Cellular adaptation to cancer therapy along a resistance continuum [scRNA-Seq: Kuramochi]
Single-cell RNA-seq · human · 10 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
- 10 samples: 8 × Kura_TGroups 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
- Cellular adaptation to cancer therapy along a resistance continuumNature · 2024
Read the full summary ↓
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 GSE206125_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 PRJNA849248 and SRA study SRP381781. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 8 samples.
How we read this: 1 replicated groups read from 10 sample titles; they account for 8 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.
- GSM6243786 Kura_C
- GSM6243787 Kura_T1 Kura_T
- GSM6243788 Kura_T2.5
- GSM6243789 Kura_T5 Kura_T
- GSM6243790 Kura_T10 Kura_T
- GSM6243791 Kura_T20 Kura_T
- GSM6243792 Kura_T40 Kura_T
- GSM6243793 Kura_T80 Kura_T
- GSM6243794 Kura_T160 Kura_T
- GSM6243795 Kura_T320 Kura_T
- GSE247691 Cellular adaptation to cancer therapy along a resistance continuum 93 samples shares adaptation, resistance, continuum, cellular, therapy, along
- GSE235863 T cell populations correlate with response and resistance to anti-PD-1 plus lenvatinib combination therapy in hepatocellular carcinoma 69 samples shares resistance, cellular, therapy
- GSE273829 GABA promotes resistance to immunotherapy of patients with TLS-positive tumors [RNA-seq] 92 samples shares resistance, therapy
- GSE286827 4-1BB+ Tregs and inhibitory progenitor exhausted T cells confer resistance to anti-PD-L1 and anti-CTLA-4 combination therapy 87 samples shares resistance, therapy
- GSE211434 Diverse immune suppressing cancer communications with myeloid cells prevent T cell activation and recruitment and provide resistance to cell cycle inhibitor therapy 81 samples shares resistance, therapy
- GSE222556 Neoadjuvant PARPi or Chemotherapy in Ovarian Cancer Informs Targeting Effector Treg Cells for Homologous-Recombination-Deficient Tumors [10x scRNA-seq] 67 samples shares scrna-seq, therapy
- GSE190564 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - whole tissue scRNA-Seq 62 samples shares scrna-seq, therapy
- GSE309004 Molecular determinants of neoadjuvant chemotherapy resistance in breast cancer: An analysis of gene expression and tumor microenvironment 54 samples shares resistance, therapy
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.