A TP53 mutation model for the prediction of prognosis and therapeutic responses in head and neck squamous cell carcinoma

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Characterization of macrophages in head and neck squamous cell carcinoma and development of MRG-based risk signature

Macrophages are immune cells in the TME that can not only inhibit angiogenesis, extracellular matrix remodeling, cancer cell proliferation, and metastasis but also mediate the phagocytosis and killing of cancer cells after activation, making them key targets in anti-tumor immunotherapy. However, there is little research on macrophages and their relation to disease prognosis in HNSCC. Initially, we collected scRNA-seq, bulk RNA-seq, and clinical data. Subsequently, we identified macrophages and distinguished MRGs. Using the K-means algorithm, we performed consensus unsupervised clustering. Next, we used ssGSEA analysis to assess immune cell infiltration in MRG clusters. A risk model was established using multivariate Cox analysis. Then, Kaplan-Meier, ROC curves, univariate and multivariate COX analyses, and C-index was used to validate the predictive power of the signature. The TIDE method was applied to assess the response to immunotherapy in patients diagnosed with HNSCC. In addition, drug susceptibility predictions were made for the GDSC database using the calcPhenotype function. We found that 8 MRGs had prognostic potential. Patients in the MRG group A had a higher probability of survival, and MRG clusters A and B had different characteristics. Cluster A had a higher degree of expression and infiltration in MRG, indicating a closer relationship with MRG. The accuracy of the signature was validated using univariate and multivariate Cox analysis, C-index, and nomogram. Immune landscape analysis found that various immune functions were highly expressed in the low-risk group, indicating an improved response to immunotherapy. Finally, drugs with high sensitivity to HNSCC (such as 5-Fluorouracil, Temozolomide, Carmustine, and EPZ5676) were explored and analyze the malignant characteristics of HNSCC. We constructed a prognostic model using multivariate Cox analysis, consisting of 8 MRGs (TGM2, STC1, SH2D3C, PIK3R3, MAP3K8, ITGA5, ARHGAP4, and AQP1). Patients in the low-risk group may have a higher response to immunotherapy. The more prominent drugs for drug selection are 5-fluorouracil, temozolomide and so on. Malignant features associated with HNSCC include angiogenesis, EMT, and the cell cycle. This study has opened up new prospects for the prognosis, prediction, and clinical treatment strategy of HNSCC.

High-grade intraductal carcinoma of the parotid gland harboring CTNNA1::ALK rearrangement: Changes in genetic status using genetic testing during treatment with an ALK inhibitor

BACKGROUND

Salivary gland carcinomas harboring anaplastic lymphoma kinase (ALK) rearrangements are rare. Here, we present the pathological characteristics, clinical course, and changes in the genetic status of a salivary gland carcinoma harboring a catenin alpha 1 (CTNNA1)::ALK rearrangement during treatment with an ALK tyrosine kinase inhibitor (TKI).

METHODS

A 59-year-old man with a parotid tumor and cervical lymph node metastases underwent total parotidectomy and radical neck dissection. One month after completion of postoperative radiotherapy, the patient experienced multiple recurrences.

RESULTS

Subsequent treatment with the ALK-TKI alectinib was initially effective against the intraductal carcinoma harboring CTNNA1::ALK rearrangement and TP53 mutation. However, 10 months later the patients' condition deteriorated, and an additional phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutation was detected. The patient ultimately succumbed to multiple organ failure.

CONCLUSION

The clinical course suggested the concurrent emergence of TP53 and PIK3CA mutations and ALK-TKI drug-selective growth of non-ALK rearrangement gene tumor cells.

Exploring the regulatory interactions between mutated genes and homeobox genes in the head and neck cancer progression

OBJECTIVE

Understanding the regulatory role of homeobox (HOX) and mutated genes in the progression of head and neck cancers is essential, although their interaction remains elusive. This study aims to decipher the critical regulation of mutation driven effects on homeobox genes to enhance our understanding of head and neck cancer progression.

METHODS

Genomic mutation data from The Cancer Genome Atlas-Head and Neck Squamous Cell Carcinoma were analyzed using VarScan2 for somatic variant detection. Mutational clustering, driver mutation identification, and cancer signaling pathway analysis were performed using the OncodriveCLUST method. Harmonizome datasets were retrieved to identify critical cancer driver genes affecting HOX genes. The effects of HPV infection on HOX and mutated genes were assessed using the oncoviral database. Altered pathway activity due to the effects of cancer drivers on HOX genes was analyzed with Gene Set Cancer Analysis. Functional enrichment analysis of gene ontology biological processes and molecular functions was conducted using the ClusterProfiler R package.

