Distinct tumor microenvironment landscapes in gastric cancer classified by cuproptosis-related lncRNAs.
Distinct tumor microenvironment landscapes in gastric cancer classified by cuproptosis-related lncRNAs.
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DOI：
10.7150/jca.79640
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发表时间：
2022
影响因子：
3.9
通讯作者：
Chen C
中科院分区：
文献类型：
--
作者：
Huang J;Chen M;Pei W;Xu Z;Ning J;Chen C
CuProtosis是一种新发现的非凋亡性细胞死亡形式，可能与肿瘤的发生发展有关。然而，在胃癌(GC)的肿瘤微环境(TME)形成和患者个性化治疗优化中，与突起相关的lncRNAs的潜在作用仍不清楚。在这项研究中，利用Lasso-Cox回归模型构建了6-lncRNA标记来量化GC的分子模式。采用受试者工作特征(ROC)曲线、C指数曲线、独立预后分析和主成分分析(PCA)对模型进行验证和评价。结果表明，该风险模型能准确可靠地预测胃癌患者的生存期。此外，基于风险模型识别了两个不同的亚组，它们在相关基因的生物学功能、TME评分、免疫细胞浸润性和免疫治疗反应方面存在显著差异。我们发现，高危亚组与免疫激活和肿瘤相关途径有关。此外，与低危亚组相比，高危亚组具有更高的TME评分、更丰富的免疫细胞浸润和更好的免疫治疗反应。为了准确识别免疫性冷瘤和热瘤，所有GC样本通过共识聚类被分为四个不同的聚类。其中，第3簇被鉴定为免疫热点肿瘤，对免疫治疗更敏感。综上所述，本研究结果表明，脱落相关的lncRNAs可以准确预测胃癌患者的预后，有助于区分免疫性冷瘤和热瘤，为胃癌的精准治疗提供依据。
Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor microenvironment (TME) formation and patient-tailored treatment optimization of gastric cancer (GC) is still unclear. In this study, the six-lncRNA signature was constructed to quantify the molecular patterns of GC using LASSO-Cox regression model. Receiver operating characteristic (ROC) curves, C-index curves, independent prognostic analysis and principal component analysis (PCA) were conducted to verify and evaluate the model. The results showed that this risk model was accurate and reliable in predicting GC patient survival. In addition, two distinct subgroups were identified based on the risk model, which showed significant difference in biological functions of the associated genes, TME scores, characteristics of infiltrating immune cells and immunotherapy responses. We found that the high-risk subgroup was associated with immune activation and tumor-related pathways. Furthermore, compared with the low-risk subgroup, the high-risk subgroup had higher TME scores, richer immune cell infiltration and a better immunotherapy response. To accurately identify immune cold tumors and hot tumors, all samples of GC were divided into four distinct clusters by consensus clustering. Among them, Cluster 3 was identified as an immune hot tumor and was more sensitive to immunotherapy. Overall, this study demonstrates that cuproptosis-related lncRNAs could accurately predict the prognosis of patients with GC, help make a distinction between immune cold tumors and hot tumors and provide a basis for the precision medicine of GC.
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