Gene expression profiling predicts the development of oral cancer

Molecular and Therapeutic Roles of Non-Coding RNAs in Oral Cancer-A Review

Oral cancer (OC) is among the most common malignancies in the world. Despite advances in therapy, the worst-case scenario for OC remains metastasis, with a 50% survival rate. Therefore, it is critical to comprehend the pathophysiology of the condition and to create diagnostic and treatment plans for OC. The development of high-throughput genome sequencing has revealed that over 90% of the human genome encodes non-coding transcripts, or transcripts that do not code for any proteins. This paper describes the function of these different kinds of non-coding RNAs (ncRNAs) in OC as well as their intriguing therapeutic potential. The onset and development of OC, as well as treatment resistance, are linked to dysregulated ncRNA expression. These ncRNAs' potentially significant roles in diagnosis and prognosis have been suggested by their differing expression in blood or saliva. We have outlined every promising feature of ncRNAs in the treatment of OC in this study.

Loss of p53-DREAM-mediated repression of cell cycle genes as a driver of lymph node metastasis in head and neck cancer

BACKGROUND

The prognosis for patients with head and neck cancer (HNC) is poor and has improved little in recent decades, partially due to lack of therapeutic options. To identify effective therapeutic targets, we sought to identify molecular pathways that drive metastasis and HNC progression, through large-scale systematic analyses of transcriptomic data.

METHODS

We performed meta-analysis across 29 gene expression studies including 2074 primary HNC biopsies to identify genes and transcriptional pathways associated with survival and lymph node metastasis (LNM). To understand the biological roles of these genes in HNC, we identified their associated cancer pathways, as well as the cell types that express them within HNC tumor microenvironments, by integrating single-cell RNA-seq and bulk RNA-seq from sorted cell populations.

RESULTS

Patient survival-associated genes were heterogenous and included drivers of diverse tumor biological processes: these included tumor-intrinsic processes such as epithelial dedifferentiation and epithelial to mesenchymal transition, as well as tumor microenvironmental factors such as T cell-mediated immunity and cancer-associated fibroblast activity. Unexpectedly, LNM-associated genes were almost universally associated with epithelial dedifferentiation within malignant cells. Genes negatively associated with LNM consisted of regulators of squamous epithelial differentiation that are expressed within well-differentiated malignant cells, while those positively associated with LNM represented cell cycle regulators that are normally repressed by the p53-DREAM pathway. These pro-LNM genes are overexpressed in proliferating malignant cells of TP53 mutated and HPV + ve HNCs and are strongly associated with stemness, suggesting that they represent markers of pre-metastatic cancer stem-like cells. LNM-associated genes are deregulated in high-grade oral precancerous lesions, and deregulated further in primary HNCs with advancing tumor grade and deregulated further still in lymph node metastases.

CONCLUSIONS

In HNC, patient survival is affected by multiple biological processes and is strongly influenced by the tumor immune and stromal microenvironments. In contrast, LNM appears to be driven primarily by malignant cell plasticity, characterized by epithelial dedifferentiation coupled with EMT-independent proliferation and stemness. Our findings postulate that LNM is initially caused by loss of p53-DREAM-mediated repression of cell cycle genes during early tumorigenesis.

SNAI2 promotes the malignant transformation of oral leukoplakia by modulating p-EMT

OBJECTIVE

Snail family transcriptional repressor 2 (SNAI2) is a key regulator of partial epithelial-mesenchymal transition (p-EMT) and is associated with tumorigenesis. Whether SNAI2 promotes oral leukoplakia (OLK) malignant transformation by modulating p-EMT is unclear.

MATERIALS AND METHODS

This study utilized two clinical datasets (GSE26549 and GSE85195) from the Gene Expression Omnibus database, cytological experiments, and a 4-nitroquinoline 1-oxide-induced mice model to explore the role of SNAI2 in OLK malignant transformation.

RESULTS

The clinical cohort found SNAI2, as a risk factor (HR = 2.50, 95% CI: 1.08-5.79, p = 0.033), could promote OLK malignant transformation (p = 0.012). Cytological experiments indicated that SNAI2 overexpression promoted DOK cell proliferation, invasion, migration, and increase the protein expression of p-EMT relative signatures, whereas SNAI2 silencing has opposite effects. Furthermore, the mice model and clinical datasets demonstrated the expression of SNAI2 and p-EMT relative signatures were increased with OLK malignant transformation. And SNAI2 was strongly correlated with p-EMT. Besides, co-expressed genes of SNAI2 were also enriched in p-EMT relative biological processes and signaling pathways.

