Laryngeal cancer (LCa) is the second most prevalent malignant tumor affecting the head and neck region, with an incidence rate second only to oral carcinoma, accounting for about 1.98% of all malignancies in the whole body, and in 2020 there was about 180,000 new patients with LCa and nearly 100,000 deaths worldwide (Sung et al., 2021; Atef et al., 2019). Squamous cell carcinoma (SCC) accounting for about 90% of LCa, is the predominant LCa subtype (Megwalu and Sikora, 2014; Siegel et al., 2020). The pathogenesis of laryngeal squamous cell carcinoma (LSCC) is still unclear, and related studies have shown that smoking, drinking, environmental factors, gastroesophageal reflux, HPV infection, radiation and other factors are associated with LSCC, which may be the result of a multifactorial interaction (Steuer et al., 2017). With the development of endoscopic and imaging technologies, the diagnosis and treatment of LSCC have been improved significantly. However, due to the lack of typical symptoms in the initial phase, approximately 60% of patients diagnosed with LSCC are already in advanced stages of tumor development. This delay in diagnosis hinders timely treatment and subsequently leads to unfavorable clinical outcomes (Strojan et al., 2013; Calhoun, 1988; Gao et al., 2019). In addition, despite the continuous improvement in surgery, chemotherapy and radiotherapy, the recurrence and metastasis rates of LSCC are still high and impose a serious impact on prognosis (Haddad et al., 2018; Gao et al., 2020; Bray et al., 2018; Lu et al., 2018; Nocini et al., 2020). In recent years, it has been pointed out that a possible way to improve the diagnostic and therapeutic effects of LSCC is the use of effective biomarkers, especially amino acid metabolic-related markers, which play an increasingly important role in the early detection of malignancies and the identification of potential immunotherapeutic targets (Zhang et al., 2018; Liu et al., 2023), but have not yet been well explored in LSCC. Therefore, the identification of effective biomarkers is important for the prediction of prognosis and guidance of personalized therapy in LSCC patients.

Tryptophan (Trp) is a crucial amino acid, constituting approximately 1% of the overall amino acids. It is not biosynthesized within our body and can solely be acquired through dietary intake (Wang et al., 2015). In the body, Trp is metabolized mainly through the Kynurenine pathway (KP) to produce downstream metabolites such as Kynurenine (KYN). Indoleamine 2,3-dioxygenase 1 (IDO1), indoleamine 2,3-dioxygenase 2 (IDO2), and tryptophan 2,3-dioxygenase 2 (TDO2) are the key rate-limiting enzymes for Trp metabolism. Numerous research studies have consistently demonstrated the significant upregulation of IDO1 in diverse tumor types, such as melanoma, cervical cancer, oral squamous cell carcinoma, colorectal cancer, esophageal cancer, and pancreatic cancer (Zhai et al., 2018; Chen et al., 2020; Prendergast et al., 2014). Furthermore, the presence of IDO1 expression in either tumor cells or stromal cells has been linked to an enhanced aggressive phenotype, unfavorable clinical outcomes, and a bleak prognosis (Zhang et al., 2022; Iversen et al., 2015; Rubel et al., 2018; Kozuma et al., 2018; Hornyak et al., 2018). Previous research has indicated that the metabolism of Trp in cancerous cells and/or surrounding cells plays a role in inhibiting the immune system’s ability to fight against tumors (Platten et al., 2021). Trp and its metabolites interact with IDO can modulate not only tumor cells, but also the entire tumor microenvironment, and ultimately promoting immunosuppression and drug resistance (Greene et al., 2019; Li and Zhao, 2021; Maleki et al., 2015). In addition, Trp metabolism, a novel immune checkpoint that can influence the outcome of immunotherapy, is also a potential therapeutic target (Li et al., 2019). From the above mentioned studies, it is known that Trp metabolism plays a pivotal role in initiation and progression of various cancers; however, the role of Trp metabolism-related genes (TMRGs) in LSCC and their prognostic value are not yet clear.

