Immune-Related Mutational Landscape and Gene Signatures: Prognostic Value and Therapeutic Impact for Head and Neck Cancer

Artificial Intelligence in Head and Neck Cancer Diagnosis: A Comprehensive Review with Emphasis on Radiomics, Histopathological, and Molecular Applications

The present review discusses the transformative role of AI in the diagnosis and management of head and neck cancers (HNCs). Methods: It explores how AI technologies, including ML, DL, and CNNs, are applied in various diagnostic tasks, such as medical imaging, molecular profiling, and predictive modeling. Results: This review highlights AI's ability to improve diagnostic accuracy and efficiency, particularly in analyzing medical images like CT, MRI, and PET scans, where AI sometimes outperforms human radiologists. This paper also emphasizes AI's application in histopathology, where algorithms assist in whole-slide image (WSI) analysis, tumor-infiltrating lymphocytes (TILs) quantification, and tumor segmentation. AI shows promise in identifying subtle or rare histopathological patterns and enhancing the precision of tumor grading and treatment planning. Furthermore, the integration of AI with molecular and genomic data aids in mutation analysis, prognosis, and personalized treatment strategies. Conclusions: Despite these advancements, the review identifies challenges in AI adoption, such as data standardization and model interpretability, and calls for further research to fully integrate AI into clinical practice for improved patient outcomes.

KIF4A functions as a diagnostic and prognostic biomarker and regulates tumor immune microenvironment in skin cutaneous melanoma

BACKGROUND

KIF4A is upregulated in various malignancies and serves as an independent risk factor. However, its function in skin cutaneous melanoma (SKCM) and the regulation of the immunological environment remains unknown.

METHODS

We first explored the mRNA and protein levels of KIF4A in SKCM through public databases. Then, the co-expressed genes with KIF4A in SKCM and their functional enrichment analysis were performed. Moreover, the clinical value, relationship with immune infiltration and tumor microenvironment (TME), as well as the correlation between KIF4A and immunomodulators were evaluated. In addition, we validated the function of KIF4A by in vitro experiments such as CCK-8 assay, clone formation and wound healing assay.

RESULTS

Our data reveal that the mRNA and protein levels of KIF4A are highly expressed in SKCM. Moreover, functional enrichment analysis of the top 50 co-expressed genes with KIF4A showed significant association with organelle fission, tubulin binding and immune processes. KIF4A can distinguish SKCM from normal tissue and predict a poorer prognosis. A negative association was observed between KIF4A and TME, and KIF4A exhibited a negative correlation with most immunomodulators. Additionally, the knockdown of KIF4A inhibited the proliferation and migration ability of A375 cells.

CONCLUSIONS

Our findings suggest that KIF4A promotes the progression of SKCM and is negatively associated with immune infiltration and immunomodulators, which indicates a poor prognosis.

Prognostic value of genetic aberrations and tumor immune microenvironment in primary acral melanoma

BACKGROUND

Acral melanoma (AM) is the most common subtype in Chinese melanoma patients with a very poor prognosis. However, our understanding of the disease pathogenesis and molecular landscape is limited by the few studies that have been conducted. Here, we profiled the clinical characteristics, mutational landscapes and tumor immune microenvironment of AM patients to gain insights into disease characteristics and potential treatment strategies.

METHODS

A total of 90 AM patients were enrolled and their tissue samples were subjected to next-generation sequencing and multiplexed immunohistochemistry tests. Kaplan-Meier curves and log-rank tests were used to analyze the prognostic potential of various genetic aberrations and immune cell compositions in AM.

RESULTS

The median disease-free survival was 21.3 months and estimated median overall survival (OS) was 60 months. More advanced stages, older ages and thickness of greater than 4 mm were associated with worse prognosis in AM patients (HR = 2.57, 95% CI 1.25-5.29, p = 0.01; HR = 2.77, 95% CI 1.22-6.28, p = 0.02; HR = 3.43, 95% CI 1.51-7.82, p < 0.01, respectively), while patients who received post-surgical treatments had better survival (HR = 0.36, 95% CI 0.17-0.76, p = 0.01). The most frequently altered genes included BRAF (14.5%), KIT (16.9%), NRAS (12%), NF1 (10.8%), APC (7.2%), and ARID2 (6%). Copy number variations (CNV) were commonly found in CCND1 (19.3%), CDK4 (19.3%), MDM2 (14.5%) and FGF19 (12%). CDK4 amplifications was independently associated with shorter OS in AM patients (HR = 3.61, 95% CI 1.38-9.46, p = 0.01). CD8 ⁺ T cells (p < 0.001) and M1 macrophages (p = 0.05) were more highly enriched in the invasive margin than in the tumor center. Patients with higher levels of M1 macrophage infiltration in the invasive margin derived markedly longer OS (HR = 0.43, 95% CI 0.20-0.95, p = 0.03). Interestingly, in CDK4-amplified patients, there tended to be a low level of M1 macrophage infiltration in the invasive margin (p = 0.06), which likely explains the poor prognosis in such patients.

