Lung cancer is the most common type of cancer and the leading cause of cancer-related deaths worldwide[15], Its incidence and mortality rates have continued to rise over the past few years[16, 17]. Currently, the 5-year survival rate for lung cancer is only 19%[18]. In 2022, it is estimated that there will be 254,850 new cases and 135,360 deaths from lung cancer[19]. LUAD is the primary subtype of lung cancer[20]. However, most patients with lung adenocarcinoma are diagnosed at advanced or metastatic stages of the disease. Early diagnosis and treatment of lung adenocarcinoma can result in significantly higher survival rates, but treatment at advanced stages often results in poor prognosis and low survival rates[21]. Therefore, it is essential to identify accurate and promising prognostic biomarkers and therapeutic targets for lung adenocarcinoma to improve the survival rates of patients with LUAD[22, 23].
IPF is a progressive lung disease with limited treatment options and a high mortality rate. Over the past few decades, numerous studies have shed light on the complex pathophysiology of IPF, including its involvement in various molecular and cellular processes such as genetics, epigenetics, microRNAs (miRNAs), developmental reprogramming, signaling pathways, apoptosis, metabolism, and autophagy[24]. However, further research is necessary to fully understand the molecular mechanisms underlying IPF.In recent years, bioinformatics has emerged as a valuable tool for analyzing complex biological data and is increasingly being used to study pathogenic genes[25]. The objective of this paper is to use bioinformatics approaches to identify the key genes and signaling pathways involved in the development of both IPF and LUAD. Through this analysis, we aim to deepen our understanding of the molecular mechanisms underlying these diseases and identify potential therapeutic targets for the future.
In this study, we identified 93 overlapping differentially expressed genes (DEGs) in both diseases and narrowed them down to 13 key genes, including COL1A1, IGF1, COL3A1, TIMP3, AKR1C3, WNT3A, HPGD, MMP12, GREM1, SULF1, CCL5, CTHRC1, and CCL19. Our subsequent three GO analyses revealed that these genes were significantly enriched in the regulation of animal organ morphogenesis, extracellular matrix organization, and extracellular structure organization. The pathophysiology underlying IPF, characterized by fibrosis of the interstitial lung tissue, is not yet fully understood. However, it is believed to involve repeated injury to alveolar epithelial cells, followed by impaired healing mechanisms[26–28], and an excessive accumulation of extracellular matrix (ECM), particularly collagen[29, 30]. These changes lead to increased tissue stiffness, which is a key factor leading to interstitial lung fibrosis[31]. Our GO analysis results support this notion. Our KEGG pathway enrichment analysis showed significant enrichment in Proteoglycans in cancer, Ovarian steroidogenesis, and Arachidonic acid metabolism. Proteoglycans are a diverse group of molecules with a protein backbone decorated with various linear sulfated glycosaminoglycan side chains. Evidence suggests that the proteoglycan-rich extracellular matrix promotes malignant transformation, increases cancer aggressiveness, and helps tumor cells evade therapeutic response[32]. Steroid hormones include two major groups: sex hormones and adrenocorticotropic hormones. There is an abundance of epidemiological evidence, preclinical in vitro and in vivo studies, and recent clinical trial data that support estrogen as an important factor influencing lung cancer development, proliferation, and metastasis[33]. Arachidonic acid (AA) is a polyunsaturated fatty acid found in cell membrane phospholipids and is essential in the metabolism of hydroxyeicosapentaenoic acid, epoxyeicosatrienoic acid, prostaglandins, and other active metabolites via cytochrome P450, lipoxygenase, and cyclooxygenase (COX)[34–36]. Studies based on tumor cell lines have shown that AA and its metabolites can promote tumor development by regulating cell proliferation, chemotaxis, mitosis, migration, and apoptosis, and by regulating the processes of cell carcinogenesis, progression, and differentiation[34, 37, 38].
COL1A1 and COL3A1 are members of the collagen protein family, which play important roles in various biological processes. COL1A1 is involved in bone growth and repair, maintenance of skin elasticity and resilience, tooth and bone morphology, and vascular wall strength and stability. COL3A1, on the other hand, contributes to the formation of fine fibers in the extracellular matrix and participates in its construction and maintenance along with other collagen proteins[39, 40]. Collagen is a major structural component of the extracellular matrix (ECM), which is a critical component of the tumor microenvironment and plays a crucial role in tumorigenesis, infiltration, and metastasis[41]. A study by Geng et al. found a significant correlation between different levels of immune cell infiltration and many immune markers in LUAD and LUSC with COL1A1 expression levels. They also observed that COL1A1 expression had a strong correlation with the degree of tumor differentiation[42]. In another study, Zhang et al. analyzed COL3A1 expression in public databases of pan-cancer versus corresponding normal tissues and observed that COL3A1 expression was highly upregulated in lung cancer, particularly LUAD and LUSC. Furthermore, they found that its expression levels correlated with cancer stage and survival[40]. These findings highlight the important role of collagen proteins in lung cancer development and progression.