In this study, we extracted TCGA-LSCC, GSE27020, and 40 TMRGs from publicly available databases, and then identified DE-TMRGs by Weighted Gene Co-expression Network Analysis (WGCNA), differential expression analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis, and finally combined with relevant clinicopathological information to construct a risk model of Trp metabolism. In addition, we further analyzed the impact of the risk model on the immunotherapy and chemotherapy for LSCC. We also identified the optimal clustering form (molecular subtypes) by consensus clustering analysis of samples from TCGA-LSCC, and explored the relationship between clustering and LSCC prognosis. Therefore, this study aims to construct a risk model by analyzing the TMRGs in LSCC to further predict the prognosis of LSCC patients and guide personalized treatment.

LSCC is the most common pathological type of LCa and also one of the most common malignant tumors of the head and neck (Johnson et al., 2020; Cohen et al., 2019). The incidence of LSCC has been on the rise in recent years, both in China and other countries, and its poor prognosis and high mortality rate have become a major risk factor for human health (Echanique et al., 2021; Costa et al., 2021; Deng et al., 2020). Despite the continuous improvement in the diagnosis and treatment of LSCC, including surgery, radiotherapy, chemotherapy, neoadjuvant therapy, immunotherapy, or strategies combining different treatment modalities,the overall survival rate has not been significantly improved (Qin et al., 2021; Bryan et al., 2016; Karam and Raben, 2019; Guidi et al., 2018). Due to the insidious onset of LSCC, which has already progressed to mid and late stages in most patients at the time of diagnosis, and the high recurrence rate, the 3, 5-year DFS of LSCC has not been significantly improved either (Volkov, 1972; Obid et al., 2019). Therefore, searching for new targets, early prediction, early diagnosis, early intervention, and providing new diagnostic and therapeutic approaches for LSCC may be important means to improve the prognosis of LSCC patients (Sung et al., 2021).

Trp metabolism produces a variety of active substances with physiological effects, which are important for maintaining cell activation and proliferation (Neavin et al., 2018; Conejos et al., 2021). Trp and its metabolites have diverse biological effects in the regulation of multiple diseases (Conejos et al., 2021; Ding et al., 2020; Wu et al., 2020). In particular, Trp and its metabolites play an important role in tumor formation and evolution (Kwiatkowska et al., 2021; Tanaka et al., 2021). Perez L et al. (Perez-Castro et al., 2023) showed that Trp metabolites activate the aromatic receptor (AHR), increase malignant degree, and inhibit anti-tumor immune responses. In a study of oral squamous cell carcinoma (OSCC), Tryptophanyl-tRNA synthetase (TrpRS) expression was upregulated in tumor tissues, and the expression level of TrpRS correlated with the clinicopathological features of OSCC patients (Lee et al., 2015). Another study regarding head and neck squamous carcinoma (HNSC) showed that IDO and TDO2 are indicators of immunosuppression and poor survival in HNSC patients, and that IDO1 in HNSC is negatively correlated with programmed cell death protein ligand 1 (PDL-1) (Riess et al., 2020). Additionally, studies revealed that TMRGs also play significant roles in LSCC and OSCC. For instance, drugs that inhibit the overexpression of Akt1 (RAC-α serine/threonine-protein kinase) and Akt2 (RAC-β serine/threonine-protein kinase) without reducing MAOB expression could serve as lead compounds for the treatment of oral squamous cell carcinoma (OSCC) (Sharif Siam et al., 2021). Furthermore, ACAT1 inhibitors have been shown to enhance the therapeutic efficacy of CSCs-DC vaccines in a mouse model of postoperative recurrence of head and neck squamous cell carcinoma (HNSCC), suggesting that ACAT1 may play an important role in cancer immunotherapy (Chen et al., 2017). Additionally, both low and high expression levels of ALDH2 have been associated with tumor progression, depending on the type of cancer, indicating that ALDH2 is a potential therapeutic target for cancer treatment (Zhang and Fu, 2021).