CONCLUSIONS

Our study provided a comprehensive portrait of the clinicopathological features, genetic aberrations and tumor microenvironment profiles in AM patients and identified candidate prognostic factors, which may facilitate development of additional therapeutic options and better inform clinical management of AM patients. Based on these prognostic factors, further studies should focus on enhancing the infiltration of M1 macrophages, especially in CDK4-amplified AM patients.

A composite score based on immune-related gene prognostic index and m6A risk score of head and neck squamous cell carcinoma

Background: Immunotherapy has been demonstrated favorable in head and neck squamous cell carcinoma (HNSCC). Studies indicated that immune-related gene prognostic index (IRGPI) was a robust signature, and N⁶-methyladenosine (m⁶A) methylation had a significant impact on the tumor immune microenvironment (TIME) and immunotherapy of head and neck squamous cell carcinoma. Thus, combining indicated that immune-related gene prognostic index with m⁶A status should offer a better predictive power for immune responses. Methods: Head and neck squamous cell carcinoma samples from the cancer genome atlas (TCGA, n = 498) and gene expression omnibus database (GSE65858, n = 270) were used in this study. Cox regression analysis was used to construct the indicated that immune-related gene prognostic index through immune-related hub genes which were identified by weighted gene co-expression network analysis (WGCNA). The m⁶A risk score was constructed by least absolute shrinkage and selection operator (LASSO) regression analysis. Principal component analysis was used to construct a composite score, and systematically correlate subgroups according to tumor immune microenvironment cell-infiltrating characteristics. Results: A composite score was determined based on indicated that immune-related gene prognostic index and m⁶A risk score. Head and neck squamous cell carcinoma patients in the cancer genome atlas were divided into four subgroups: A (IRGPI-High&m⁶A-risk-High, n = 127), B (IRGPI-High&m⁶A-risk-Low, n = 99), C (IRGPI-Low&m⁶A-risk-High, n = 99), and D (IRGPI-Low&m⁶A-risk-Low, n = 128), and overall survival (OS) was significantly different between subgroups (p < 0.001). The characteristics of tumor immune microenvironment cell infiltration in the four subgroups were significantly different in subgroups (p < 0.05). The receiver operating characteristic (ROC) curves show the predictive value of composite score for overall survival was superior to other scores. Conclusion: The composite score is a promising prognostic signature which might distinguish immune and molecular characteristics, predict prognosis, and guide more effective immunotherapeutic strategies for head and neck squamous cell carcinoma.

Role of immune-inflamed phenotype in the prognosis of hypopharyngeal carcinoma following primary surgery

BACKGROUND

The immune profile in primary resected hypopharyngeal squamous cell carcinoma (HPSCC) and its prognostic value remain to be defined.

METHODS

We enrolled 100 patients with HPSCC underwent primary surgical resection at our department. HPSCC samples were examined using immunohistochemistry for the expressions of CD8, Foxp3, CD163, CD66B, programmed death ligand-1 (PD-L1), and interferon (IFN)-γ. The immune pattern of the tumor microenvironment (TME) was discriminated into inflamed and non-inflamed tumors based on the presence or absence of parenchymal CD8⁺ T cells.

RESULTS

We found that 74% of HPSCC cases in our cohort were characterized by an immune-inflamed TME. Immune-inflamed patterns demonstrated an inferior survival with a significantly increased density of CD163⁺ tumor-associated macrophages and Foxp3⁺ regulatory T cells. Additionally, the inflamed tumor showed increased expression of PD-L1, without IFN-γ upregulation.

CONCLUSIONS

The immune-inflamed pattern is the predominant preexisting immune phenotype in HPSCC and demonstrates immunosuppressive immune cell recruitment.