RESULTS

Significant alterations in HOX genes were observed in head and neck cancer cohorts with mutated TP53, FAT1, and CDKN2A. HOX genes were identified as functionally downstream targets of TP53, signifying transcriptionally mediated regulation. The interaction between HOX genes and mutated TP53, FAT1, and CDKN2A dysregulated the epithelial-to-mesenchymal transition, cell cycle, and apoptosis pathways in head and neck cancer progression.

CONCLUSION

The interplay between cancer driver genes and HOX genes is pivotal in regulating the oncogenic processes underlying the pathogenesis of head and neck squamous cell carcinoma.

High-Resolution Profiling of Head and Neck Squamous Cells Carcinoma Identifies Specific Biomarkers and Expression Subtypes of Clinically Relevant Vulnerabilities

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) is the seventh most common cancer worldwide. Although there are several options for the treatment of HNSC, there is still a lack of better biomarkers to accurately predict the response to treatment and thus be more able to correctly treat the therapeutic modality.

METHODS

First, we typed cases from the TCGA-HNSC cohort into subtypes by a Bayesian non-negative matrix factorization (BayesNMF)-based consensus clustering approach. Subsequently, genomic and proteomic data from HNSC cell lines were integrated to identify biomarkers of response to targeted therapies and immunotherapies. Finally, associations between HNSC subtypes and CD8 T-cell-associated effector molecules, common immune checkpoint genes, were compared to assess the potential of HNSC subtypes as clinically predictive immune checkpoint blockade therapy.

RESULTS

The 500 HNSC cases from TCGA were put through a consensus clustering approach to identify six HNSC expression subtypes. In addition, subtypes with unique proteomics and dependency profiles were defined based on HNSC cell line histology and proteomics data. Subtype 4 (S4) exhibits hyperproliferative and hyperimmune properties, and S4-associated cell lines show specific vulnerability to ADAT2, EIF5AL1, and PAK2. PD-L1 and CASP1 inhibitors have therapeutic potential in S4, and we have also demonstrated that S4 is more responsive to immune checkpoint blockade therapy.

CONCLUSION

Overall, our HNSC typing approach identified robust tumor-expressing subtypes, and data from multiple screens also revealed subtype-specific biology and vulnerabilities. These HNSC expression subtypes and their biomarkers will help develop more effective therapeutic strategies.

Predicting therapeutic responses in head and neck squamous cell carcinoma from TP53 mutation detected by cell-free DNA

Background

Head and neck squamous cell carcinoma (HNSCC) is an epithelial malignant tumor originating from the oral cavity, oropharynx, nasal cavity, sinuses, nasopharynx, hypopharynx, or larynx. Mutations in TP53 are the most common of all somatic genomic changes in HNSCC, and TP53 mutations are associated with the response to immunotherapy and chemotherapy. Tumor-derived circulating cell-free DNA (cfDNA) is a minimally invasive method to determining genetic alterations in cancer. This study aimed to explore the therapeutic responses of patients with HNSCC with TP53 mutation and the accuracy of cfDNA for detecting TP53 mutation.

Methods

Information on TP53 mutations, patient survival time, and clinical data in HNSCC were downloaded from The Cancer Genome Atlas database. The difference in immune infiltration between the TP53-mutant group and the wild-type group was compared. We applied the single-sample gene set enrichment analysis method on the transcriptome of HNSCC samples to assess the distribution of immune cell types between the two groups. The chemotherapy response was constructed using the R software package, "pRRophetic". Gene set enrichment analysis was performed based on the TP53 mutation. The next-generation sequencing was executed on cfDNA from nine patients with HNSCC to detect genetic alterations. Tumor biopsy (n=9) was sequenced using the same technique.

Results

TP53 was the most frequently mutated gene in HNSCC. The TP53 mutation was related to immune cells and the expression of immune-associated genes. The TP53 mutation group showed lower response to immunotherapy but high sensitivity to some chemotherapies compared with the wild-type group. TP53 was the most frequently mutated gene (6/9; 66.67%) in cfDNA. Only 27.27% of TP53 mutations in tumor tissue were detected outside of cfDNA.

