Department of Oncology, Jiangdu People's Hospital Affiliated to Medical College of Yangzhou University, Yangzhou 225200, China.
Department of Pharmacy, Yizheng People's Hospital, Yizheng 211400, China.
Dis Markers. 2020 Nov 9;2020:8867019. doi: 10.1155/2020/8867019. eCollection 2020.
Autophagy is considered to be closely associated with cancer, functioning as either an anticancer or procancer mechanism depending on the cancer stage. However, the prognostic value of autophagy on papillary renal cell carcinoma (pRCC) remains unclear. In this study, our purpose was to determine the autophagy-related mRNA signature to predict the overall survival of patients with pRCC.
A total of 284 patients with pathologic confirmed pRCC in The Cancer Genome Atlas (TCGA) dataset were recruited and included. We choose patients who have smoked less than 15 years but staging 3 or 4 (including nontobacco exposure) vs. more than 15 years but staging 1 or 2. Fourteen differentially expressed mRNAs were found with fold change > 2 and value < 0.001 through package after making a pair between nontobacco exposure or less than 15 years and tobacco exposure more than 15 years by package.
Six mRNAs were identified to be significantly associated with overall survival. Then, using a risk score based on the signature of these six mRNAs, we divided the patients into low-risk and high-risk groups with significantly different OS. Further multivariate Cox regression analyses revealed that the 6-mRNA signature was independent of age, TNM stage, and tumor type. In the present study, a novel 6-mRNA signature that is useful in survival prediction in pRCC patients was developed. If validated, this mRNA signature might assist in selecting high-risk subpopulation that needs more aggressive therapeutic intervention. The risk score involved in several cancer-related pathways was identified using gene set enrichment analysis.
We initially generated a six autophagy-related genes' signature, which correlates with AJCC N stage, tumor type, and pathological stage and independently predicts OS.
自噬被认为与癌症密切相关，其作用是作为抗癌或促癌机制，具体取决于癌症阶段。然而，自噬对乳头状肾细胞癌（pRCC）的预后价值尚不清楚。在本研究中，我们的目的是确定与自噬相关的 mRNA 特征，以预测 pRCC 患者的总生存率。
共招募并纳入了来自癌症基因组图谱（TCGA）数据集的 284 名病理证实的 pRCC 患者。我们选择吸烟少于 15 年但分期为 3 或 4 期（包括非吸烟暴露）的患者与吸烟超过 15 年但分期为 1 或 2 期的患者进行配对。通过 包，我们在非吸烟暴露或吸烟少于 15 年与吸烟超过 15 年之间进行配对后，发现了 14 个差异表达的 mRNAs，其 fold change > 2 和 value < 0.001。
有 6 个 mRNAs 被确定与总生存率显著相关。然后，我们使用基于这 6 个 mRNAs 特征的风险评分，将患者分为低风险和高风险组，两组之间的 OS 有显著差异。进一步的多变量 Cox 回归分析表明，6-mRNA 特征独立于年龄、TNM 分期和肿瘤类型。在本研究中，开发了一种新的用于预测 pRCC 患者生存的 6-mRNA signature。如果得到验证，这种 mRNA 特征可能有助于选择需要更积极治疗干预的高危亚群。基因集富集分析确定了与几种癌症相关途径相关的风险评分。
我们最初生成了一个与 AJCC N 分期、肿瘤类型和病理分期相关的六个自噬相关基因的特征，并独立预测了 OS。
