Polyploid cancer cells reveal signatures of chemotherapy relapse [scRNA-seq]
Single-cell RNA-seq · human · 605 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 605 samples: 605 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
- Polyploid cancer cells reveal signatures of chemotherapy resistancebioRxiv : the preprint server for biology · 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 GSE270568_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1127498 and SRA study SRP515888. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from the first 400 of 605 sample titles: 400 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.
- GSM8346981 3_MDAMB231_cis_DPT1
- GSM8346982 7_MDAMB231_cis_DPT10
- GSM8346983 9_MDAMB231_cis_DPT10
- GSM8346984 11_MDAMB231_cis_DPT10
- GSM8346985 12_MDAMB231_cis_DPT10
- GSM8346986 14_MDAMB231_cis_DPT10
- GSM8346987 16_MDAMB231_cis_DPT10
- GSM8346988 18_MDAMB231_cis_DPT10
- GSM8346989 20_MDAMB231_cis_DPT10
- GSM8346990 21_MDAMB231_cis_DPT10
- GSM8346991 23_MDAMB231_cis_DPT10
- GSM8346992 24_MDAMB231_cis_DPT1
- GSM8346993 28_MDAMB231_cis_DPT10
- GSM8346994 30_MDAMB231_cis_DPT10
- GSM8346995 32_MDAMB231_cis_DPT10
- GSM8346996 34_MDAMB231_cis_DPT10
- GSM8346997 37_MDAMB231_cis_DPT10
- GSM8346998 39_MDAMB231_cis_DPT10
- GSM8346999 41_MDAMB231_cis_DPT10
- GSM8347000 43_MDAMB231_cis_DPT10
- GSM8347001 45_MDAMB231_cis_DPT10
- GSM8347002 47_MDAMB231_cis_DPT1
- GSM8347003 51_MDAMB231_cis_DPT10
- GSM8347004 53_MDAMB231_ctrl
- GSM8347005 55_MDAMB231_ctrl
- GSM8347006 57_MDAMB231_ctrl
- GSM8347007 59_MDAMB231_ctrl
- GSM8347008 61_MDAMB231_ctrl
- GSM8347009 63_MDAMB231_ctrl
- GSM8347010 65_MDAMB231_ctrl
- GSM8347011 67_MDAMB231_ctrl
- GSM8347012 70_MDAMB231_cis_DPT1
- GSM8347013 93_MDAMB231_cis_DPT1
- GSM8347014 106_MDAMB231_cis_DPT1
- GSM8347015 119_MDAMB231_cis_DPT1
- GSM8347016 144_MDAMB231_cis_DPT1
- GSM8347017 156_MDAMB231_cis_DPT1
- GSM8347018 167_MDAMB231_cis_DPT1
- GSM8347019 171_MDAMB231_cis_DPT1
- GSM8347020 184_MDAMB231_cis_DPT1
+ 565 more — browse all 605 samples with per-sample file links →
- GSE222556 Neoadjuvant PARPi or Chemotherapy in Ovarian Cancer Informs Targeting Effector Treg Cells for Homologous-Recombination-Deficient Tumors [10x scRNA-seq] 67 samples shares chemotherapy, scrna-seq
- GSE296649 Clonal evolution permits outgrowth of chemoresistant LMPP-like early progenitors in relapsed NPM1c AML [scRNA-Seq] 58 samples shares scrna-seq, relapse
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares scrna-seq
- GSE337246 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [scRNA-Seq organoids] 35 samples shares scrna-seq
- GSE278450 Glioblastoma scRNA-seq shows treatment-induced, immune-dependent increase in mesenchymal cancer cells and structural variants in distal neural stem cells 22 samples shares scrna-seq
- GSE297041 Chemoradiation Reprograms Tumor Cells and Immune Microenvironment In Cervical Cancer [scRNA-seq] 18 samples shares scrna-seq
- GSE241908 Transcriptomic profiles of ovarian cancer cells isolated from paired cancer ascites before and after chemotherapy 14 samples shares chemotherapy
- GSE205472 A Single-Cell Atlas of HR+ Breast Cancer Reveals the Shifting of the Tumor Microenvironment in Response to Neoadjuvant Chemotherapy 13 samples shares chemotherapy
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.