Department of Pulmonary and Critical Care Medicine, Chongqing University Three Gorges Hospital, Chongqing 404100, China.
Department of Oncology, Chongqing University Three Gorges Hospital, Chongqing 404100, China.
Dis Markers. 2022 Aug 18;2022:6703053. doi: 10.1155/2022/6703053. eCollection 2022.
Lung adenocarcinoma is the most common lung cancer subtype and accounts for the highest proportion of cancer-related deaths. The tumor microenvironment influences prognostic outcomes in lung adenocarcinoma (LUAD).
We used the ESTIMATE algorithm (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) to investigate the role of microenvironment-related genes and stromal cells in lung adenocarcinoma prognosis. This analysis was done on lung adenocarcinoma cases from The Cancer Genome Atlas (TCGA). The cases were divided into high and low groups on the basis of immune and stromal scores, respectively.
There were close correlations between immune scores with prognosis and disease stage. There were 367 differentially expressed genes. Combining the Gene Expression Omnibus (GEO) database, we found 14 prognosis-related genes.
There were close correlations between immune scores with prognosis and disease stage. There were 367 differentially expressed genes. Combining the Gene Expression Omnibus (GEO) database, we found 14 prognosis-related genes. . Based on the enrichment levels of the immune cell types, we clustered LUAD into Immunity_H and Immunity_L subtypes. Most of these genes were upregulated in Immunity_H subtype. Finally, using the Human Protein Atlas (HPA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, most of the proteins corresponding to prognostic genes were verified to be differentially expressed between the tumor and normal groups.
The key genes identified in this study are involved in molecular mechanisms of LUAD.
肺腺癌是最常见的肺癌亚型，也是癌症相关死亡的主要原因。肿瘤微环境影响肺腺癌（LUAD）的预后结果。
我们使用 ESTIMATE 算法（基于表达数据估计恶性肿瘤组织中的基质和免疫细胞）来研究微环境相关基因和基质细胞在肺腺癌预后中的作用。这项分析是基于癌症基因组图谱（TCGA）中的肺腺癌病例进行的。根据免疫和基质评分，将病例分别分为高分和低分组。
免疫评分与预后和疾病分期密切相关。共有 367 个差异表达基因。结合基因表达综合数据库（GEO），我们发现了 14 个与预后相关的基因。基于免疫细胞类型的富集水平，我们将 LUAD 聚类为 Immunity_H 和 Immunity_L 亚型。这些基因大多数在 Immunity_H 亚型中上调。最后，使用人类蛋白质图谱（HPA）和临床蛋白质组肿瘤分析联盟（CPTAC）数据库，验证了与预后相关基因相对应的大多数蛋白质在肿瘤和正常组织之间存在差异表达。
本研究中鉴定的关键基因涉及 LUAD 的分子机制。
