Development and validation of a novel ferroptosis-related gene signature for predicting prognosis and immune microenvironment in head and neck squamous cell carcinoma

Ferroptosis-Related Gene Signatures: Prognostic Role in HPV-Positive Oropharyngeal Squamous Cell Carcinoma

BACKGROUND

Despite advances in the management of head and neck squamous cell carcinoma (HNSCC), prognostic models and treatment strategies remain inadequate, particularly for HPV-positive oropharyngeal squamous cell carcinoma (OPSCC). The rising incidence of HPV-positive OPSCC highlights an urgent need for innovative therapeutic approaches. Ferroptosis, a regulated form of non-apoptotic cell death, has gained attention for its role in cancer progression, but its potential as a prognostic and therapeutic target in HPV-positive OPSCC remains largely unexplored. This study investigates the role of ferroptosis in HPV-positive OPSCC, aiming to identify prognostic markers and provide insights into potential therapeutic strategies that could improve patient outcomes.

METHODS

Thirteen ferroptosis gene expression signatures were retrieved from the literature, and their performance and association to the immune microenvironment were validated on a meta-analysis of 267 HPV-positive cases (Metanalysis-HPV267) and 286 samples from the BD2Decide project (BD2-HPV286).

RESULTS

Our analysis revealed that specific ferroptosis-related gene expression signatures, particularly FER3, FER4, FER6, and FER12, are significantly associated (p-value < 0.05) with high-risk patient groups and adverse tumor microenvironment features, including suppressed immune activity and enhanced stromal involvement. Elevated expression of CAV1, a ferroptosis suppressor, further delineates high-risk profiles.

CONCLUSIONS

These findings highlight the prognostic significance of ferroptosis in stratifying patients and identifying those with poorer clinical outcomes. Targeting ferroptosis pathways represents a novel and promising approach to addressing the unmet need for effective prognostic and therapeutic strategies in HPV-positive OPSCC. Future research should focus on translating these findings into clinical applications to advance precision oncology and improve outcomes for this growing patient population.

Radiomics-based model for prediction of TGF-β1 expression in head and neck squamous cell carcinoma

OBJECTIVE

To explore the connection between TGF-β1 expression and the survival of patients with head and neck squamous cell carcinoma (HNSCC), as well as whether non-invasive CT-based Radiomics can predict TGF-β1 expression in HNSCC patients.

METHODS

Data on transcriptional profiling and clinical information were acquired from the TCGA database and subsequently categorized based on the TGF-β1 expression cutoff value. Based on the completeness of enhanced arterial phase CT scans, 139 HNSCC patients were selected. The PyRadiomics package was used to extract radiomic features, and the 3D Slicer software was used for image segmentation. Using the mRMR_RFE and Repeat LASSO algorithms, the optimal features for establishing the corresponding gradient enhancement prediction models were identified.

RESULTS

A survival analysis was performed on 483 patients, who were divided into two groups based on the TGF-β1 expression cut-off. The Kaplan-Meier curve indicated that TGF-β1 was a significant independent risk factor that reduced patient survival. To construct gradient enhancement prediction models, we used the mRMR_RFE algorithm and the Repeat_LASSO algorithm to obtain two features (glrlm and ngtdm) and three radiation features (glrlm, first order_10percentile, and gldm). In both the training and validation cohorts, the two established models demonstrated strong predictive potential. Furthermore, there was no statistically significant difference in the calibration curve, DCA diagram, or AUC values between the mRMR_RFE_GBM model and the LASSO_GBM model, suggesting that both models fit well.

CONCLUSION

Based on these findings, TGF-β1 was shown to be significantly associated with a poor prognosis and to be a potential risk factor for HNSCC. Furthermore, by employing the mRMR_RFE_GBM and Repeat_LASSO_GBM models, we were able to effectively predict TGF-β1 expression levels in HNSCC through non-invasive CT-based Radiomics.

Multiple Roles of Apolipoprotein E4 in Oxidative Lipid Metabolism and Ferroptosis During the Pathogenesis of Alzheimer's Disease

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide and has a great socio-economic impact. Modified oxidative lipid metabolism and dysregulated iron homeostasis have been implicated in the pathogenesis of this disorder, but the detailed pathophysiological mechanisms still remain unclear. Apolipoprotein E (APOE) is a lipid-binding protein that occurs in large quantities in human blood plasma, and a polymorphism of the APOE gene locus has been identified as risk factors for AD. The human genome involves three major APOE alleles (APOE2, APOE3, APOE4), which encode for three subtly distinct apolipoprotein E isoforms (APOE2, APOE3, APOE4). The canonic function of these apolipoproteins is lipid transport in blood and brain, but APOE4 allele carriers have a much higher risk for AD. In fact, about 60% of clinically diagnosed AD patients carry at least one APOE4 allele in their genomes. Although the APOE4 protein has been implicated in pathophysiological key processes of AD, such as extracellular beta-amyloid (Aβ) aggregation, mitochondrial dysfunction, neuroinflammation, formation of neurofibrillary tangles, modified oxidative lipid metabolism, and ferroptotic cell death, the underlying molecular mechanisms are still not well understood. As for all mammalian cells, iron plays a crucial role in neuronal functions and dysregulation of iron homeostasis has also been implicated in the pathogenesis of AD. Imbalances in iron homeostasis and impairment of the hydroperoxy lipid-reducing capacity induce cellular dysfunction leading to neuronal ferroptosis. In this review, we summarize the current knowledge on APOE4-related oxidative lipid metabolism and the potential role of ferroptosis in the pathogenesis of AD. Pharmacological interference with these processes might offer innovative strategies for therapeutic interventions.

Development of a novel head and neck squamous cell carcinoma prognostic signature by bulk/single-cell sequencing data integration

BACKGROUND

Identifying cell subpopulations conferring unfavorable prognosis in cancer holds clinical significance. Here, we sought to identify prognostic cell subsets and develop a novel, prognostic signature for head neck squamous cell carcinoma (HNSCC).

METHODS

Highly prognostic cell subpopulations in HNSCC were identified by integrating single-cell and bulk transcriptomic datasets. The prognostic signature and nomogram were developed by least absolute shrinkage and selection operator and multivariate Cox regression analyses based on significantly upregulated genes in this specific cell subpopulation, respectively. The qRT-PCR experiments were utilized for independent validation in our patient cohort.

RESULTS

A specific cancer cell subset associated with unfavorable prognoses was identified. Functional dissections revealed that its transcriptional programs were significantly enriched in E2F, epithelial-to-mesenchymal transition, and glycolysis. A novel prognostic signature comprising six genes was developed and further validated. Risk scores based on qRT-PCR data robustly stratified patients into subgroups with distinct prognoses. A nomogram integrated from this signature and clinical stage had superior performance.

CONCLUSION

Our model derived from integrative analyses of single-cell and bulk RNA-sequencing is a novel, robust prognostic biomarker for HNSCC.

Quantified pathway mutations associate epithelial-mesenchymal transition and immune escape with poor prognosis and immunotherapy resistance of head and neck squamous cell carcinoma

BACKGROUND

Pathway mutations have been calculated to predict the poor prognosis and immunotherapy resistance in head and neck squamous cell carcinoma (HNSCC). To uncover the unique markers predicting prognosis and immune therapy response, the accurate quantification of pathway mutations are required to evaluate epithelial-mesenchymal transition (EMT) and immune escape. Yet, there is a lack of score to accurately quantify pathway mutations.

MATERIAL AND METHODS

Firstly, we proposed Individualized Weighted Hallmark Gene Set Mutation Burden (IWHMB, https://github.com/YuHongHuang-lab/IWHMB ) which integrated pathway structure information and eliminated the interference of global Tumor Mutation Burden to accurately quantify pathway mutations. Subsequently, to further elucidate the association of IWHMB with EMT and immune escape, support vector machine regression model was used to identify IWHMB-related transcriptomic features (IRG), while Adversarially Regularized Graph Autoencoder (ARVGA) was used to further resolve IRG network features. Finally, Random walk with restart algorithm was used to identify biomarkers for predicting ICI response.

