Evidence map›Paper›PMID 34368371›Full record

ArticleJournal of immunology research2021

A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma.

Zedan Zhang, Yanlin Tang, Yanjun Liu, Hongkai Zhuang, Enyu Lin, Lu Xie, Xiaoqiang Feng, Kaiwen Tian, Jiayi Zeng, Jiumin Liu and 1 more

Abstract read
In one paragraph

Article in Journal of immunology research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  10. Long Noncoding RNAs as Orchestrators of CD4Frontiers in cell and developmental biology · 2022
    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

11 authors.

Zedan ZhangDepartment of Urology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.ORCID https://orcid.org/0000-0002-0299-8818
Yanlin TangDepartment of Urology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.ORCID https://orcid.org/0000-0001-7942-8365
Yanjun LiuDepartment of Immunology, School of Basic Medical Science, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0003-4222-3280
Hongkai ZhuangShantou University Medical College, Shantou, China.ORCID https://orcid.org/0000-0002-4106-8736
Enyu LinDepartment of Urology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.ORCID https://orcid.org/0000-0002-5874-370X
Lu XieDepartment of Urology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Xiaoqiang FengCenter of Stem Cell and Regenerative Medicine, Gaozhou People's Hospital, Maoming, Guangdong, China.ORCID https://orcid.org/0000-0003-0672-1549
Kaiwen TianDepartment of Urology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.ORCID https://orcid.org/0000-0002-5133-4591
Jiayi ZengDepartment of Urology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.ORCID https://orcid.org/0000-0002-6575-8600
Jiumin LiuDepartment of Urology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.ORCID https://orcid.org/0000-0002-2593-0285
Yuming YuDepartment of Urology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.ORCID https://orcid.org/0000-0002-7194-6392

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer whose incidence and mortality rate are increasing. Identifying immune-related lncRNAs and constructing a model would probably provide new insights into biomarkers and immunotherapy for ccRCC and aid in the prognosis prediction.

methodsThe transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. Tumor samples were divided into the training set and the testing set. Immune-related differentially expressed lncRNAs (IDElncRNAs) were identified from the whole set. Univariate Cox regression, LASSO, and stepwise multivariate Cox regression were performed to screen out ideal prognostic IDElncRNAs (PIDElncRNAs) from the training set and develop a multi-lncRNA signature.

resultsConsequently, AC012236.1, AC078778.1, AC078950.1, AC087318.1, and AC092535.4 were screened to be significantly related to the prognosis of ccRCC patients, which were used to establish the five-lncRNA signature. Its wide diagnostic capacity was revealed in different subgroups of clinical parameters. Then AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7-year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The calibration plots showed great agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis showed the signature and each lncRNA were mainly enriched in pathways associated with regulation of immune response. Several kinds of tumor-infiltrating immune cells like regulatory T cells, T follicular helper cells, CD8

conclusionTherefore, we constructed a five-lncRNA model integrating clinical parameters to help predict the prognosis of ccRCC patients. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellComputational BiologyDatabases, GeneticDisease SusceptibilityGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunityKaplan-Meier EstimateKidney NeoplasmsMolecular Sequence AnnotationPrognosisProportional Hazards ModelsRNA, Long NoncodingTranscription FactorsBiomarkers, TumorRNA, Long NoncodingTranscription Factors

Identifiers

PMID34368371
PMCPMC8339875

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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.