A composite score based on immune-related gene prognostic index and m6A risk score of head and neck squamous cell carcinoma.. [DOI: 10.21203/rs.3.rs-1987322/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background:Immunotherapy has been demonstrated favorable in head and neck squamous cell carcinoma (HNSCC). Studies indicated that immune-related gene prognostic index (IRGPI) was a robust signature, and N6-methyladenosine (m6A) methylation had a significant impact on the tumor immune microenvironment (TIME) and immunotherapy of HNSCC. Thus, combining IRGPI with m6A status should offer a better predictive power for immune responses.Methods:HNSCC samples from The Cancer Genome Atlas (TCGA, n=498) and Gene Expression Omnibus database (GSE65858, n = 270) were used in this study. Cox regression analysis was used to construct the IRGPI through immune-related hub genes which were identified by weighted gene co-expression network analysis (WGCNA). The m6A risk score was constructed by least absolute shrinkage and selection operator regression analysis. Principal component analysis was used to construct a composite score, and systematically correlate subgroups according to TIME cell-infiltrating characteristics.Results:A composite score was determined based on IRGPI and m6A risk score. HNSCC patients in the TCGA were divided into four subgroups：A (IRGPI-High&m6A-risk-High, n=127), B (IRGPI-High&m6A-risk-Low, n=99), C (IRGPI-Low&m6A-risk-High, n=99) and D (IRGPI-Low&m6A-risk-Low, n=128), and overall survival (OS) was significantly different between subgroups (P< 0.001). The characteristics of TIME cell infiltration in the four subgroups were significantly different in subgroups (P< 0.05). The ROC curves show the predictive value of composite score for OS was superior to any other scores.Conclusions:The composite score is a promising prognostic signature which might distinguish immune and molecular characteristics, predict prognosis, and guide more effective immunotherapeutic strategies for HNSCC.

Nasopharyngeal Carcinoma Progression: Accumulating Genomic Instability and Persistent Epstein–Barr Virus Infection

Genomic instability facilitates the evolution of cells, tissues, organs, and species. The progression of human malignancies can be regarded as the accumulation of genomic instability, which confers a high evolutionary potential for tumor cells to adapt to continuous changes in the tumor microenvironment. Nasopharyngeal carcinoma (NPC) is a head-and-neck squamous-cell carcinoma closely associated with Epstein–Barr virus (EBV) infection. NPC progression is driven by a combination of accumulated genomic instability and persistent EBV infection. Here, we present a review of the key characteristics of genomic instability in NPC and the profound implications of EBV infection. We further discuss the significance of profiling genomic instability for the assessment of disease progression and treatment efficacy, as well as the opportunities and challenges of targeted therapies for NPC based on its unique genomic instability.

Complete Response to Nivolumab in Recurrent/Metastatic HPV-Positive Head and Neck Squamous Cell Carcinoma Patient After Progressive Multifocal Leukoencephalopathy: A Case Report

In an immune-competent context nivolumab showed long-term benefit in overall survival in recurrent/metastatic head and neck squamous cell carcinoma (HNSCC); however, in special cancer population such as these patients with immunodeficiency and viral infections, data on checkpoint inhibitors (ICI) activity are scant. Herein, we report a patient with a Human papilloma virus (HPV)-related oropharyngeal cancer (OPC) and CD4 lymphocytopenia. After a first-line treatment complete remission, the patient experienced Human Polyomavirus (JCV) infection in the brain. Consequently, to the recovery from progressive multifocal leukoencephalopathy (PML) the patient metastasized and was enrolled in a single-arm trial with nivolumab (EudraCT number: 2017-000562-30). A complete and durable response (more 3 years) was observed after 10 nivolumab injections Q2wks, interrupted for persistent drug related G2 diarrhea and a syndrome of inappropriate antidiuretic hormone secretion. We describe the circulating immune profile (before-, during-, and after nivolumab), consistent with the clinical history. Moreover, during nivolumab treatment, brain MRI evidenced the presence of small punctuate areas of contrast enhancement, reflecting a mild immune response in perivascular spaces. By cytofluorimetry, we observed that during JCV infection the CD4/CD8 ratio of the patient was under the normal values. After JCV infection recovery and before nivolumab treatment, CD4/CD8 ratio reached the normality threshold, even if the CD4⁺ T cell count remained largely under the normal values. During ICI, gene expression xCell analyses of circulating immune cells of the patient, showed a progressive normalization of the total immune profile, with significant boost in CD4⁺ and CD8⁺ T cells and a reduction in NK T, comparable to the circulating immune profile of reference tumor-free HNSCC patients. The present case supports the activity of ICI in a population of special cancer patients; whether JCV and HPV infections (alone or together) might have a possible role as immune booster(s), require further investigations.

