Evidence map›Paper›PMID 37740762›Full record

ArticleJournal of cancer research and clinical oncology2023

Functional enrichment analysis of LYSET and identification of related hub gene signatures as novel biomarkers to predict prognosis and immune infiltration status of clear cell renal cell carcinoma.

Yuxing Chen, Jinhang He, Tian Jin, Ye Zhang, Yunsheng Ou

Open access · hybridAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 28% 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Yuxing ChenDepartment of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jinhang HeFirst Clinical Medical College, Chongqing Medical University, Chongqing, China.
Tian JinDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Ye ZhangDepartment of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yunsheng OuDepartment of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China. ouyunsheng2001@163.com.
Chongqing Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CN

Funding

2022 First-class Discipline Construction Project of the First Affiliated Hospital of Chongqing Medical University CYYY-BSYJSCXXM-202207National Natural Science Foundation of China 81572634
6 · The paper itself

Abstract

purposeThe latest research shows that the lysosomal enzyme trafficking factor (LYSET) encoded by TMEM251 is a key regulator of the amino acid metabolism reprogramming (AAMR) and related pathways significantly correlate with the progression of some tumors. The purpose of this study was to explore the potential pathways of the TMEM251 in clear cell renal cell carcinoma (ccRCC) and establish related predictive models based on the hub genes in these pathways for prognosis and tumor immune microenvironment (TIME).

methodsWe obtained mRNA expression data and clinical information of ccRCC samples from The Cancer Genome Atlas (TCGA), E-MATE-1980, and immunotherapy cohorts. Single-cell sequencing data (GSE152938) were downloaded from the Gene Expression Omnibus (GEO) database. We explored biological pathways of the LYSET by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of TMEM251-coexpression genes. The correlation of LYSET-related pathways with the prognosis was conducted by Gene Set Variation Analysis (GSVA) and unsupervised cluster analysis. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to identify hub prognostic genes and construct the risk score. Immune infiltration analysis was conducted by CIBERSORTx and Tumor Immune Estimation Resource (TIMER) databases. The predictive value of the risk score and hub prognostic genes on immunotherapy responsiveness was analyzed through the tumor mutation burden (TMB) score, immune checkpoint expression, and survival analysis. Immunohistochemistry (IHC) was finally used to verify the expressions of hub prognostic genes.

resultsThe TMEM251 was found to be significantly correlated with some AAMR pathways. AAGAB, ENTR1, SCYL2, and WDR72 in LYSET-related pathways were finally identified to construct a risk score model. Immune infiltration analysis showed that LYSET-related gene signatures significantly influenced the infiltration of some vital immune cells such as CD4 + cells, NK cells, M2 macrophages, and so on. In addition, the constructed risk score was found to be positively correlated with TMB and some common immune checkpoint expressions. Different predictive values of these signatures for Nivolumab therapy responsiveness were also uncovered in immunotherapy cohorts. Finally, based on single-cell sequencing analysis, the TMEM251 and the hub gene signatures were found to be expressed in tumor cells and some immune cells. Interestingly, IHC verification showed a potential dual role of four hub genes in ccRCC progression.

conclusionThe novel predictive biomarkers we built may benefit clinical decision-making for ccRCC. Our study may provide some evidence that LYSET-related gene signatures could be novel potential targets for treating ccRCC and improving immunotherapy efficacy. Our nomogram might be beneficial to clinical choices, but the results need more experimental verifications in the future.

Indexed as

CarcinomaCarcinoma, Renal CellKidney NeoplasmsAdaptor Proteins, Vesicular TransportBiomarkersHumansPrognosisTumor MicroenvironmentAAGAB protein, humanAdaptor Proteins, Vesicular TransportBiomarkersAmino acid metabolism reprogrammingccRCCImmunotherapyLysosomal enzyme trafficking factor (LYSET)PathwaysPrognosisTumor immune microenvironment

Identifiers

PMID37740762
PMCPMC10645642
OpenAlexW4386981255

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LicenceCC BY
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Registered trials

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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.