Trial reportPloS one2020
MinION Sequencing of colorectal cancer tumour microbiomes-A comparison with amplicon-based and RNA-Sequencing.
Trial report in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Impact of Gut Microbiota on the Clinical Course and Treatment Outcomes of Colorectal Cancer-A Systematic Review.Medicina (Kaunas, Lithuania) · 2026Pooled it
- The modulatory role of short-chain fatty acids on peripheral circadian gene expression: a systematic review.Frontiers in physiology · 2025Pooled it
- MinION Sequencing of colorectal cancer tumour microbiomes-A comparison with amplicon-based and RNA-Sequencing.PloS one · 2020Trial
- Intratumoral Microorganisms in Tumors: Current Understanding and Emerging Therapeutic Strategies.MedComm · 2026Review
- Gut microbiota in colorectal cancer: a review of its influence on tumor immune surveillance and therapeutic response.Frontiers in oncology · 2025Review
- Article
- Review
- Mucosal Microbiome in Patients with Early Bowel Polyps: Inferences from Short-Read and Long-Read 16S rRNA Sequencing.Cancers · 2023Article
- Microbiomes, Their Function, and Cancer: How Metatranscriptomics Can Close the Knowledge Gap.International journal of molecular sciences · 2023Review
- Species-Level Characterization of the Microbiome in Breast Tissues with Different Malignancy and Hormone-Receptor Statuses Using Nanopore Sequencing.Journal of personalized medicine · 2023Article
- Bacterial cancer therapy in autochthonous colorectal cancer affects tumor growth and metabolic landscape.JCI insight · 2021Article
- Nanopore-Based Surveillance of Zoonotic Bacterial Pathogens in Farm-Dwelling Peridomestic Rodents.Pathogens (Basel, Switzerland) · 2021Article
- Gut Dysbiosis and Intestinal Barrier Dysfunction: Potential Explanation for Early-Onset Colorectal Cancer.Frontiers in cellular and infection microbiology · 2021Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecent evidence suggests a role for the gut microbiome in the development and progression of many diseases and many studies have been carried out to analyse the microbiome using a variety of methods. In this study, we compare MinION sequencing with meta-transcriptomics and amplicon-based sequencing for microbiome analysis of colorectal tumour tissue samples.
methodsDNA and RNA were extracted from 11 colorectal tumour samples. 16S rRNA amplicon sequencing and MinION sequencing was carried out using genomic DNA, and RNA-Sequencing for meta-transcriptomic analysis. Non-human MinION and RNA-Sequencing reads, and 16S rRNA amplicon sequencing reads were taxonomically classified using a database built from available RefSeq bacterial and archaeal genomes and a k-mer based algorithm in Kraken2. Concordance between the three platforms at different taxonomic levels was tested on a per-sample basis using Spearman's rank correlation.
resultsThe average number of reads per sample using RNA-Sequencing was greater than 129 times that generated using MinION sequencing. However, the average read length of MinION sequences was more than 13 times that of RNA or 16S rRNA amplicon sequencing. Taxonomic assignment using 16S sequencing was less reliable beyond the genus level, and both RNA-Sequencing and MinION sequencing could detect greater numbers of phyla and genera in the same samples, compared to 16S sequencing. Bacterial species associated with colorectal cancer, Fusobacterium nucleatum, Parvimonas micra, Bacteroides fragilis and Porphyromonas gingivalis, were detectable using MinION, RNA-Sequencing and 16S rRNA amplicon sequencing data.
conclusionsLong-read sequences generated using MinION sequencing can compensate for low numbers of reads for bacterial classification. MinION sequencing can discriminate between bacterial strains and plasmids and shows potential as a cost-effective tool for rapid microbiome sequencing in a clinical setting.
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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.