RESULTS

We quantified the HNSCC pathway mutation signatures and identified pathway mutation subtypes using IWHMB. The IWHMB-related transcriptomic features (IRG) identified by support vector machine regression were divided into 5 communities by ARVGA, among which the Community 1 enriching malignant mesenchymal components promoted EMT dynamically and regulated immune patterns associated with ICI responses. Bridge Hub Gene (BHG) identified by random walk with restart was key to IWHMB in EMT and immune escape, thus, more predictive for ICI response than other 70 public signatures.

CONCLUSION

In summary, the novel pathway mutation scoring-IWHMB suggested that the elevated malignancy mediated by pathway mutations is a major cause of poor prognosis and immunotherapy failure in HNSCC, and is capable of identifying novel biomarkers to predict immunotherapy response.

Baicalin induces ferroptosis in oral squamous cell carcinoma by suppressing the activity of FTH1

BACKGROUND

This study investigated the role of the ferroptosis-related gene FTH1 in oral squamous cell carcinoma (OSCC) and evaluated the therapeutic potential of baicalin in OSCC cell treatment.

METHODS

A prognostic model was established by bioinformatic analysis, consisting of 12 ferroptosis related genes (FRGs), and FTH1 was selected as the most significantly up-regulated FRGs. The clinical correlation of FTH1 in OSCC samples was evaluated by both immunohistochemical and bioinformatic characterizations. The effects of FTH1 on migration, invasion, epithelial-mesenchymal transition (EMT) and proliferation were determined by wound healing assays, transwell assays, western blotting and 5'-ethynl 2'-deoxyuridine proliferation assays, respectively. The effects of FTH1 on ferroptosis were tested via ferroptosis markers and Mito Tracker staining. In addition, the therapeutic effects of baicalin on OSCC cells were confirmed using EMT, migration, invasion, proliferation and ferroptosis assays.

RESULTS

The 12 FRGs were predictive of the prognosis for OSCC patients, and FTH1 expression was identified as significantly up-regulated in OSCC samples, which was highly associated with survival, immune cell infiltration and drug sensitivity. Moreover, knocking down FTH1 inhibited cell proliferation, EMT and invasive phenotypes, but induced ferroptosis in OSCC cells (Cal27 and SCC25). Furthermore, baicalin directly suppressed expression of FTH1 in OSCC cells, and effectively promoted ferroptosis and inhibited the proliferation as well as EMT by directly targeting FTH1.

CONCLUSIONS

This study has demonstrated that FTH1 is a therapeutic target for OSCC treatment, and has provided evidence that baicalin offers a promising alternative for OSCC treatment.

Exploring the frontiers: tumor immune microenvironment and immunotherapy in head and neck squamous cell carcinoma

The global prevalence of head and neck malignancies positions them as the sixth most common form of cancer, with the head and neck squamous cell carcinoma (HNSCC) representing the predominant histological subtype. Despite advancements in multidisciplinary approaches and molecular targeted therapies, the therapeutic outcomes for HNSCC have only marginally improved, particularly in cases of recurrent or metastatic HNSCC (R/MHNSCC). This situation underscores the critical necessity for the development of innovative therapeutic strategies. Such strategies are essential not only to enhance the efficacy of HNSCC treatment but also to minimize the incidence of associated complications, thus improving overall patient prognosis. Cancer immunotherapy represents a cutting-edge cancer treatment that leverages the immune system for targeting and destroying cancer cells. It's applied to multiple cancers, including melanoma and lung cancer, offering precision, adaptability, and the potential for long-lasting remission through immune memory. It is observed that while HNSCC patients responsive to immunotherapy often experience prolonged therapeutic benefits, only a limited subset demonstrates such responsiveness. Additionally, significant clinical challenges remain, including the development of resistance to immunotherapy. The biological characteristics, dynamic inhibitory changes, and heterogeneity of the tumor microenvironment (TME) in HNSCC play critical roles in its pathogenesis, immune evasion, and therapeutic resistance. This review aims to elucidate the functions and mechanisms of anti-tumor immune cells and extracellular components within the HNSCC TME. It also introduces several immunosuppressive agents commonly utilized in HNSCC immunotherapy, examines factors influencing the effectiveness of these treatments, and provides a comprehensive summary of immunotherapeutic strategies relevant to HNSCC.

MTDH enhances radiosensitivity of head and neck squamous cell carcinoma by promoting ferroptosis based on a prognostic signature

Ionizing radiation (IR) induces ferroptosis in head and neck squamous cell carcinoma (HNSCC). But, it remains unclear whether ferroptosis affects the prognosis of HNSCC patients after receiving radiotherapy. This study aims to develop a ferroptosis signature to predict the radiosensitivity and prognosis of HNSCC. Ferroptosis-related genes, clinical data and RNA expression profiles were obtained from the FerrDb database, The Cancer Genome Atlas and GEO database. Prognostic genes were identified by random survival forest, univariate Cox regression, Kaplan-Meier and ROC analyses. Principal component analysis, multivariate Cox regression, nomogram and DCA analyses were conducted to estimate its predictive ability. Functional enrichment and immune-related analyses were performed to explore potential biological mechanisms and tumor immune microenvironment. The effect of the hub gene on ferroptosis and radiosensitivity was verified using flow cytometry, quantitative real-time PCR and clonogenic survival assay. We constructed a ferroptosis-related signature, including IL6, NCF2, metadherin (MTDH) and CBS. We classified patients into high-risk (HRisk) and low-risk groups according to the risk scores. The risk score was confirmed to be an independent predictor for overall survival (OS). Combining the clinical stage with the risk score, we established a predictive nomogram for OS. Furthermore, pathways related to tumorigenesis and tumor immune suppression were mainly enriched in HRisk. MTDH was verified to have a potent effect on IR-induced ferroptosis and consequently promoted radiosensitivity. We constructed a ferroptosis-related signature to predict radiosensitivity and OS in HNSCC patients. MTDH was identified as a promising therapeutic target in radioresistant HNSCC patients.

An EMT-Related Gene Signature to Predict the Prognosis of Triple-Negative Breast Cancer

INTRODUCTION

Epithelial-mesenchymal transition (EMT) is an important biological process in tumor invasion and metastasis, and thus a potential indicator of the progression and drug resistance of breast cancer. This study comprehensively analyzed EMT-related genes in triple-negative breast cancer (TNBC) to develop an EMT-related prognostic gene signature.

METHODS

With the application of The Cancer Genome Atlas (TCGA) database, Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and the Genotype-Tissue Expression (GTEx) database, we identified EMT-related signature genes (EMGs) by Cox univariate regression and LASSO regression analysis. Risk scores were calculated and used to divide patients with TNBC into high-risk group and low-risk groups by the median value. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were applied for model validation. Independent prognostic predictors were used to develop nomograms. Then, we assessed the risk model in terms of the immune microenvironment, genetic alteration and DNA methylation effects on prognosis, the probability of response to immunotherapy and chemotherapy, and small molecule drugs predicted by The Connectivity Map (Cmap) database.

RESULTS

Thirteen EMT-related genes with independent prognostic value were identified and used to stratify the patients with TNBC into high- and low-risk groups. The survival analysis revealed that patients in the high-risk group had significantly poorer overall survival than patients in the low-risk group. Populations of immune cells, including CD4 memory resting T cells, CD4 memory activated T cells, and activated dendritic cells, significantly differed between the high- and low-risk groups. Moreover, some therapeutic drugs to which the high-risk group might show sensitivity were identified.

CONCLUSIONS

Our research identified the significant impact of EMGs on prognosis in TNBC, providing new strategies for personalizing TNBC treatment and improving clinical outcomes.

Identification of molecular subgroups and establishment of risk model based on the response to oxidative stress to predict overall survival of patients with lung adenocarcinoma

OBJECTIVE

Oxidative stress is associated with the occurrence and development of lung cancer. However, the specific association between lung cancer and oxidative stress is unclear. This study aimed to investigate the role of oxidative stress in the progression and prognosis of lung adenocarcinoma (LUAD).

