Identification of novel potential homologous repair deficiency-associated genes in pancreatic adenocarcinoma via WGCNA coexpression network analysis and machine learning.

IF 3.4 3区 生物学 Q3 CELL BIOLOGY
Cell Cycle Pub Date : 2023-11-01 Epub Date: 2024-01-18 DOI:10.1080/15384101.2023.2293594
Chun Liu, Jingyun Fang, Weibiao Kang, Yang Yang, Changjun Yu, Hao Chen, Yongwei Zhang, Huan Ouyang
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引用次数: 0

Abstract

Homologous repair deficiency (HRD) impedes double-strand break repair, which is a common driver of carcinogenesis. Positive HRD status can be used as theranostic markers of response to platinum- and PARP inhibitor-based chemotherapies. Here, we aimed to fully investigate the therapeutic and prognostic potential of HRD in pancreatic adenocarcinoma (PAAD) and identify effective biomarkers related to HRD using comprehensive bioinformatics analysis. The HRD score was defined as the unweighted sum of the LOH, TAI, and LST scores, and it was obtained based on the previous literature. To characterize PAAD immune infiltration subtypes, the "ConsensusClusterPlus" package in R was used to conduct unsupervised clustering. A WGCNA was conducted to elucidate the gene coexpression modules and hub genes in the HRD-related gene module of PAAD. The functional enrichment study was performed using Metascape. LASSO analysis was performed using the "glmnet" package in R, while the random forest algorithm was realized using the "randomForest" package in R. The prognostic variables were evaluated using univariate Cox analysis. The prognostic risk model was built using the LASSO approach. ROC curve and KM survival analyses were performed to assess the prognostic potential of the risk model. The half-maximal inhibitory concentration (IC50) of the PARP inhibitors was estimated using the "pRRophetic" package in R and the Genomics of Drug Sensitivity in Cancer database. The "rms" package in R was used to create the nomogram. A high HRD score indicated a poor prognosis and an advanced clinical process in PAAD patients. PAAD tumors with high HRD levels revealed significant T helper lymphocyte depletion, upregulated levels of cancer stem cells, and increased sensitivity to rucaparib, Olaparib, and veliparib. Using WGCNA, 11 coexpression modules were obtained. The red module and 122 hub genes were identified as the most correlated with HRD in PAAD. Functional enrichment analysis revealed that the 122 hub genes were mainly concentrated in cell cycle pathways. One novel HRD-related gene signature consisting of CKS1B, HJURP, and TPX2 were screened via LASSO analysis and a random forest algorithm, and they were validated using independent validation sets. No direct association between HRD and CKS1B, HJURP, or TPX2 has not been reported in the literature so far. Thus, these findings indicated that CKS1B, HJURP, and TPX2 have potential as diagnostic and prognostic biomarkers for PAAD. We constructed a novel HRD-related prognostic model that provides new insights into PAAD prognosis and immunotherapy. Based on bioinformatics analysis, we comprehensively explored the therapeutic and prognostic potential of HRD in PAAD. One novel HRD-related gene signature consisting of CKS1B, HJURP, and TPX2 were identified through the combination of WGCNA, LASSO analysis and a random forest algorithm. A novel HRD-related risk model that can predict clinical prognosis and immunotherapeutic response in PAAD patients was constructed.

通过WGCNA共表达网络分析和机器学习识别胰腺癌中潜在的同源修复缺陷相关新基因
同源修复缺陷(HRD)会阻碍双链断裂修复,而双链断裂修复是常见的致癌因素。HRD阳性可作为铂类和PARP抑制剂化疗反应的治疗标志物。在此,我们旨在全面研究胰腺腺癌(PAAD)HRD的治疗和预后潜力,并通过综合生物信息学分析确定与HRD相关的有效生物标志物。HRD评分定义为LOH、TAI和LST评分的非加权和,它是根据以往文献获得的。为确定 PAAD 免疫浸润亚型的特征,使用 R 软件包 "ConsensusClusterPlus "进行了无监督聚类。为阐明 PAAD HRD 相关基因模块中的基因共表达模块和枢纽基因,进行了 WGCNA 分析。使用 Metascape 进行了功能富集研究。预后变量采用单变量 Cox 分析法进行评估。预后风险模型采用 LASSO 方法建立。为评估风险模型的预后潜力,进行了 ROC 曲线和 KM 生存分析。PARP抑制剂的半数最大抑制浓度(IC50)是用R软件包 "pRRophetic "和癌症药物敏感性基因组学数据库估算的。R软件包 "rms "用于创建提名图。高HRD评分表明PAAD患者的预后较差,临床过程较晚。HRD水平高的PAAD肿瘤显示出明显的T辅助淋巴细胞耗竭、癌症干细胞水平上调以及对鲁卡帕利、奥拉帕利和veliparib的敏感性增加。利用 WGCNA,得到了 11 个共表达模块。红色模块和122个中心基因被确定为与PAAD的HRD最相关的基因。功能富集分析显示,这122个中心基因主要集中在细胞周期通路中。通过LASSO分析和随机森林算法筛选出了一个由CKS1B、HJURP和TPX2组成的新型HRD相关基因特征,并通过独立的验证集进行了验证。迄今为止,尚未有文献报道HRD与CKS1B、HJURP或TPX2直接相关。因此,这些发现表明 CKS1B、HJURP 和 TPX2 有可能成为 PAAD 的诊断和预后生物标志物。我们构建了一个与 HRD 相关的新型预后模型,为 PAAD 的预后和免疫疗法提供了新的见解。基于生物信息学分析,我们全面探讨了HRD在PAAD中的治疗和预后潜力。通过结合WGCNA、LASSO分析和随机森林算法,我们发现了一个由CKS1B、HJURP和TPX2组成的新型HRD相关基因特征。建立了一个新型的HRD相关风险模型,该模型可预测PAAD患者的临床预后和免疫治疗反应。
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来源期刊
Cell Cycle
Cell Cycle 生物-细胞生物学
CiteScore
7.70
自引率
2.30%
发文量
281
审稿时长
1 months
期刊介绍: Cell Cycle is a bi-weekly peer-reviewed journal of high priority research from all areas of cell biology. Cell Cycle covers all topics from yeast to man, from DNA to function, from development to aging, from stem cells to cell senescence, from metabolism to cell death, from cancer to neurobiology, from molecular biology to therapeutics. Our goal is fast publication of outstanding research.
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