Evidence map›Paper›PMID 37559997›Full record

ArticleAmerican journal of cancer research2023

Construction of molecular typing in LIHC microenvironment based on lipid metabolism-related genes.

Shan Cong, Shanshan Bai, Yanfang Bi, Yu Wang, Shi Jin, Hui He

Abstract read
In one paragraph

Article in American journal of cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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.

Shan CongDepartment of Laparoscopic Surgery, The First Affiliated Hospital of Dalian Medical University Dalian 116000, Liaoning, China.
Shanshan BaiDepartment of Ultrasound, The First Affiliated Hospital of Dalian Medical University Dalian 116000, Liaoning, China.
Yanfang BiDepartment of Nursing, The First Affiliated Hospital of Dalian Medical University Dalian 116000, Liaoning, China.
Yu WangDepartment of Laparoscopic Surgery, The First Affiliated Hospital of Dalian Medical University Dalian 116000, Liaoning, China.
Shi JinDepartment of Laparoscopic Surgery, The First Affiliated Hospital of Dalian Medical University Dalian 116000, Liaoning, China.
Hui HeDepartment of Laparoscopic Surgery, The First Affiliated Hospital of Dalian Medical University Dalian 116000, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Consensus on the stage of liver hepatocellular carcinoma (LIHC) in patients is difficult, which restricts the diagnosis and treatment of liver cancer. Molecular typing based on genes related to the lipid metabolism pathways can reflect deeper characteristics of liver cancer and complement the deficiency of the clinical staging system. In this study, we constructed and verified two cell subtypes: C1 and C2 in LIHC, based on six lipid metabolic pathway-associated genes identified in two independent external validation cohorts comprising single-cell RNA-sequencing technology (scRNA-Seq) data and bulk RNA-seq data downloaded from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The C2 subtype showed poorer prognosis, higher immune scores, and greater correlation with pathways associated with tumor progression as compared to the C1 subtype. Moreover, the sensitivity of many tested targeted drugs in C1 was relative to C2. Furthermore, Gene Set Enrichment Analysis (GSEA) revealed several significantly enriched oncological signatures and metabolic processes, which might help elucidate the underlying molecular mechanisms. At the same time, we identified there were significantly different metabolites in C1 and C2 subtypes using 11 LIHC tissue samples. In conclusion, we constructed two molecular subtypes based on the lipid metabolism-associated genes, which may provide valuable information to further study the pathogenesis and devise clinical management strategies for LIHC.

Indexed as

data analysisheterogeneitylipid metabolismLiver hepatocellular carcinomaprognosisscRNA-Seq

Identifiers

PMID37559997
PMCPMC10408469

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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.