Identification and validation of a prognostic signature and combination drug therapy for immunotherapy of head and neck squamous cell carcinoma

Hypoxia-related signature to risk stratify patients for the benefit of immune checkpoint inhibitors therapy in head and neck squamous cell carcinoma: An experimental study

BACKGROUND

Increasing evidence has shown that hypoxia is a biomarker of tumor proliferation and metastasis. This research aimed to identify a hypoxia-associated gene prognostic index (HAGPI) in head and neck squamous cell carcinoma (HNSCC) and based on HAGPI-defined subgroups to predict prognosis and response to immune checkpoint inhibitors therapy.

METHODS

RNA-sequencing transcriptomic data for patients with HNSCC were downloaded from The Cancer Genome Atlas (TCGA). Protein-protein interaction network analysis was performed to select hypoxia-related hub genes. Univariate and multivariate cox regression analyses were used to identify hub genes to develop the HAGPI. Afterward expression data were imported into CIBERSORT to evaluate the relative proportion of 22 immune cells and compared the relative proportions of immune cells between the 2 HAGPI subgroups. The relationship between immunopheno score (IPS) and HAGPI was validated for immune checkpoint inhibitors (ICIs) response in TCGA cohorts.

RESULTS

The HAGPI was constructed based on HS3ST1, HK1, PGK1, STC2, SERPINE1, PKLR genes. In high-HAGPI patients, the primary and secondary endpoint events in TCGA and GEO cohorts were significantly lower than low-HAGPI groups (P < .05). HAGPI-high patients exhibited a poorer prognosis than HAGPI-low patients did. The abundance of M2 macrophages and NK cell were significantly enhanced in the high-HAGPI while T cells regulatory and T cells CD8, were markedly elevated in the low-HAGPI. Meanwhile, patients in the low-HAGPI patients had higher levels of immunosuppressant expression and less aggressive phenotypes. Furthermore, IPS analysis showed that the low-HAGPI group with higher IPS represented a more immunogenic phenotype.

CONCLUSION

The current study developed and verified a HAPGI model that can be considered as an independent prognostic biomarker and elucidated the tumor immune microenvironment of HNSCC.

Association of a gene-expression subtype to outcome and treatment response in patients with recurrent/metastatic head and neck squamous cell carcinoma treated with nivolumab

BACKGROUND

Immune checkpoint inhibitors have been approved and currently used in the clinical management of recurrent and metastatic head and neck squamous cell carcinoma (R/M HNSCC) patients. The reported benefit in clinical trials is variable and heterogeneous. Our study aims at exploring and comparing the predictive role of gene-expression signatures with classical biomarkers for immunotherapy-treated R/M HNSCC patients in a multicentric phase IIIb trial.

METHODS

Clinical data were prospectively collected in Nivactor tiral (single-arm, open-label, multicenter, phase IIIb clinical trial in platinum-refractory HNSCC treated with nivolumab). Findings were validated in an external independent cohort of immune-treated HNSCC patients, divided in long-term and short-term survivors (overall survival >18 and <6 months since the start of immunotherapy, respectively). Pretreatment tumor tissue specimen from immunotherapy-treated R/M HNSCC patients was used for PD-L1 (Tumor Proportion Score; Combined Positive Score (CPS)) and Tumor Mutational Burden (Oncopanel TSO500) evaluation and gene expression profiling; classical biomarkers and immune signatures (retrieved from literature) were challenged in the NIVACTOR dataset.

RESULTS

Cluster-6 (Cl6) stratification of NIVACTOR cases in high score (n=16, 20%) and low score (n=64, 80%) demonstrated a statistically significant and clinically meaningful improvement in overall survival in the high-score cases (p=0.00028; HR=4.34, 95% CI 1.84 to 10.22) and discriminative ability reached area under the curve (AUC)=0.785 (95% CI 0.603 to 0.967). The association of high-score Cl6 with better outcome was also confirmed in: (1) NIVACTOR progression-free survival (p=4.93E-05; HR=3.71, 95% CI 1.92 to 7.18) and objective-response-rate (AUC=0.785; 95% CI 0.603 to 0.967); (2) long survivors versus short survivors (p=0.00544). In multivariate Cox regression analysis, Cl6 was independent from Eastern Cooperative Oncology Group performance status, PDL1-CPS, and primary tumor site.

