Lung cancer ranks as the second most commonly diagnosed malignancy worldwide, exceeded only by breast cancer in incidence. It represents the most frequent primary tumor type that metastasizes to the brain, followed by breast cancer and melanoma (Cagney et al., 2017). Non-small cell lung cancer (NSCLC) comprises approximately 85% of all lung cancer cases (Sung et al., 2021; Jonna and Subramaniam, 2019), with brain metastasis (BM) being particularly common in this subgroup. Between 10% and 20% of NSCLC patients present with BM at initial diagnosis (Waqar et al., 2018), and an additional 25%–40% will develop BM throughout the disease course (Page et al., 2020). The prognosis for NSCLC patients with BM remains poor, and symptomatic cases are often associated with rapid deterioration in quality of life (Matsui et al., 2022). Historical reports indicate a median survival of only 4–6 months (Cheng and Perez-Soler, 2018). More recent epidemiological studies show that 15%–20% of NSCLC patients are diagnosed with BM at initial presentation, a figure that increases to 25%–40% over time (Waqar et al., 2018; Nayak et al., 2012; Hubbs et al., 2010). This incidence is even higher among patients with stage IV adenocarcinoma, among whom 40%–50% have BM at diagnosis (Yang et al., 2019). NSCLC patients harboring EGFR or ALK mutations are especially prone to developing BM and exhibit a higher incidence of such events (Gillespie et al., 2023). While historical median survival was reported between several months to one year—and below 6 months without treatment (Ali et al., 2013)-contemporary series report improved outcomes, with a median survival of approximately 15 months in lung adenocarcinoma patients with BM (Sperduto et al., 2020). The Lung-molGPA index further stratifies prognosis, identifying a small subgroup (4%) of patients with scores of 3.5–4.0 who may achieve a median survival of nearly 4 years (Sperduto et al., 2017). This prognostic tool incorporates clinical variables such as age, performance status, number of metastases, and extracranial disease burden, alongside molecular markers including EGFR and ALK mutations (Sperduto et al., 2017). The pathogenesis of BM in NSCLC entails complex crosstalk among tumor cells, immune components, and the specialized brain tumor microenvironment (TME). Metastasis is not solely an intrinsic trait of certain tumors, but a multistep, multidimensional process shaped by mutational landscapes, epigenetic alterations, and growth factor signaling (Srinivasan et al., 2021). As illustrated in Figure 1, the metastatic cascade initiates with local invasion through the basement membrane of the primary lung tumor—a step involving epithelial-mesenchymal transition (EMT) and intravasation into blood or lymphatic vessels. This allows circulating tumor cells (CTCs) to circumvent host immune surveillance and survive in circulation. Nevertheless, the precise mechanisms driving BM remain inadequately characterized, impeding the development of more effective treatment approaches.

The identification of biomarkers associated with lung cancer brain metastasis may provide deeper insights into the molecular mechanisms underlying metastatic progression. This study aimed to analyze NSCLC gene expression data to identify differentially expressed genes (DEGs), elucidate key molecular pathways, determine critical hub proteins, and characterize relevant regulatory biomolecules through a multi-omics data integration framework, with the ultimate goal of discovering potential therapeutic targets for NSCLC. Our gene expression profiling identified 56 DEGs, including 19 upregulated and 37 downregulated genes. Functional enrichment analysis revealed that these DEGs were significantly associated with several oncogenic molecular functions and pathways. GSEA results demonstrated marked upregulation of the “interleukin-17 signaling pathway.” Notably, the interleukin-17 (IL-17) signaling pathway has been previously established to contribute to the progression of lung cancer bone metastasis (Zhou et al., 2023). GO and KEGG enrichment analyses identified several critical biological processes and pathways, including immune response, signal transduction, inflammatory response, cell surface receptor signaling pathway, positive regulation of cell migration, cell-cell signaling, signaling receptor binding, chemokine activity, cytokine activity, transmembrane signaling receptor activity, plasma membrane, membrane, extracellular region, extracellular space, cytokine-cytokine receptor interaction, chemokine signaling pathway, viral protein interaction with cytokine and cytokine receptor, and PI3K-Akt signaling pathway. Existing evidence suggests that inflammatory chemokines and their receptors regulate tumor cell migration and participate in tumor growth, metastasis, angiogenesis, and invasion through interactions between mesenchymal and tumor cells (Cheng et al., 2016; Zhao et al., 2019). All these functions and pathways are significantly associated with cancer development and play crucial roles in the NSCLC microenvironment. Protein-protein interaction (PPI) network analysis has emerged as a promising approach for investigating the fundamental mechanisms of brain metastasis in lung cancer (Sevimoglu and Arga, 2014). Our PPI network analysis revealed hub proteins encoded by hub DEGs. The CCR5/CCL5 signaling axis has been shown to increase infiltration of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) into the tumor microenvironment (TME), creating an immune effector cell desert that promotes cancer survival and progression (Sevimoglu and Arga, 2014), while potentially contributing to immunotherapy resistance. This pathway has also demonstrated prognostic and predictive value in metastatic colorectal cancer (CRC) (Suarez-Carmona et al., 2019; Schlechter and Stebbing, 2024). CD27, a member of the TNF receptor superfamily, is essential for T cell immunity generation and