METHODS

The gene expression profiles and corresponding clinical information were collected from GEO and TCGA databases. Differentially expressed oxidative stress-related genes (OSRGs) were identified between normal and tumor samples. Consensus clustering was applied to identify oxidative stress-related molecular subgroups. Functional enrichment analysis, GSEA, and GSVA were performed to investigate the potential mechanisms. xCell was used to assess the immune status of the subgroups. A risk model was developed by the LASSO algorithm and validated using TCGA-LUAD, GSE13213, and GSE30219 datasets.

RESULTS

A total of 40 differentially expressed OSRGs and two oxidative stress-associated subgroups were identified. Enrichment analysis revealed that cell cycle-, inflammation- and oxidative stress-related pathways varied significantly in the two subgroups. Furthermore, a risk model was developed and validated based on the OSRGs, and findings indicated that the risk model exhibits good prediction and diagnosis values for LUAD patients.

CONCLUSION

The risk model based on the oxidative stress could act as an effective prognostic tool for LUAD patients. Our findings provided novel genetic biomarkers for prognosis prediction and personalized clinical treatment for LUAD patients.

The identification of tumor antigens and immune subtypes based on the development of immunotherapies targeting head and neck squamous cell carcinomas resulting from periodontal disease

Among cancer treatments, immunotherapy is considered a promising strategy. Nonetheless, only a small number of individuals with head and neck squamous cell carcinoma exhibit positive responses to immunotherapy. This study aims to discover possible antigens for head and neck squamous cell carcinoma, create an mRNA vaccine for this type of cancer, investigate the connection between head and neck squamous cell carcinoma and periodontal disease, and determine the immune subtype of cells affected by head and neck squamous cell carcinoma. To ascertain gene expression profiles and clinical data corresponding to them, an examination was carried out on the TCGA database. Antigen-presenting cells were detected using TIMER. Targeting six immune-related genes (CXCL5, ADM, FGF9, AIMP1, STC1, and CDKN2A) in individuals diagnosed with head and neck squamous cell carcinoma has shown promising results in immunotherapy triggered by periodontal disease. These genes have been linked to improved prognosis and increased immune cell infiltration. Additionally, CXCL5, ADM, FGF9, AIMP1, STC1, and CDKN2A exhibited potential as antigens in the creation of an mRNA vaccine. A nomogram model containing ADM expression and tumor stage was constructed for clinical practice. To summarize, ADM shows potential as a candidate biomarker for predicting the prognosis, molecular features, and immune characteristics of head and neck squamous cell carcinoma cells. Our results, obtained through real-time PCR analysis, showed a significant upregulation of ADM in the SCC-25 cell line compared to the NOK-SI cell line. This suggests that ADM might be implicated in the pathogenesis of HNSC, highlighting the potential of ADM as a target in HNSC treatment. However, further research is needed to elucidate the functional role of ADM in HNSC. Our findings provide a basis for the further exploration of the molecular mechanisms underlying HNSC and could help develop novel therapeutic strategies.

The pyroptotic role of Caspase-3/GSDME signalling pathway among various cancer: A Review

Cytotoxic drugs have long been recognised to kill cancer cells through apoptosis. According to a current study, pyroptosis inhibits cell proliferation and shrinks tumors. Pyroptosis and apoptosis are caspase-dependent programmed cell death (PCD) processes. Inflammasomes activate caspase-1 and latent cytokines, including IL-1β and IL-18, to cleave gasdermin E (GSDME) and induce pyroptosis. Gasdermin proteins activate caspase-3 to induce pyroptosis, which is associated with tumour genesis, development, and therapy response. These proteins may serve as therapeutic biomarkers for cancer detection, and their antagonists may be a new target. Caspase-3, a crucial protein in both pyroptosis and apoptosis, governs tumour cytotoxicity when activated, and GSDME expression modulates this. Once active caspase-3 cleaves GSDME, its N-terminal domain punches holes in the cell membrane, causing it to expand, burst, and die. To understand the cellular and molecular mechanisms of PCD mediated by caspase-3 and GSDME, we focused on pyroptosis. Hence, caspase-3 and GSDME may be promising targets for cancer treatment.

Integrative analyses of ferroptosis and immune related biomarkers and the osteosarcoma associated mechanisms

Osteosarcoma (OS) is the most common primary malignant bone tumor with high metastatic potential and relapse risk. To study the regulatory mechanism of the OS microenvironment, a complex regulatory network involving the ferroptosis- and immune response-related genes remains to be established. In the present study, we determined the effect of a comprehensive evaluation system established on the basis of ferroptosis- and immune-related genes on the immune status, related biomarkers, prognosis, and the potential regulatory networks underlying OS based on the TARGET and Gene Expression Omnibus databases that contain information on OS patients by bioinformatics analyses. We first characterized individual ferroptosis scores and immune scores through gene set variation analysis (GSVA) against TARGET-OS datasets. We then identified differentially expressed genes by score groups. Weighted gene co-expression network analysis was performed to identify the most relevant ferroptosis-related and immune-related gene modules, which facilitated the identification of 327 ferroptosis gene and 306 immune gene candidates. A 4-gene (WAS, CORT, WNT16, and GLB1L2) signature was constructed and valuation using the least absolute shrinkage and selection operator-Cox regression models to effectively predict OS prognosis. The prediction efficiency was further validated by GSE39055. We stratified patients based on the prognostic scoring systems. Eight hub genes (namely CD3D, CD8A, CD3E, IL2, CD2, MYH6, MYH7, and MYL2) were identified, and TF-miRNA target regulatory networks were constructed. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and GSVA were used to determine the signature's potential pathways and biological functions, which showed that the hub genes were enriched in ferroptosis-associated biological functions and immune-associated molecular mechanisms. Thereafter, we investigated the proportion and infiltration extent of 22 infiltrating immune cells by using CIBERSORT, which revealed significant subgroup differences in CD8 + T cells, M0 macrophages, and M2 macrophages. In conclusion, we determined a new ferroptosis-related and immune-related gene signature for predicting OS patients' prognosis and further explored the ferroptosis and immunity interactions during OS development, which provides insights into the exploration of molecular mechanisms and targeted therapies in patients with OS.

Development and validation of a novel anoikis-related gene signature for predicting prognosis in ovarian cancer

Anoikis plays a critical role in variable cancer types. However, studies that focus on the prognostic values of anoikis-related genes (ANRGs) in OV are scarce. Cohorts with transcriptome data and corresponding clinicopathologic data of OV patients were collected and consolidated from public databases. Multiple bioinformatics approaches were used to screen key genes from 446 anoikis-related genes, including Cox regression analysis, random survival forest analysis, and Kaplan-Meier analysis of best combinations. A five-gene signature was constructed in the discovery cohort (TCGA) and validated in four validation cohorts (GEO). Risk score of the signature stratified patients into high-risk (HRisk) and low-risk (LRisk) subgroups. Patients in the HRisk group were associated with worse OS than those in the LRisk group in both the TCGA cohort (p<0.0001, HR=2.718, 95%CI:1.872-3.947) and the four GEO cohorts (p<0.05). Multivariate Cox regression analyses confirmed that the risk score served as an independent prognostic factor in both cohorts. The signature's predictive capacity was further demonstrated by the nomogram analysis. Pathway enrichment analysis revealed that immunosuppressive and malignant progression-related pathways were enriched in the HRisk group, including TGF-β, WNT and ECM pathways. The LRisk group was characterized by immune-active signaling pathways (interferon-gamma, T cell activation, etc.) and higher proportions of anti-tumor immune cells (NK, M1, etc.) while HRisk patients were associated with higher stromal scores and less TCR richness. In conclusion, the signature reveals a close relationship between the anoikis and prognosis and may provide a potential therapeutic target for OV patients.

