Evidence map›Paper›PMID 37033357›Full record

ArticleTranslational cancer research2023

An innovative risk index based on neutrophils and macrophages can effectively predict prognosis and immunotherapy response in patients with muscle-invasive bladder cancer.

Xingxing Zhang, Anxia Zhang, Lisha Hu, Wei Xiong, Panfeng Shang

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Article in Translational cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Xingxing ZhangDepartment of Urology, Institute of Urology, Gansu Nephro-Urological Clinical Center, Key Laboratory of Urological Diseases in Gansu Province, Lanzhou University Second Hospital, Lanzhou, China.
Anxia ZhangUltrasonic Special Examination Department, Tai An TSCM Hospital, Taian, China.
Lisha HuUltrasonic Special Examination Department, Tai An TSCM Hospital, Taian, China.
Wei XiongDepartment of Urology, Institute of Urology, Gansu Nephro-Urological Clinical Center, Key Laboratory of Urological Diseases in Gansu Province, Lanzhou University Second Hospital, Lanzhou, China.
Panfeng ShangDepartment of Urology, Institute of Urology, Gansu Nephro-Urological Clinical Center, Key Laboratory of Urological Diseases in Gansu Province, Lanzhou University Second Hospital, Lanzhou, China.
Lanzhou University Second Hospital · CNLanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to establish an innovative prognostic risk index based on tumor-infiltrating immune cells (TIICs) for patients with muscle-invasive bladder cancer (MIBC). Methods: We used the CIBERSORT algorithm to calculate the abundance of immune cells in MIBC samples from the The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and stepwise regression analysis were used to identify the included immune cells. Then, we constructed the risk index based on these cells through multivariate Cox regression analysis. By the risk index formula, we obtained the risk score of each patient and divided the patients into high-risk and low-risk groups. Kaplan-Meier (K-M) curve was used for survival analysis between groups. The receiver operating characteristic (ROC) curve was used to measure the prediction accuracy of the index. We validated the performance of the index in the IMvigor210 immunotherapy cohort. In addition, we established a nomogram combining the index and clinical characteristics. Finally, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differential genes between groups. Results: The risk index we constructed consists of three variables, including M0 macrophages, M2 macrophages, and neutrophils. K-M curve showed that the risk score had good risk stratification performance. Moreover, the risk score correlates with the patient's response to chemotherapy and immunotherapy. The nomogram has good accuracy and clinical benefit. GO and KEGG enrichment analysis revealed the tumor-promoting molecular mechanism of the index. Conclusions: The risk index based on TIICs can facilitate individualized treatment of MIBC patients by predicting prognosis and immunotherapy response.

Indexed as

immunotherapymacrophagesMuscle-invasive bladder cancer (MIBC)neutrophilsrisk index

Identifiers

PMID37033357
PMCPMC10080466
OpenAlexW4327886470

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LicenceCC BY-NC-ND
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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.