Department of Translational Medicine and Clinical Research, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Front Endocrinol (Lausanne). 2023 Jul 31;14:1201755. doi: 10.3389/fendo.2023.1201755. eCollection 2023.
Single-cell sequencing technology has become an indispensable tool in tumor mechanism and heterogeneity studies. Pancreatic adenocarcinoma (PAAD) lacks early specific symptoms, and comprehensive bioinformatics analysis for PAAD contributes to the developmental mechanisms.
We performed dimensionality reduction analysis on the single-cell sequencing data GSE165399 of PAAD to obtain the specific cell clusters. We then obtained cell cluster-associated gene modules by weighted co-expression network analysis and identified tumorigenesis-associated cell clusters and gene modules in PAAD by trajectory analysis. Tumor-associated genes of PAAD were intersected with cell cluster marker genes and within the signature module to obtain genes associated with PAAD occurrence to construct a prognostic risk assessment tool by the COX model. The performance of the model was assessed by the Kaplan-Meier (K-M) curve and the receiver operating characteristic (ROC) curve. The score of endocrine pathways was assessed by ssGSEA analysis.
The PAAD single-cell dataset GSE165399 was filtered and downscaled, and finally, 17 cell subgroups were filtered and 17 cell clusters were labeled. WGCNA analysis revealed that the brown module was most associated with tumorigenesis. Among them, the brown module was significantly associated with C11 and C14 cell clusters. C11 and C14 cell clusters belonged to fibroblast and circulating fetal cells, respectively, and trajectory analysis showed low heterogeneity for fibroblast and extremely high heterogeneity for circulating fetal cells. Next, through differential analysis, we found that genes within the C11 cluster were highly associated with tumorigenesis. Finally, we constructed the RiskScore system, and K-M curves and ROC curves revealed that RiskScore possessed objective clinical prognostic potential and demonstrated consistent robustness in multiple datasets. The low-risk group presented a higher endocrine metabolism and lower immune infiltrate state.
We identified prognostic models consisting of APOL1, BHLHE40, CLMP, GNG12, LOX, LY6E, MYL12B, RND3, SOX4, and RiskScore showed promising clinical value. RiskScore possibly carries a credible clinical prognostic potential for PAAD.
单细胞测序技术已成为肿瘤机制和异质性研究不可或缺的工具。胰腺导管腺癌（PAAD）缺乏早期特异性症状，对 PAAD 的全面生物信息学分析有助于了解其发病机制。
我们对 PAAD 的单细胞测序数据 GSE165399 进行降维分析，以获得特定的细胞簇。然后，我们通过加权共表达网络分析获得与细胞簇相关的基因模块，并通过轨迹分析鉴定 PAAD 中的肿瘤发生相关细胞簇和基因模块。将 PAAD 的肿瘤相关基因与细胞簇标记基因和特征模块内的基因进行交集，以获得与 PAAD 发生相关的基因，构建 COX 模型的预后风险评估工具。通过 Kaplan-Meier（K-M）曲线和受试者工作特征（ROC）曲线评估模型的性能。通过 ssGSEA 分析评估内分泌途径的评分。
筛选和降维 PAAD 单细胞数据集 GSE165399，最终筛选出 17 个细胞亚群并标记 17 个细胞簇。WGCNA 分析显示，棕色模块与肿瘤发生的相关性最强。其中，棕色模块与 C11 和 C14 细胞簇显著相关。C11 和 C14 细胞簇分别属于成纤维细胞和循环胎儿细胞，轨迹分析显示成纤维细胞的异质性较低，而循环胎儿细胞的异质性极高。接下来，通过差异分析，我们发现 C11 簇内的基因与肿瘤发生高度相关。最后，我们构建了 RiskScore 系统，K-M 曲线和 ROC 曲线表明 RiskScore 具有客观的临床预后潜力，并在多个数据集上表现出一致的稳健性。低风险组表现出更高的内分泌代谢和更低的免疫浸润状态。
我们鉴定了由 APOL1、BHLHE40、CLMP、GNG12、LOX、LY6E、MYL12B、RND3、SOX4 和 RiskScore 组成的预后模型具有良好的临床价值。RiskScore 可能为 PAAD 提供可靠的临床预后潜力。