The Concordant Disruption of B7/CD28 Immune Regulators Predicts the Prognosis of Oral Carcinomas

Immune modulation is a critical factor in determining the survival of patients with malignancies, including those with oral squamous cell carcinoma (OSCC) and head and neck SCC (HNSCC). Immune escape or stimulation may be driven by the B7/CD28 family and other checkpoint molecules, forming ligand-receptor complexes with immune cells in the tumor microenvironment. Since the members of B7/CD28 can functionally compensate for or counteract each other, the concomitant disruption of multiple members of B7/CD28 in OSCC or HNSCC pathogenesis remains elusive. Transcriptome analysis was performed on 54 OSCC tumors and 28 paired normal oral tissue samples. Upregulation of CD80, CD86, PD-L1, PD-L2, CD276, VTCN1, and CTLA4 and downregulation of L-ICOS in OSCC relative to the control were noted. Concordance in the expression of CD80, CD86, PD-L1, PD-L2, and L-ICOS with CD28 members was observed across tumors. Lower ICOS expression indicated a worse prognosis in late-stage tumors. Moreover, tumors harboring higher PD-L1/ICOS, PD-L2/ICOS, or CD276/ICOS expression ratios had a worse prognosis. The survival of node-positive patients was further worsened in tumors exhibiting higher ratios between PD-L1, PD-L2, or CD276 and ICOS. Alterations in T cell, macrophage, myeloid dendritic cell, and mast cell populations in tumors relative to controls were found. Decreased memory B cells, CD8⁺ T cells, and Tregs, together with increased resting NK cells and M0 macrophages, occurred in tumors with a worse prognosis. This study confirmed frequent upregulation and eminent co-disruption of B7/CD28 members in OSCC tumors. The ratio between PD-L2 and ICOS is a promising survival predictor in node-positive HNSCC patients.

Special transcriptome landscape and molecular prognostic signature of non-smoking head and neck cancer patients

As a well-known behavioral risk factor for human health, smoking is involved in carcinogenesis, tumor progression, and therapeutic interventions of head and neck squamous cell carcinoma (HNSCC). The stratification of disease subtypes according to tobacco use is expressively needed for HNSCC precision therapy. High-throughput transcriptome profiling by RNA sequencing (RNA-seq) from The Cancer Genome Atlas (TCGA) was collected and collated for differential expression analysis and pathway enrichment analysis to characterize the molecular landscape for non-smoking HNSCC patients. Molecular prognostic signatures specific to non-smoking HNSCC patients were identified by the least absolute shrinkage and selection operator (LASSO) analysis and were then verified via internal and external validation cohorts. While proceeding to immune cell infiltration and after drug sensitivity analysis was further carried out, a proprietary nomogram was finally developed for their respective clinical applications. In what it relates to the non-smoking cohort, the enrichment analysis pointed to human papillomavirus (HPV) infection and PI3K-Akt signaling pathway, with the prognostic signature consisting of another ten prognostic genes (COL22A1, ADIPOQ, RAG1, GREM1, APBA2, SPINK9, SPP1, ARMC4, C6, and F2RL2). These signatures showed to be independent factors, and the related nomograms were, thus, constructed for their further and respective clinical applications. While the molecular landscapes and proprietary prognostic signature were characterized based on non-smoking HNSCC patients, a clinical nomogram was constructed to provide better HNSCC patient classification and guide treatment for non-smoking HNSCC patients. Nonetheless, there are still significant challenges in the recognition, diagnosis, treatment, and understanding of the potentially efficient mechanisms of HNSCC with no tobacco use.

Discovery of novel 2-oximino-2-indolylacetamide derivatives as potent anticancer agents capable of inducing cell autophagy and ferroptosis

A series of 2-oximino-2-indolylacetamide derivatives were designed, synthesized and evaluated for their antitumour effects. Among them, 4d exhibited the most potent antiproliferative effect in vitro on the tested human cancer cells. Additionally, 4d significantly induced cell apoptosis, caused mitochondrial dysfunction, promoted Bax, cleaved-PARP and p53 expression and inhibited Bcl-2 expression in 5-8F cells. Moreover, 4d remarkably promoted autophagosome formation, leading to cell apoptosis. Further investigation indicated that 4d could trigger cell death through cell ferroptosis, including increased ROS generation and lipid peroxidation and decreased glutathione peroxidase 4 (GPx4) expression and glutathione (GSH) levels. More importantly, 4d induced 5-8F cell death by activating ROS/MAPK and inhibiting the AKT/mTOR and STAT3 signalling pathways. Interestingly, 4d significantly suppressed tumour growth in a 5-8F cell xenograft model without obvious toxicity to mice. Overall, these results demonstrate that 4d may be a potential compound for cancer therapy.

Exploration of the heterogeneity and interaction of epithelial cells and NK/T-cells in Laryngeal Squamous Cell Carcinoma based on single-cell RNA sequencing data

OBJECTIVES

We aimed to explore the heterogeneity and differentiation trajectories of epithelial cells and NK/T-cells in Laryngeal Squamous Cell Carcinoma (LSCC).

METHODS

We downloaded the GSE150321 data set containing LSCC01 and LSCC02 samples single cell RNA data from Gene Expression Omnibus. The UMAP analysis was performed to identify the cell subpopulations and cell locations of subpopulations. Seurat package was used to analyze the differential expression of genes. The function of differential expression genes was analyzed using DAVID database. The monocle2 package was used to analyze differentiation trajectories. We used the CellChat package to observe the signaling pathways and ligand-receptor pairs for epithelial cells and NK/T-cells.

RESULTS

All the LSCC cells were divided into 16 subpopulation that included 7 epithelial cell subsets, 3 T-cell subsets. The function analysis indicated that epithelial cells and NK/T-cells mainly participated in different process, such as cell cycle, immune response, and cell migration. Then, the results of differentiation trajectory indicated that the ability of migration, and the activation of the immune system increases, while the ability of apoptosis, and glucose metabolic process decreases as pseudotime. Migration-related epithelial cells act on all T-cells via the CNTN2-CNTN2 ligand-receptor pair, which suggested that CNTN2 might be an important biomarker for regulating migration of epithelial cells.

CONCLUSIONS

Our study characterized the heterogeneity of LSCC, which provided novel insights into LSCC and identified a new mechanism and target for clinical LSCC threapies.

EVIDENCE

IV.

Ferroptosis Biomarkers for Predicting Prognosis and Immunotherapy Efficacy in Adrenocortical Carcinoma

BACKGROUND

Numerous studies have suggested that ferroptosis plays an important regulatory role in cancer cell death. Nonetheless, the potential effects of ferroptosis regulators on the prognosis, the expression of immunomodulatory factors in the tumor microenvironment and on the efficacy of immunotherapy in adrenocortical carcinoma (ACC) remain largely unknown.

METHODS

Public ACC datasets were used to investigate the relationship between ferroptosis regulators and prognosis and clinical features. A ferroptosis scoring system was established for individual cases of ACC using principal component analysis algorithms. Hub ferroptosis-related genes involved in immunoregulation and immunotherapy efficacy in ACC were further identified.

RESULTS

Twenty ferroptosis regulators were differentially expressed in ACC and 17 ferroptosis regulators were closely related to prognosis in ACC. A ferroptosis scoring system was developed based on ACSL4, FANCD2, and SLC7A1 expression, and the ferroptosis regulators could serve as an independent prognostic factor for ACC. Further analyses indicated that the ferroptosis score integrated with the tumor mutation burden (TMB), and immune-checkpoint gene expression could predict prognosis in ACC. RNA isolation and reverse transcription‑quantitative polymerase chain reaction (RT-qPCR) demonstrated significant differences in the expression levels of ACSL4, FANCD2, and SLC7A1 between ACC and normal tissues. Furthermore, FANCD2 was significantly related to immunotherapy efficacy and prognosis in ACC.

CONCLUSION

Our study demonstrated that ferroptosis was significantly associated with prognosis, clinical characteristics, immune-checkpoint gene expression, and tumor microenvironment immune cell infiltration in ACC. The current study provides comprehensive evidence for further research on ferroptosis regulators in ACC and provides new insight into the epigenetic regulation of the antitumor immune response.

FAM3D as a Prognostic Indicator of Head and Neck Squamous Cell Carcinoma Is Associated with Immune Infiltration

Background

Globally, head and neck squamous cell carcinoma (HNSCC) is a common malignant tumor with high morbidity and mortality. Hence, it is important to find effective biomarkers for the diagnosis and prediction of the prognosis of patients with HNSCC. FAM3D had been proven to be vital in other cancers. However, its predictive and therapeutic value in HNSCC is unclear. Therefore, it is valuable to explore the association between the expression level of FAM3D and its impacts on the prognosis and tumor microenvironment in HNSCC.