CC motif chemokine ligands (CCLs) are a class of small molecule cytokine proteins that play a crucial role in regulating immune and inflammatory responses. Among them, CCL5 (also known as RANTES) and CCL19 (also known as MIP-3β) are two important members of this family[43]. Elevated levels of pro-inflammatory factors lead to increased expression of CCL5, which in turn attracts various immune cells to the site of inflammation[44], CCL5 has been found to promote infiltration of NK cells[45, 46], DC cells[47], Th1 cells[48], and Tc1 cells[49] into the tumor. However, CCL5 can also inhibit immune cell function, promote tumor angiogenesis, and facilitate metastasis[50, 51], Experimental studies have shown that CCL5 increases tumor cell resistance to apoptosis and drug resistance by activating the Akt/PKB→NF-κB and STAT3 pathways[52–54]. It also stimulates cancer cells to express more programmed death ligand 1 (PD-L1), which provides protection against cytotoxic lymphocytes[55]. CCL19, on the other hand, plays an important role in promoting chemotaxis and activation of lymphocytes, dendritic cells, and other immune cells[56], In tumors, CCL19 expression can attract tumor-infiltrating lymphocytes (TIL) to produce a cytotoxic effect that enhances anti-tumor activity[57, 58]。
Matrix metalloproteinase 12 (MMP12) is a member of the metalloproteinase family, which comprises enzymes involved in the degradation and remodeling of the extracellular matrix. Its primary expression occurs in immune cells such as macrophages, dendritic cells, and neutrophils, where it plays a critical role in the degradation and remodeling of the extracellular matrix. MMP12's expression level in lung tissue is associated with the development of various respiratory diseases, including chronic obstructive pulmonary disease (COPD), emphysema, and lung cancer[59–61]. By promoting inflammation, damaging lung tissue, and facilitating the growth and metastasis of cancer cells[62, 63], MMP12 is believed to be involved in the pathogenesis of these diseases. Cytokines, growth factors, and oxidative stress are among the factors that regulate MMP12 expression[64]. Therefore, MMP12 has potential as a therapeutic target for the treatment of respiratory diseases and cancer. Although the precise mechanisms underlying the involvement of MMP12 in these diseases are not yet fully understood, continued research on this enzyme promises to expand our knowledge of its roles in health and disease and pave the way for the development of new diagnostic and therapeutic strategies.
The TIMP3 gene encodes the tissue inhibitor of metalloproteinases 3 (TIMP-3) protein, which belongs to a class of proteinase inhibitors known as tissue inhibitors of metalloproteinases (TIMPs). These proteins regulate extracellular matrix degradation by binding to metalloproteinases, and TIMP3 specifically plays a critical role in maintaining extracellular matrix homeostasis by inhibiting the activity of matrix metalloproteinases (MMPs). In addition to its physiological functions, TIMP3 also plays a role in various pathological processes, including tissue remodeling, cell apoptosis, and inflammatory response. Recent studies have shed light on the potential therapeutic value of targeting TIMP3. For example, KDM1A has been shown to promote cancer metastasis in NSCLC cells by repressing TIMP3[65]. Another study demonstrated that miR-34b-5p knockdown can increase TIMP3 expression and resist bleomycin-induced lung fibrosis in mice[66]. As such, TIMP3 is regarded as a potential therapeutic target and may provide new strategies for treating related diseases.
The HPGD gene encodes the 15-hydroxyprostaglandin dehydrogenase (15-PGDH) protein, which is a critical component of the prostaglandin metabolic pathway and participates in the degradation of prostaglandin E2 (PGE2). By converting PGE2 to 13,14-dihydro-PGE2, which is biologically inactive, HPGD plays an essential role in regulating a variety of biological processes, including inflammation, immune modulation, cell proliferation, differentiation, and apoptosis. Studies have shown that YY1 directly inhibits LINC01089, which suppresses lung cancer progression through the miR-301b-3p/HPGD axis[67]. Additionally, in vitro experiments have revealed that PGDH was significantly downregulated in an epithelial-mesenchymal transition (EMT) model established in human lung epithelial A549 cells. Furthermore, PGDH knockdown induced EMT in A549 cells[68], which is a crucial pathological process in IPF[69, 70]. Therefore, HPGD is considered a promising therapeutic target and diagnostic marker for cancer.
However, our study has several inherent limitations that must be acknowledged. Firstly, the DEGs identified through bioinformatic analysis provide insights into the mechanisms underlying the occurrence of IPF and LUAD; however, no sample of IPF combined with LUAD was available for validation. Secondly, our samples were derived from a single population, and the results may not be generalizable to other populations, highlighting the need for validation in diverse populations. Finally, larger, multicenter studies are necessary to further validate our findings.