CONCLUSIONS

These data highlight the presence of underlying biological differences able to predict survival and response following treatment with immunotherapy in platinum-refractory R/M HNSCC that could have translational implications improving treatment selection.

TRIAL REGISTRATION NUMBER

EudraCT Number: 2017-000562-30.

Expanding the role of combined immunochemotherapy and immunoradiotherapy in the management of head and neck cancer (Review)

Immunotherapy has become one of the most promising approaches in tumor therapy, and there are numerous associated clinical trials in China. As an immunosuppressive tumor, head and neck squamous cell carcinoma (HNSCC) carries a high mutation burden, making immune checkpoint inhibitors promising candidates in this field due to their unique mechanism of action. The present review outlines a comprehensive multidisciplinary cancer treatment approach and elaborates on how combining immunochemotherapy and immunoradiotherapy guidelines could enhance clinical efficacy in patients with HNSCC. Furthermore, the present review explores the immunology of HNSCC, current immunotherapeutic strategies to enhance antitumor activity, ongoing clinical trials and the future direction of the current immune landscape in HNSCC. Advanced-stage HNSCC presents with a poor prognosis, low survival rates and minimal improvement in patient survival trends over time. Understanding the potential of immunotherapy and ways to combine it with surgery, chemotherapy and radiotherapy confers good prospects for the management of human papillomavirus (HPV)-positive HNSCC, as well as other HPV-positive malignancies. Understanding the immune system and its effect on HNSCC progression and metastasis will help to uncover novel biomarkers for the selection of patients and to enhance the efficacy of treatments. Further research on why current immune checkpoint inhibitors and targeted drugs are only effective for some patients in the clinic is needed; therefore, further research is required to improve the overall survival of affected patients.

Integrated analysis of diagnostic, prognostic value and potential drug treatment of GSDME in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) poses a global health challenge. Effective biomarkers for early detection are necessary to improve the survival rate of HNSC patient. The purpose of this study was using integrated bioinformatic analysis to investigate the potential biological roles of GSDME in HNSC.

METHODS

The Gene Expression Omnibus (GEO) and Cancer Gnome Atlas (TCGA) databases were used to analyze the expression of GSDME in different cancer types. The correlation between GSDME expression and immune cell infiltration or immune checkpoint genes was examined by Spearman correlation analysis. DNA methylation analysis of the GSDME gene was conducted using the MethSurv database. Kaplan-Meier (K-M) survival curves, diagnostic receiver operating characteristic (ROC) curves, nomogram model, and Cox regression analysis were chosen to evaluate the diagnostic and prognostic predictive value of GSDME. Connectivity Map (Cmap) online platform, Protein Data Bank (PDB) database and Chem3D, AutoDock Tool and PyMol software were used to predict and visualize potential molecular drugs aimed for GSDME.

RESULTS

GSDME expression level in HNSC was significantly higher than in the controls (p < 0.001). Differentially expressed genes (DEGs) correlation with GSDME were enriched in the GO pathways, such as protein activation cascade, complement activation and classical pathway (p < 0.05). According to GSEA, GSDME-associated differentially expressed genes were significantly enriched in KRAS signaling pathway and cytokine signaling molecule (p < 0.05). There is a significant relation between GSDME expression and immune cell infiltration in HNSC tissues, as well as immune checkpoint genes expression (p < 0.001). DNA methylation status of cg17790129 CpG islands of GSDME gene is correlated with HNSC prognosis (p < 0.05). Based on Cox regression analysis of HNSC patients, GSDME as a potential risk gene has high correlation with overall survival (OS) and disease specific survival (DSS) (p < 0.05). In a ROC curve analysis, HNSC tissues were differentiated from adjacent peritumoral tissues based on GSDME expression levels (AUC = 0.928). Totally six potential drugs targeted for GSDME were screened and the molecular docking tests between GSDME protein and candidate drugs were conducted.

