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Circadian transcriptome of pancreatic adenocarcinoma unravels chronotherapeutic targets.

GSE262627 Homo sapiens (human) RNA-seq (gene expression) 68 samples Submitted 2024/03/27 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 68 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)
Topic
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
68 samples: 52 distinct titles, 3 of them repeatedGroups 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)
Pancreatic ductal adenocarcinoma (PDA) is a lethal cancer characterized by a poor outcome and an increasing incidence. A significant majority (>80%) of newly diagnosed cases are deemed unresectable, leaving chemotherapy as the sole viable option, though with only moderate success. This necessitates the identification of improved therapeutic options for PDA.
Read the full summary ↓
We hypothesized that there are temporal variations in cancer-relevant processes within PDA tumors, offering insights into the optimal timing of drug administration—a concept termed chronotherapy. In this study, we explored the presence of the circadian transcriptome in PDA using patient-derived organoids (PDOs) and validated these findings by comparing PDA data from TCGA with non-cancerous healthy pancreas data from GTeX. Several PDA-associated pathways (cell cycle, stress response, Rho GTPase signaling) and cancer driver hub genes (EGFR, JUN) exhibited a cancer-specific rhythmic pattern intricately linked to the circadian clock. Through the integration of multiple functional measurements for rhythmic cancer driver genes, we identified top chronotherapy targets and validated key findings in molecularly divergent pancreatic cancer cell lines. Testing the chemotherapeutic efficacy of clinically relevant drugs further revealed temporal variations that correlated with drug-target cycling. Collectively, our study unravels the PDA circadian transcriptome and highlights a potential approach for optimizing chrono-chemotherapeutic efficacy.
This dataset
Open GSE262627 in finder → Find more human RNA-seq datasets → Pancreatic cancer landscape →
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 GSE262627_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 PRJNA1092668 and SRA study SRP498297. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
52 distinct titles, 3 of them repeated
PDO10_ZT ×7 PDO6_ZT ×6 PDO15_ZT ×6

How we read this: Read from 68 sample titles: 52 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

+ 28 more — browse all 68 samples with per-sample file links →

More Pancreatic cancer datasets

Search all human RNA-seq datasets in GEO →

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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.