Pembrolizumab plus docetaxel for the treatment of recurrent/metastatic head and neck cancer: A prospective phase I/II study

BACKGROUND

Taxane-based checkpoint inhibitor combination therapy might improve the outcome in recurrent/metastatic (R/M) head and neck cancer (HNSCC) patients. Thus, we investigated the efficacy and safety of docetaxel (DTX) plus pembrolizumab (P) in a prospective phase I/II trial.

METHODS

Platinum-resistant R/M HNSCC patients received DTX 75 mg/m^2 plus P 200 mg for up to six cycles followed by P maintenance therapy. The primary endpoint was overall response rate (ORR) and safety. Secondary endpoints comprised disease control rate (DCR), overall survival (OS) and progression free survival (PFS).

RESULTS

Twenty-two patients were enrolled. Nine patients (40.9%) had a primary tumor in the oropharynx, 8 (36.4%) in the oral cavity, 3 (13.6%) in the hypopharynx and 2 (9.1%) in the larynx. The ORR was 22.7% (95% CI 10.1%-43.4%) and one (4.5%) complete response was achieved. The DCR was 54.6% (95% 34.7%-73.1%). The median PFS was 5.8 months (95% CI 2.7-11.6) and the median OS 21.3 months (95% CI 6.3-31.1). The 1-year PFS and OS rates were 27.3% and 68.2%, respectively. While the most frequent adverse event (AE) was myelosuppression, which was reported in all 22 patients, 3 (13.6%) patients experienced grade 3 febrile neutropenia. The most common immune-related AEs were grade skin rash (40.9%) and hypothyroidism (40.9%). One patient (4.5%) experienced grade 5 immune thrombocytopenia.

CONCLUSION

DXT in combination with P shows promising activity accompanied with a manageable side effect profile in pre-treated R/M HNSCC patients.

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.

Combination of Tumor Mutational Burden and Specific Gene Mutations Stratifies Outcome to Immunotherapy Across Recurrent and Metastatic Head and Neck Squamous Cell Carcinoma

Purpose: To investigate the prognostic significance of tumor mutational burden (TMB) combined with specific prognosis-related gene mutations in immunotherapy for recurrent and metastatic head and neck squamous cell carcinoma (r/m HNSCC).

Methods: One hundred thirty-two r/m HNSCC patients from the Morris and Allen cohorts had undergone immunotherapy. We constructed the immunotherapy-related gene prognostic index TP-PR combining TMB and PIK3CA, TP53, or ROS1 mutation. And we analyzed the differences in overall survival (OS) and immune cell infiltration between samples in different groups. The association of each signature’s single-sample gene set enrichment analysis scores with TP-PR was tested using Spearman’s correlation test.

Results: The median OS of the patients with high TMB (TMB ≥10 mut/Mb) who received immunotherapy for r/m HNSCC was 2.5 times as long as that of the patients with low TMB (25 vs. 10 months). More importantly, the high TP-PR (TP-PR >0) group had better median OS (25 vs. 8 months) than the low TP-PR (TP-PR ≤0) group. CD8⁺ T cells and activated memory CD4⁺ T cells in the tissues of the patients with high TP-PR were higher than those in the patients with low TP-PR. Results showed that TP-PR stratification had a higher area under the curve (AUC) value (0.77, 95% CI 0.86–0.68) compared with TMB stratification (0.56, 95% CI 0.68–0.44). The differential gene expression in the high and low TP-PR groups mainly influenced metabolism-related signaling pathways.

Conclusion: TP-PR was an effective predictor of immunotherapy outcome for r/m HNSCC, which might be better than TMB alone. Patients with high TP-PR had a better survival benefit than had the patients with low TP-PR.

Bayesian Networks to Support Decision-Making for Immune-Checkpoint Blockade in Recurrent/Metastatic (R/M) Head and Neck Squamous Cell Carcinoma (HNSCC)

Simple Summary

Tumor therapy in many human malignancies, including head and neck cancer, is increasingly demanding due to advances in diagnostics and individualized treatments. Multidisciplinary tumor boards, especially molecular tumor boards, consider a great amount of information to find the optimal treatment decision. Clinical decision support systems can help in optimizing this complex decision-making process. We designed a digital patient model based on conditional probability algorithms as Bayesian networks to support the decision-making process regarding treatment with approved immunotherapeutic agents (Nivolumab and Pembrolizumab). The model is able to process relevant clinical information to recommend a certain immunotherapeutic agent based on literature, approval, and guidelines.

