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Abstract：
Prostate cancer (PCa) is the second disease threatening men\'s health, and anti-androgen therapy (AAT) is a primary approach for treating this condition. Increasing evidence suggests that long non-coding RNAs (lncRNAs) play crucial roles in the development of PCa and the process of AAT resistance. The objective of this study is to utilize bioinformatics methods to excavate lncRNAs association with AAT resistance and investigate their biological functions.
AAT resistance-related risk score model (ARR-RSM) was established by multivariate Cox analysis. Paired clinical tissue samples of 36 PCa patients and 42 blood samples from patients with PSA over 4 ng/ml were collected to verify the ARR-RSM. In vitro, RT-qPCR, CCK-8 and clone formation assays were displayed to verify the expression and function of AL354989.1 and AC007405.2.
Pearson correlation analysis identified 996 lncRNAs were associated with AAT resistance (ARR-LncRs). ARR-RSM was established using multivariate Cox regression analysis, and PCa patients were divided into high-risk and low-risk groups. High-risk patients showed increased expression of AL354989.1 and AC007405.2 had poorer prognoses. The high-risk score correlated with advanced T-stage and N-stage. The AUC of ARR-RSM outperformed tPSA in diagnosing PCa. Silencing of AC007405.2 and AL354989.1 inhibited PCa cells proliferation and AAT resistance.
In this study, we have discovered the clinical significance of AC007405.2 and AL354989.1 in predicting the prognosis and diagnosing PCa patients. Furthermore, we have confirmed their correlation with various clinical features. These findings provide potential targets for PCa treatment and a novel diagnostic and predictive indicator for precise PCa diagnosis.
AAT resistance-related risk score model (ARR-RSM) was established by multivariate Cox analysis. Paired clinical tissue samples of 36 PCa patients and 42 blood samples from patients with PSA over 4 ng/ml were collected to verify the ARR-RSM. In vitro, RT-qPCR, CCK-8 and clone formation assays were displayed to verify the expression and function of AL354989.1 and AC007405.2.
Pearson correlation analysis identified 996 lncRNAs were associated with AAT resistance (ARR-LncRs). ARR-RSM was established using multivariate Cox regression analysis, and PCa patients were divided into high-risk and low-risk groups. High-risk patients showed increased expression of AL354989.1 and AC007405.2 had poorer prognoses. The high-risk score correlated with advanced T-stage and N-stage. The AUC of ARR-RSM outperformed tPSA in diagnosing PCa. Silencing of AC007405.2 and AL354989.1 inhibited PCa cells proliferation and AAT resistance.
In this study, we have discovered the clinical significance of AC007405.2 and AL354989.1 in predicting the prognosis and diagnosing PCa patients. Furthermore, we have confirmed their correlation with various clinical features. These findings provide potential targets for PCa treatment and a novel diagnostic and predictive indicator for precise PCa diagnosis.
摘要：
目的：前列腺癌（PCa）是威胁男性健康的第二大疾病，抗雄激素治疗（AAT）是治疗这种疾病的主要方法。越来越多的证据表明，长链非编码RNA（lncRNA）在PCa的发展和AAT抗性过程中起着至关重要的作用。本研究的目的是利用生物信息学方法挖掘lncRNAs与AAT抗性的关联并研究其生物学功能。
方法：采用多因素Cox分析建立AAT抵抗相关风险评分模型(ARR-RSM)。收集36名PCa患者的配对临床组织样品和42名PSA超过4ng/ml的患者的血液样品以验证ARR-RSM。体外，RT-qPCR,展示CCK-8和克隆形成试验以验证AL354989.1和AC007405.2的表达和功能。
结果：Pearson相关性分析鉴定出996个lncRNAs与AAT抗性(ARR-LncRs)相关。使用多变量Cox回归分析建立ARR-RSM，将PCa患者分为高危组和低危组。高危患者显示AL354989.1表达增加，AC007405.2预后较差。高风险评分与晚期T期和N期相关。ARR-RSM的AUC优于tPSA诊断PCa。沉默AC007405.2和AL354989.1抑制PCa细胞增殖和AAT抗性。
结论：在这项研究中，我们发现AC007405.2和AL354989.1在预测PCa患者预后和诊断中的临床意义。此外，我们已经证实了它们与各种临床特征的相关性.这些发现为PCa治疗提供了潜在的靶标，并为精确的PCa诊断提供了新的诊断和预测指标。
方法：采用多因素Cox分析建立AAT抵抗相关风险评分模型(ARR-RSM)。收集36名PCa患者的配对临床组织样品和42名PSA超过4ng/ml的患者的血液样品以验证ARR-RSM。体外，RT-qPCR,展示CCK-8和克隆形成试验以验证AL354989.1和AC007405.2的表达和功能。
结果：Pearson相关性分析鉴定出996个lncRNAs与AAT抗性(ARR-LncRs)相关。使用多变量Cox回归分析建立ARR-RSM，将PCa患者分为高危组和低危组。高危患者显示AL354989.1表达增加，AC007405.2预后较差。高风险评分与晚期T期和N期相关。ARR-RSM的AUC优于tPSA诊断PCa。沉默AC007405.2和AL354989.1抑制PCa细胞增殖和AAT抗性。
结论：在这项研究中，我们发现AC007405.2和AL354989.1在预测PCa患者预后和诊断中的临床意义。此外，我们已经证实了它们与各种临床特征的相关性.这些发现为PCa治疗提供了潜在的靶标，并为精确的PCa诊断提供了新的诊断和预测指标。
