TP53 缺失通过上调 NF-κB-IFN-β-MHC-Ia 信号促进骨肉瘤对 NK 细胞的抵抗
TP53 Loss Elevates NF-κB-IFN-β-MHC-Ia Signaling to Promote NK Cell Resistance in Osteosarcoma.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Identification of a Novel Mesenchymal Stem Cell-Related Signature for Predicting the Prognosis and Therapeutic Responses of Bladder Cancer.
Identification of a Novel Mesenchymal Stem Cell-Related Signature for Predicting the Prognosis and Therapeutic Responses of Bladder Cancer.
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间充质干细胞(MSC)已被发现具有独特的迁移模式,可趋向多种癌症的肿瘤部位,并在癌症进展、治疗耐药和免疫抑制中发挥重要作用。本研究旨在建立基于MSC相关标志物的预后模型,以有效预测膀胱癌(BC)患者的临床结局和治疗应答。
从癌症基因组图谱尿路上皮膀胱癌(TCGA-BLCA)及GSE31684数据库中提取临床和转录组数据。系统量化MSC丰度及基质指数,并通过加权基因共表达网络分析筛选与基质MSC相关的基因。随后结合单变量和最小绝对收缩与选择算子(LASSO)Cox回归模型,建立MSC相关综合风险特征。研究还利用分子对接筛选靶向MSC相关基因的药物。
MSC预后模型包括5个关键基因:ZNF165、基质重塑相关蛋白7(MXRA7)、CEMIP、ADP-核糖基化因子样4C(ARL4C)和脑内皮细胞黏附分子(CERCAM)。依据MSC风险评分中位数,将BC患者分为不同风险组。MSC高风险组与不良预后相关。与高风险组相比,MSC低风险患者对免疫治疗应答更好。高风险组对若干化疗药物(包括吉西他滨、长春新碱、紫杉醇、吉非替尼和索拉非尼)更敏感;相反,低MSC评分患者对顺铂反应更好。分子对接结果显示,山奈酚与ZNF165、槲皮素与MXRA7、mairin与CEMIP、limonin diosphenol与ARL4C均具有良好对接效果。
由5个基因构成的MSC预后模型可有效预测临床结局以及对化疗和免疫治疗的应答。ZNF165、MXRA7、CEMIP、ARL4C和CERCAM是值得进一步探索的抗MSC治疗候选靶点,可为膀胱癌个体化治疗提供新思路。
Background: Mesenchymal stem cells (MSCs) have been identified to have a unique migratory pattern toward tumor sites across diverse cancer types, playing a crucial role in cancer progression, treatment resistance, and immunosuppression.
This study aims to formulate a prognostic model focused on MSC-associated markers to efficiently predict the clinical outcomes and responses to therapy in individuals with bladder cancer (BC). Methods: Clinical and transcriptome profiling data were extracted from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) and GSE31684 databases. Systematic quantification of MSC prevalences and stromal indices was undertaken, culminating in the discernment of genes correlated with stromal MSCs following a thorough application of weighted gene coexpression network analysis techniques. Subsequently, an exhaustive risk signature pertinent to MSC was formulated by amalgamating methods from univariate and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression models. Drugs targeting genes associated with MSCs were screened using molecular docking. Results: The prognostic model for MSC incorporated five critical genes: ZNF165, matrix remodeling-associated 7 (MXRA7), CEMIP, ADP-ribosylation factor-like 4C (ARL4C), and cerebral endothelial cell adhesion molecule (CERCAM). In the case of BC patients, stratification was performed into discrete risk categories, utilizing the median MSC risk score as a criterion.
It was striking that those classified within the high-MSC-risk bracket demonstrated correlations with unfavorable prognostic implications. Enhanced responsiveness to immunotherapy in low-MSC-risk patients was delineated compared to their high-MSC-risk counterparts. A heightened receptivity was noted toward particular chemotherapy drugs, encompassing gemcitabine, vincristine, paclitaxel, gefitinib, and sorafenib, within this high-risk group. Conversely, a superior reaction to cisplatin was distinctly evident among those marked by low MSC scores.
The results of molecular docking demonstrated that kaempferol exhibited favorable docking with ZNF165, quercetin exhibited favorable docking with MXRA7, mairin exhibited favorable docking with CEMIP, and limonin diosphenol exhibited favorable docking with ARL4C.
Conclusions: The five-gene MSC prognostic model demonstrates substantial efficacy in prognosticating clinical outcomes and gauging responsiveness to chemotherapy and immunotherapy regimens. The genes ZNF165, MXRA7, CEMIP, ARL4C, and CERCAM are underscored as promising candidates warranting further exploration for anti-MSC therapeutic strategies, thereby offering novel insights for personalized treatment approaches in BC.
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