Evidence map›Paper›PMID 38212482›Full record

ArticleBritish journal of cancer2024

Integrative score based on CDK6, PD-L1 and TMB predicts response to platinum-based chemotherapy and PD-1/PD-L1 blockade in muscle-invasive bladder cancer.

Xiaohe Su, Kaifeng Jin, Qiji Guo, Ziyue Xu, Zhaopei Liu, Han Zeng, Yiwei Wang, Yu Zhu, Le Xu, Zewei Wang and 2 more

Open access · hybridAbstract read
In one paragraph

Article in British journal of cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
4.0field-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

8 citing papers in PubMed, 7 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

12 authors at 4 institutions in 1 country.

Xiaohe Su *NHC Key Laboratory of Glycoconjugate Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China.
Kaifeng Jin *NHC Key Laboratory of Glycoconjugate Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China.ORCID 0000-0001-9867-6516
Qiji GuoNHC Key Laboratory of Glycoconjugate Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China.
Ziyue XuNHC Key Laboratory of Glycoconjugate Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China.
Zhaopei LiuNHC Key Laboratory of Glycoconjugate Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China.ORCID 0000-0002-5288-5037
Han ZengNHC Key Laboratory of Glycoconjugate Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China.ORCID 0000-0001-6486-2038
Yiwei WangDepartment of Urology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yu ZhuDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID 0000-0002-3332-5202
Le XuDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zewei WangDepartment of Urology, Zhongshan Hospital, Fudan University, Shanghai, China. zwwang12@fudan.edu.cn.
Yuan ChangDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China. yuanchang@fudan.edu.cn.ORCID 0000-0003-2042-9317
Jiejie XuNHC Key Laboratory of Glycoconjugate Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China. jjxufdu@fudan.edu.cn.ORCID 0000-0001-7431-9063
Fudan University · CNSun Yat-sen University · CNFudan University Shanghai Cancer Center · CNShanghai Jiao Tong University · CN

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82002670,82103408,82272786,82272930,82373276
6 · The paper itself

Abstract

backgroundCyclin-dependent kinase 6 (CDK6) was proved to be an important regulator in the progression of cell cycle and has been a promising therapeutic target in cancer treatment. However, the clinical significance of CDK6 in muscle-invasive bladder cancer (MIBC) remains obscure. Herein, we attempt to explore the clinical relevance of CDK6 and assess the feasibility of the integrative model to predict immune checkpoint blockade (ICB) response.

methodsThis study enrolled 933 patients with muscle-invasive bladder cancer (MIBC) from Zhongshan Hospital (ZSHS), The Cancer Genome Atlas (TCGA), Chemo, IMvigor210 and UC-GENOME cohorts. Kaplan-Meier survival and Cox regression analyses were performed to assess clinical outcomes based on CDK6 expression.

resultsHigh CDK6 expression conferred poor prognosis and superior response to platinum-based chemotherapy but inferior response to ICB in MIBC. Furthermore, the integrative model named response score based on CDK6, PD-L1 and TMB could better predict the response to ICB and chemotherapy. Patients with higher response scores were characterised by inflamed immune microenvironment and genomic instability.

conclusionsCDK6 expression was correlated with prognosis and therapy response in MIBC. Integration of CDK6, PD-L1 and TMB could better identify patients who were most likely to benefit from ICB and chemotherapy.

Indexed as

Immune Checkpoint InhibitorsUrinary Bladder NeoplasmsB7-H1 AntigenCyclin-Dependent Kinase 6HumansMusclesPlatinumProgrammed Cell Death 1 ReceptorTumor MicroenvironmentB7-H1 AntigenCDK6 protein, humanCyclin-Dependent Kinase 6Immune Checkpoint InhibitorsPlatinumProgrammed Cell Death 1 Receptor

Identifiers

PMID38212482
PMCPMC10912081
OpenAlexW4390741035

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.