In this study, we analyzed the RNA-seq data, copy number, somatic mutation data and clinicopathological features of the TCGA-LSCC dataset to explore the mechanisms related to Trp metabolism in LSCC, and finally identified five genes (SERPINA1, TMC8, RENBP, SDS, and FAM107A) to establish a risk model. Tryptophan metabolism, particularly through the kynurenine pathway, plays a crucial role in shaping the tumor immune microenvironment (Qin et al., 2021). Key enzymes such as IDO1 and TDO2 catalyze the conversion of tryptophan to kynurenine, producing immunosuppressive metabolites that inhibit anti-tumor immune responses (Prendergast et al., 2014). In LSCC, the upregulation of these enzymes may lead to increased immune evasion and tumor progression. Additionally, TMRGs may affect the infiltration of immune cells such as Tregs and MDSCs, which contribute to an immunosuppressive microenvironment (Perez-Castro et al., 2023). The potential pathway interactions of TMRGs in LSCC are illustrated in Figure 8. In addition, two molecular clusters related to Trp metabolism were also identified.

The SERPINA1 encodes the alpha-1 antitrypsin (AAT) protein, which is involved in the regulation of enzyme activity and protein metabolism, as well as cell growth, differentiation, motility and signaling (Ando et al., 2021; Lim et al., 2020; Cipriani et al., 2018). Previous research findings have indicated that there is a significant upregulation of SERPINA1 in various types of tumor tissues, which has been strongly linked to the advancement and prognosis of tumors. Jiang and Hu (2020) found that SERPINA1 expression was linked to the development of gastric cancer and enhanced the invasion and migration of the disease’s cells. As a result, it may offer a viable target for the disease’s prevention. Kwon et al. (2015) found that SERPINA1 expression was linked to poor prognosis of colorectal cancer, as well as tumor stage, and lymph node metastasis, and that overexpression of SERPINA1 increased the capacity of cancer cells to invade and migrate, whereas silencing of SERPINA1 expression decreased this capacity. In hepatocellular carcinoma, Dongre and Weinberg (2019) reached a similar conclusion that patients with high expression of SERPINA1 in hepatocellular carcinoma tissues may have a higher risk of recurrence and metastasis. The expression level of SERPINA1 in oral tumor tissues was notably higher than normal tissues, which was associated with the progression, metastasis and prognosis of the tumor (Kawahara et al., 2016). In our study, we used qRT-PCR to detect the expression level of SERPINA1 in tumor and adjacent tissues of LSCC patients, and the results showed that the expression level of SERPINA1 in LSCC was significantly higher, which was in line with the results of other scholars’ studies.

The mammalian transmembrane channel-like (TMC) gene family consists of eight genes, ranging from TMC 1 to 8, and TMC8 is also known as EVER2. It is widely acknowledged that individuals diagnosed with HNSC frequently exhibit HPV infection, and studies in recent years have suggested that common variants of TMC8 are noteworthily related to HPV infection and HNSC patients prognosis (Lin et al., 2021). Liang et al. (2015) also have reported a correlation between genetic variation in TMC8 and the occurrence of high-risk HPV infection as well as its role in the development of HNSC, and it is also a fundamental regulatory factor for the persistence and carcinogenicity of HPV infection. In addition, TMC8 has the potential to impact tumor behavior by modulating immune pathways; The presence of TMC8 in tumor tissues showed a significant and positive correlation with the infiltration of various immune cells, including B cells, CD4⁺ T cells, macrophages, CD8⁺ T cells, and dendritic cells, and TMC8 may increase the infiltration of cytotoxic T cells and B lymphocytes by influencing the functionality of CD4⁺ T cells (Liang et al., 2015). According to a study by Lin et al. (2021) TMC8 expression was shown to be considerably higher in HPV-positive HNSC patients. This finding indicated a positive link between Th2 infiltration and B cell enrichment, indicating that TMC8 may operate as a barrier to HPV through Th2 cells. We propose that TMC8 could potentially contribute to the development of resistance against HPV infection, consequently reducing the vulnerability of LSCC patients.

