Transcriptome profiling of lung cancer bone metastasis
RNA-seq (gene expression) · human · 28 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
- 28 samples: 10 × lu-b vs 8 × lu-f vs 8 × gGroups 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
- RAC1 inhibition ameliorates IBSP-induced bone metastasis in lung adenocarcinomaCell reports · 2024
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE225208_RAW.tar (it can run to tens of gigabytes).
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 PRJNA934500 and SRA study SRP422607. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 26 samples.
How we read this: 3 replicated groups read from 28 sample titles; they account for 26 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.
- GSM7041452 lu-b-1 lu-b
- GSM7041453 lu-b-2 lu-b
- GSM7041454 lu-b-3 lu-b
- GSM7041455 lu-f-1 lu-f
- GSM7041456 lu-f-2 lu-f
- GSM7041457 lu-f-3 lu-f
- GSM7041458 lu-b-4 lu-b
- GSM7041459 lu-f-4 lu-f
- GSM7041460 lu-b-5 lu-b
- GSM7041461 lu-f-5 lu-f
- GSM7041462 lu-f-6 (f12)
- GSM7041463 lu-b-6 lu-b
- GSM7041464 lu-b-7 lu-b
- GSM7041465 lu-f-6 (f15)
- GSM7041466 lu-f-7 lu-f
- GSM7041467 lu-f-8 lu-f
- GSM7041468 lu-b-8 lu-b
- GSM7041469 lu-b-9 lu-b
- GSM7041470 lu-f-9 lu-f
- GSM7041471 lu-b-10 lu-b
- GSM7041472 g-1112 g
- GSM7041473 g-1718 g
- GSM7041474 g-34 g
- GSM7041475 g-910 g
- GSM7041476 g-56 g
- GSM7041477 g-1314 g
- GSM7041478 g-1516 g
- GSM7041479 g-78 g
- GSE266330 Single cell profiling of bone metastasis ecosystems from multiple cancer types reveals convergent and divergent mechanisms of bone colonization 63 samples shares metastasis, bone
- GSE223499 Non-small Cell Lung Cancer Brain Metastasis Atlas [single nuclei RNAseq] 42 samples shares metastasis, lung
- GSE242951 Contribution of crosstalk of mesothelial and tumoral epithelial cells in pleural metastasis of lung cancer 12 samples shares metastasis, lung
- GSE223503 Non-small Cell Lung Cancer Brain Metastasis Atlas 136 samples shares metastasis, lung
- GSE271689 Enhancing Immunotherapy Outcomes: Spatial Multi-Omics Predictive Models for Non-Small Cell Lung Cancer 586 samples shares lung
- GSE205335 Single-cell transcriptome profiles of tumor tissues from lung cancer patients receiving immune checkpoint inhibitors. 33 samples shares lung
- GSE225182 Gene expression profiling study to identify distinct subtypes in Peritoneal metastasis of colorectal cancer 33 samples shares metastasis
- GSE243013 A single-cell atlas of immune heterogeneity in anti-PD1-treated non-small cell lung cancer 243 samples shares lung
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.