CONCLUSIONS

p-EMT plays a significant role in promoting the OLK malignant transformation. As an important regulator of p-EMT, SNAI2 could be a target to block the OLK malignant transformation.

Total RNA sequencing reveals gene expression and microbial alterations shared by oral pre-malignant lesions and cancer

Head and neck cancers are a complex malignancy comprising multiple anatomical sites, with cancer of the oral cavity ranking among the deadliest and the most disfiguring cancers globally. Oral cancer (OC) constitutes a subset of head and neck cancer cases, presenting primarily as tobacco- and alcohol-associated oral squamous cell carcinoma (OSCC), with a 5-year survival rate of ~ 65%, partly due to the lack of early detection and effective treatments. OSCC arises from premalignant lesions (PMLs) in the oral cavity through a multi-step series of clinical and histopathological stages, including varying degrees of epithelial dysplasia. To gain insights into the molecular mechanisms associated with the progression of PMLs to OSCC, we profiled the whole transcriptome of 66 human PMLs comprising leukoplakia with dysplasia and hyperkeratosis non-reactive (HkNR) pathologies, alongside healthy controls and OSCC. Our data revealed that PMLs were enriched in gene signatures associated with cellular plasticity, such as partial EMT (p-EMT) phenotypes, and with immune response. Integrated analyses of the host transcriptome and microbiome further highlighted a significant association between differential microbial abundance and PML pathway activity, suggesting a contribution of the oral microbiome toward PML evolution to OSCC. Collectively, this study reveals molecular processes associated with PML progression that may help early diagnosis and disease interception at an early stage.

RNA-Based Liquid Biopsy in Head and Neck Cancer

Head and neck cancer (HNC) is a prevalent and diverse group of malignancies with substantial morbidity and mortality rates. Early detection and monitoring of HNC are crucial for improving patient outcomes. Liquid biopsy, a non-invasive diagnostic approach, has emerged as a promising tool for cancer detection and monitoring. In this article, we review the application of RNA-based liquid biopsy in HNC. Various types of RNA, including messenger RNA (mRNA), microRNA (miRNA), long non-coding RNA (lncRNA), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), circular RNA (circRNA) and PIWI-interacting RNA (piRNA), are explored as potential biomarkers in HNC liquid-based diagnostics. The roles of RNAs in HNC diagnosis, metastasis, tumor resistance to radio and chemotherapy, and overall prognosis are discussed. RNA-based liquid biopsy holds great promise for the early detection, prognosis, and personalized treatment of HNC. Further research and validation are necessary to translate these findings into clinical practice and improve patient outcomes.

The Way to Malignant Transformation: Can Epigenetic Alterations Be Used to Diagnose Early-Stage Head and Neck Cancer?

Identifying and treating tumors early is the key to secondary prevention in cancer control. At present, prevention of oral cancer is still challenging because the molecular drivers responsible for malignant transformation of the 11 clinically defined oral potentially malignant disorders are still unknown. In this review, we focused on studies that elucidate the epigenetic alterations demarcating malignant and nonmalignant epigenomes and prioritized findings from clinical samples. Head and neck included, the genomes of many cancer types are largely hypomethylated and accompanied by focal hypermethylation on certain specific regions. We revisited prior studies that demonstrated that sufficient uptake of folate, the primary dietary methyl donor, is associated with oral cancer reduction. As epigenetically driven phenotypic plasticity, a newly recognized hallmark of cancer, has been linked to tumor initiation, cell fate determination, and drug resistance, we discussed prior findings that might be associated with this hallmark, including gene clusters (11q13.3, 19q13.43, 20q11.2, 22q11-13) with great potential for oral cancer biomarkers, and successful examples in screening early-stage nasopharyngeal carcinoma. Although one-size-fits-all approaches have been shown to be ineffective in most cancer therapies, the rapid development of epigenome sequencing methods raises the possibility that this nonmutagenic approach may be an exception. Only time will tell.

