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Tuning circadian rhythm of CAFs against cancer progression

GSE279327 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2024/10/18 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 14 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
14 samples: 14 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)
Circadian disruption orchestrates various biological functions associated with carcinogenesis and tumor progression in cancer cells. Yet the influential role in the tumor microenvironment (TME), including cancer-associated fibroblasts (CAFs), remains unveiled. Here, we report an uncovered signaling axis, BMAL1-LHX8, that elicits the transitioning of CAF-like properties via coordinating the tumor-supportive activity in ameloblastoma (AM) stromal.
Read the full summary ↓
Both in the co-culture system and stroma-rich AM tumoroid model, CAFs augmented tumor growth, cell proliferation, and metabolic activities. Time-series RNA-sequencing analysis indicated the perturbation of circadian rhythm in the AM+CAF group and LHX8 was considerably involved. CRISPR/cas9 system-based loss-of-function study suggested that the BMAL1-LHX8 signaling axis was highly correlated with several tumor-supportive activities, including secretion of growth factors and ECM remodeling molecules. It also contributed to the resistance of BRAF inhibitor (PLX4032), which could be effectively suppressed by the clock regulator (GSK4112, an agonist of REV-ERB which suppresses BMAL1 expression). This phenomenon confirmed that GSK4112 elevated the anti-tumor efficacy of PLX4032 in the xenograft model. Collectively, these data underscore the role of the BMAL1-LHX8 axis in exacerbating the CAF-like transitioning in AM stromal and tuning the circadian rhythm via clock regulators. This research offering the experimental evidence for the development of chrono-chemotherapy and offering new possibilities for the cancer treatment in the future.
This dataset
Open GSE279327 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 GSE279327_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 PRJNA1171862 and SRA study SRP537999. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
14 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 14 sample titles: 14 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
Datasets on a similar topic

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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.