In 2020, global cancer burden data revealed that lung cancer is one of the most prevalent cancers in 36 countries and the primary cause of cancer-related mortality in 93 countries [19]. Therefore, it is imperative to investigate the mechanisms underlying lung cancer development and identify early diagnostic and prognostic biomarkers for this cancer. S100A16, a calcium-binding protein, is widely expressed in tumor tissues, suggesting its potential involvement in malignant transformation or tumorigenesis. Specifically, S100A16 overexpression has been observed in bladder, lung, thyroid, pancreatic, glioma, and ovarian tumors [12, 20]. Functionally, S100A16 is involved in various aspects of tumorigenesis, including cell proliferation, differentiation, migration, invasion, and epithelial-mesenchymal transition. Our comprehensive analysis revealed the overexpression of S100A16 in various human tumors, emphasizing its key role in the progression of different cancers, such as LUAD. Prognostic assessment also underscored the adverse effect of high S100A16 expression on the outcomes of LUAD. Univariate and multivariate analyses confirmed the prognostic significance of S100A16 expression, establishing it as an independent biomarker for patients with LUAD. S100A16 overexpression was observed in multiple cancer types, including BLCA, CESC, CHOL, ESCA, GBM, HNSC, KIRC, KIRP, LIHC, LUSC, PAAD, and THCA, suggesting its pivotal role in oncogenesis. Our extensive analysis revealed additional associations between S100A16 and clinicopathologic features of LUAD, affirming its positive correlation with the risk of LUAD and its ability to accurately signify the clinical staging and grading of patients with LUAD.
Numerous studies investigated the role of S100A16 in various tumor cells, revealing its significance in cancer progression. S100A16 is markedly overexpressed in pancreatic ductal adenocarcinoma (PDAC) and contributes to PDAC progression by activating the AKT and ERK1/2 signaling pathways through FGF19. These findings indicate that S100A16 is a promising therapeutic target in PDAC [21]. Jie Zhu and colleagues also observed an association between increased S100A16 expression and poor prognosis in lung adenocarcinoma [22], consistent with our findings. Furthermore, Chen et al. reported that S100A16 can serve as an independent predictive factor for the prognosis of LUAD, linked by DNA methylation [23]. However, the correlations between S100A16 and immune checkpoints or drug susceptibility remain unclear [23]. Our findings revealed the association between S100A16 and the effectiveness of immunotherapy. Furthermore, we discovered that overexpression of S100A16 may play a role in resistance to various chemotherapy drugs, in line with the findings reported by Katono et al. [24]. Immune cell infiltration holds paramount significance in cancer progression. Employing bioinformatics techniques, we analyzed immune cell infiltration in LUAD. Our findings revealed a robust positive correlation between S100A16 gene expression and the abundance of various immune cells, including mast cells and dendritic cells. T cells, mast cells, and natural killer cells are pivotal in recognizing and targeting tumor cells. Macrophages possess two phenotypes: classical (M1) and alternative (M2). M1 macrophages restrain tumor growth by instigating inflammatory responses. In contrast, M2 macrophages resolve inflammation and promote tissue repair, thereby enhancing cancer progression. The abundance of memory B cells, activated NK cells, and resting M1 macrophages was significantly lower in samples with S100A16 overexpression than in samples with low S100A16 expression. These findings suggest that the S100A16 gene may contribute to oncogenesis. Further analyses revealed a positive association between the expression of S100A16 and that of several immune checkpoint genes, such as LGALS9, LGALS9, and TNFSF9. In our study, we identified a significant association between the expression of S100A16 and that of various immune checkpoint genes. This finding suggests that S100A16 is a potential predictive biomarker for assessing response to immunotherapy. KEGG network analysis showed that molecules associated with S100A16 were primarily enriched in neuroactive ligand-receptor interaction, calcium signaling pathway, and protein digestion and absorption. Genes co-expressed with S100A16 may modulate chemical synaptic transmission, regulate trans-synaptic signaling, and control the membrane potential. These findings were also supported by GO term annotations, indicating the potential involvement of S100A16 in diverse biological processes, including synaptic communication, neuronal signaling, and cellular homeostasis.
Collectively, these findings suggest that the S100A16 gene may possess immunomodulatory functions. Furthermore, the correlation between S100A16 expression and IC50 of various anticancer drugs revealed that patients with high S100A16 expression exhibit resistance to several anticancer drugs, including 5-fluorouracil, bortezomib, cisplatin, cytarabine, docetaxel, doxorubicin, etoposide, vinorelbine, and gemcitabine. These findings introduce a novel avenue for studying the mechanisms underlying chemoresistance.