Evidence map›Paper›PMID 38822402›Full record

ArticleBMC medical genomics2024

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients.

Mengjiao Zhang, Jiqiang Zhang, Xuemei Liang, Ming Zhang

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Article in BMC medical genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Mengjiao ZhangDepartment of Geriatric Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
Jiqiang ZhangDepartment of Orthopedics/Sports Medicine Center, Southwest Hospital, Army Medical University, Chongqing, 400038, China.
Xuemei LiangDepartment of Geriatric Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China. liang2002@swmu.edu.cn.
Ming ZhangDepartment of Respiratory and Critical Care Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China. zhangming041@swmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsNeoplastic Stem CellsRNA, Long NoncodingTumor MicroenvironmentBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMalePrognosisBiomarkers, TumorRNA, Long NoncodingCancer stem cellsClear cell renal cell carcinomaLong non-coding RNAsPrognosisTumor immune microenvironment

Identifiers

PMID38822402
PMCPMC11141027

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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.