Total RNA sequencing reveals gene expression and microbial alterations shared by oral pre-malignant lesions and cancer

Head and neck cancers are a complex malignancy comprising multiple anatomical sites, with cancer of the oral cavity ranking among the deadliest and most disfiguring cancers globally. Oral cancer (OC) constitutes a subset of head and neck cancer cases, presenting primarily as tobacco-and alcohol-associated oral squamous cell carcinoma (OSCC), with a 5-year survival rate of ∼65%, partly due to the lack of early detection and effective treatments. OSCC arises from premalignant lesions (PMLs) in the oral cavity through a multi-step series of clinical and histopathological stages, including varying degrees of epithelial dysplasia. To gain insights into the molecular mechanisms associated with the progression of PMLs to OSCC, we profiled the whole transcriptome of 66 human PMLs comprising leukoplakia with dysplasia and hyperkeratosis non-reactive (HkNR) pathologies, alongside healthy controls and OSCC. Our data revealed that PMLs were enriched in gene signatures associated with cellular plasticity, such as partial EMT (p-EMT) phenotypes, and with immune response. Integrated analyses of the host transcriptome and microbiome further highlighted a significant association between differential microbial abundance and PML pathway activity, suggesting a contribution of the oral microbiome towards PML evolution to OSCC. Collectively, this study reveals molecular processes associated with PML progression that may help early diagnosis and disease interception at an early stage.

AUTHOR SUMMARY

Patients harboring oral premalignant lesions (PMLs) have an increased risk of developing oral squamous cell carcinoma (OSCC), but the underlying mechanisms driving transformation of PMLs to OSCC remain poorly understood. In this study, Khan et al., analyzed a newly generated dataset of gene expression and microbial profiles of oral tissues from patients diagnosed with PMLs from differing histopathological groups, including hyperkeratosis not reactive ( HkNR ) and dysplasia, comparing these profiles with OSCC and normal oral mucosa. Significant similarities between PMLs and OSCC were observed, with PMLs manifesting several cancer hallmarks, including oncogenic and immune pathways. The study also demonstrates associations between the abundance of multiple microbial species and PML groups, suggesting a potential contribution of the oral microbiome to the early stages of OSCC development. The study offers insights into the nature of the molecular, cellular and microbial heterogeneity of oral PMLs and suggests that molecular and clinical refinement of PMLs may provide opportunities for early disease detection and interception.

Role of E2F transcription factor in Oral cancer: Recent Insight and Advancements

The family of mammalian E2F transcription factors (E2Fs) comprise of 8 members (E2F1-E2F8) classified as activators (E2F1-E2F3) and repressors (E2F4-E2F8) primarily regulating the expression of several genes related to cell proliferation, apoptosis and differentiation, mainly in a cell cycle-dependent manner. E2F activity is frequently controlled via the retinoblastoma protein (pRb), cyclins, p53 and the ubiquitin-proteasome pathway. Additionally, genetic or epigenetic changes result in the deregulation of E2F family genes expression altering S phase entry and apoptosis, an important hallmark for the onset and development of cancer. Although studies reveal E2Fs to be involved in several human malignancies, the mechanisms underlying the role of E2Fs in oral cancer lies nascent and needs further investigations. This review focuses on the role of E2Fs in oral cancer and the etiological factors regulating E2Fs activity, which in turn transcriptionally control the expression of their target genes, thus contributing to cell proliferation, metastasis, and drug/therapy resistance. Further, we will discuss therapeutic strategies for E2Fs, which may prevent oral tumor growth, metastasis, and drug resistance.

Identification of gene profiles related to the development of oral cancer using a deep learning technique

BACKGROUND

Oral cancer (OC) is a debilitating disease that can affect the quality of life of these patients adversely. Oral premalignant lesion patients have a high risk of developing OC. Therefore, identifying robust survival subgroups among them may significantly improve patient therapy and care. This study aimed to identify prognostic biomarkers that predict the time-to-development of OC and survival stratification for patients using state-of-the-art machine learning and deep learning.

