A prognostic signature based on seven T-cell-related cell clustering genes in bladder urothelial carcinoma
Abstract: Bladder urothelial carcinoma (BLCA) is one of the most common cancer-related deaths in the world, along with high mortality. Due to the difficult detection of early symptoms, the treatment for this disease is still dissatisfactory. Thus, the current research hotspot is beginning to focus on the immune microenvironment in this disease, aiming to provide guidance for diagnosis and treatment. In this study, the single-cell RNA sequencing data downloaded from the gene expression omnibus database was used to classify the immune cells of BLCA. And the final seven T-cell-related cell clustering genes associated with BLCA prognosis (HSPA2, A2M, JUN, PDGFRB, GBP2, LGALS1, and GAS6) were screened out, and then used for constructing the prognostic model against BLCA based on the Cox and LASSO regression analysis. Satisfactorily, the model could efficiently evaluate the overall survival of BLCA and had the potential to be applied for the clinic treatment. Moreover, we also revealed that the difference in immune infiltration levels and gene mutation might account for the diverse prognosis in BLCA patients. In a word, our findings provided a novel insight for designing efficient immunotherapies for BLCA.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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A prognostic signature based on seven T-cell-related cell clustering genes in bladder urothelial carcinoma ; volume:18 ; number:1 ; year:2023 ; extent:11
Open medicine ; 18, Heft 1 (2023) (gesamt 11)
- Urheber
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Yang, Jie
Zhou, Fenghai
Yang, Xia
Ma, Pengcheng
Ma, Xiaoling
- DOI
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10.1515/med-2023-0773
- URN
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urn:nbn:de:101:1-2023091914024473212926
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 14.08.2025, 10:44 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Yang, Jie
- Zhou, Fenghai
- Yang, Xia
- Ma, Pengcheng
- Ma, Xiaoling
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