Evidence map›Paper›PMID 36280825›Full record

ArticleBMC medical genomics2022

Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer.

Yaobin Lin, Yu Xiao, Shan Liu, Liang Hong, Lingdong Shao, Junxin Wu

Abstract read
In one paragraph

Article in BMC medical genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

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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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Long non‑coding RNAs, lipid metabolism and cancer (Review).Experimental and therapeutic medicine · 2023
    Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. NJournal of hepatocellular carcinoma · 2023
    Article
  14. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Yaobin Lin *Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Rd, Jin'an District, Fuzhou, 350014, Fujian, China.
Yu Xiao *Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Rd, Jin'an District, Fuzhou, 350014, Fujian, China.
Shan LiuDepartment of Hematology-Oncology, Fujian Children's Hospital, Fuzhou, 350000, China.
Liang HongDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Rd, Jin'an District, Fuzhou, 350014, Fujian, China.
Lingdong ShaoDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Rd, Jin'an District, Fuzhou, 350014, Fujian, China.
Junxin WuDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Rd, Jin'an District, Fuzhou, 350014, Fujian, China. junxinwufj@aliyun.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEnergy metabolism disorder, especially lipid metabolism disorder, is an important biological characteristic of colon cancer. This research sought to examine the association between lipid metabolism-related long non-coding RNAs (lncRNAs) and prognoses among colon cancer patients.

methodsThe transcriptome profile and clinical data of patients with colon cancer were retrieved from The Cancer Genome Atlas database. Using consensus clustering, cases were divided into two clusters and Kaplan-Meier analysis was executed to analyze differences in their prognoses. The gene set enrichment analysis (GSEA) was used to discover biological processes and signaling pathways. A lipid metabolism-related lncRNA prognostic model (lipid metabolism-LncRM) was created utilizing the least absolute shrinkage and selection operator (LASSO) regression. The tumor microenvironment was evaluated on the basis of the composition of immune and stromal cells.

resultsThe patients in Cluster 2 were found to have a better prognosis and higher expression of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) relative to Cluster 1. The results of GSEA showed the enrichment of energy metabolism pathways in Cluster 2. LASSO regression was used to identify the five LncRNAs that were shown to be most substantially linked to patient prognosis. These were NSMCE1-DT, LINC02084, MYOSLID, LINC02428, and MRPS9-AS1. Receiver operating characteristic (ROC) curves and survival analysis illustrated that the lipid metabolism-LncRM had a significant prognostic value. Further analysis showed that high- and low-risk groups were significantly different in terms of clinical characteristics and immune cells infiltration.

conclusionsLipid metabolism-related lncRNAs could predict the prognoses and tumor microenvironment of colon cancer and might be important biomarkers relevant to immunotherapy.

Indexed as

Colonic NeoplasmsRNA, Long NoncodingB7-H1 AntigenBiomarkers, TumorGene Expression Regulation, NeoplasticHumansLigandsLipid MetabolismPrognosisProgrammed Cell Death 1 ReceptorRisk AssessmentTumor MicroenvironmentB7-H1 AntigenBiomarkers, TumorLigandsProgrammed Cell Death 1 ReceptorRNA, Long NoncodingColon cancerLipid metabolismLong non-coding RNAsPrognosisTumor microenvironment

Identifiers

PMID36280825
PMCPMC9590147

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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.