Evidence map›Paper›PMID 36158075›Full record

ArticleHeliyon2022

Analysis of the role of m6A and lncRNAs in prognosis and immunotherapy of hepatocellular carcinoma.

Yan Xu, Rong Liu

Abstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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. Review
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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

2 authors.

Yan XuDepartment of Hepatopancreatobiliary Surgical Oncology, Chinese People's Liberation Army (PLA) General Hospital, Beijing, 100853, China.
Rong LiuDepartment of Hepatopancreatobiliary Surgical Oncology, Chinese People's Liberation Army (PLA) General Hospital, Beijing, 100853, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To study the role of m6A and lncRNAs in the prognosis and immunotherapy of hepatocellular carcinoma, construct the risk score of overall survival of hepatocellular carcinoma, and search for new therapeutic targets and drugs. Methods: The data used in this study are obtained from The Cancer Genome Atlas (TCGA) database. A total of 424 HCC samples were included. The co-expression of lncRNAs and M6A-related genes in HCC was analyzed, COX regression analysis was conducted to construct the risk score for HCC prognosis, and the model's validity was further verified in different clinical trials subtypes and principal component analysis. GO enrichment analysis and immune function analysis were performed for the differential genes in the high-risk group and the low-risk group divided by risk score and analyzed the prognostic effect of TMB on the two groups. Based on the results, potential therapeutic agents for HCC were screened. Results: The risk score can better predict the prognosis of HCC, the area under the ROC curve is 0.727. Differential genes were mainly located in the extracellular matrix and chromosomal regions and may play regulatory roles in binding sites and catalytic enzymes, thereby affecting the chromosome division and cell proliferation of cells. Type Ⅱ IFN response, type Ⅰ IFN response and MHC class Ⅰ were the three most different functions in terms of immune function between the high-risk group and the low-risk group. Type II IFN response, type I IFN response was significantly down-regulated in the high-risk group, while MHC class I was up-regulated. 14 potential therapeutic drugs were screened out. Conclusions: The risk score constructed with NRAV and AL031985.3 had a good predictive effect on the prognosis of HCC. Differences in genes and immune function between high-risk and low-risk groups promoted the occurrence and progression of HCC.

Indexed as

AL031985.3Hepatocellular carcinomaImmune functionm6ANRAVRisk score

Identifiers

PMID36158075
PMCPMC9489786

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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.