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Background <p>Bladder cancer (BLCA) is notably associated with advanced age, characterized by its high incidence and mortality among the elderly. Despite promising advancements in models that amalgamate molecular subtypes with treatment and prognostic outcomes, the considerable heterogeneity in BLCA poses challenges to their universal applicability. Consequently, there is an urgent need to develop a new molecular subtyping system focusing on a critical clinical feature of BLCA: senescence.</p> Methods <p>Utilizing unsupervised clustering on the Cancer Genome Atlas Program (TCGA)-BLCA cohort, we crafted a senescence-associated molecular classification and precision quantification system (Senescore). This method underwent systematic validation against established molecular subtypes, treatment strategies, clinical outcomes, the immune tumor microenvironment (TME), relevance to immune checkpoints, and identification of potential therapeutic targets.</p> Results <p>External validations were conducted using the Xiangya cohort, IMvigor210 cohort, and meta-cohort, with multiplex immunofluorescence confirming the correlation between Senescore, immune infiltration, and cellular senescence. Notably, patients categorized within higher Senescore group were predisposed to the basal subtype, showcased augmented immune infiltration, harbored elevated driver gene mutations, and exhibited increased senescence-associated secretory phenotype (SASP) factors expression in the transcriptome. Despite poorer prognoses, these patients revealed greater responsiveness to immunotherapy and neoadjuvant chemotherapy.</p> Conclusions <p>Our molecular subtyping and Senescore, informed by age-related clinical features, accurately depict age-associated biological traits and its clinical application potential in BLCA. Moreover, this personalized assessment framework is poised to identify senolysis targets unique to BLCA, furthering the integration of aging research into therapeutic strategies.</p>

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Senescence-specific molecular subtypes stratify the hallmarks of the tumor microenvironment and guide precision medicine in bladder cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月19日

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  • Luzhe Yan,
  • Haisu Liang,
  • Tiezheng Qi,
  • Dingshan Deng,
  • Jinhui Liu,
  • Yunbo He,
  • Jinbo Chen,
  • Benyi Fan,
  • Yiyan Yao,
  • Kun Wang,
  • Xiongbing Zu,
  • Minfeng Chen,
  • Yuanqing Dai,
  • Jiao Hu

摘要

Background

Bladder cancer (BLCA) is notably associated with advanced age, characterized by its high incidence and mortality among the elderly. Despite promising advancements in models that amalgamate molecular subtypes with treatment and prognostic outcomes, the considerable heterogeneity in BLCA poses challenges to their universal applicability. Consequently, there is an urgent need to develop a new molecular subtyping system focusing on a critical clinical feature of BLCA: senescence.

Methods

Utilizing unsupervised clustering on the Cancer Genome Atlas Program (TCGA)-BLCA cohort, we crafted a senescence-associated molecular classification and precision quantification system (Senescore). This method underwent systematic validation against established molecular subtypes, treatment strategies, clinical outcomes, the immune tumor microenvironment (TME), relevance to immune checkpoints, and identification of potential therapeutic targets.

Results

External validations were conducted using the Xiangya cohort, IMvigor210 cohort, and meta-cohort, with multiplex immunofluorescence confirming the correlation between Senescore, immune infiltration, and cellular senescence. Notably, patients categorized within higher Senescore group were predisposed to the basal subtype, showcased augmented immune infiltration, harbored elevated driver gene mutations, and exhibited increased senescence-associated secretory phenotype (SASP) factors expression in the transcriptome. Despite poorer prognoses, these patients revealed greater responsiveness to immunotherapy and neoadjuvant chemotherapy.

Conclusions

Our molecular subtyping and Senescore, informed by age-related clinical features, accurately depict age-associated biological traits and its clinical application potential in BLCA. Moreover, this personalized assessment framework is poised to identify senolysis targets unique to BLCA, furthering the integration of aging research into therapeutic strategies.