ArticleScientific reports2025
Stool shed cell transcriptomics mirrors tumor biology and enables colorectal cancer diagnosis.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Screening and molecular characterization of human intestinal pathologies such as colorectal cancer (CRC) currently depends on colonoscopy, an invasive procedure associated with risks and poor adherence. A non-invasive method that captures host molecular changes could improve early detection and monitoring of intestinal diseases. Transcriptomic profiling of shed intestinal cells in stool has shown potential in neonates but is limited in adults by the dominance of bacterial RNA. To address this, we combined microbial ribosomal RNA (rRNA) depletion with unique molecular identifier (UMI)-based RNA sequencing to enrich and quantify human transcripts in stool. Applying this method to samples from 54 CRC patients and 24 healthy controls, we profiled thousands of human genes per sample. Stool-derived gene expression distinguished CRC from control samples with high accuracy (AUC = 0.86) and strongly correlated with matched tumor tissue signatures. Notably, stool transcriptomes reverted to control-like patterns after tumor resection. Our approach offers a powerful, non-invasive alternative to current CRC diagnostics and enables molecular insights into tumor biology. This method could complement or replace existing screening tools and may be applicable to other gastrointestinal diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.