Tumors are composed of cancer cells and TME. TME contains tumor-infiltrating immune cells, cancer-associated fibroblasts (CAFs), endothelial cells, the extracellular matrix, and a wide range of metabolites and cytokines (26). As tumors grow, preexisting blood vessels fail to sufficiently perfuse the tumor and oxygen levels drop, which lead to a hypoxic and acidic environment (27). Hypoxia is rapidly sensed by the O2/prolyl hydroxylase (PHD)/Von Hippel Lindau (VHL) axis, which induces the stabilization of HIF-1α or HIF-2α and the subsequent activation of a gene signature that orchestrates the cellular adaptation to hypoxia (28). Furthermore, an acidic environment caused by hypoxia impacts the metabolic and functional reprogramming of cancer cells and tumor-associated stromal cells (29). Therefore, in connection with our research direction, the effect of hypoxia on lung adenocarcinoma is a topic worthy of further discussion.
According to published studies (16, 30), 15-gene expression signature (ACOT7, ADM, ALDOA, CDKN3, ENO1, LDHA, MIF, MRPS17, NDRG1, P4HA1, PGAM1, SLC2A1, TPI1, TUBB6, and VEGFA) that has been shown to perform the best when classifying hypoxia status were selected. These 15 genes make up a common hypoxia signature which will be upregulated and are consistently co-expressed with previously validated hypoxia-regulated genes under hypoxic conditions in various cancers (31). In this study, TCGA-LUAD samples were clustered into different hypoxia status according to the 15 genes expression. All of these 15 genes were upregulated in cluster 1 (Fig. 1K-L), which were defined as “hypoxic subgroup”. In the analysis of the relationship between hypoxia status of lung adenocarcinoma and clinicopathological characteristics, we found that hypoxia is associated with worse TNM staging, which suggests that hypoxia is associated with poor prognosis (Fig. 2A, Table 1).
Numerous studies indicate that the hypoxia of TME is an important reason for promoting tumor immunosuppression and resistance to immunotherapy (32). Tumor hypoxia region can recruit immunosuppressive cells such as myeloid derived suppressor cells (MDSC), tumor-associated macrophages (TAM), tumor-associated neutrophils (TANs) and Tregs, and negatively affect the activation of CD8 + T cells and CD4 + T cells (33). Hypoxia cancer cells, via HIF-1α, secrete the chemokine CCL28 that recruits CXCR10 + Tregs into tumors (34). TGF-β is a cytokine highly abundant in hypoxic regions of the tumor (35), which leads to the arise of TANs. TGF-β induces the production of Foxp3 and RORγt in CD4 + T cells, which induces the differentiation of Tregs and enhances immunosuppression (36). In this study, the infiltration of 24 immune cell types were compared in cluster1 and cluster2. The results showed that the infiltration of CD4 + T cells and Tfh cells was lower, while the infiltration of nTreg cells and iTreg cells was higher in cluster 1 (Fig. 2), which indicates that there is an immunosuppressive state in cluster1. A study in breast cancer showed that hypoxic increased TMB by driving genome instability and altering DNA damage repair pathways (37). The same phenomenon was observed in this study. The TMB score, the PD-1 and PD-L1 expression of cluster1 was significantly higher than that of cluster 2 (Fig. 2H), which indicated immunosuppressive status.
Under hypoxia conditions, tumor cells activate multiple adaptive pathways to promote the evolution of a more aggressive tumor phenotype including the activation of DNA damage repair proteins, altered metabolism, and decreased proliferation (38). In the study, the differentially expressed genes between cluster 1 and cluster 2 were identified and performed GO/KEGG analysis. The results showed the differentially expressed genes related to metabolism, such as ATP binding, related to cell cycle and proliferation, such as cell division, cell proliferation, G1/S/G2/M transition of the mitotic cell cycle, stc., related to DNA damage repair, such as DNA replication, DNA repair, etc., related immune regulation, such as FoxO signaling pathway (Fig. 3). HIF stable expression under hypoxia, and promotes angiogenesis through VEGF-A, glycolysis, and pH control through CA-IX (39). There is extensive evidence showing down regulation of numerous proteins involved in homologous recombination, mismatch repair, base excision repair, and nucleotide excision repair under hypoxic conditions (40). FoxO signaling pathway is a pivotal regulator of Tregs cell function, which promotes immune suppression (41). Furthermore, there is a large amount of DGEs enriched in microtubule-based movement, protein kinase activity, p53 signaling pathway, microRNAs in cancer, etc., which all related to tumor invasion and metastasis. These underlying mechanisms together lead to the negative impact of hypoxia on tumor prognosis. To better predict the prognosis of patients, we constructed a risk signature containing 7 genes by univariate Cox and LASSO Cox regression analysis, which showed a well-prediction ability (Fig. 4).
MiRNAs and lncRNAs are identified as key regulators of gene expression in various biological and pathological processes (42). We identified potential ncRNA regulatory pathways involving miRNA, lncRNA and mRNA based on ceRNA theory, and built a PPI network which might promote the development of LUAD (Fig. 5). Researches showed hsa-miR-196b was potential biomarker in LUAD (43), ATP1A2 mutation was found in pulmonary carcinoid tumors and involved in multiple biological processes, such as cellular metabolism, immune regulation, etc, and NEAT1 function as a competing endogenous lncRNA in multiple tumors (44). According to the results of this research, NEAT1 as a sponge of hsa-miR-196b alleviates its repression on ATP1A2, and regulates multiple biological in LUAD. Similarly, hsa-miR-31 and its predicting target lncRNA (MIR497HG), mRNA (CEBPA) all involved in multiple tumors (45) (46), there is also a competing endogenous between them in LUAD according to our results. The levels of hsa-miR-9 correlate with tumor grade and metastatic status (47), and its upregulation led to enhanced NSCLC cell invasion and adhesion via the regulation of multiple pathways (48). According to this study, samples in TCGA-LUAD with high expression of hsa-miR-9 have worse survival, and various lncRNAs (AC020978.7, NEAT1, AC021078.1) and mRNAs (PCSK2, FREM2, ALPL) targeted are all related to survival.
In conclusion, this study explored the role and potential mechanism of hypoxia in LUAD from the perspective of gene signature and ceRNA theory in silico analyses, the results showed hypoxia promoted tumor progression and immunosuppressive status through multiple pathways, and the regulatory effect of ceRNA theory on LUAD had also been observed. However, it is undeniable that our research still has some limitations. All our results are based on silico analyses of TCGA and some website analysis. More functional experiments are needed to verify the results of this research, which will be the focus of our next exploration.