RENBP encodes renin-binding protein, an important regulator in the renin-angiotensin-aldosterone system, which is responsible for participating in blood pressure regulation and maintenance of sodium homeostasis. RENBP has been proved to be expressed in mouse lungs and may promote local lesion development through an inflammatory response (Huffnagle et al., 2017), so we hypothesized that micro-metabolic changes induced by inflammation in LSCC may affect RENBP gene expression and consequently affects tumorigenesis.

The family with sequence similarity 107 member A (FAM107A) gene, also known as DRR1 or TU3A, a specific set of codons encodes multiple amino acids. Previously published studies have shown that FAM107A has reduced expression in various tumor tissues, including prostate cancer, hepatocellular carcinoma, lymphoma and non-small cell lung cancer, which exhibits the properties of an oncogene (Vanaja et al., 2006; Udali et al., 2015; Lawrie et al., 2018; Pastuszak-Lewandoska et al., 2015); while FAM107A was highly expressed in the aggressive component of gliomas and was associated with increased aggressiveness and disease progression in neuroblastoma, meningioma and malignant glioma (Mu et al., 2017; Asano et al., 2010; Fevre-Montange et al., 2009; Nakajima and Koizumi, 2014). The study of Kiwerska et al. (2017) found that FAM107A functioned as an oncogene in LSCC, and it led to the decrease of its expression in LSCC through DNA methylation and combined deletion. In the present study, the expression level of FAM107A in tumor tissues was significantly lower than that in the adjacent normal tissues, which was in line with the findings of other scholars.

Compared with other genes, SDS has not been deeply studied in LSCC, and the specific mechanism of SDS as a pro-carcinogenic gene in LSCC still needs to be further explored in the future.

We further confirmed that risk score alone was an independent prognostic factor by univariate Cox analysis of clinical characteristics and risk score, and in turn created a nomogram for prediction of risk and survival probability in LSCC. Hallmark pathway enrichment analysis reveals the risk model was also engaged in bile acid metabolism, fatty acid metabolism, xenobiotic metabolism, heme metabolism, IL6 JAK stat3 signaling and other hallmark pathways.

