Evidence map›Paper›PMID 30412600›Full record

ArticlePloS one2018

Re-purposing 16S rRNA gene sequence data from within case paired tumor biopsy and tumor-adjacent biopsy or fecal samples to identify microbial markers for colorectal cancer.

Manasi S Shah, Todd DeSantis, Jose-Miguel Yamal, Tiffany Weir, Elizabeth P Ryan, Julia L Cope, Emily B Hollister

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 12% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. The Human Microbiome in Relation to Cancer Risk: A Systematic Review of Epidemiologic Studies.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Pooled it
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  17. The Interaction Between the Microbiome and Tumors.Frontiers in cellular and infection microbiology · 2021
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  19. A gut butyrate-producing bacteriumOncology letters · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 1 country.

Manasi S ShahUniversity of Texas School of Public Health, Houston, TX, United States of America.ORCID 0000-0001-7094-7628
Todd DeSantisInformatics, Second Genome, Inc, South San Francisco, CA, United States of America.
Jose-Miguel YamalUniversity of Texas School of Public Health, Houston, TX, United States of America.
Tiffany WeirDepartment of Food Science and Human Nutrition, Colorado State University, Fort Collins, CO, United States of America.
Elizabeth P RyanDepartment of Environmental and Radiological Health Sciences, Colorado State University/Colorado School of Public Health, Fort Collins, CO, United States of America.
Julia L CopeDepartment of Pathology & Immunology, Baylor College of Medicine, Houston, TX, United States of America.ORCID 0000-0003-4600-5600
Emily B HollisterDepartment of Pathology & Immunology, Baylor College of Medicine, Houston, TX, United States of America.
Baylor College of Medicine · USColorado School of Public Health · USColorado State University · USSecond Genome (United States) · USThe University of Texas Health Science Center at Houston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbes colonizing colorectal cancer (CRC) tumors have the potential to affect disease, and vice-versa. The manner in which they differ from microbes in physically adjacent tissue or stool within the case in terms of both, taxonomy and biological activity remains unclear. In this study, we systematically analyzed previously published 16S rRNA sequence data from CRC patients with matched tumor:tumor-adjacent biopsies (n = 294 pairs, n = 588 biospecimens) and matched tumor biopsy:fecal pairs (n = 42 pairs, n = 84 biospecimens). Procrustes analyses, random effects regression, random forest (RF) modeling, and inferred functional pathway analyses were conducted to assess community similarity and microbial diversity across heterogeneous patient groups and studies. Our results corroborate previously reported association of increased Fusobacterium with tumor biopsies. Parvimonas and Streptococcus abundances were also elevated while Faecalibacterium and Ruminococcaceae abundances decreased in tumors relative to tumor-adjacent biopsies and stool samples from the same case. With the exception of these limited taxa, the majority of findings from individual studies were not confirmed by other 16S rRNA gene-based datasets. RF models comparing tumor and tumor-adjacent specimens yielded an area under curve (AUC) of 64.3%, and models of tumor biopsies versus fecal specimens exhibited an AUC of 82.5%. Although some taxa were shared between fecal and tumor samples, their relative abundances varied substantially. Inferred functional analysis identified potential differences in branched amino acid and lipid metabolism. Microbial markers that reliably occur in tumor tissue can have implications for microbiome based and microbiome targeting therapeutics for CRC.

Indexed as

Gastrointestinal MicrobiomeArea Under CurveBacteriaColonColorectal NeoplasmsFecesFusobacteriumHumansRNA, Ribosomal, 16SROC CurveRuminococcusRNA, Ribosomal, 16S

Identifiers

PMID30412600
PMCPMC6226189
OpenAlexW2900296445

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.