METHODS

Gene expression profiles (29,096 probes) related to 86 patients from the GSE26549 dataset from the GEO repository were used. An autoencoder deep learning neural network model was used to extract features. We also used a univariate Cox regression model to select significant features obtained from the deep learning method (P < 0.05). High-risk and low-risk groups were then identified using a hierarchical clustering technique based on 100 encoded features (the number of units of the encoding layer, i.e., bottleneck of the network) from autoencoder and selected by Cox proportional hazards model and a supervised random forest (RF) classifier was used to identify gene profiles related to subtypes of OC from the original 29,096 probes.

RESULTS

Among 100 encoded features extracted by autoencoder, seventy features were significantly related to time-to-OC-development, based on the univariate Cox model, which was used as the inputs for the clustering of patients. Two survival risk groups were identified (P value of log-rank test = 0.003) and were used as the labels for supervised classification. The overall accuracy of the RF classifier was 0.916 over the test set, yielded 21 top genes (FUT8-DDR2-ATM-CD247-ETS1-ZEB2-COL5A2-GMAP7-CDH1-COL11A2-COL3A1-AHR-COL2A1-CHORDC1-PTP4A3-COL1A2-CCR2-PDGFRB-COL1A1-FERMT2-PIK3CB) associated with time to developing OC, selected among the original 29,096 probes.

CONCLUSIONS

Using deep learning, our study identified prominent transcriptional biomarkers in determining high-risk patients for developing oral cancer, which may be prognostic as significant targets for OC therapy. The identified genes may serve as potential targets for oral cancer chemoprevention. Additional validation of these biomarkers in experimental prospective and retrospective studies will launch them in OC clinics.

Screening for Biomarkers for Progression from Oral Leukoplakia to Oral Squamous Cell Carcinoma and Evaluation of Diagnostic Efficacy by Multiple Machine Learning Algorithms

The aim of the study is to identify key genes during the progression from oral leukoplakia (OL) to oral squamous cell carcinoma (OSCC) and predict effective diagnoses. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were performed to identify seven genes associated with the progression from OL to OSCC. Twelve machine learning algorithms including k-nearest neighbor (KNN), neural network (NNet), and extreme gradient boosting (XGBoost) were used to construct multi-gene models, which revealed that each model had good diagnostic efficacy. The functional mechanism or the pathways associated with these genes were evaluated using enrichment analysis, subtype clustering, and immune infiltration analysis. The enrichment analysis revealed that the genes enriched were associated with the cell cycle, cell division, and intracellular energy metabolism. The immunoassay results revealed that the genes primarily affected the infiltration of proliferating T cells and macrophage polarization. Finally, a nomogram and Kaplan-Meier survival analysis were used to predict the prognostic efficacy of key genes in OSCC patients. The results showed that genes could predict the prognosis of the patients, and patients in the high-risk group had a poor prognosis. Our study identified that the seven key genes, including DHX9, BCL2L12, RAD51, MELK, CDC6, ANLN, and KIF4A, were associated with the progression from OL to OSCC. These genes had good diagnostic efficacy and could be used as potential biomarkers for the prognosis of OSCC patients.

Pathogenesis and prognosis of primary oral squamous cell carcinoma based on microRNAs target genes: a systems biology approach

Oral squamous cell carcinoma (OSCC) is the most prevalent head and neck malignancy, with frequent cervical lymph-node metastasis, leading to a poor prognosis in OSCC patients. The present study aimed to identify potential markers, including microRNAs (miRNAs) and genes, significantly involved in the etiology of early-stage OSCC. Additionally, the main OSCC's dysregulated Gene Ontology annotations and significant signaling pathways were identified. The dataset GSE45238 underwent multivariate statistical analysis in order to distinguish primary OSCC tissues from healthy oral epithelium. Differentially expressed miRNAs (DEMs) with the criteria of p-value < 0.001 and |Log2 fold change| > 1.585 were identified in the two groups, and subsequently, validated targets of DEMs were identified. A protein interaction map was constructed, hub genes were identified, significant modules within the network were illustrated, and significant pathways and biological processes associated with the clusters were demonstrated. Using the GEPI2 database, the hub genes' predictive function was assessed. Compared to the healthy controls, main OSCC had a total of 23 DEMs. In patients with head and neck squamous cell carcinoma (HNSCC), upregulation of CALM1, CYCS, THBS1, MYC, GATA6, and SPRED3 was strongly associated with a poor prognosis. In HNSCC patients, overexpression of PIK3R3, GIGYF1, and BCL2L11 was substantially correlated with a good prognosis. Besides, “proteoglycans in cancer” was the most significant pathway enriched in the primary OSCC. The present study results revealed more possible mechanisms mediating primary OSCC and may be useful in the prognosis of the patients with early-stage OSCC.