Immunotherapy is currently a more promising means of tumor treatment, especially immune checkpoint-based immunotherapy, which has made significant breakthroughs in the treatment of various tumors and reshaped the landscape of tumor treatment (Marabelle et al., 2020; Kruger et al., 2019; Ribas and Wolchok, 2018). In this study, we found that a total of nine immune checkpoints were sensitively expressed in high/low-risk subgroups. The high risk subgroup had much higher levels of immune checkpoint gene expression, such as Neuropilin-1 (NRP1). NRP1 is a neuronal and endothelial cell receptor essential for normal embryonic development and angiogenesis, whereas it suppresses anti-tumor immune response in the formation and development of malignant tumors, which correlates with poor clinical outcome (Delgoffe et al., 2013; Overacre-Delgoffe et al., 2017). On the one hand, NRP1 promotes tumor cell growth through multiple pathways, such as neoangiogenesis, metastasis; on the other hand, NRP1 facilitates immune escape by regulating intra-tumor Treg cells and CD8⁺ T and orchestrating multiple inhibitory processes in the tumor microenvironment (TME) (Overacre-Delgoffe et al., 2017; Liu et al., 2020). As a member of the B7/CD28 family, the molecular structure of human endogenous retrovirus-H long terminal repeat-associated protein 2 (HHLA2) shares some homology and similarity with other B7 family members, such as PD-L1, and exhibits both co-stimulatory and co-inhibitory effects on T cells (Janakiram et al., 2017; Xiao and Freeman, 2015) TMIGD2 is one of the specific receptors for HHLA2, often also known as CD28H (Zhu et al., 2013). It has been discovered that several solid tumors have high expressions of HHLA2, including breast cancer (Liu et al., 2017), osteosarcoma (Koirala et al., 2016), colon cancer (Zhu and Dong, 2018), clear cell carcinoma of the kidney (Chen et al., 2019), and bladder cancer (Lin et al., 2019), and so on. Based on this, HHLA2/TMIGD2 is expected to be one of the new pathways and targets for tumor immunotherapy, especially providing new ideas for PD-L1-negative tumor immunotherapy. Some published research indicated that HHLA2 may have different effects on prognosis in different types of tumors. On the one hand, overexpression of HHLA2 in pancreatic, ampullary and ovarian carcinoma is closely associated with a favorable prognosis (Boor et al., 2020; Xu G. et al., 2021). On the other hand, co-expression of HHLA2 and PD-L1 in renal clear cell carcinoma shows a poor prognosis (Zhou et al., 2020). In our study, HHLA2 was highly expressed in patients with low-risk, suggesting that LSCC patients with low-risk may benefit from immunotherapy based on this target. CD40LG (also known as CD154) is the ligand gene for CD40, belonging to the tumor necrosis factor (TNF) gene superfamily, predominantly expressed on activated T cells and platelets (Kuhn et al., 2019). It is also involved in tumor pathogenesis and anti-tumor immunity (Hassan et al., 2015). CD40 ⁻ CD40LG interaction is an important signal for B-cell proliferation, activation biomarker expression and immunoglobulin production, which directly inhibits the growth of CD40-positive tumor cells and may indirectly inhibit tumor growth by downregulating the immune response (Laman et al., 2017; Jansen et al., 2016). Yuan et al. (2021) found that CD40LG is a valuable prognostic molecular marker in breast cancer, and its low expression is associated with poor outcomes. In our study, we found that CD40LG was lowly expressed in the high risk subgroup, which may be associated with a poorer prognosis in these patients. For the TIDE score, it was higher in patients with high-risk than low-risk, suggesting that high-risk patients may have a higher likelihood of immune escape in response to immune checkpoint therapy, which may have a negative impact on the effect of immunotherapy in these patients.

To explore the role of risk model in LSCC chemotherapy and find chemotherapy-sensitive drugs in high/low-risk subgroup, we performed a drug sensitivity analysis and found that patients in the low-risk subgroup were sensitive to Salubrinal, while those in the high-risk subgroup were sensitive to these drugs including Docetaxel, AUY922, Embelin, and CHIR.99021. Salubrinal is a selective inhibitor of eIF2α that acts by inducing phosphorylation and inhibiting dephosphorylation of eIF2α. Salubrinal was found to act differently when combined with different types of chemotherapeutic agents, it can enhance the inhibitory effect of drugs such as doxorubicin on tumors (Jeon et al., 2016); whereas in combination with platinum-based drugs, Salubrinal attenuates the antineoplastic efficacy of platinum-based chemotherapeutic agents (Chen et al., 2011; Feng et al., 2013). Therefore, when selecting chemotherapeutic drugs for patients in the high-risk subgroup, attention should be paid to the rational selection of drugs to maximize the antitumor activity of different types of drugs.

Based on consensus clustering analysis, we identified two different clusters, and the cluster 1 had worse DFS compared to the cluster 2. The proportions of immune cells such as MDSC, Macrophage, and Regulatory T cells were also higher in cluster 1 than in cluster 2 subtype, which is important for the formation of an immunosuppressive tumor microenvironment and the inhibition of migration and infiltration of immune cells into tumor tissues, and this may be one of the reasons for the worse DFS of the cluster 1, which is in line with the studies of other scholars (Sica and Massarotti, 2017; Wang et al., 2021).