Abstract

New diagnostic methods and novel therapeutic agents spawn additional and heterogeneous information, leading to an increasingly complex decision-making process for optimal treatment of cancer. A great amount of information is collected in organ-specific multidisciplinary tumor boards (MDTBs). By considering the patient’s tumor properties, molecular pathological test results, and comorbidities, the MDTB has to consent an evidence-based treatment decision. Immunotherapies are increasingly important in today’s cancer treatment, resulting in detailed information that influences the decision-making process. Clinical decision support systems can facilitate a better understanding via processing of multiple datasets of oncological cases and molecular genetic information, potentially fostering transparency and comprehensibility of available information, eventually leading to an optimum treatment decision for the individual patient. We constructed a digital patient model based on Bayesian networks to combine the relevant patient-specific and molecular data with depended probabilities derived from pertinent studies and clinical guidelines to calculate treatment decisions in head and neck squamous cell carcinoma (HNSCC). In a validation analysis, the model can provide guidance within the growing subject of immunotherapy in HNSCC and, based on its ability to calculate reliable probabilities, facilitates estimation of suitable therapy options. We compared actual treatment decisions of 25 patients with the calculated recommendations of our model and found significant concordance (Cohen’s κ = 0.505, p = 0.009) and 84% accuracy.

Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity

Simple Summary

Squamous cell carcinoma (SCC) is the most prevalent type of human cancer worldwide and represents the majority of head and neck tumors. As SCC from aerodigestive or genitourinary tracts share not only common etiology and histological features but also molecular patterns, the major objectives of this study were the establishment of a pan-SCC-related prognostic gene signature by an integrative analysis of multi-omics data and the elucidation of underlying oncogenic pathway activities as potential vulnerabilities for a more efficient and less toxic therapy. Our approach delivers a reliable molecular classifier to identify HNSCC and other SCC patients at higher risk for treatment failure with tumors characterized by a more prominent MAPK activity, who might benefit from a targeted treatment with MEK inhibitors.

Abstract

Squamous cell carcinoma (SCC) is the most prevalent histological type of human cancer, including head and neck squamous cell carcinoma (HNSCC). However, reliable prognostic gene signatures for SCC and underlying genetic and/or epigenetic principles are still unclear. We identified 37 prognostic candidate genes by best cutoff computation based on survival in a pan-SCC cohort (n = 1334) of The Cancer Genome Atlas (TCGA), whose expression stratified not only the pan-SCC cohort but also independent HNSCC validation cohorts into three distinct prognostic subgroups. The most relevant prognostic genes were prioritized by a Least Absolute Shrinkage and Selection Operator Cox regression model and were used to identify subgroups with high or low risks for unfavorable survival. An integrative analysis of multi-omics data identified FN1, SEMA3A, CDH2, FBN1, COL5A1, and ADAM12 as key nodes in a regulatory network related to the prognostic phenotype. An in-silico drug screen predicted two MEK inhibitors (Trametinib and Selumetinib) as effective compounds for high-risk SCC based on the Cancer Cell Line Encyclopedia, which is supported by a higher p-MEK1/2 immunohistochemical staining of high-risk HNSCC. In conclusion, our data identified a molecular classifier for high-risk HNSCC as well as other SCC patients, who might benefit from treatment with MEK inhibitors.

Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review

Recent developments have revolutionized the study of biomolecules. Among them are molecular markers, amplification and sequencing of nucleic acids. The latter is classified into three generations. The first allows to sequence small DNA fragments. The second one increases throughput, reducing turnaround and pricing, and is therefore more convenient to sequence full genomes and transcriptomes. The third generation is currently pushing technology to its limits, being able to sequence single molecules, without previous amplification, which was previously impossible. Besides, this represents a new revolution, allowing researchers to directly sequence RNA without previous retrotranscription. These technologies are having a significant impact on different areas, such as medicine, agronomy, ecology and biotechnology. Additionally, the study of biomolecules is revealing interesting evolutionary information. That includes deciphering what makes us human, including phenomena like non-coding RNA expansion. All this is redefining the concept of gene and transcript. Basic analyses and applications are now facilitated with new genome editing tools, such as CRISPR. All these developments, in general, and nucleic-acid sequencing, in particular, are opening a new exciting era of biomolecule analyses and applications, including personalized medicine, and diagnosis and prevention of diseases for humans and other animals.