long-term maintenance; Pagès et al. (Pages et al., 2005) found that CD27 expression correlates with early metastasis in colorectal cancer. IL-7R has emerged as a potential prognostic marker in breast cancer patients, particularly in maintaining immunologically active states in the TME and promoting immune reconstitution (Yu et al., 2024). PRF1, a crucial cytotoxic molecule, plays a vital role in the killing functions of natural killer (NK) cells and cytotoxic T lymphocytes (CTLs) (Guan et al., 2024). GZMA, GZMK, and PRF1 (Tibbs and Cao, 2022; Paczek et al., 2022; Park et al., 2021; Lavergne et al., 2021) not only induce apoptosis and modulate immune responses within the TME but also exhibit other distinct functions. Inhibition of tumor growth has been associated with reduced expression of the immune checkpoint molecule TIGIT (Shaw et al., 2022). The subnetwork modules containing these hub genes provide strong evidence supporting their reliability as therapeutic targets. The TF–mRNA–miRNA regulatory network analysis identified six transcription factors (STAT5A, STAT5B, NFKB1, EGR1, RELA, and CTCF) and four miRNAs (hsa-miR-204, hsa-miR-148b, hsa-miR-618, and hsa-miR-103) as key transcriptional and post-transcriptional regulators of hub DEGs. Previous studies have reported that various tumor-associated genes are regulated by STAT5A/STAT5B, which maintain multiple cancer-related pathways (Erdogan et al., 2022). NFKB1 plays critical roles in tumor cell invasion and metastasis, with its expression linked to invasion and metastasis across various cancer types (Zhang et al., 2023). EGR1 acts as a pro-metastatic factor in pancreatic cancer cells, promoting cell migration and invasion through the SNAI2–EMT pathway (Wang et al., 2023). Currently, there are limited reports on the tumor-related effects of RELA and CTCF. hsa-miR-204 has been reported to be downregulated and function as a tumor suppressor in various cancers including colorectal cancer, papillary thyroid carcinoma, malignant melanoma, and hepatocellular carcinoma (Chu et al., 2018). Studies have demonstrated significant enrichment of hsa-miR-148b in cancer-related pathways including Wnt, MAPK, and Jak-STAT signaling pathways (Luo et al., 2015). Dysregulation of hsa-miR-618 has been associated with numerous cancers (Radanova et al., 2021). hsa-miR-103a can function as either a tumor promoter or suppressor, modulating tumor progression in various cancers (Li et al., 2021). Survival curve analysis clearly demonstrated significant differences in hub gene expression between high-risk and low-risk groups, indicating their important roles in patient survival. Furthermore, immune infiltration analysis revealed interactions between these key genes and B/T cells in LUAD patients, suggesting their influence on the TME. On the other hand, in cancer cells, gene mutations, amplifications, and deletions can lead to altered target proteins that fail to bind drugs, resulting in drug resistance. In particular, missense mutations may significantly affect protein function (Chen et al., 2004). Our mutation analysis of 10 genes in NSCLC revealed that IL7R and PRF1 had the highest missense mutation rates at 39% and 13%, respectively. It has been demonstrated that IL7R mutations activate downstream IL7R signaling independent of IL7 and promote cell transformation and tumor formation, indicating that IL7R exon 6 mutations are gain-of-function mutations (Kim et al., 2013). PRF1 plays important roles in various aspects of tumor cell development, immune escape mechanisms, cancer immunotherapy, and prognosis (Guan et al., 2024). However, the functional characteristics of most missense mutations in IL7R and PRF1 in tumors remain poorly characterized. Importantly, we found strong associations between IL7R/PRF1 mutation co-occurrence and immune-related pathways, particularly B cell and T cell signaling. The presence of infiltrating immune cells in these tumors, some of which inhibit or promote disease progression, further supports the involvement of immune pathways. In conclusion, although this study has certain limitations including a small sample size and lack of clinical sample validation, our current analysis has identified several key genes and pathways closely associated with NSCLC-BM that may enhance current understanding of its complex mechanisms. Notably, these findings warrant further investigation and experimental validation.

This study employed bioinformatics approaches to compare non-small cell lung cancer (NSCLC) and brain metastasis (NSCLC-BM) samples, leading to the preliminary identification of 56 differentially expressed genes (DEGs) potentially associated with metastatic progression. These genes were significantly enriched in key pathways including cytokine-cytokine receptor interaction, chemokine signaling pathway, viral protein-cytokine receptor interaction, and the PI3K-Akt signaling pathway. Among them, ten genes—CD19, CD27, IL7R, SELL, CCL5, CCR5, PRF1, GZMK, GZMA, and TIGIT—were selected as potential hub genes. Furthermore, predictions suggested that miRNAs such as hsa-miR-204 and hsa-miR-148b, along with certain transcription factors, may contribute to metastasis by modulating the tumor immune microenvironment. It is important to emphasize that the findings of this study are computational predictions, and all identified genes and regulatory molecules remain candidate biomarkers that have not been experimentally validated. None of the conclusions presented should be interpreted as established biomarkers or clinically applicable outcomes. These predictions require further experimental validation—including qRT-PCR, immunohistochemistry, independent patient cohort analyses, and in vitro/in vivo functional assays—to confirm their biological significance and translational potential. Future research will focus on experimental verification to evaluate the diagnostic or therapeutic value of these candidate molecules.