This study aims to identify the potential necroptosis related genes (NRGs)-associated miRNAs signature and explore the impact on the prognosis of stomach adenocarcinoma (STAD). Employing rigorous methodologies, we utilized univariate Cox, Lasso and multivariate Cox regression analyses to develop a prognostic signature. Kaplan-Meier (K-M) and ROC curves were applied to assess the prognostic value of signature in a training group and an independent test group. Furthermore, we conducted Gene Set Enrichment Analysis (GSEA) for enrichment of tumor-related pathways. The risk score was calculated for each patient based on the expression of miRNAs which were enrolled in the signature. Patients were stratified into high- and low-risk groups. The immune cell infiltration and immunotherapy were compared between the two groups. Finally, the diagnostic potential of the miRNA was explored by RT-qPCR. We constructed a prognostic model based on 6 NRGs-associated miRNAs. K-M plots underscored superior survival outcomes in the low-risk group. GSEA results revealed the enrichment of several tumor-related pathways in the high-risk group. Notably, CD8 T cells, Tregs and activated memory CD4 T cells exhibited negative correlations with the risk score. Additionally, a few immune checkpoint genes, such as CTLA4, PD1 and PD-L1, were significantly upregulated in the low-risk group. Furthermore, the serum expression levels of all these 6 miRNAs were significantly elevated in STAD patients. Our study identified a robust risk score derived from a signature of 6 NRGs-associated miRNAs, demonstrating high efficacy for prognosis of STAD. These results not only contributed to our understanding of STAD pathogenesis, but also held promise for potential clinical applications, particularly in the realm of personalized immunotherapy for STAD patients.

中文翻译：

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鉴定坏死性凋亡相关 miRNA 特征以预测胃腺癌的预后和免疫状况

本研究旨在鉴定潜在的坏死性凋亡相关基因 (NRG) 相关 miRNA 特征，并探讨其对胃腺癌 (STAD) 预后的影响。我们采用严格的方法，利用单变量 Cox、Lasso 和多元 Cox 回归分析来开发预后特征。应用卡普兰-迈耶 (KM) 和 ROC 曲线来评估训练组和独立测试组中签名的预后价值。此外，我们还进行了基因集富集分析（GSEA）以富集肿瘤相关通路。根据签名中登记的 miRNA 的表达，计算每位患者的风险评分。患者被分为高风险组和低风险组。比较两组的免疫细胞浸润情况及免疫治疗情况。最后，通过 RT-qPCR 探索了 miRNA 的诊断潜力。我们构建了基于 6 个 NRG 相关 miRNA 的预后模型。KM 图强调了低风险组的优越生存结果。GSEA 结果揭示了高危组中多种肿瘤相关通路的富集。值得注意的是，CD8 T 细胞、Treg 细胞和活化的记忆 CD4 T 细胞与风险评分呈负相关。此外，一些免疫检查点基因，如 CTLA4、PD1 和 PD-L1，在低风险组中显着上调。此外，所有这 6 种 miRNA 的血清表达水平在 STAD 患者中均显着升高。我们的研究确定了源自 6 个 NRG 相关 miRNA 特征的稳健风险评分，证明了 STAD 预后的高效性。这些结果不仅有助于我们对 STAD 发病机制的理解，而且还为潜在的临床应用带来了希望，特别是在 STAD 患者的个性化免疫治疗领域。