Methods

The Cancer Genome Atlas (TCGA) dataset, Genotype-Tissue Expression (GTEx) dataset, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset, and The Human Protein Atlas (THPA) website were used to assess HNSCC expressions in tumor and nontumor tissues. Then, we further conducted immunohistochemistry experiment as internal cohort to validate the same results. The Cox regression analysis, Kaplan-Meier analysis, and nomograms were performed to find the predictive prognostic value of FAM3D in HNSCC patients and its relationship with the clinicopathological features in HNSCC. The Gene Expression Omnibus (GEO) dataset was utilized to externally verify the prognosis value of FAM3D in HNSCC. Gene Set Enrichment Analysis (GESA) was applied to search the molecular and biological functions of FAM3D. The association between FAM3D and immune cell infiltration was investigated with the Tumor Immune Estimating Resource, version 2 (TIMER2). The relationships between FAM3D expression and tumor microenvironment (TME) scores, immune checkpoints, and antitumor compound half-maximal inhibitory concentration predictions were also explored.

Results

In different datasets, FAM3D mRNA and protein levels were all significantly lower in HNSCC tissues than in normal tissues, and they were strongly inversely associated with tumor grade, stage, lymph node metastasis, and T stage. Patients with high-FAM3D-expression displayed better prognosis than those with low-FAM3D-expression. FAM3D was also determined to be a suitable biomarker for predicting the prognosis of patients with HNSCC. This was externally validated in the GEO dataset. As for gene and protein level, the functional and pathway research results of FAM3D indicated that it was enriched in alteration of immune-related pathways in HNSCC. The low-expression group had higher stromal and ESTIMATE scores by convention than the high-expression group. FAM3D expression were found to be positively correlated with immune infiltrating cells, such as cancer-associated fibroblasts, myeloid-derived suppressor cells, macrophage cells, T cell CD8+ cells, regulatory T cells, and T cell follicular helper cells. FAM3D's relationships with immune checkpoints and sensitivity to antitumor drugs were also investigated.

Conclusion

Our study explored the impact of FAM3D as a favorable prognostic marker for HNSCC on the tumor immune microenvironment from multiple perspectives. The results may provide new insights into HNSCC-targeted immunotherapy.

Identification of cuproptosis-related subtypes, construction of a prognosis model, and tumor microenvironment landscape in gastric cancer

Introduction

Cuproptosis is a novel identified regulated cell death (RCD), which is correlated with the development, treatment response and prognosis of cancer. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of gastric cancer (GC) remains unknown.

Methods

Transcriptome profiling, somatic mutation, somatic copy number alteration and clinical data of GC samples were downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database to describe the alterations of CRGs from genetic and transcriptional fields. Differential, survival and univariate cox regression analyses of CRGs were carried out to investigate the role of CRGs in GC. Cuproptosis molecular subtypes were identified by using consensus unsupervised clustering analysis based on the expression profiles of CRGs, and further analyzed by GO and KEGG gene set variation analyses (GSVA). Genes in distinct molecular subtypes were also analyzed by GO and KEGG gene enrichment analyses (GSEA). Differentially expressed genes (DEGs) were screened out from distinct molecular subtypes and further analyzed by GO enrichment analysis and univariate cox regression analysis. Consensus clustering analysis of prognostic DEGs was performed to identify genomic subtypes. Next, patients were randomly categorized into the training and testing group at a ratio of 1:1. CRG Risk scoring system was constructed through logistic least absolute shrinkage and selection operator (LASSO) cox regression analysis, univariate and multivariate cox analyses in the training group and validated in the testing and combined groups. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to evaluate the expression of key Risk scoring genes. Sensitivity and specificity of Risk scoring system were examined by using receiver operating characteristic (ROC) curves. pRRophetic package in R was used to investigate the therapeutic effects of drugs in high- and low- risk score group. Finally, the nomogram scoring system was developed to predict patients' survival through incorporating the clinicopathological features and CRG Risk score.

Results

Most CRGs were up-regulated in tumor tissues and showed a relatively high mutation frequency. Survival and univariate cox regression analysis revealed that LIAS and FDX1 were significantly associated with GC patients' survival. After consensus unsupervised clustering analysis, GC patients were classified into two cuproptosis molecular subtypes, which were significantly associated with clinical features (gender, age, grade and TNM stage), prognosis, metabolic related pathways and immune cell infiltration in TME of GC. GO enrichment analyses of 84 DEGs, obtained from distinct molecular subtypes, revealed that DEGs primarily enriched in the regulation of metabolism and intracellular/extracellular structure in GC. Univariate cox regression analysis of 84 DEGs further screened out 32 prognostic DEGs. According to the expression profiles of 32 prognostic DEGs, patients were re-classified into two gene subtypes, which were significantly associated with patients' age, grade, T and N stage, and survival of patients. Nest, the Risk score system was constructed with moderate sensitivity and specificity. A high CRG Risk score, characterized by decreased microsatellite instability-high (MSI-H), tumor mutation burden (TMB) and cancer stem cell (CSC) index, and high stromal and immune score in TME, indicated poor survival. Four of five key Risk scoring genes expression were dysregulated in tumor compared with normal samples. Moreover, CRG Risk score was greatly related with sensitivity of multiple drugs. Finally, we established a highly accurate nomogram for promoting the clinical applicability of the CRG Risk scoring system.

Discussion

Our comprehensive analysis of CRGs in GC demonstrated their potential roles in TME, clinicopathological features, and prognosis. These findings may improve our understanding of CRGs in GC and provide new perceptions for doctors to predict prognosis and develop more effective and personalized therapy strategies.

Immunometabolism in the tumor microenvironment and its related research progress

The tumor immune microenvironment has been a research hot spot in recent years. The cytokines and metabolites in the microenvironment can promote the occurrence and development of tumor in various ways and help tumor cells get rid of the surveillance of the immune system and complete immune escape. Many studies have shown that the existence of tumor microenvironment is an important reason for the failure of immunotherapy. The impact of the tumor microenvironment on tumor is a systematic study. The current research on this aspect may be only the tip of the iceberg, and a relative lack of integrity, may be related to the heterogeneity of tumor. This review mainly discusses the current status of glucose metabolism and lipid metabolism in the tumor microenvironment, including the phenotype of glucose metabolism and lipid metabolism in the microenvironment; the effects of these metabolic methods and their metabolites on three important immune cells Impact: regulatory T cells (Tregs), tumor-associated macrophages (TAM), natural killer cells (NK cells); and the impact of metabolism in the targeted microenvironment on immunotherapy. At the end of this article,the potential relationship between Ferroptosis and the tumor microenvironment in recent years is also briefly described.

Identification of ATG7 as a Regulator of Proferroptosis and Oxidative Stress in Osteosarcoma

Background

Ferroptosis has gained significant attention from oncologists as a vital outcome of oxidative stress. The aim of this study was to develop a prognostic signature that was based on the ferroptosis-related genes (FRGs) for osteosarcoma patients and explore their specific role in osteosarcoma.

Methods

The training cohort dataset was extracted from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Different techniques like the univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, multivariate Cox regression analyses, and the Kaplan-Meier (KM) survival analyses were utilized to develop a prognostic signature. Then, the intrinsic relationship between the developed gene signature and the infiltration levels of the immune cells was further investigated. An external validation dataset from the Gene Expression Omnibus (GEO) database was employed to assess the predictive ability of the developed gene signature. Subsequently, the specific function of potential FRG in affecting the oxidative stress reaction and ferroptosis of osteosarcoma cells was identified.

Results

A prognostic signature based on 5 FRGs (CBS, MUC1, ATG7, SOCS1, and PEBP1) was developed, and the patients were classified into the low- and high-risk groups (categories). High-risk patients displayed poor overall survival outcomes. The risk level was seen to be an independent risk factor for determining the prognosis of osteosarcoma patients (p < 0.001, hazard ratio: 7.457, 95% CI: 3.302-16.837). Additionally, the risk level was associated with immune function, which might affect the survival status of osteosarcoma patients. Moreover, the findings of the study indicated that the expression of ATG7 was related to the regulation of oxidative stress in osteosarcoma. Silencing the ATG7 gene promoted the proliferation and migration in osteosarcoma cells, suppressing the oxidative stress and ferroptosis process.