Trp metabolism is closely associated with the formation of the tumor immune microenvironment and impacts anti-tumor immune responses through multiple pathways. Increased activity of rate-limiting enzymes in Trp metabolism leads to Trp depletion in the tumor microenvironment, which in turn induces cell-cycle arrest of peripheral T cells and promotes the generation of Tregs (Wolf et al., 2015; Fallarino et al., 2006). Moreover, Kyn, a metabolite of Trp metabolism, can activate AHR on CD4⁺ T cells and induce differentiation of CD4⁺ T cells to regulatory T cells (Mezrich et al., 2010). Within the tumor microenvironment, Tregs inhibit the function of effector T cells by secreting inhibitory cytokines or interacting with antigen-presenting cells, thereby modulating anti-tumor immune responses. This aligns with the immune cell infiltration pattern we observed in cluster 1, suggesting that Trp metabolism plays a pivotal role in shaping an immunosuppressive microenvironment. We further examined the expression of immune checkpoint genes across various clusters. Intriguingly, a higher degree of suppression was observed in cluster 2 compared to cluster 1, suggesting that a favorable clinical outcome for cluster 2 may be achieved through immune checkpoint blockade rather than immune cell infiltration, and this is similar to the study by Luo P et al. on Trp metabolism in gastric cancer (Luo et al., 2023). Meanwhile, the TIDE score of cluster 1 was significantly higher than that of cluster 2, indicating that patients in cluster 1 are more likely to be refractory to immunotherapy, leading to a poorer prognosis. In the analysis of chemotherapeutic drug sensitivity between the two molecular subtypes, we found that patients in cluster 1 were more sensitive to drugs such as AZ628, AZD7762, CEP.701, KIN001.135, and Pazopanib, while patients in cluster 2 were more sensitive to rapamycin, Salubrinal, and Tipifarnib.

Our study suggests that high-risk LSCC patients may have a poorer response to immunotherapy, as indicated by higher TIDE scores and lower immune cell infiltration. While our findings are based on bioinformatics analysis and require experimental validation, they provide a potential framework for identifying patients who may benefit less from standard immunotherapy approaches. In clinical settings, this could help in stratifying patients for alternative or combination therapies. For instance, for high-risk patients, personalized immunotherapy strategies could be developed. In addition to conventional immunotherapy, combination treatments (such as chemotherapy, targeted therapy, or other immunotherapeutic approaches) could be considered to improve treatment outcomes. Future research should focus on validating these findings through prospective clinical trials and functional studies to explore the therapeutic potential of targeting specific TMRGs or immune checkpoints in LSCC.

Nevertheless, it is important to acknowledge certain limitations in our investigation. Firstly, the data utilized in our study were retrospectively collected from the TCGA and GEO databases. Therefore, the potential bias in case selection might affect the results. Secondly, these data were analyzed only by bioinformatics, and future investigations should include relevant in vivo and in vitro validation experiments to confirm the efficacy of risk modeling. In addition, the molecular mechanisms associated with Trp metabolism in LSCC remain to be further validated. In addition, the molecular mechanisms associated with Trp metabolism in LSCC remain to be further validated. Moreover, the sample size of our qRT-PCR validation was relatively small, which limits the robustness of our findings. Future studies should validate the identified TMRGs in larger patient cohorts. Furthermore, functional assays, such as gene knockdown or overexpression studies, are needed to establish the mechanistic roles of these genes in LSCC progression. Additionally, immunohistochemistry or Western blot analysis should be incorporated to verify protein-level expression and localization.

In this study, five TMRGs (SERPINA1, TMC8, RENBP, SDS and FAM107A) were identified to further establish a risk model, which had specifically good predictive performance, and can provide an effective method for evaluating the prognosis LSCC patients. The nomogram based on the five TMRGs can provide a concise and digital predictions to patients through simple calculations. Our study also reveals the clinical significance of Trp metabolism and its underlying association with LSCC, which may provide a new approach for personalized comprehensive treatment of LSCC patients.