Evidence map›Paper›PMID 38107762›Full record

ArticleOncoTargets and therapy2023

Investigating the Diagnostic and Therapeutic Potential of SREBF2-Related Lipid Metabolism Genes in Colon Cancer.

Yuteng Ma, Zhe Wang, Jian Sun, Jingtong Tang, Jianping Zhou, Ming Dong

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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

6 authors at 2 institutions in 1 country.

Yuteng MaDepartment of Gastrointestinal Surgery, First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Zhe WangDepartment of Pathology, Shengjing Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Jian SunDepartment of Gastrointestinal Surgery, First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Jingtong TangDepartment of Gastrointestinal Surgery, First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Jianping ZhouDepartment of Gastrointestinal Surgery, First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.ORCID 0000-0003-2789-7244
Ming DongDepartment of Gastrointestinal Surgery, First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.ORCID 0000-0003-2685-1420
First Hospital of China Medical University · CNChina Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Colon cancer is one of the leading causes of death worldwide, and screening of effective molecular markers for the diagnosis is prioritised for prevention and treatment. This study aimed to investigate the diagnostic and predictive potential of genes related to the lipid metabolism pathway, regulated by a protein called sterol-regulatory element-binding transcription Factor 2 (SREBF2), for colon cancer and patient outcomes. Methods: We used machine-learning algorithms to identify key genes associated with SREBF2 in colon cancer based on a public database. A nomogram was created to assess the diagnostic value of these genes and validated in the Cancer Genome Atlas. We also analysed the relationship between these genes and the immune microenvironment of colon tumours, as well as the correlation between gene expression and clinicopathological characteristics and prognosis in the China Medical University (CMU) clinical cohort. Results: Three genes, Conclusion: This study highlights the potential of

Indexed as

7-dehydrocholesterol reductasecolon cancerDHCR7diagnosismachine learningSREBF2sterol-regulatory element-binding transcription Factor 2

Identifiers

PMID38107762
PMCPMC10723182
OpenAlexW4389570663

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.