Conclusions

A novel FRG signature was developed in this study to predict the prognosis of osteosarcoma patients. The results indicated that ATG7 might regulate the process of oxidative stress and ferroptosis in osteosarcoma cells and could be used as a potential target to develop therapeutic strategies for treating osteosarcoma.

A multifaceted and feasible prognostic model of amino acid metabolism-related genes in the immune response and tumor microenvironment of head and neck squamous cell carcinomas

We investigated the role of amino acid metabolism (AAM) in head and neck squamous cell carcinoma (HNSCC) tissues to explore its prognostic value and potential therapeutic strategies. A risk score based on four AAM-related genes (AMG) was constructed that could predict the prognosis of HNSCC. These four genes were up-regulated in HNSCC tissues and might act as oncogenes. Internal validation in The Cancer Genome Atlas (TCGA) by bootstrapping showed that patients with high-risk scores had a poorer prognosis than patients with low-risk scores, and this was confirmed in the Gene Expression Omnibus (GEO) cohort. There were also differences between the high-risk and low-risk groups in clinical information and different anatomical sites such as age, sex, TNM stage, grade stage, surgery or no surgery, chemotherapy, radiotherapy, no radiotherapy, neck lymph node dissection or not, and neck lymphovascular invasion, larynx, overlapping lesion of lip, and oral cavity and pharynx tonsil of overall survival (OS). Immune-related characteristics, tumor microenvironment (TME) characteristics, and immunotherapy response were significantly different between high- and low-risk groups. The four AMGs were also found to be associated with the expression of markers of various immune cell subpopulations. Therefore, our comprehensive approach revealed the characterization of AAM in HNSCC to predict prognosis and guide clinical therapy.

NXPH4 Used as a New Prognostic and Immunotherapeutic Marker for Muscle-Invasive Bladder Cancer

Background

One of the most common malignant tumors of the urinary system is muscle-invasive bladder cancer (MIBC). With the increased use of immunotherapy, its importance in the field of cancer is becoming abundantly evident. This study classifies MIBC according to GSVA score from the perspective of the GSEA immune gene set.

Methods

This study integrated the sequencing and clinical data of MIBC patients in TCGA and GEO databases, then scored the data using the GSVA algorithm, the CNMF algorithm was implemented to divide the subtypes of GEO and TCGA datasets, respectively, and finally screened and determined the key pathways in combination with clinical data. Simultaneously, LASSO Cox regression model was constructed based on key pathway genes to assess the model's predictive ability (ROC) and describe the immune landscape differences between high- and low-risk groups; key genes were further analyzed and verified in patient tissues.

Results

404 TCGA and 297 GEO datasets were divided into C1-3 groups (TCGA-C1:120/C2:152/C3:132; GEO- C1:112/C2:101/C3:84), of which TCGA-C2 (n = 152) subtype and GEO-C1 (n = 112) subtype had the worst prognosis. LASSO Cox regression model with ROC (train set = 0.718, test set = 0.667) could be constructed. When combined with the Cancer Immunome Atlas database, it was found that patients with high-risk scores were more sensitive to PD-1 inhibitor and PD-1 inhibitor combined with CTLA-4. NXPH4, as a key gene, plays a role in MIBC with tissue validation results show that nxph4 is highly expressed in tumor.

Conclusion

The immune gene score of MIBC data in TCGA and GEO databases was successfully evaluated using GSVA in this research. The lasso Cox expression model was successfully constructed by screening immune genes, the high-risk group had a worse prognosis and higher sensitivity to immunotherapy, PD-1 inhibitors or PD-1 combined with CTLA-4 inhibitors can be preferentially used in high-risk patients who are sensitive to immunotherapy, and NXPH4 may be a molecular target to adjust the effect of immunotherapy.

Integrated Machine Learning and Single-Sample Gene Set Enrichment Analysis Identifies a TGF-Beta Signaling Pathway Derived Score in Headneck Squamous Cell Carcinoma

Background

The TGF-β signaling pathway is clinically predictive of pan-cancer. Nevertheless, its clinical prognosis and regulation of immune microenvironment (TME) characteristics as well as the prediction of immunotherapy efficacy need to be further elucidated in head and neck squamous cell carcinoma.

Method

At first, we summarized TGF-β related genes from previous published articles, used ssGSEA to establish the TGF-β risk score. Considering the complexity of its clinical application, we improved it with the LASSO-COX algorithm to construct the model. In addition, we explored the predictive efficacy of TGF-β risk score in the observation of TME phenotype and immunotherapy effect. Finally, the potency of TGF-β risk score in adjusting precise treatment of HNSC was evaluated.

Results

We systematically established TGF-β risk score with multi-level predictive ability. TGF-β risk score was employed to predict the tumor microenvironment status, which was negatively associated with NK cells but positively related to macrophages and fibroblasts. It reveals that patients with high TGF-β risk score predict “cold” TME status. In addition, higher risk scores indicate higher sensitivity to immunotherapy.

Conclusion

We first construct and validate TGF-β characteristics that can predict immune microenvironment phenotypes and immunotherapeutic effect in multiple datasets. Noteworthy, TGF-β risk score is helpful for individualized precise treatment of patients with the head and neck squamous cell carcinoma.

A cuproptosis and copper metabolism–related gene prognostic index for head and neck squamous cell carcinoma

Background

The purpose of this study was to identify the prognostic value of cuproptosis and copper metabolism–related genes, to clarify their molecular and immunological characteristics, and to elucidate their benefits in head and neck squamous cell carcinoma (HNSCC).

Methods

The details of human cuproptosis and copper metabolism–related genes were searched and filtered from the msigdb database and the latest literature. To identify prognostic genes associated with cuproptosis and copper metabolism, we used least absolute shrinkage and selection operator regression, and this coefficient was used to set up a prognostic risk score model. HNSCC samples were divided into two groups according to the median risk. Afterwards, the function and immune characteristics of these genes in HNSCC were analyzed.

Results

The 14-gene signature was constructed to classify HNSCC patients into low-risk and high-risk groups according to the risk level. In the The Cancer Genome Atlas (TCGA) cohort, the overall survival (OS) rate of the high-risk group was lower than that of the low-risk group (P &lt; 0.0001). The area under the curve of the time-dependent Receiver Operator Characteristic (ROC) curve assessed the good performance of the genetic signature in predicting OS and showed similar performance in the external validation cohort. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment assays and Protein-Protein Interaction (PPI) protein networks have been used to explore signaling pathways and potential mechanisms that were markedly active in patients with HNSCC. Furthermore, the 14 cuproptosis and copper metabolism-related genes were significantly correlated with the immune microenvironment, suggesting that these genes may be linked with the immune regulation and development of HNSCC.

Conclusions

Our results emphasize the significance of cuproptosis and copper metabolism as a predictive biomarker for HNSCC, and its expression levels seem to be correlated with immune- related features; thus, they may be a possible biomarker for HNSCC prognosis.

A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma

Background

In the era of immunotherapy, predictive or prognostic biomarkers for head and neck squamous cell carcinoma (HNSCC) are urgently needed. Metabolic reprogramming in the tumor microenvironment (TME) is a non-negligible reason for the low therapeutic response to immune checkpoint inhibitor (ICI) therapy. We aimed to construct a metabolism-related gene prognostic index (MRGPI) for HNSCC bridging metabolic characteristics and antitumor immune cycling and identified the immunophenotype, genetic alternations, potential targeted inhibitors, and the benefit of immunotherapy in MRGPI-defined subgroups of HNSCC.

Methods

Based on The Cancer Genome Atlas (TCGA) HNSCC dataset (n = 502), metabolism-related hub genes were identified by the weighted gene co-expression network analysis (WGCNA). Seven genes were identified to construct the MRGPI by using the Cox regression method and validated with an HNSCC dataset (n = 270) from the Gene Expression Omnibus (GEO) database. Afterward, the prognostic value, metabolic activities, genetic alternations, gene set enrichment analysis (GSEA), immunophenotype, Connectivity map (cMAP), and benefit of immunotherapy in MRGPI-defined subgroups were analyzed.

