Table 9_Identification of anoikis-related molecular patterns and the novel risk model to predict prognosis, tumor microenvironment infiltration and immunotherapy response in bladder cancer.docx

BackgroundAnoikis, a unique form of cell death, serves as a vital part of the organism's defense by preventing shedding cells from re-attaching to the incorrect positions, and plays pivotal role in cancer metastasis. Nonetheless, the specific mechanisms among anoikis, the clinical prognosis and tumor microenvironment (TME) of bladder cancer (BLCA) are insufficiently understood.
MethodBLCA patients were classified into different anoikis subtypes based on the expression of candidate anoikis-related genes (ARGs), and differences in the clinicopathological features, TME, immune cell infiltration, and immune checkpoints between two anoikis subtypes were analyzed. Next, patients in the TCGA cohort were randomized into the train and test groups in a 1:1 ratio. Subsequently, the anoikis-related model was constructed to predict the prognosis via utilizing the univariate Cox, LASSO and multivariate Cox analyses, and validated internally and externally. Moreover, the relationships between the risk score and clinicopathologic features, immune cell infiltration, immunotherapy response, and antitumor drug sensitivity were also analyzed. In addition, representative genes were evaluated using immunohistochemistry in clinical specimens, and in BLCA cell lines, functional experiments were performed to determine the biological behavior of hub gene PLOD1.
ResultTwo definite anoikis subgroups were identified. Compared to ARGcluster A, patients assigned to ARGcluster B were characterized by an immunosuppressive microenvironment and worse prognosis. Then, the anoikis-related model, including PLOD1, EHBP1, and CSPG4, was constructed, and BLCA patients in the low-risk group were characterized by a better prognosis. Next, the accurate nomogram was built to improve the clinical applicability by combining the age, tumor stage and risk Score. Moreover, immune infiltration and clinical features differed significantly between high- and low-risk groups. We also found that the low-risk group exhibited a lower tumor immune dysfunction and exclusion score, a higher immunophenoscore (IPS), had more sensitivity to immunotherapy. Eventually, the expression levels of three genes were verified by our experiment, and knockdown of PLOD1 could inhibit invasion and migration abilities in BLCA cell lines.
ConclusionThese results demonstrated a new direction in precision therapy for BLCA, and indicated that the ARGs might be helpful to in predicting prognosis and as therapeutic targets in BLCA.

背景
失巢凋亡（Anoikis）是一类特殊的细胞死亡形式，可通过防止脱落细胞异常黏附于非适宜位置，成为机体防御机制的重要组成部分，同时在肿瘤转移过程中发挥关键作用。然而，膀胱癌（BLCA）中失巢凋亡、临床预后与肿瘤微环境（TME）三者间的具体调控机制尚未完全阐明。
方法
本研究基于候选失巢凋亡相关基因（ARGs）的表达水平，将膀胱癌患者划分为不同的失巢凋亡亚型，并分析了两种亚型在临床病理特征、肿瘤微环境、免疫细胞浸润及免疫检查点方面的差异。随后，将癌症基因组图谱（The Cancer Genome Atlas, TCGA）队列中的患者以1:1的比例随机分为训练集与测试集。通过单变量Cox分析、最小绝对收缩和选择算子（Least Absolute Shrinkage and Selection Operator, LASSO）回归及多变量Cox分析，构建失巢凋亡相关预后预测模型，并分别进行内部与外部验证。此外，本研究还分析了风险评分与临床病理特征、免疫细胞浸润、免疫治疗应答及抗肿瘤药物敏感性之间的关联。同时，通过免疫组化技术对临床标本中的代表性基因进行表达验证，并在膀胱癌细胞系中开展功能实验，以明确核心基因PLOD1的生物学行为。
结果
本研究成功鉴定出两个明确的失巢凋亡亚型。与ARGcluster A组相比，ARGcluster B组患者呈现免疫抑制性肿瘤微环境且预后更差。随后构建了包含PLOD1、EHBP1及CSPG4的失巢凋亡相关预后模型，其中低风险组膀胱癌患者预后更佳。进一步结合患者年龄、肿瘤分期与风险评分，构建了精准列线图以提升模型的临床适用性。高低风险组的免疫浸润状态与临床特征存在显著差异。本研究还发现，低风险组的肿瘤免疫功能异常和排斥（Tumor Immune Dysfunction and Exclusion, TIDE）评分更低，免疫评分（immunophenoscore, IPS）更高，对免疫治疗的敏感性更强。最终，本团队的实验验证了三个目标基因的表达水平，且敲低PLOD1可显著抑制膀胱癌细胞系的侵袭与迁移能力。
结论
本研究结果为膀胱癌的精准治疗提供了全新方向，同时提示失巢凋亡相关基因有望作为膀胱癌预后预测的生物标志物及潜在治疗靶点。