UNASSIGNED: Gene expression and miRNA expression, using RNA sequencing (RNA-seq), and SpliceSeq data were downloaded from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to construct predictive models. Kaplan-Meier survival analyses were used to evaluate patients\' prognosis. Single-sample gene set enrichment analysis (ssGSEA) conducted via the R package \"GSEAbase\" was used to evaluate the immune-related characteristics. Immunohistochemistry was used to examine protein expression. The Connectivity Map (CMap) database was used to screen for potential drugs. The 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT) assay was used to determine and calculate the half-maximal inhibitory concentration (IC50) of the drugs, sulforaphane and parthenolide.
UNASSIGNED: In this study, bioinformatics were used to identify mRNAs, miRNAs, and AS events related to response to cisplatin and to establish an integrated prognostic signature for 70 patients with LUSC and cisplatin resistance. The prognostic signature served as an independent prognostic factor with high accuracy [hazard ratio (HR) =2.346, 95% confidence interval (CI): 1.568-3.510; P<0.001], yielding an area under the curve (AUC) of 0.825, 0.829, and 0.877 for 1-, 3-, and 5-year survival, respectively. It also demonstrated high predictive performance in this cohort of patients with LUSC, with an AUC of 0.734, 0.767, and 0.776 for 1-, 3-, and 5-year survival, respectively. This integrated signature was also found to be an independent indicator among conventional clinical features (HR =2.288, 95% CI: 1.547-3.383; P<0.001). In addition, we analyzed the correlation of the signature with immune infiltration and identified several small-molecule drugs that had the potential to improve the survival of patients with LUSC.
UNASSIGNED: This study provides a framework for the mRNA-, miRNA-, and AS-based evaluation of cisplatin response and several potential therapeutic drugs for targeting cisplatin resistance in LUSC. These findings may serve as a theoretical basis for the clinical alleviation of cisplatin resistance and thus help to improve treatment responses to chemotherapy in patients with LUSC.
■基因表达和miRNA表达,使用RNA测序(RNA-seq),和SpliceSeq数据从癌症基因组图谱(TCGA)数据库下载。采用最小绝对收缩和选择算子(LASSO)Cox回归分析构建预测模型。Kaplan-Meier生存分析用于评估患者的预后。通过R包“GSEAbase”进行的单样品基因组富集分析(ssGSEA)用于评估免疫相关特征。使用免疫组织化学检查蛋白质表达。ConnectivityMap(CMap)数据库用于筛选潜在药物。使用3-(4,5)-二甲基硫代偶氮(-z-y1)-3,5-二苯基四唑啉(MTT)测定法来确定和计算药物的半数最大抑制浓度(IC50),萝卜硫素和小白菊内酯。
■在这项研究中,生物信息学用于鉴定mRNA,miRNA,和AS事件与顺铂反应相关,并为70例LUSC和顺铂耐药患者建立综合预后特征。预后特征作为独立的预后因素,具有很高的准确性[风险比(HR)=2.346,95%置信区间(CI):1.568-3.510;P<0.001],对于1-,产生0.825、0.829和0.877的曲线下面积(AUC)3-,5年生存率,分别。它还在这一LUSC患者队列中显示出高预测性能,1-的AUC为0.734、0.767和0.776,3-,5年生存率,分别。该整合特征也被发现是常规临床特征中的独立指标(HR=2.288,95%CI:1.547-3.383;P<0.001)。此外,我们分析了该标记与免疫浸润的相关性,并确定了几种有可能改善LUSC患者生存率的小分子药物.
■这项研究为mRNA-,miRNA-,以及基于AS的顺铂反应评估和靶向LUSC顺铂耐药的几种潜在治疗药物。这些发现可以作为临床缓解顺铂耐药性的理论基础,从而有助于改善LUSC患者对化疗的治疗反应。