Evidence map›Paper›PMID 35812372›Full record

ArticleFrontiers in immunology2022

Decoding the Immune Microenvironment of Clear Cell Renal Cell Carcinoma by Single-Cell Profiling to Aid Immunotherapy.

Jie Liu, Jiangfan Xu, Tong Zhang, Kailong Xu, Peihua Bao, Zhibo Zhang, Kaiwen Xue, Ruyi He, Lixin Ma, Yang Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

10 citing papers in PubMed, 14 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

10 authors at 4 institutions in 1 country.

Jie LiuState Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China.
Jiangfan XuState Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China.
Tong ZhangState Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China.
Kailong XuState Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China.
Peihua BaoCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
Zhibo ZhangDepartment of Cardiothoracic Surgery, The 78th Group Army Hospital of Chinese People's Liberation Army, Mudanjiang, China.
Kaiwen XueCollege of Chemistry and Chemical Engineering, Hubei University, Wuhan, China.
Ruyi HeSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Lixin MaState Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China.
Yang WangState Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China.
Hubei University · CNChinese People's Liberation Army · CNHarbin Engineering University · CNWuhan Polytechnic University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer, and it is the major cause of kidney cancer death. Understanding tumor immune microenvironments (TMEs) is critical in cancer immunotherapies. Here, we studied the immune characterization at single-cell resolution by integrating public data of ccRCC across different tissue types, and comparing the transcriptome features and tumor TME differences in tumors, normal adjacent tissue, and peripheral blood. A total of 16 different types of cell components of ccRCC were identified. We revealed that there is an overall increase in T-cell and myeloid populations in tumor-infiltrated immune cells compared to normal renal tissue, and the B-cell population in the tumor showed a sharp decrease, which indicates that the cells in tumor tissue undergo strong immune stress. In addition, the cell-cell communication analysis revealed specific or conserved signals in different tissue types, which may aid to uncover the distinct immune response. By combining and analyzing publicly available ccRCC bulk RNA-seq datasets, 10 genes were identified as marker genes in specific cell types, which were significantly associated with poor prognosis. Of note, UBE2C, which may be a good indicator of tumor proliferation, is positively associated with reductions in overall survival and highly associated with tumor grade. Our integrated analysis provides single-cell transcriptomic profiling of ccRCC and their TME, and it unmasked new correlations between gene expression, survival outcomes, and immune cell-type components, enabling us to dissect the dynamic variables in the tumor development process. This resource provides deeper insight into the transcriptome features and immune response of ccRCC and will be helpful in kidney cancer immunotherapy.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsHumansImmunotherapyPrognosisTumor Microenvironmentbiomarkerclear cell renal cell carcinomaimmunotherapysingle celltumor microenvironment

Identifiers

PMID35812372
PMCPMC9263726
OpenAlexW4283454781

What OpenQuestion holds

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LicenceCC BY
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.