GEO series

Mechanisms of drugs-resistance in small cell lung cancer III

GSE280212 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/03/31 Platform GPL30173

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)
Topic: Small cell lung cancerThis series is part of our curated briefing on it.
Samples: 12 samples: 3 × 273P vs 3 × 273CP vs 3 × SBC5P vs 3 × SBC5CPGroups 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)

Lung cancer is the leading cause of cancer mortality and is classified by the World Health Organization into two broad histological subtypes. Non–small cell lung cancer (NSCLC), including adenocarcinoma, squamous cell carcinoma, and large cell carcinoma, accounts for ~85% of all lung cancer cases, with the remaining 15% of cases being due to small cell lung cancer (SCLC), which arises from neuroendocrine cells in the lung.

Read the full summary ↓

Although most SCLC tumors are initially responsive to chemotherapy and radiation, patients often experience relapse, with the tumor acquiring an aggressiveness and therapeutic resistance that lead to a poor clinical outcome. Improvement of overall survival in individuals with SCLC will require the identification of novel therapeutic targets based on a better understanding of the changes in intracellular signaling of aggressive SCLC cells. The malignant progression of SCLC often occurs concomitantly with the acquisition of chemoresistance, suggesting that phenotypic malignant change is related to adaptation to the stresses induced by chemotherapy. In order to analyze gene expression changes associated with malignant transformation in SCLC, we established a cisplatin-resistant SCLC cell line and performed RNA sequencing.

This dataset

Open GSE280212 in finder → Find more human RNA-seq datasets → Small cell lung 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 GSE280212_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 PRJNA1177374 and SRA study SRP540601. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × 273P vs 3 × 273CP vs 3 × SBC5P vs 3 × SBC5CP

Supports a between-group comparison across 12 samples.

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

GSM8592273 273P-1 273P
GSM8592274 273P-2 273P
GSM8592275 273P-3 273P
GSM8592276 273CPr-1 273CP
GSM8592277 273CPr-2 273CP
GSM8592278 273CPr-3 273CP
GSM8592279 SBC5P-1 SBC5P
GSM8592280 SBC5P-2 SBC5P
GSM8592281 SBC5P-3 SBC5P
GSM8592282 SBC5CPr-1 SBC5CP
GSM8592283 SBC5CPr-2 SBC5CP
GSM8592284 SBC5CPr-3 SBC5CP

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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.