Conclusions

TP53 mutation could be used as a specific predictor of treatment response in patients with HNSCC. Using cfDNA to detect the TP53 mutations in patients with HSNCC is a feasible method. The results suggested that the therapeutic response in patients could be predicted by detecting TP53 mutations in cfDNA, and large-scale and prospective studies are needed to validate this hypothesis.

The repertoire of mutational signatures in tobacco- and non-tobacco-induced oral cancer

The use of tobacco products is one of the established contributors toward the development and spread of oral cancer. Additionally, recent research has indicated oral microbiome, infections with Human papilloma virus (HPV), Epstein-Barr virus (EBV), Candida as significant contributing factors to this disease along with lifestyle habits. Deregulation of cellular pathways envisaging metabolism, transcription, translation, and epigenetics caused by these risk factors either individually or in unison is manifold, resulting in the increased risk of oral cancer. Globally, this cancer continues to exist as one of the major causes of cancer-related mortalities; the numbers in the developing South Asian countries clearly indicate yearly escalation. This review encompasses the variety of genetic modifications, including adduct formation, mutation (duplication, deletion, and translocation), and epigenetic changes evident in oral squamous cell carcinoma (OSCC). In addition, it highlights the interference caused by tobacco products in Wnt signaling, PI3K/Akt/mTOR, JAK-STAT, and other important pathways. The information provided also ensures a comprehensive and critical revisit to non-tobacco-induced OSCC. Extensive literature survey and analysis has been conducted to generate the chromosome maps specifically highlighting OSCC-related mutations with the potential to act as spectacles for the early diagnosis and targeted treatment of this disease cancer.

Characterization on the oncogenic effect of the missense mutations of p53 via machine learning

Dysfunctions caused by missense mutations in the tumour suppressor p53 have been extensively shown to be a leading driver of many cancers. Unfortunately, it is time-consuming and labour-intensive to experimentally elucidate the effects of all possible missense variants. Recent works presented a comprehensive dataset and machine learning model to predict the functional outcome of mutations in p53. Despite the well-established dataset and precise predictions, this tool was trained on a complicated model with limited predictions on p53 mutations. In this work, we first used computational biophysical tools to investigate the functional consequences of missense mutations in p53, informing a bias of deleterious mutations with destabilizing effects. Combining these insights with experimental assays, we present two interpretable machine learning models leveraging both experimental assays and in silico biophysical measurements to accurately predict the functional consequences on p53 and validate their robustness on clinical data. Our final model based on nine features obtained comparable predictive performance with the state-of-the-art p53 specific method and outperformed other generalized, widely used predictors. Interpreting our models revealed that information on residue p53 activity, polar atom distances and changes in p53 stability were instrumental in the decisions, consistent with a bias of the properties of deleterious mutations. Our predictions have been computed for all possible missense mutations in p53, offering clinical diagnostic utility, which is crucial for patient monitoring and the development of personalized cancer treatment.

FBP1 is a potential prognostic biomarker and correlated with tumor immunosuppressive microenvironment in glioblastoma

Hypoxia has been shown to contribute to tumor immunosuppressive microenvironment and is an effective prognostic indicator. This study aimed to screen prognostic hypoxia-related genes (HRGs) in glioblastoma and investigate the association between HRGs and tumor immunosuppressive microenvironment. The glioblastoma-related mRNA data were collected from TCGA, GEO, and CGGA databases. Totally 200 HRGs were obtained from the GSEA website. The prognostic HRGs were screened by univariate Cox regression analysis. Somatic mutation data of glioblastoma from TCGA was visualized using the "maftools" of R package. Immune cell infiltration proportions were calculated by CIBERSORT. The TISIDB online tool was applied to analyze the relationship between HRGs and immunoinhibitors as well as the HRG expression in different glioblastoma immune and molecular subtypes. Hub gene's mRNA and protein levels in cell lines were determined by qRT-PCR and western blot, respectively. The effects of hub gene knockdown on cell viability and migration ability were evaluated employing CCK8 and wound healing assays. The univariate Cox regression showed that high level of FBP1 (fructose-1,6-bisphosphatase 1) was a poor prognostic biomarker, and FBP1 was mainly expressed in lymphocyte depleted immune subtype of glioblastoma. High FBP1 mRNA and protein levels have been successfully validated in vitro. The somatic mutation analysis suggested that TP53 mutation rate was the highest in the high FBP1 glioblastoma group, while EGFR mutation rate was the highest in the low FBP1 glioblastoma group. In the high FBP1 group, the infiltration proportions and types of immune cells were less, dominated by macrophages M2, and the expression of CTLA4, LAG3, TIGIT, PDL1, and PDL2 was significantly upregulated. The expression of FBP1 was positively correlated with several immunoinhibitors, such as IL-10 and TGFβ-1. In conclusion, we demonstrated that FBP1 could serve as a prognostic biomarker for glioblastoma. The immune microenvironment in the high FBP1 group might be suppressed by up-regulating immune checkpoints and immunoinhibitors.

Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has one of the highest mortality rates among solid cancers. Late diagnosis and a lack of efficacious treatment options contribute to the dismal prognosis of HCC. Immune checkpoint inhibitor (ICI)-based immunotherapy has presented a new milestone in the treatment of cancer. Immunotherapy has yielded remarkable treatment responses in a range of cancer types including HCC. Based on the therapeutic effect of ICI alone (programmed cell death (PD)-1/programmed death-ligand1 (PD-L)1 antibody), investigators have developed combined ICI therapies including ICI + ICI, ICI + tyrosine kinase inhibitor (TKI), and ICI + locoregional treatment or novel immunotherapy. Although these regimens have demonstrated increasing treatment efficacy with the addition of novel drugs, the development of biomarkers to predict toxicity and treatment response in patients receiving ICI is in urgent need. PD-L1 expression in tumor cells received the most attention in early studies among various predictive biomarkers. However, PD-L1 expression alone has limited utility as a predictive biomarker in HCC. Accordingly, subsequent studies have evaluated the utility of tumor mutational burden (TMB), gene signatures, and multiplex immunohistochemistry (IHC) as predictive biomarkers. In this review, we aim to discuss the current state of immunotherapy for HCC, the results of the predictive biomarker studies, and future direction.

Potential Alternative Therapeutic Modalities for Management Head and Neck Squamous Cell Carcinoma: A Review

Head and neck squamous cell carcinoma (HNSCC) includes malignancies of the lip and oral cavity, oropharynx, nasopharynx, larynx, and hypopharynx. It is among the most common malignancy worldwide, affecting nearly 1 million people annually. The traditional treatment options for HNSCC include surgery, radiotherapy, and conventional chemotherapy. However, these treatment options have their specific sequelae, which produce high rates of recurrence and severe treatment-related disabilities. Recent technological advancements have led to tremendous progress in understanding tumor biology, and hence the emergence of several alternative therapeutic modalities for managing cancers (including HNSCC). These treatment options are stem cell targeted therapy, gene therapy, and immunotherapy. Therefore, this review article aims to provide an overview of these alternative treatments of HNSCC.

Prognostic signature of endoplasmic reticulum stress-related long noncoding RNAs in head and neck squamous cell carcinoma: Association with somatic mutation and tumor immune microenvironment

Background/purpose

Analysis of endoplasmic reticulum stress (ERS)-related long noncoding RNAs (LncRNAs) may enable prognostic stratification in patients with head and neck squamous cell carcinoma (HNSCC). This study aimed to comprehensively analyze the ERS-related LncRNAs signature and its effects on the prognosis, tumorigenesis, and tumor immune microenvironment in HNSCC.

Materials and methods

The transcriptome data of HNSCC were obtained from TCGA. Least absolute shrinkage selection operator algorithm, and multivariate Cox regression were used to screen LncRNAs for the signature construction. Somatic mutation, gene enrichment, and immune infiltration analyses were further performed.

Results

458 ERS-related LncRNAs were identified and 55 of which were correlated with HNSCC prognosis. Ten ERS-related LncRNAs were selected to establish a risk prediction signature. When dividing patients into high-risk and low-risk groups by signature score, high-risk group correlated with worse survival rates (hazard ratio = 1.211; 95% confidence interval 1.123-1.306, P < 0.001). The area under the curve was 0.751 and 0.716 in the training and validation cohorts at 3-year. Moreover, high-risk group have increased somatic mutation rates and reduced infiltration abundancy of B cells and CD8+ T cells.

