Evidence map›Paper›PMID 35574378›Full record

ArticleFrontiers in oncology2022

Prediction of Pathogenic Factors in Dysbiotic Gut Microbiomes of Colorectal Cancer Patients Using Reverse Microbiomics.

Haihe Wang, Kaibo Zhang, Lin Wu, Qian Qin, Yongqun He

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 46% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Association ofGut microbiome (Cambridge, England) · 2025
    Review
  4. Article
  5. Review
  6. Review
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

5 authors at 2 institutions in 2 countries.

Haihe WangDepartment of Immunology and Pathogen Biology, Lishui University, Lishui, China.
Kaibo ZhangDepartment of Immunology and Pathogen Biology, Lishui University, Lishui, China.
Lin WuCenter of Computer Experiment, Lishui University, Lishui, China.
Qian QinDepartment of Immunology and Pathogen Biology, Lishui University, Lishui, China.
Yongqun HeUnit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, MI, United States.
Lishui University · CNMichigan Center for Translational Pathology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gut microbiome plays a crucial role in the formation and progression of colorectal cancer (CRC). To better identify the underlying gene-level pathogenic mechanisms of microbiome-associated CRC, we applied our newly developed Reverse Microbiomics (RM) to predict potential pathogenic factors using the data of microbiomes in CRC patients. Results: Our literature search first identified 40 bacterial species enriched and 23 species depleted in the guts of CRC patients. These bacteria were systematically modeled and analyzed using the NCBI Taxonomy ontology. Ten species, including 6 enriched species (e.g., Conclusions: The RM strategy was used to predict 18 autoantigens and 76 potential virulence factors from CRC-associated microbiome data. In addition to many of these autoantigens and virulence factors experimentally verified as reported in the literature, our study predicted many new pathogenetic factors and developed a new model of CRC pathogenesis involving the riboflavin synthase from the enriched colorectal bacteria and other associated proteins.

Indexed as

bioinformaticscolorectal cancergut microbiomeontologyreverse microbiomicsreverse vaccinology

Identifiers

PMID35574378
PMCPMC9091335
OpenAlexW4224942333

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.