Evidence map›Paper›PMID 35720278›Full record

ArticleFrontiers in immunology2022

Comprehensive Analysis of Senescence Characteristics Defines a Novel Prognostic Signature to Guide Personalized Treatment for Clear Cell Renal Cell Carcinoma.

Peng Zhou, Zheng Liu, Henglong Hu, Yuchao Lu, Jun Xiao, Yanan Wang, Yang Xun, Qidong Xia, Chenqian Liu, Jia Hu and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
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 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

17 citing papers in PubMed, 24 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

11 authors at 2 institutions in 1 country.

Peng ZhouDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zheng LiuDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Henglong HuDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yuchao LuDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jun XiaoDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yanan WangDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yang XunDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Qidong XiaDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chenqian LiuDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jia HuDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Shaogang WangDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Huazhong University of Science and Technology · CNTongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accumulating evidence has suggested the impact of senescence on tumor progression, but no report has yet described how senescence shapes the tumor microenvironment of clear cell renal cell carcinoma (ccRCC). The objective of this study was to delineate the senescence features of ccRCC and its role in shaping the tumor microenvironment through a comprehensive analysis of multiple datasets, including 2,072 ccRCC samples. Unsupervised consensus clustering identified three senescence subtypes, and we found that the senescence-activated subtype survived the worst, even in the condition of targeted therapy and immunotherapy. The activated senescence program was correlated to increased genomic instability, unbalanced PBMR1/BAP1 mutations, elevated immune cell infiltration, and enhanced immune inhibitory factors (cancer-associated fibroblasts, immune suppression, immune exclusion, and immune exhaustion signaling). A senescence score based on nine senescence-related genes (i.e., P3H1, PROX1, HJURP, HK3, CDKN1A, AR, VENTX, MAGOHB, and MAP2K6) was identified by adaptive lasso regression and showed robust prognostic predictive power in development and external validation cohorts. Notably, we found that the senescence score was correlated to immune suppression, and the low-score subgroup was predicted to respond to anti-PD-1 therapy, whereas the high-score subgroup was predicted to respond to Sunitinib/Everolimus treatment. Collectively, senescence acted as an active cancer hallmark of ccRCC, shaped the immune microenvironment, and profoundly affected tumor prognosis and drug treatment response.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsHumansPrecision MedicinePrognosisSunitinibTumor MicroenvironmentSunitinibcellular senescenceimmune checkpoint blockadeprognostic signaturetargeted therapytumor microenvironment

Identifiers

PMID35720278
PMCPMC9201070
OpenAlexW4281756487

What OpenQuestion holds

Textmetadata
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.