Cancer is a highly heterogeneous and complex disease involving a variety of genetic factors. The hallmarks of cancer include maintaining proliferative signaling, evading growth inhibitors, resisting cell death, immortalizing replication, inducing angiogenesis, and activating cancer cell invasion and metastasis. LUAD is one of the most invasive subtypes of lung cancer with a high recurrence rate, short DFS, and easy distant metastasis. LUAD is composed of small airway epithelial, type II alveolar cells secreting mucus, and other substances. The current treatment of LUAD ranges from surgery to chemotherapy to radiotherapy to targeted therapy as well as immunotherapy. The rapid development of gene chip detection technology has great advantages for functionally related differential gene screening. An in-depth discussion of specific mutations related to LUAD can better provide theoretical basis for clinical individualized treatment of tumors. Some current studies have found that tumor heterogeneity and molecular differences in different individuals may lead to poor outcomes or even failure of treatment. Comprehensive bioinformatics analysis can be widely used to identify potential biomarkers related to the diagnosis, treatment, and prognosis of LUAD. These analysis methods include screening DEGs, finding network-based hub nodes, and performing survival analysis on DEGs. In our study, to understand the pathogenesis of LUAD at the molecular level, we analyzed the expression profiles of cancer-related genes based on the TCGA database, and a variety of bioinformatics methods, such as GO term analysis, KEGG enrichment analysis, and PPI network construction, were utilized to deeply explore the DEGs associated with the tumor microenvironment. Moreover, survival curves were drawn for common DEGs identified in the high vs low immune/stromal score groups.
First, based on the ESTIMATE algorithm, the immune scores and stromal scores of LUAD were different from statistically significant genders. In addition, the immune scores were meaningful for overall survival and T staging. In contrast, stromal scores were significantly related to distant metastasis. Many studies have shown that immune cells and stromal cells are part of the tumor microenvironment and have an impact on tumor progression, metastasis, and therapeutic resistance[17, 18]. Importantly, stromal cells can be reprogrammed by tumor epithelial cells, and they acquire an “activate” protumorigenic phenotype.
A total of 379 overlapping genes were included in the overall survival analysis, of which 129 genes were correlated with the prognosis of LUAD patients (p < 0.05). Furthermore, 30 potential target genes with more hub nodes were selected and analyzed for survival. Eleven target genes with diagnostic and prognostic markers were extracted ultimately (CD33, IRF8, CD80, CD53, IL16, LY86, CD79B, TYROBP, CD1E, CD1C, and CD1B).
The CD33 is a well-known target in Myeloid-derived suppressor cells (MDSCs), which may constitute the innate system and facilitates efficient interaction within the immune cells. MDSCs can influence tumor progression and metastasis, and tumor microenvironment. Furthermore, a previous study has found that M-MDSCs were significantly increased after surgery. Besides, CD33 is involved in inhibiting T cells proliferation and affecting the development of Treg cells, and it is also involved in identifying tumor cells.
IRF8, Interferon regulatory factor 8, is a member of the IRF family of transcription factors. IRF8 regulates the development and function of a variety of immune cells, linking innate and adaptive immunity. It plays a regulatory role in the cell's immune response to cancer and can mediate the expression of Fas, Bax, JAK, and STAT, leading to the apoptosis of solid tumor cells and has been shown to have antitumor activity in a variety of tumor cells. IRF8 inhibits AKT signaling, affects apoptotic genes, and results in the senescence of lung cancer cells. The expression of IRF8 in tumor cells leads to the regression of lung cancer nodules and has a tumor-suppressive effect. It can be a potent lung tumor suppressor gene.
CD80 is one of the Dendritic cells (DCs) mature markers. The expression level of CD80 on the surface of tumor-infiltrating dendritic cells (TIDCs) in tumor tissue was significantly lower than that in normal tissues and adjacent tissues, which may affect the antigen presentation of DC cells. As a co-stimulatory molecule, CD80 expression is involved in the activation and proliferation of T lymphocytes and is affected by the tumor microenvironment. It can also cause tumor cells to escape immune surveillance and promote tumor cell development[25, 26]. In addition, lower CD80 expression independently predicts a poor prognosis in patients with gastric adenocarcinoma.
CD53 is one of the earliest members of the tetraspanin/transmembrane-4 superfamily. CD53 can influence cell migration and adhesion. Lack of CD53 protein expression can lead to repeated infections in the body, indicating the important role of CD53 in immunity. CD53 is abnormally expressed in radiation-resistant tumor cells. Under some circumstances, CD53 antigen stimulation may protect against programmed cell death. CD53 may also activate the effector functions of NK cells and stimulate their proliferation.
In recent years, it has been shown that IL-16 activates the stress-activated protein kinase (SAPK) signaling pathway in macrophages. IL-16 is a pro-inflammatory cytokine that stimulates the release of different types of pro-inflammatory factors, such as IL1β, IL6, IL15, and Tumor Necrosis Factor-α (TNF-α), through monocytes. These cytokines play an important role in tumor formation. IL-16 may also regulate the expression of cytochrome P450 enzymes through microRNAs, further causing activation of various carcinogens and damaging the DNA. Besides, IL-16 mutations can cause changes in cell viability and function, and ultimately cause individuals to be susceptible to tumors. In NSCLC, patients with IL-16 gene mutations may show a higher risk of death and they severely affect patient survival.
LY86, the “lymphocyte antigen 86” also known as protein Myeloid differentiation protein 1 (MD-1), is a well-known secreted glycoprotein that forms the radioprotective protein 105 (RP105) /MD-1 complex in a variety of pathological conditions, further targeting the TLR4 pathway. The RP105/MD-1 complex can be expressed on a variety of immune cells, including B cells, macrophages, and DCs. RP105/MD-1 RNA was found to be strongly up-regulated in tumor-associated macrophages (TAMs) as compared to normal macrophages, while tumor cells again showed no expression.
CD79B is a component of the B-cell antigen receptor and is almost universal on the surface of most B-cell derived malignancies, making it an attractive therapeutic target. CD79B is mainly expressed in most patients with non-Hodgkin lymphoma (NHL) and chronic lymphocytic leukemia (CLL). This gene has not been previously reported to be associated with the lung cancer microenvironment, but it may serve as a potential biomarker.
TYROBP, also known as DAP12; KARAP; PLOSL; PLOSL1, is expressed in natural killer cells, monocyte-macrophages, dendritic cells, and neutrophils, and it plays a pivotal role in the immune receptor tyrosine activation motif (ITAM) pathway. The DAP12/ITAM pathway might participate in the polarization of macrophages, which secrete TGF-β to act on tumor tissues, This pathway can also promote tumor progression and metastasis through TGF-β-mediated changes in the microenvironment of the tumor, such as EMT, changes in anti-apoptotic genes, increased escape from immune surveillance, and immune suppression. DAP12 is expressed in breast cancer (BRC) and hepatocellular carcinoma cells and is closely related to the malignant progression of tumors, distant metastases (such as bone metastases, liver metastases), and prognosis. A previous study suggested that TYROBP might be a target gene for diagnosing kidney cancer.
CD1 molecules are usually expressed on malignant cells and can contribute to anti-tumor immune responses by presenting tumor-derived lipid and glycolipid antigens to T cells and NKT cells.CD1d has been demonstrated in not only hematological malignancies (such as AML, B-ALL, CLL, lymphomas, and multiple myeloma), but also in some solid tumors (glioma, medulloblastoma, renal cell carcinoma, and breast and prostate cancers). CD1d has been shown to reduce lung tumor burden and enhance the anti-tumor immunity of DC cells.