Evidence map›Paper›PMID 34988460›Full record

ArticleNAR cancer2021

Characterization of the consensus mucosal microbiome of colorectal cancer.

Lan Zhao, Susan M Grimes, Stephanie U Greer, Matthew Kubit, HoJoon Lee, Lincoln D Nadauld, Hanlee P Ji

Abstract read
In one paragraph

Article in NAR cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The Human Respiratory Microbiome: Current Understandings and Future Directions.American journal of respiratory cell and molecular biology · 2023
    Pooled it
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  17. Exploring the patient-microbiome interaction patterns for pan-cancer.Computational and structural biotechnology journal · 2022
    Article
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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.

Lan ZhaoDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0003-2681-7695
Susan M GrimesDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Stephanie U GreerDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Matthew KubitDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
HoJoon LeeDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Lincoln D NadauldIntermountain Precision Genomics Program, Intermountain Healthcare, Saint George, UT 84790, USA.
Hanlee P JiDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0003-3772-3424

Funding

Statistical Models for Genome Sequencing and AssociationR01HG006137 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI JI, HANLEE P, ZHANG, NANCY R · 2011 to 2022
$4.3M
NHGRI NIH HHS R01 HG006137
6 · The paper itself

Abstract

Dysbioisis is an imbalance of an organ's microbiome and plays a role in colorectal cancer pathogenesis. Characterizing the bacteria in the microenvironment of a cancer through genome sequencing has advantages compared to culture-based profiling. However, there are notable technical and analytical challenges in characterizing universal features of tumor microbiomes. Colorectal tumors demonstrate microbiome variation among different studies and across individual patients. To address these issues, we conducted a computational study to determine a consensus microbiome for colorectal cancer, analyzing 924 tumors from eight independent RNA-Seq data sets. A standardized meta-transcriptomic analysis pipeline was established with quality control metrics. Microbiome profiles across different cohorts were compared and recurrently altered microbial shifts specific to colorectal cancer were determined. We identified cancer-specific set of 114 microbial species associated with tumors that were found among all investigated studies. Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria were among the four most abundant phyla for the colorectal cancer microbiome. Member species of Clostridia were depleted and

Identifiers

PMID34988460
PMCPMC8693571

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.