CONCLUSIONS

GSDME is a promising therapeutic target as well as a potential clinical biomarker in HNSC patients.

Prophylactic cranial irradiation-related lymphopenia affects survival in patients with limited-stage small cell lung cancer

Background

The study aimed to identify the relations of the absolute lymphocyte count (ALC) nadir during prophylactic cranial irradiation (PCI) and patient outcomes in limited-stage small cell lung cancer (LS-SCLC).

Methods

We analyzed 268 L S-SCLC patients who underwent PCI from 2012 to 2019. ALC values were collected prior, during, and 3 months post PCI. Kaplan-Meier and Cox regression analyses were performed to assess the relation of ALC to patient prognosis. Two nomograms were developed on the basis of clinical variables for survival prediction.

Results

Compared with the ALC before PCI (1.13 × 10⁹ cells/L), the ALC nadir during PCI was significantly reduced by 0.68 × 10⁹ cells/L (P < 0.001) and raised to 1.02 × 10⁹ cells/L 3 months post PCI. Patients with a low ALC nadir during PCI (<0.68 × 10⁹ cells/L) had inferior progression free survival (PFS) (median PFS: 17.2 m vs. 43.7 m, P = 0.019) and overall survival (OS) (median OS: 29.0 m vs 39.1 m, P = 0.012). Multivariate Cox analysis revealed that age, smoking history, clinical stage, and ALC nadir were independent OS (P = 0.006, P = 0.005, P < 0.001 and P = 0.027, respectively), as well as independent PFS predictors (P = 0.032, P = 0.012, P = 0.012 and P = 0.018, respectively). After internal cross-validation, the corrected concordance indices of the predictive nomograms for PFS and OS were 0.637 and 0.663, respectively.

Conclusion

LS-SCLC patients with a low ALC nadir during PCI likely have worse survival outcomes. Dynamic evaluation of the ALC during PCI is recommended for LS-SCLC 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.

Identification and validation of neurotrophic factor-related genes signature in HNSCC to predict survival and immune landscapes

Background: Head and neck squamous cell carcinoma (HNSCC) is the seventh most common type of cancer worldwide. Its highly aggressive and heterogeneous nature and complex tumor microenvironment result in variable prognosis and immunotherapeutic outcomes for patients with HNSCC. Neurotrophic factor-related genes (NFRGs) play an essential role in the development of malignancies but have rarely been studied in HNSCC. The aim of this study was to develop a reliable prognostic model based on NFRGs for assessing the prognosis and immunotherapy of HNSCC patients and to provide guidance for clinical diagnosis and treatment. Methods: Based on the TCGA-HNSC cohort in the Cancer Genome Atlas (TCGA) database, expression profiles of NFRGs were obtained from 502 HNSCC samples and 44 normal samples, and the expression and prognosis of 2601 NFRGs were analyzed. TGCA-HNSC samples were randomly divided into training and test sets (7:3). GEO database of 97 tumor samples was used as the external validation set. One-way Cox regression analysis and Lasso Cox regression analysis were used to screen for differentially expressed genes significantly associated with prognosis. Based on 18 NFRGs, lasso and multivariate Cox proportional risk regression were used to construct a prognostic risk scoring system. ssGSEA was applied to analyze the immune status of patients in high- and low-risk groups. Results: The 18 NFRGs were considered to be closely associated with HNSCC prognosis and were good predictors of HNSCC. The multifactorial analysis found that the NFRGs signature was an independent prognostic factor for HNSCC, and patients in the low-risk group had higher overall survival (OS) than those in the high-risk group. The nomogram prediction map constructed from clinical characteristics and risk scores had good prognostic power. Patients in the low-risk group had higher levels of immune infiltration and expression of immune checkpoints and were more likely to benefit from immunotherapy. Conclusion: The NFRGs risk score model can well predict the prognosis of HNSCC patients. A nomogram based on this model can help clinicians classify HNSCC patients prognostically and identify specific subgroups of patients who may have better outcomes with immunotherapy and chemotherapy, and carry out personalized treatment for HNSCC patients.

