucose dependency and an inability to metabolize fats. CPT1A-deficient ErbB2+ tumor cells exhibited increased oxidative stress and upregulated nuclear factor erythroid 2-related factor 2 (NRF2) activity. Inhibiting NRF2 or silencing its expression reduced proliferation and glucose consumption in CPT1A-deficient cells. In pre-clinical models of ErbB2+ breast cancer, combining a ketogenic diet with an anti-ErbB2 monoclonal antibody in the context of CPT1A deficiency significantly reduced tumor growth and increased survival. Furthermore, combining the ketogenic diet with CPT1A ablation suppressed tumor growth, enhanced apoptosis, and reduced lung metastasis. Additionally, using an immunocompetent model, we provide evidence that CPT1A inhibition attenuated tumor growth and proliferation by promoting an antitumor immune microenvironment that enhanced the efficacy of ErbB2 targeted therapy. These findings provide insight into the metabolic rewiring in HER2+ breast cancer and highlight the potential of targeting fatty acid oxidation and employing metabolic interventions as a combination therapy strategy for HER2+ breast cancer patients, including those resistant to standard treatment regimes.
Published in
Targeting fatty acid oxidation enhances response to HER2-targeted therapy
Nandi I, Ji L, Smith HW et al. · Nature communications 2024 · PMID 39097623 · doi:10.1038/s41467-024-50998-3
This dataset
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.

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 GSE254622_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1071151 and SRA study SRP486919. Searching any of these in the dataset finder brings you back here.

Study design
11 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 11 sample titles: 11 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
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