HNSCC, the most prevalent malignant tumor of the head and neck, has increased in incidence owing to risk factors such as smoking, alcohol consumption, environmental pollutants, and pathogenic viruses such as HPV and EBV [26]. Immunotherapy has emerged as a promising treatment for HNSCC as it reactivates the ability of the immune system to recognize cancer cells [27]. TAMs, as a crucial role in immune infiltration in HNSCC can activate pathways that increase tumor stemness and chemotherapy resistance, reduce chemotherapy sensitivity, and elevate the risk of recurrence in some HNSCC patients [28]. Single-cell studies have also revealed that TAMs promote angiogenesis, lymph node metastasis, and tumor invasion by secreting CCL8 and CXCL18, thus promoting HNSCC progression [29].
We quantitatively analyzed the infiltration abundance of macrophages in the two cohorts, identified key modules related to MRGs in HNSCC, ultimately obtaining 194 key MRGs. We classified HNSCC into two molecular subtypes and found that the OS of patients in cluster 1 was lower than that in cluster 2, which may be linked to the differences in enriched functional pathways: cluster 1 was enriched in metabolic pathways, while cluster 2 was mainly related to inflammatory response, which may be due to the strong “immune clearance effect” of the body’s immune system on tumor cells. In addition, cluster 2 had higher matrix, immune, and infiltration scores than cluster 1, and the functional pathways of immune cells and the expression of HLA molecules were enriched in cluster 2. Owing to immune editing, the absence or downregulation of HLA molecules is a common early event in cancer occurrence, which can lead to impaired recognition of tumor cells by cytotoxic T cells, resulting in immune escape and is closely associated with tumor recurrence and metastasis [30]. The ICI gene was predominantly expressed in cluster 2, which was closely linked to malignant characteristics such as epithelial-mesenchymal transition, angiogenesis, and the dissemination and invasion of malignancies. We hypothesized that highly expressed ICI genes may not play a prominent role in cluster 2 [31]. The tumor purity of cluster 2 was significantly lower than that of cluster1, and the treatment sensitivity against CTLA4 and PD1 was higher, suggesting that attention should be paid to the role of immunotherapy in the treatment of HNSCC patients in cluster 2, which can be combined with conventional methods to further improve patient survival.
To better apply macrophage-related typing to the diagnosis and treatment of HNSCC, we constructed an MRS using a combination of 101 machine learning algorithms to further identify molecular targets related to the prognosis of HNSCC. A total of nine genes were found to comprise the MRS, which was utilized to stratify patients with HNSCC into high- and low-risk groups. The high-risk group exhibited a considerably poorer survival rate, and the risk score may serve as an independent risk factor for predicting patient survival outcomes.
Among the nine genes in MRS, APOC1 has been shown that inhibition of its expression can induce ferroptosis to reverse M2 macrophages to M1 macrophages, leading to immune activation and increased sensitivity to PD1 therapy [32]. More detailed studies have indicated that APOC1 inhibits KEAP1, promotes NRF2 nuclear translocation, and increases the expression of cystathionine-beta-synthase (CBS) to inhibit ferroptosis, thereby promoting tumor proliferation [33]. CYP27A1 mainly regulates cholesterol homeostasis using the CYP27A1/27-hydroxycholesterol (27-HC) axis as a mediator to regulate cell apoptosis and the cell cycle and is associated with good clinicopathological characteristics and prognosis [34]. Similarly, NTN4 is also associated with better survival rates facilitated by Wnt/β- Catenin signal transduction, and is positively correlated with the degree of infiltration of immune cells, including macrophages and neutrophils, as well as the immunosuppressive condition of tumors [35]. Previous studies have demonstrated that IGF2BP2 promotes the clearance, synthesis, metabolism, and growth of HNSCC cells and that its overexpression is a risk factor for poor prognosis in patients. Furthermore, by increasing the stability of CDK6, IGF2BP2 can upregulate its expression, which in turn promotes malignant characteristics [36]. The CTLA4 molecule, which is mainly located on the surface of T cells, can effectively bind to the B7 protein to induce T cell dysfunction and immune suppression [37]. SLC7A5 maintains the levels of essential amino acids in cancer cells through transcription and metabolic recording, which are crucial for the proliferation of cancer cells. Specific knockout of SLC7A5 significantly downregulates the mTORC1 signaling pathway in cancer cells, mobilizing the general amino acid control (GAAC) pathway to inhibit the synthesis of specific proteins, thereby hindering tumor progression [38]. Other genes in the MRS, including KRT9, PPP1R14C, and RAC2, can influence to varying degrees the proliferation, invasion, metastasis, and angiogenesis of tumor cells, as well as the functions of immune cells in the TME. The specific mechanisms by which these genes regulate HNSCC warrant further investigation.
