基于单细胞测序分析和转录组分析的胰腺癌坏死性凋亡相关预后模型。

BACKGROUND: As a tumor type with high mortality and poor therapeutic effect, the pathogenesis of pancreatic cancer is still unclear. It is necessary to explore the significance of necroptosis in pancreatic cancer. METHODS: Pancreatic cancer transcriptome data were obtained from the TCGA database, ICGC database, and GSE85916 in the GEO database. The TCGA cohort was set as a training cohort, while the ICGC and GSE85916 cohort were set as the validation cohorts. Single-cell sequencing data of pancreatic cancer were obtained from GSE154778 in the GEO database. The genes most associated with necroptosis were identified by weighted co-expression network analysis and single-cell sequencing analysis. COX regression and Lasso regression were performed for these genes, and the prognostic model was established. By calculating risk scores, pancreatic cancer patients could be divided into NCPTS_high and NCPTS_low groups, and survival analysis, immune infiltration analysis, and mutation analysis between groups were performed. Cell experiments including gene knockdown, CCK-8 assay, clone formation assay, transwell assay and wound healing assay were conducted to explore the role of the key gene EPS8 in pancreatic cancer. PCR assays on clinical samples were further used to verify EPS8 expression. RESULTS: We constructed the necroptosis-related signature in pancreatic cancer using single-cell sequencing analysis and transcriptome analysis. The calculation formula of risk score was as follows: NCPTS = POLR3GL * (-0.404) + COL17A1 * (0.092) + DDIT4 * (0.007) + PDE4C * (0.057) + CLDN1 * 0.075 + HMGA2 * 0.056 + CENPF * 0.198 +EPS8 * 0.219. Through this signature, pancreatic cancer patients with different cohorts can be divided into NCPTS_high and NCPTS_low group, and the NCPTS_high group has a significantly poorer prognosis. Moreover, there were significant differences in immune infiltration level and mutation level between the two groups. Cell assays showed that in CAPAN-1 and PANC-1 cell lines, EPS8 knockdown significantly reduced the viability, clonogenesis, migration and invasion of pancreatic cancer cells. Clinical PCR assay of EPS8 expression showed that EPS8 expression was significantly up-regulated in pancreatic cancer (*P<0.05). CONCLUSION: Our study can provide a reference for the diagnosis, treatment and prognosis assessment of pancreatic cancer.

背景：胰腺癌是一种死亡率高、治疗效果差的肿瘤类型，其发病机制仍不清楚。有必要探讨坏死性凋亡在胰腺癌中的意义。

方法：从 TCGA 数据库、ICGC 数据库和 GEO 数据库中的 GSE85916 获得胰腺癌转录组数据。TCGA 队列被设置为训练队列，而 ICGC 和 GSE85916 队列被设置为验证队列。从 GEO 数据库中的 GSE154778 获得胰腺癌单细胞测序数据。通过加权共表达网络分析和单细胞测序分析确定与坏死性凋亡最相关的基因。对这些基因进行 COX 回归和 Lasso 回归，并建立预后模型。通过计算风险评分，将胰腺癌患者分为 NCPTS_high 和 NCPTS_low 组，并进行组间生存分析、免疫浸润分析和突变分析。进行基因敲低、CCK-8 测定、克隆形成测定、Transwell 测定和划痕愈合测定等细胞实验，以探讨关键基因 EPS8 在胰腺癌中的作用。进一步对临床样本进行 PCR 检测以验证 EPS8 的表达。

结果：我们使用单细胞测序分析和转录组分析构建了胰腺癌中的坏死性凋亡相关特征。风险评分的计算公式如下：NCPTS = POLR3GL*(-0.404) + COL17A1*(0.092) + DDIT4*(0.007) + PDE4C*(0.057) + CLDN10.075 + HMGA20.056 + CENPF0.198 +EPS80.219。通过该特征，不同队列的胰腺癌患者可分为 NCPTS_high 和 NCPTS_low 组，NCPTS_high 组的预后明显较差。此外，两组之间的免疫浸润水平和突变水平存在显著差异。细胞实验表明，在 CAPAN-1 和 PANC-1 细胞系中，EPS8 敲低显著降低了胰腺癌细胞的活力、克隆形成、迁移和侵袭。临床 EPS8 表达的 PCR 检测显示，胰腺癌细胞中 EPS8 的表达显著上调(*P<0.05)。

结论：本研究可为胰腺癌的诊断、治疗和预后评估提供参考。