Prognostic Significance and Immune Landscape of an Efferocytosis-Related Gene Signature in Bladder Cancer.

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Fuchun Zheng, Zhipeng Wang, Qianxi Dong, Sheng Li, Situ Xiong, Yuyang Yuan, Songhui Xu, Bin Fu
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引用次数: 0

Abstract

Bladder cancer poses a significant global health challenge, underscoring the imperative for precise prognostic instruments to advance patient care. Against the backdrop of efferocytosis's increasingly recognized role in cancer, this research endeavors to develop and authenticate a prognostic signature intricately linked to efferocytosis in bladder cancer. LASSO-COX regression analysis crafted an efferocytosis-related genes risk prognostic model, followed by the construction of a column chart. External validation sets confirmed the predictive accuracy of both the model and chart. Clinical, tumor microenvironment, drug sensitivity, and immunotherapy analyses were employed to comprehensively assess efferocytosis-related scores. The expression of TGFB3 key genes was validated via RT-PCR and western blotting. Further validation included Transwell, Wound healing, Colony formation, and EDU assays. We formulated and validated an efferocytosis-related genes risk model in bladder cancer, comprising 13 core genes. The risk model demonstrated autonomous prognostic significance in both univariate and multivariate Cox analyses. Following the multivariate analysis, we devised a nomogram. Moreover, by utilizing individual risk scores derived from this risk model, we successfully stratified patients into two discernible risk cohorts, unveiling noteworthy variances in immune infiltration profiles and responsiveness to immunotherapy. Notably, the model's key gene TGFB3 was validated through comprehensive experimental investigations, including Transwell assays for migration and invasion and Wound healing assays for motility on the T24 and BIU cell lines. This study has furnished innovative perspectives on an efferocytosis-related prognostic signature, elucidating the prognosis and immune milieu intricacies in patients with bladder cancer.

膀胱癌中与胞吐有关的基因特征的预后意义和免疫格局
膀胱癌对全球健康构成了重大挑战,因此需要精确的预后工具来促进对患者的治疗。在流出细胞增多在癌症中的作用日益得到认可的背景下,本研究致力于开发和鉴定与膀胱癌流出细胞增多密切相关的预后特征。LASSO-COX回归分析建立了一个与排出细胞相关的基因风险预后模型,然后构建了一个柱状图。外部验证集证实了模型和图表的预测准确性。通过临床、肿瘤微环境、药物敏感性和免疫疗法分析,全面评估了流出相关评分。TGFB3关键基因的表达通过RT-PCR和Western印迹进行了验证。进一步的验证包括 Transwell、伤口愈合、菌落形成和 EDU 试验。我们制定并验证了膀胱癌的流出细胞相关基因风险模型,其中包括 13 个核心基因。该风险模型在单变量和多变量 Cox 分析中均显示出自主预后意义。在多变量分析之后,我们设计了一个提名图。此外,通过利用从该风险模型中得出的个体风险评分,我们成功地将患者分成了两个明显的风险群组,揭示了免疫浸润特征和对免疫疗法反应性方面值得注意的差异。值得注意的是,该模型的关键基因 TGFB3 通过全面的实验研究得到了验证,包括 T24 和 BIU 细胞系迁移和侵袭的 Transwell 试验以及运动性的伤口愈合试验。这项研究为流出细胞相关预后特征提供了创新视角,阐明了膀胱癌患者的预后和免疫环境的复杂性。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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