CNV is a driving force in cancer development and plays a critical role in oncogene activation and tumor suppressor gene inactivation [39]. Data analysis revealed that CTLA4 is prone to copy number loss, whereas IFNG is prone to copy number amplification. TMB can reflect the number of gene mutations in tumor cells and predict the sensitivity and resistance of patients to ICI treatment; the more mutations, the more new antigens, and the higher the probability of triggering a T cell immune response [40]. Our analysis revealed a significant correlation between the expression levels of hub genes CD80, CTLA4, and CCL2 and TMB. Previous studies have demonstrated that T cells in the TME, activated in a CTLA4 dependent manner, exhibit strong immunogenicity in high-TMB tumor cells, leading to a series of immune responses [41]. In addition, TP53 showed a higher mutation frequency in the high-risk group, whereas TTN showed a higher mutation frequency in the low-risk group. TP53, as the gene with the highest mutation frequency in human cancer, plays an important role in inducing cell apoptosis, aging, cell cycle arrest, and DNA damage repair, and is associated with increased chromosomal instability [42, 43]. Previous studies have shown that TP53 mutations can increase the expression of relevant immune checkpoint molecules, and inhibit the infiltration of cytotoxic CD8+T cells, leading to immunosuppressive states that induce macrophage polarization towards the M2 phenotype of TAMs, resulting in sustained tumor progression and a higher mutation frequency in high-risk groups [44]. TTN mutations can cause varied gene expression in cancers, boost tumor immune response, and increase susceptibility to immunotherapy [45]. Mutations in TTN are strongly associated with the conversion of macrophages into M1 type TAM, which could explain the increased occurrence of TTN mutations in the low-risk group [46].
Cancer immunotherapy is an innovative strategy that seeks to augment the capacity of the immune system to combat cancer by performing radical cancer treatment and preventing recurrence [47]. We observed that the vast majority of immune checkpoint genes and HLA genes were significantly upregulated in the high-risk group, which could potentially affect the level of immune infiltration and exacerbate tumor growth by recruiting various immune cells or cytokines. The TIDE score of tumors was positively correlated with the risk score of the MRS model, indicating that the tumor cells in the high-risk group have a stronger immune escape ability, whereas patients in the low-risk group may be more sensitive to ICI therapy and have a higher positive immune response rate. To confirm the reliability of the MRS model in accurately forecasting the effectiveness of immunotherapy and patient survival, we used clinical data from individuals with urothelial carcinoma in the IMvigor210 cohort to assess the predictive capacity of immunotherapy. We found the high-risk group had lower survival rates and the predictive power of the risk score for patient survival was higher. It is worth noting that the sensitivity of patients with HNSCC to chemotherapy drugs varied among different risk groups, which was related to tumor heterogeneity caused by mutations in drug resistance-related genes and crosstalk between different immune cells [48]. Hence, the MRS model score can be utilized to determine specific chemotherapeutic medications for patients with HNSCC, thereby attaining precision in medicine.
Finally, our single-cell analysis indicated that SLC7A5, RAC2, and APOC1 were highly expressed in the macrophage subpopulation in the MRS. Macrophages in the TME mainly stagnated in G2.M phase, which is related to the downregulation of multiple functional pathways, with the inhibition of epithelial-mesenchymal transition being the most prominent and the highest abundance in the HPV− patient population, all of which confirm that macrophages themselves may play a favorable role in the progression of HNSCC. This phenomenon could be attributed to the scavenging functions of macrophages, which also regulate the immune response to tumor cells and preserve tissue homeostasis. By regulating the differentiation of TAM into M2 macrophages with cytokines or metabolites, the TME may induce anti-tumor immunity [49, 50].
This study aimed to categorize HNSCC patients into subtypes based on MRGs, identify DEGs among these clusters, and develop an MRS model for patient prognosis assessment to aid immunotherapy selection. Through comprehensive validation across various perspectives and databases, we developed an MRS model that effectively predicts patient survival and provides information on treatment strategies. However, this study has some limitations. HNSCC patient data, sourced solely from public databases, often lack critical details, such as HPV infection status and microvascular infiltration. However, the effects of these factors remain unclear. To authenticate and assess the diagnostic and therapeutic efficacy of the MRS model, future studies should include broader multicenter clinical cohorts. Additionally, our validation of MRS-related gene expression was restricted to the RNA and protein levels. The specific molecular mechanisms and pathways in HNSCC have been inferred from the literature and warrant further exploration through in vivo and in vitro experiments.
In summary, this study identified characteristic genes associated with macrophages in HNSCC and established an MRS model that fully validated its diagnostic efficacy in predicting patient survival prognosis, clarified its potential relationship with tumor cell genome mutations, and provided a theoretical basis for immunotherapy and chemotherapy drug selection. These results will help us further explore the characteristics and related molecular mechanisms of macrophage immune infiltration in HNSCC to identify new molecular targets for personalized diagnosis and treatment of HNSCC patients in the future.