Integrated analysis of bulk and single‐cell RNA‐seq data reveals cell differentiation‐related subtypes and a scoring system in bladder cancer
Bladder cancer (BLCA) exhibits notable molecular heterogeneity, influencing diverse clinical outcomes. However, the molecular subtypes associated with cell differentiation‐related genes (CDR) and their prognostic implications remain unexplored. Analysing two GEO single‐cell datasets, we identified g...
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Veröffentlicht in: | Journal of cellular and molecular medicine 2024-10, Vol.28 (19), p.e70111-n/a |
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Zusammenfassung: | Bladder cancer (BLCA) exhibits notable molecular heterogeneity, influencing diverse clinical outcomes. However, the molecular subtypes associated with cell differentiation‐related genes (CDR) and their prognostic implications remain unexplored. Analysing two GEO single‐cell datasets, we identified genes linked to cell differentiation. Utilizing these genes, we explored distinct molecular subtypes. WGCNA analysis further identified CDR‐associated genes, and the CDR score system, constructed using Lasso and Cox regression, was developed. Clinical prognosis and variations in immune‐related factors among patient groups were assessed. Core genes were selected and confirmed through in vitro experiments. Two BLCA subtypes related to cell differentiation were identified: Subtype B demonstrated a favourable prognosis, while Subtype A exhibited significant immune cell infiltration. The CDR score system of nine genes revealed a positive correlation between higher scores and a poorer prognosis. The comprehensive analysis uncovered a positive association between CDR genes and M2 macrophages and unresponsiveness to immune therapy. Functional experiments validated that ANXA5 downregulation influences tumour cell migration without affecting proliferation. Our study reveals distinct cell differentiation‐related molecular subtypes and introduces the CDR scoring system in BLCA. ANXA5 emerges as a potential therapeutic target, offering promising avenues for personalized treatment strategies. |
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ISSN: | 1582-1838 1582-4934 1582-4934 |
DOI: | 10.1111/jcmm.70111 |