METTL3 suppresses anlotinib sensitivity by regulating m6A modification of FGFR3 in oral squamous cell carcinoma

Background

N6-methyladenosine (m⁶A) is an abundant nucleotide modification in mRNA, but there were few studies on its role in cancer drug sensitivity and resistance. Anlotinib has been proved to have effective antitumor effects in oral squamous cell carcinoma (OSCC) in our previous study. Here, we sought to investigate the treatment target of anlotinib and the function and mechanisms of m⁶A modification in regulating anlotinib effect in OSCC.

Methods

Anlotinib treatment in a dose-dependent manner, western blotting, qRT-PCR and cell lost-of-function assays were used to study the treatment target of anlotinib in OSCC. RNA m⁶A dot blot assays, the m⁶A MeRIP-seq and MeRIP-qPCR, RNA and protein stability assays were used to explore the m⁶A modification of the treatment target of anlotinib. Cell lost-of-function assays after METTL3 depletion were conducted to investigate the effect of m⁶A modification level on the therapeutic effect of anlotinib in OSCC. Patient-derived tumor xenograft (PDX) models and immunohistochemistry staining were performed to study the relationship of METTL3 and antitumor sensitivity of anlotinib in vivo.

Results

Anlotinib targeted FGFR3 in the treatment of OSCC and inhibited tumor cell proliferation and promoted apoptosis by inactivating the FGFR3/AKT/mTOR signaling pathway. METTL3 was identified to target and modify FGFR3 m⁶A methylation and then decrease the stability of mRNA. METTL3 expression level was related to the anlotinib sensitivity in OSCC cells in vitro and METTL3 knockdown promoted anlotinib sensitivity of OSCC cells by inhibiting the FGFR3 expression. PDX models samples furthermore showed that METTL3 and FGFR3 levels were tightly correlated with the anlotinib efficacy in OSCC.

Conclusions

In summary, our work revealed that FGFR3 was served as the treatment target of anlotinib and METTL3-mediated FGFR3 m⁶A modification played a critical function in the anlotinib sensitivity in OSCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02715-7.

Identification of a Novel Cuproptosis-Related Gene Signature for Prognostic Implication in Head and Neck Squamous Carcinomas

Simple Summary

Head and neck squamous carcinoma (HNSC) is a common malignancy that requires novel therapeutic targets. Cuproptosis is an emerging research hotspot. The purpose of this study is to mine the cuproptosis-related genes to find prognosis-related genes. We successfully identified a 24-gene signature for predicting overall survival (OS) in HNSC patients and may expand the range of potential targets for treating HNSC.

Abstract

Head and neck squamous carcinoma (HNSC) is a frequent and deadly malignancy that is challenging to manage. The existing treatment options have considerable efficacy limitations. Hence, the identification of new therapeutic targets and the development of efficacious treatments are urgent needs. Cuproptosis, a non-apoptotic programmed cell death caused by excess copper, has only very recently been discovered. The present study investigated the prognostic importance of genes involved in cuproptosis through the mRNA expression data and related clinical information of HNSC patients downloaded from public databases. Our results revealed that many cuproptosis-related genes were differentially expressed between normal and HNSC tissues in the TCGA cohort. Moreover, 39 differentially expressed genes were associated with the prognosis of HNSC patients. Then, a 24-gene signature was identified in the TCGA cohort utilizing the LASSO Cox regression model. HNSC expression data used for validation were obtained from the GEO database. Consequently, we divided patients into high- and low-risk groups based on the 24-gene signature. Furthermore, we demonstrated that the high-risk group had a worse prognosis when compared to the low-risk group. Additionally, significant differences were found between the two groups in metabolic pathways, immune microenvironment, etc. In conclusion, we found a cuproptosis-related gene signature that can be used effectively to predict OS in HNSC patients. Thus, targeting cuproptosis might be an alternative and promising strategy for HNSC patients.

