GEO series

Whole-transcriptome profilings between a pair of HCA7-derived KRAS-wildtype cetuximab sensitive and resistant colon cancer cells from 3D culture

GSE82236 Homo sapiens (human) Non-coding RNA profiling 12 samples Submitted 2017/08/30 Platform GPL11154Platform GPL18573

At a glance

Non-coding RNA profiling · human · 12 samples

What it is: Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism: Homo sapiens (human)
Topic: Colorectal cancerThis series is part of our curated briefing on it.
Samples: 12 samples
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)

We report the results of RNA-Seq and small RNA-Seq from a pair of HCA7-derived, KRAS wildtype CC and CC-CR cultured in 3D. A total of 361 genes showed more than a two-fold change in expression (false-discovery rate [FDR] - adjusted p<0.01) between CC-CR and CC; there were 141 transcripts upregulated and 220 transcripts downregulated in CC-CR compared to CC.

Read the full summary ↓

Small RNA-Seq detected 7 miRNAs upregulated and 24 miRNAs downregulated in CC-CR cells compared to CC cells (fold change>2, FDR<0.01). Differential expression analysis revealed several novel candidates that may contribute to cetuximab resistance. The whole-transcriptome profilings using cetuximab resistance model from 3D culture provide novel candidates for cetuximab resistance and further functional studies might open the door to a novel understanding of how non-mutational mechanisms mediate cetuximab resistance.

This dataset

Open GSE82236 in finder → Find more human RNA-seq datasets → Colorectal 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 GSE82236_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 ↗

Also filed as BioProject PRJNA324412 and SRA study SRP076105. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 29035371) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 12 more — browse all 12 samples with per-sample file links →

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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.