Evidence map›Paper›PMID 33076720›Full record

ArticleThe Journal of international medical research2020

Machine learning identifies two autophagy-related genes as markers of recurrence in colorectal cancer.

Jianping Wu, Sulai Liu, Xiaoming Chen, Hongfei Xu, Yaoping Tang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of international medical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. 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 1 country.

Jianping WuHunan University of Science and Engineering, Yongzhou, China.
Sulai LiuDepartment of Hepatobiliary Surgery, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Xiaoming ChenHunan University of Science and Engineering, Yongzhou, China.
Hongfei XuHunan University of Science and Engineering, Yongzhou, China.
Yaoping TangHunan University of Science and Engineering, Yongzhou, China.ORCID https://orcid.org/0000-0002-0763-2540
Hunan University of Science and Engineering · CNHunan Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveColorectal cancer (CRC) is the most common cancer worldwide. Patient outcomes following recurrence of CRC are very poor. Therefore, identifying the risk of CRC recurrence at an early stage would improve patient care. Accumulating evidence shows that autophagy plays an active role in tumorigenesis, recurrence, and metastasis.

methodsWe used machine learning algorithms and two regression models, univariable Cox proportion and least absolute shrinkage and selection operator (LASSO), to identify 26 autophagy-related genes (ARGs) related to CRC recurrence.

resultsBy functional annotation, these ARGs were shown to be enriched in necroptosis and apoptosis pathways. Protein-protein interactions identified

conclusionThese results shed light on prediction of CRC recurrence by ARGs. Stratification of patients into recurrence risk groups by testing ARGs would be a valuable tool for early detection of CRC recurrence.

Indexed as

Colonic NeoplasmsColorectal NeoplasmsAutophagyHumansMachine LearningNeoplasm Recurrence, Localautophagyautophagy-related geneColorectal cancermachine learningrecurrenceregression

Identifiers

PMID33076720
PMCPMC7780659
OpenAlexW3092967989

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.