Analyzing the Systems Biology Effects of COVID-19 mRNA Vaccines to Assess Their Safety and Putative Side Effects

COVID-19 vaccines have been instrumental tools in reducing the impact of SARS-CoV-2 infections around the world by preventing 80% to 90% of hospitalizations and deaths from reinfection, in addition to preventing 40% to 65% of symptomatic illnesses. However, the simultaneous large-scale vaccination of the global population will indubitably unveil heterogeneity in immune responses as well as in the propensity to developing post-vaccine adverse events, especially in vulnerable individuals. Herein, we applied a systems biology workflow, integrating vaccine transcriptional signatures with chemogenomics, to study the pharmacological effects of mRNA vaccines. First, we derived transcriptional signatures and predicted their biological effects using pathway enrichment and network approaches. Second, we queried the Connectivity Map (CMap) to prioritize adverse events hypotheses. Finally, we accepted higher-confidence hypotheses that have been predicted by independent approaches. Our results reveal that the mRNA-based BNT162b2 vaccine affects immune response pathways related to interferon and cytokine signaling, which should lead to vaccine success, but may also result in some adverse events. Our results emphasize the effects of BNT162b2 on calcium homeostasis, which could be contributing to some frequently encountered adverse events related to mRNA vaccines. Notably, cardiac side effects were signaled in the CMap query results. In summary, our approach has identified mechanisms underlying both the expected protective effects of vaccination as well as possible post-vaccine adverse effects. Our study illustrates the power of systems biology approaches in improving our understanding of the comprehensive biological response to vaccination against COVID-19.

Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis

Objectives

Patients with head and neck squamous cell carcinoma (HNSCC) have poor prognosis and show poor responses to immune checkpoint (IC) inhibitor (ICI) therapy. Competing endogenous RNA (ceRNA) networks, tumor-infiltrating immune cells (TIICs), and ICIs may influence tumor prognosis and response rates to ICI therapy. This study is aimed at identifying prognostic and IC-related biomarkers and key TIIC signatures to improve prognosis and ICI therapy response in HNSCC patients.

Methods and Results

Ninety-five long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and 1746 mRNAs were identified using three independent methods. We constructed a ceRNA network and estimated the proportions of 22 immune cell subtypes. Ten ceRNAs were related to prognosis according to Kaplan–Meier analysis. Two risk signatures based, respectively, on nine ceRNAs (ANLN, CFL2, ITGA5, KDELC1, KIF23, NFIA, PTX3, RELT, and TMC7) and three immune cell types (naïve B cells, neutrophils, and regulatory T cells) via univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses could accurately and independently predict the prognosis of HNSCC patients. Key mRNAs in the ceRNA network were significantly correlated with naïve B cells and regulatory T cells and with stage, grade, and immune and molecular subtype. Eight IC genes exhibited higher expression in tumor tissues and were correlated with eight key mRNAs in the ceRNA network in HNSCC patients with different HPV statuses according to coexpression and TIMER 2.0 analyses. Most drugs were effective in association with expression of these key signatures (ANLN, CFL2, ITGA5, KIF23, NFIA, PTX3, RELT, and TMC7) based on GSCALite analysis. The prognostic value of key biomarkers and associations between key ceRNAs and IC genes were validated using online databases. Eight key ceRNAs were confirmed to predict response to ICI in other cancers based on TIDE analysis.

Conclusions

We constructed two risk signatures to accurately predict prognosis in HNSCC. Key IC-related signatures may be associated with response to ICI therapy. Combinations of ICIs with inhibitors of eight key mRNAs may improve survival outcomes of HNSCC patients.