Evidence map›Paper›PMID 33790572›Full record

ArticleOncoTargets and therapy2021

Global Characterization of Immune Infiltration in Clear Cell Renal Cell Carcinoma.

Yan Zheng, Yibo Wen, Huixia Cao, Yue Gu, Lei Yan, Yanliang Wang, Limeng Wang, Lina Zhang, Fengmin Shao

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

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

25 citing papers in PubMed, 25 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

9 authors at 2 institutions in 1 country.

Yan Zheng *Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China.
Yibo Wen *Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, People's Republic of China.
Huixia CaoHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China.
Yue GuHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China.
Lei YanHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China.
Yanliang WangHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China.
Limeng WangHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China.
Lina ZhangHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China.ORCID 0000-0002-7742-0252
Fengmin ShaoHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China.
Henan Provincial People's Hospital · CNFirst Affiliated Hospital of Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmunotherapy has revolutionized the treatment of clear cell renal cell carcinoma (ccRCC). However, the therapy is constrained by drug resistance. Therefore, further characterization of immune infiltration in ccRCC is needed to improve its efficacy.

methodsHere, we adopted the CIBERSORT method to analyze the level of 22 immune cells, and analyzed the correlation of immune cells and clinical parameters in ccRCC in The Cancer Genome Atlas. We used consensus clustering to cluster ccRCC and identified differently expressed genes (DEGs) between hot and cold tumors using the "Limma" package, and then performed enrichment analysis of DEGs. Finally, we constructed and validated a Cox regression model using the "survival", "glmnet", and "survivalROC" packages, implemented in R.

resultsRegulatory T cells upregulated in tumor tissue increased during tumor progression, and correlated with poor overall survival in ccRCC. Consensus clustering identified four clusters of ccRCC. To elucidate the underlying mechanisms of immune cell infiltration, we subdivided these four clusters into two major types, immune hot and cold, and identified DEGs between them. The results revealed different transcription profiles in the two tumor types, with hot tumors being enriched in immune-related signaling, whereas cold tumors were enriched in extracellular matrix remodeling and the phosphatidylinositol 3-kinase-AKT (PI3K/AKT) pathway. We further identified hub genes and prognostic-related genes from the DEGs, and constructed a Cox regression model for predicting the overall survival of patients with ccRCC. The areas under the receiver operating characteristics curve for the risk model for the training, testing, and external Zhengzhou validation cohorts were 0.834, 0.733, and 0.812, respectively. Notably, gene sets in the prediction model could also predict the overall survival of patients receiving immunotherapy.

conclusionThese findings provide a comprehensive characterization of immune infiltration in ccRCC, while the constructed model can be used effectively to predict the overall survival of ccRCC patients.

Indexed as

clear renal cell carcinomaCox risk modelimmune infiltrationtranscriptome profiling

Identifiers

PMID33790572
PMCPMC7997590
OpenAlexW3137955416

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.