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Interrogating the mechanistic link between neighborhood deprivation and colorectal cancer risk through gene expression analysis of normal colorectal biopsies

GSE319878 Homo sapiens (human) RNA-seq (gene expression) 171 samples Submitted 2026/04/10 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 171 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
171 samples: 171 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.
Summary (written by the submitters)
Importance: Neighborhood socioeconomic status has been associated with increased colorectal cancer (CRC) risk, particularly among different racial groups, yet the biological mechanisms underlying this association remain unclear. Objective: To investigate whether neighborhood deprivation, as assessed by Neighborhood Deprivation Index (NDI), is associated with differential gene expression in normal colorectal biopsies; to explore molecular links to CRC risk and to identify potential chemoprevention targets.
Read the full summary ↓
Design: A cross-sectional study involving transcriptomic analysis of normal colorectal tissues and meta-analysis of gene expression data between African Americans (AA) and European Americans (EA), and an experimental study exposing colon organoids derived from healthy colon biopsies to metformin. Setting: Participants were enrolled in the Cleveland Colon Screening and Risk Factors Study (2012-2018) in metropolitan Cleveland, Ohio. Organoids were derived from colon biopsies of patients undergoing colonoscopy in Charlottesville, Virginia. Participants: Normal colorectal biopsies from AA (n = 34) and EA (n = 23) adults undergoing colonoscopy were analyzed. Colon organoids were derived from AA (n = 4) and EA (n = 6) individuals. RNA-seq data was generated from each participant. Main Outcome(s) and Measures: Differentially expressed genes (DEGs) associated with NDI in normal colorectal biopsies and overlap with DEGs identified in CRC tumor tissues; and association of metformin on NDI-associated, CRC risk gene expression. Results: A total of 237 DEGs were found to be commonly associated with NDI across individual-matched biopsy triplets (right and left colon, and rectum) in both racial groups. Cellular metabolism pathways were amongst the most significantly enriched within identified DEGs. Of the 237 NDI associated DEGs, 82 overlapped with CRC tumor DEGs from a publicly available dataset (TCGA-COADREAD; P=2.21×10⁻⁵; OR=1.83), and nine were prioritized as therapeutic targets, including MYC overexpression (BH=2.48E-12). Metformin exposure in colon organoids also altered the expression of 28 of these genes, with ~79% showing opposite direction, including reduced MYC expression (BH=0.095). Conclusion and Relevance: NDI is associated with CRC-related transcriptional differences. These findings suggest potential molecular mechanisms linking neighborhood deprivation to CRC risk. The observed reversal of gene expression by metformin suggests a potential role for metformin in reducing CRC risk in high NDI-populations, who face greater than average risk of developing CRC.
This dataset
Open GSE319878 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 GSE319878_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 ↗

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 PRJNA1425462 and SRA study SRP678014. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
171 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 171 sample titles: 171 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.

Samples in this study

+ 131 more — browse all 171 samples with per-sample file links →

More Colorectal cancer datasets

Search all human RNA-seq datasets in GEO →

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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.