Results

The MRGPI was constructed based on HPRT1, AGPAT4, AMY2B, ACADL, CKM, PLA2G2D, and ADA. Patients in the low-MRGPI group had better overall survival than those in the high-MRGPI group, consistent with the results in the GEO cohort (cutoff value = 1.01). Patients with a low MRGPI score display lower metabolic activities and an active antitumor immunity status and more benefit from immunotherapy. In contrast, a higher MRGPI score was correlated with higher metabolic activities, more TP53 mutation rate, lower antitumor immunity ability, an immunosuppressive TME, and less benefit from immunotherapy.

Conclusion

The MRGPI is a promising indicator to distinguish the prognosis, the metabolic, molecular, and immune phenotype, and the benefit from immunotherapy in HNSCC.

Inflammation-Related Gene Signature for Predicting the Prognosis of Head and Neck Squamous Cell Carcinoma

Purpose

The inflammatory response was associated with the prognosis of head and neck squamous cell carcinoma (HNSCC). This study aimed to perform a novel prognostic signature based on inflammation-related genes (IRGs) for a better understanding of the prognosis of HNSCC.

Patients and Methods

IRGs were obtained from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Functional enrichment analysis was performed to explore potential pathways. Univariate and multivariate Cox regression as well as the Least Absolute Shrinkage and Selection Operator (LASSO) were utilized to construct an IRGs-based prognostic model on TCGA database and the GEO database was utilized for outcome validation. The nomogram model was constructed based on independent prognostic factors after univariate and multivariate Cox regression. The immune cell infiltration level was analyzed via the Tumor Immune Estimation Resource (TIMER) database.

Results

In this study, we confirmed that 60% IRGs were abnormally expressed in HNSCC samples, and these were associated with important oncobiology. Then, a prognostic signature comprising 7 hub genes was generated based on TCGA database. The results were validated in 97 patients from GSE41613. A nomogram comprising risk score, age, M stage and N stage was generated to improve the accuracy of prognosis evaluation. The immune cell infiltration analysis suggested that 5 hub genes (ADGRE1, OLR1, TIMP1, GPR132 and CCR7) were negatively correlated with tumor purity and positively correlated with the infiltration of immune cells.

Conclusion

Our study established a novel signature consisting of 7 hub genes for the prognostic prediction in patients with HNSCC.

Comprehensive Analysis of mTORC1 Signaling Pathway–Related Genes in the Prognosis of HNSCC and the Response to Chemotherapy and Immunotherapy

Objective: The mammalian target of the rapamycin complex 1 (mTORC1) signaling pathway has emerged as a crucial player in the oncogenesis and development of head and neck squamous cell carcinoma (HNSCC), however, to date, no relevant gene signature has been identified. Therefore, we aimed to construct a novel gene signature based on the mTORC1 pathway for predicting the outcomes of patients with HNSCC and their response to treatment.

Methods: The gene expression and clinical data were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The key prognostic genes associated with the mTORC1 pathway were screened by univariate Cox regression analyses. A prognostic signature was then established based on significant factors identified in the multivariate Cox regression analysis. The performance of the multigene signature was evaluated by the Kaplan–Meier (K–M) survival analysis and receiver operating characteristic (ROC) analysis. Based on the median risk score, patients were categorized into high- and low-risk groups. Subsequently, a hybrid prognostic nomogram was constructed and estimated by a calibration plot and decision curve analysis. Furthermore, immune cell infiltration and therapeutic responses were compared between the two risk groups. Finally, we measured the expression levels of seven genes by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC).

Results: The mTORC1 pathway–based signature was constructed using the seven identified genes (SEC11A, CYB5B, HPRT1, SLC2A3, SC5D, CORO1A, and PIK3R3). Patients in the high-risk group exhibited a lower overall survival (OS) rate than those in the low-risk group in both datasets. Through the univariate and multivariate Cox regression analyses, this gene signature was confirmed to be an independent prognostic risk factor for HNSCC. The constructed nomogram based on age, American Joint Committee on Cancer (AJCC) stage, and the risk score exhibited satisfactory performance in predicting the OS. In addition, immune cell infiltration and chemotherapeutic and immunotherapeutic responses differed significantly between the two risk groups. The expression levels of SEC11A and CYB5B were higher in HNSCC tissues than in normal tissues.

Conclusion: Our study established and verified an mTORC1 signaling pathway–related gene signature that could be used as a novel prognostic factor for HNSCC.

Pan-Cancer Analyses Confirmed the Ferroptosis-Related Gene SLC7A11 as a Prognostic Biomarker for Cancer

Purpose

Ferroptosis is an iron-dependent and reactive oxygen species (ROS)-reliant form of cell death, exhibiting cellular, molecular, and gene-level characteristics distinct from those of necrosis, autophagy, apoptosis, and pyroptosis. Solute carrier family 7 member 11 (SLC7A11), which encodes a cystine/glutamate antiporter transmembrane protein, inhibits ferroptosis by importing cystine and promoting glutathione (GSH) biosynthesis and was found to be overexpressed in multiple human cancers. However, the specific role and underlying mechanism of SLC7A11 in cancers remains poorly characterized. This research aimed to identify the relationship between SLC7A11 expression and tumor microenvironment and visualize its prognostic value in pan-cancer.

Patients and Methods

Transcriptomic data for 6313 tumors and normal samples across 20 cancer types were acquired from The Cancer Genome Atlas (TCGA) database. Besides, we presented a novel bioinformatics pipeline that uncovered the impacts of SLC7A11 on cancer prognosis, tumor mutational burden (TMB), immune cell infiltration in tumor microenvironment, and drug responses. The Genotype-Tissue Expression (GTEx), cBioportal, TCGA and Connectivity Map (CMap) databases were used to explore the expression, genetic alterations, immune microenvironment, and drug responses of SLC7A11. A series of deconvolution algorithms, including EPIC, CIBERSORT and GSEA, were utilized for multidimensional analyses of the cancer transcriptomic data.

Results

SLC7A11 was found to be highly expressed in the 20 types of cancer, especially in solid tumors. Survival analysis uncovered that most cancer patients with up-regulated expression of SLC7A11 showed poor prognosis, suggesting that SLC7A11 is a potential oncogene in most cancer types. Furthermore, the expression level of SLC7A11 was confirmed to be associated with immune cell infiltration in tumor microenvironment, TMB, and drug responses. Gene set enrichment analysis (GESA) revealed that dysregulation of SLC7A11 was associated with metabolic and immunity-related signaling pathways in the cancers.

Conclusion

The comprehensive pan-cancer analyses identified SLC7A11 as an attractive biomarker for immune infiltration and poor prognosis in cancers, shedding new light on the therapeutics of cancers.

Identification and Validation of a Ferroptosis-Related Signature for Predicting Prognosis and Immune Microenvironment in Papillary Renal Cell Carcinoma

Objective

We aimed to explore the prognostic patterns of ferroptosis-related genes in papillary renal cell carcinoma (PRCC) and investigate the relationship between ferroptosis-related genes and PRCC tumor immune microenvironment.

Methods

We obtained the mRNA expression and corresponding clinical data of PRCC from the public tumor cancer genome atlas database (TCGA). The PRCC patients were randomly divided into two cohort, training cohort and verification cohort, respectively. Univariate Cox regression, LASSO Cox regression, multivariate Cox regression analysis were utilized to construct ferroptosis signature for PRCC patients. And then, risk prognostic model was established and verified. The correlation of ferroptosis-related signature with survival and immune microenvironment was systematically analyzed.

Results

A 4-genes ferroptosis signature (CDKN1A, MIOX, PSAT1, and RRM2) was constructed. Multivariate Cox regression assay indicates that the risk score of ferroptosis signature was an independent prognostic indicator (HR=1.391, p<0.001). The survival curve shows that the high-risk group has a poorer prognosis than the low-risk group (p<0.001). The risk prognostic model was established based on prognostic factors of clinical-stage, hemoglobin, and risk score. The time-dependent receiver operating characteristic curve (ROC) analysis proves the predictive capacity of the ferroptosis signature, the 3 years area under the curve (AUC) is 0.890, and the 5 years AUC is 0.733. Further analysis suggested that cell cycle, pentose phosphate pathway, P53 signaling pathway were significantly enriched in the high-risk group. The significantly different fractions of dendritic cells resting, macrophage cells, and T cells follicular helper were observed in risk groups.