Conclusion

The prognostic signature based on ERS-related LncRNAs may serve as a predictor of altered oncogene mutations and immune microenvironment, which provided an insight into the relationship between ERS, LncRNAs, and tumor progression.

Update of a prognostic survival model in head and neck squamous cell carcinoma patients treated with immune checkpoint inhibitors using an expansion cohort

Background

Immune checkpoint inhibitors (ICI) treatment in recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) offers new therapeutic venues. We have previously developed a predictive survival model in this patient population based on clinical parameters, and the purpose of this study was to expand the study cohort and internally validate the model.

Methods

A single institutional retrospective analysis of R/M HNSCC patients treated with ICI. Clinical parameters collected included p-16 status, hemoglobin (Hb), albumin (Alb), lactate dehydrogenase (LDH), neutrophil, lymphocyte and platelet counts. Cox proportional hazard regression was used to assess the impact of patient characteristics and clinical variables on survival. A nomogram was created using the rms package to generate individualized survival prediction.

Results

201 patients were included, 47 females (23%), 154 males (77%). Median age was 61 years (IQR: 55-68). P-16 negative (66%). Median OS was 12 months (95% CI: 9.4, 14.9). Updated OS model included age, sex, absolute neutrophil count, absolute lymphocyte count, albumin, hemoglobin, LDH, and p-16 status. We stratified patients into three risk groups based on this model at the 0.33 and 0.66 quantiles. Median OS in the optimal risk group reached 23.7 months (CI: 18.5, NR), 13.8 months (CI: 11.1, 20.3) in the average risk group, and 2.3 months (CI: 1.7, 4.4) in the high-risk group. Following internal validation, the discriminatory power of the model reached a c-index of 0.72 and calibration slope of 0.79.

Conclusions

Our updated nomogram could assist in the precise selection of patients for which ICI could be beneficial and cost-effective.

Inhibition of TP53 Mutant Oral Cancer by Reactivating p53

Background: Mutation of p53 is a frequent event, and mutant p53 exhibits low levels of acetylation and phosphorylation. This study aimed to investigate the effect of the histone deacetylase (HDAC) inhibitor, 4-hexylresorcinol (4HR), on the acetylation and phosphorylation of mutant p53 carcinoma cells and its therapeutic effects in a xenograft model. Methods: To determine the effect of 4HR on the acetylation and phosphorylation of p53, western blot analysis was performed using YD-9 and YD-15 cells. p53 siRNA was used to examine whether 4HR acts in a p53-dependent or independent manner. This was evaluated using a xenograft model. Results: In in vitro experiments when the concentration of 4HR was increased, the expression levels of HDAC4, acetylated p53 (Ac-p53), and phosphorylated p53 (p-p53) increased. Transfection with TP53 siRNA successfully suppressed p53 protein and TP53 mRNA expression. When 4HR was administered to a xenograft model, the tumour expansion rate was suppressed compared with the control, and the mice exhibited a higher survival rate. Conclusions: Our findings reveal that 4HR is a potential agent that restores loss of function in mutant p53 cancer cells via acetylation and phosphorylation of p53 as well as inhibition of HDAC4.

NAMPT Inhibitor and P73 Activator Represses P53 R175H Mutated HNSCC Cell Proliferation in a Synergistic Manner

The p53 family has the following three members: p53, p63 and p73. p53 is a tumor suppressor gene that frequently exhibits mutation in head and neck cancer. Most p53 mutants are loss-of-function (LoF) mutants, but some acquire some oncogenic function, such as gain of function (GoF). It is known that the aggregation of mutant p53 can induce p53 GoF. The p73 activators RETRA and NSC59984 have an anti-cancer effect in p53 mutation cells, but we found that p73 activators were not effective in all head and neck squamous cell carcinoma (HNSCC) cell lines, with different p53 mutants. A comparison of the gene expression profiles of several regulator(s) in mutant HNSCC cells with or without aggregation of p53 revealed that nicotinamide phosphoribosyltransferase (NAMPT) is a key regulator of mutant p53 aggregation. An NAMPT inhibitor, to reduce abnormal aggregation of mutant p53, used in combination with a p73 activator, was able to effectively repress growth in HNSCC cells with p53 GoF mutants. This study, therefore, suggests a potential combination therapy approach for HNSCC with a p53 GoF mutation.