Prognostic and diagnostic value of metal metabolism in colorectal cancer
RNA-seq (gene expression) · human · 20 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
- Colorectal cancerThis series is part of our curated briefing on it.
- Samples
- 20 samples: 3 × HCT-15 cells, GFP, biol vs 3 × HCT-15 cells, WT, biol vs 3 × HuTu80 cells, GFP, biol vs 3 × HuTu80 cells, WT, biolGroups 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
- Forced Overexpression and Knockout Analysis of SLC30A and SLC39A Family Genes Suggests Their Involvement in Establishing Resistance to Cisplatin in Human Cancer CellsInternational journal of molecular sciences · 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 GSE276849_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 PRJNA1159221 and SRA study SRP531877. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 8 samples read as cases, 6 as controls.
How we read this: 4 replicated groups read from 20 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.
- GSM8506748 HCT-15 cells, GFP, biol rep 1 HCT-15 cells, GFP, biol
- GSM8506749 HCT-15 cells, GFP, biol rep 2 HCT-15 cells, GFP, biol
- GSM8506750 HCT-15 cells, GFP, biol rep 3 HCT-15 cells, GFP, biol
- GSM8506751 HCT-15 cells, SLC30A10 overexpression
- GSM8506752 HCT-15 cells, SLC30A3 overexpression
- GSM8506753 HCT-15 cells, WT, biol rep 1 HCT-15 cells, WT, biol
- GSM8506754 HCT-15 cells, WT, biol rep 2 HCT-15 cells, WT, biol
- GSM8506755 HCT-15 cells, WT, biol rep 3 HCT-15 cells, WT, biol
- GSM8506756 HCT-15 cells, SLC39A14 knockout
- GSM8506757 HuTu80 cells, SLC39A8 knockout
- GSM8506758 HuTu80 cells, GFP, biol rep 1 HuTu80 cells, GFP, biol
- GSM8506759 HuTu80 cells, SLC39A14 knockout
- GSM8506760 HuTu80 cells, GFP, biol rep 3 HuTu80 cells, GFP, biol
- GSM8506761 HuTu80 cells, SLC30A10 overexpression
- GSM8506762 HuTu80 cells, SLC30A3 overexpression
- GSM8506763 HuTu80 cells, GFP, biol rep 2 HuTu80 cells, GFP, biol
- GSM8506764 HuTu80 cells, WT, biol rep 1 HuTu80 cells, WT, biol
- GSM8506765 HuTu80 cells, WT, biol rep 2 HuTu80 cells, WT, biol
- GSM8506766 HuTu80 cells, WT, biol rep 3 HuTu80 cells, WT, biol
- GSM8506767 HuTu80 cells, SLC39A8 overexpression
- GSE250000 Bulk RNA-sequencing of transduced colorectal cancer cell line HCT-116 and breast cancer cell line MCF-7 overexpressing full-lenght p53β or p53β-stop-lost. 4 samples same disease briefing · shares colorectal
- GSE12032 Inherent gene signature of stage II and III colorectal cancer leads in individual recurrence 198 samples same disease briefing · shares colorectal
- GSE110009 Single cell transcriptome landscape of primary and metastatic tumor in colon cancer 76 samples same disease briefing
- GSE109308 Single-cell transcriptomic survey of adenomatous polyposis patients with germline APC mutations 97 samples same disease briefing
- GSE275647 Role of Cancer-Associated Fibroblasts in Prognostic Stratification of Advanced-Stage Gastric Cancer through Interacting with Endothelial and Malignant Epithelial Cells [AGC RNA-seq] 216 samples shares prognostic
- GSE312983 A single-nucleus RNA-seq atlas of colorectal cancer across the age continuum reveals distinct features of early-onset colorectal cancer 189 samples shares colorectal
- GSE319878 Interrogating the mechanistic link between neighborhood deprivation and colorectal cancer risk through gene expression analysis of normal colorectal biopsies 171 samples shares colorectal
- GSE281917 Gene expression data to identify molecular characteristics of mucinous colorectal cancer 140 samples shares colorectal
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.