Conclusion

This study implicates a ferroptosis signature which has a good predict capacity of the prognosis in PRCC patients. Ferroptosis-related genes may have a key role in the process of anti-tumor and serve as therapeutic targets for PRCC.

A Neutrophil Extracellular Traps Signature Predicts the Clinical Outcomes and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma

Background: Neutrophil extracellular traps (NETs) play an important role in the occurrence, metastasis and immune escape of cancers. This study aimed to investigate NET-related genes, their clinical prognostic value and their correlation with immunotherapy and anticancer drugs in patients with head and neck squamous cell carcinoma (HNSCC).

Methods: Differentially expressed NET-related genes in HNSCC were identified based on multiple public databases. To improve the clinical practicability and avoid overfitting, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were used to construct a prognostic risk model. A nomogram was further used to explore the clinical value of the model. Internal and external validation were conducted to test the model. Furthermore, the immune microenvironment, immunophenoscore (IPS) and sensitivity to anticancer drugs in HNSCC patients with different prognostic risks were explored.

Results: Six NET-related genes were screened to construct the risk model. In the training cohort, Kaplan–Meier (K-M) analysis showed that the overall survival (OS) of low-risk HNSCC patients was significantly better than that of high-risk HNSCC patients (p < 0.001). The nomogram also showed a promising prognostic value with a better C-index (0.726 vs 0.640) and area under the curve (AUC) (0.743 vs 0.706 at 3 years, 0.743 vs 0.645 at 5 years) than those in previous studies. Calibration plots and decision curve analysis (DCA) also showed the satisfactory predictive capacity of the nomogram. Internal and external validation further strengthened the credibility of the clinical prognostic model. The level of tumor mutational burden (TMB) in the high-risk group was significantly higher than that in the low-risk group (p = 0.017), and the TMB was positively correlated with the risk score (R = 0.11; p = 0.019). Moreover, the difference in immune infiltration was significant in HNSCC patients with different risks (p < 0.05). Furthermore, the IPS analysis indicated that anti-PD-1 (p < 0.001), anti-CTLA4 (p < 0.001) or combining immunotherapies (p < 0.001) were more beneficial for low-risk HNSCC patients. The response to anticancer drugs was also closely correlated with the expression of NET-related genes (p < 0.001).

Conclusion: This study identified a novel prognostic model that might be beneficial to develop personalized treatment for HNSCC patients.

Development of a lncRNA-based prognostic signature for oral squamous cell carcinoma

BACKGROUND

We aimed to establish a long noncoding RNA (lncRNA)-based signature for accurately predicting prognosis and guiding the personalized clinical management of oral squamous cell carcinoma (OSCC).

METHODS

OSCC RNA sequencing profiles were acquired from The Cancer Genome Atlas and Gene Expression Omnibus. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were performed to construct a lncRNA-based prognostic signature. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves and calibration curves were used to assess the effectiveness and accuracy of the signature. Additionally, we conducted single-sample gene-set enrichment analysis to infer the different degrees of immunocyte infiltration. Weighted correlation network analysis, enrichment analysis and Spearman's correlation analysis were implemented to screen immune-related genes that interact with the lncRNA signature.

RESULTS

In total, 14 lncRNAs were defined as potential prognostic biomarkers. Based on these lncRNAs, patients were divided into low- and high-risk subgroups with different survival times (p < 0.001). In addition, the reliability of the prognostic signature was verified by Kaplan-Meier analysis, ROC analysis and calibration curves. Patients in the low-risk group exhibited more significant immune cell infiltration. Simultaneously, a potential regulatory network consisting of 8 lncRNAs and 159 protein-coding genes in the top 10 immune-related biological process terms was constructed.

CONCLUSIONS

Our findings suggested that the 14-lncRNA signature has satisfactory performance in predicting the prognosis of OSCC, thereby providing new insights to the pathogenesis, clinical patient management and therapeutic intervention. The different immune cell infiltration statuses of OSCC patients may encourage immunotherapy.

Construction of a Ferroptosis-Related Gene Signature for Head and Neck Squamous Cell Carcinoma Prognosis Prediction

Background

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant cancers, and few studies have demonstrated the value of ferroptosis-related genes in prognosis.

Methods

The original counts of RNA sequencing data and clinicopathological data were obtained from TCGA and GSE65858 datasets. Common ferroptosis-related genes related to prognosis were identified from the training set and were included in LASSO to determine the best prognosis. To evaluate the efficacy, time-dependent ROC and Kaplan–Meier (KM) survival analyses were applied. Moreover, univariate and multivariate Cox regression analyses were used to screen independent parameters of prognosis and build a nomogram. Eventually, possible biological pathways were proposed based on GSEA.

Results

Among 242 ferroptosis-related genes, we identified that the FLT3, IL6, Keap1, NQO1, SOCS1 and TRIB3 genes were significantly connected with HNSCC patient prognosis as a six-gene signature. After, the patients were divided into high- and low-risk groups based on the six-gene signature. The KM survival curves demonstrated that the high-risk group had worse OS (p < 0.0001) and higher AUC values (0.654, 0.735, and 0.679 for 1-, 3-, and 5-year survival, respectively) for the prognostic signature of the six genes compared with other genes, which were also validated in the GSE65858 dataset. Moreover, GSEA suggested that the epithelial mesenchymal transition pathway was abundant and that the mesenchymal status in the high-risk group was substantially higher than that in the low-risk group. Finally, the immune microenvironment and differences in the content of immune cell types were demonstrated.

Conclusion

We established a six-ferroptosis-related-gene model crossing clinical prognostic parameters that can predict HNSCC patient prognosis and provide a reliable prognostic evaluation tool to assist clinical treatment decisions.

Prognostic Value of a Ferroptosis-Related Gene Signature in Patients With Head and Neck Squamous Cell Carcinoma

Background: Ferroptosis is an iron-dependent programmed cell death (PCD) form that plays a crucial role in tumorigenesis and might affect the antitumor effect of radiotherapy and immunotherapy. This study aimed to investigate distinct ferroptosis-related genes, their prognostic value and their relationship with immunotherapy in patients with head and neck squamous cell carcinoma (HNSCC). Methods: The differentially expressed ferroptosis-related genes in HNSCC were filtered based on multiple public databases. To avoid overfitting and improve clinical practicability, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were performed to construct a prognostic risk model. Moreover, a nomogram was constructed to forecast individual prognosis. The differences in tumor mutational burden (TMB), immune infiltration and immune checkpoint genes in HNSCC patients with different prognoses were investigated. The correlation between drug sensitivity and the model was firstly analyzed by the Pearson method. Results: Ten genes related to ferroptosis were screened to construct the prognostic risk model. Kaplan-Meier (K-M) analysis showed that the prognosis of HNSCC patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.001), and the area under the curve (AUC) of the 1-, 3- and 5-year receiver operating characteristic (ROC) curve increased year by year (0.665, 0.743, and 0.755). The internal and external validation further verified the accuracy of the model. Then, a nomogram was build based on the reliable model. The C-index of the nomogram was superior to a previous study (0.752 vs. 0.640), and the AUC (0.729 vs. 0.597 at 1 year, 0.828 vs. 0.706 at 3 years and 0.853 vs. 0.645 at 5 years), calibration plot and decision curve analysis (DCA) also shown the satisfactory predictive capacity. Furthermore, the TMB was revealed to be positively correlated with the risk score in HNSCC patients (R = 0.14; P < 0.01). The differences in immune infiltration and immune checkpoint genes were significant (P < 0.05). Pearson analysis showed that the relationship between the model and the sensitivity to antitumor drugs was significant (P < 0.05). Conclusion: Our findings identified potential novel therapeutic targets, providing further potential improvement in the individualized treatment of patients with HNSCC.