Transcriptional analysis highlights three distinct immune profiles of high-risk oral epithelial dysplasia

Oral potentially malignant disorders (OPMD) are precursors of oral squamous cell carcinoma (OSCC), and the presence of oral epithelial dysplasia (OED) in OPMD confers an increased risk of malignant transformation. Emerging evidence has indicated a role for the immune system in OPMD disease progression; however, the underlying immune mechanisms remain elusive. In this study, we used immune signatures established from cancer to delineate the immune profiles of moderate and severe OED, which are considered high-risk OPMD. We demonstrated that moderate and severe OEDs exhibit high lymphocyte infiltration and upregulation of genes involved in both immune surveillance (major histocompatibility complex-I, T cells, B cells and cytolytic activity) and immune suppression (immune checkpoints, T regulatory cells, and tumor-associated macrophages). Notably, we identified three distinct subtypes of moderate and severe OED: immune cytotoxic, non-cytotoxic and non-immune reactive. Active immune surveillance is present in the immune cytotoxic subtype, whereas the non-cytotoxic subtype lacks CD8 immune cytotoxic response. The non-immune reactive subtype showed upregulation of genes involved in the stromal microenvironment and cell cycle. The lack of T cell infiltration and activation in the non-immune reactive subtype is due to the dysregulation of CTNNB1, PTEN and JAK2. This work suggests that moderate and severe OED that harbor the non-cytotoxic or non-immune reactive subtype are likely to progress to cancer. Overall, we showed that distinct immune responses are present in high-risk OPMD, and revealed targetable pathways that could lead to potential new approaches for non-surgical management of OED.

Evaluation Criteria for Chromosome Instability Detection by FISH to Predict Malignant Progression in Premalignant Glottic Laryngeal Lesions

Background: The definition of objective, clinically applicable evaluation criteria for FISH 1c/7c in laryngeal precursor lesions for the detection of chromosome instability (CI). Copy Number Variations (CNV) for chromosomes 1 and 7 reflect the general ploidy status of premalignant head and neck lesions and can therefore be used as a marker for CI. Methods: We performed dual-target FISH for chromosomes 1 and 7 centromeres on 4 µm formalin-fixed, paraffin-embedded tissue sections of 87 laryngeal premalignancies to detect CNVs. Thirty-five normal head and neck squamous cell samples were used as a control. First, the chromosome 7:1 ratio (CR) was evaluated per lesion. The normal range of CRs (≥0.84 ≤ 1.16) was based on the mean CR +/− 3 x SD found in the normal population. Second, the percentage of aberrant nuclei, harboring > 2 chromosomes of chromosome 1 and/or 7 (PAN), was established (cut-off value for abnormal PAN ≥ 10%). Results: PAN showed a stronger correlation with malignant progression than CR (resp. OR 5.6, p = 0.001 and OR 3.8, p = 0.009). PAN combined with histopathology resulted in a prognostic model with an area under the ROC curve (AUC) of 0.75 (s.e. 0.061, sensitivity 71%, specificity 70%). Conclusions: evaluation criteria for FISH 1c/7c based on PAN ≥ 10% provide the best prognostic information on the risk of malignant progression of premalignant laryngeal lesions as compared with criteria based on the CR. FISH 1c/7c detection can be applied in combination with histopathological assessment.

Oral Epithelial Dysplasia: A Review of Diagnostic Criteria for Anatomic Pathologists

Oral epithelial dysplasia (OED) represents a spectrum of histologic changes in the oral cavity mucosa that has the potential to transform into oral squamous cell carcinoma. Predicting the risk of malignant transformation is predominantly based on clinicopathologic correlation, histologic examination and grading. OED often poses a diagnostic challenge, primarily due to its histologic mimics and a large number of terminologies used in the literature. The grading system for OED is also fraught with significant interobserver variability. This review summarizes the essential clinical and histopathologic features of OED and its mimics. Practical preanalytical, analytical, and postanalytical considerations for anatomic pathologists are discussed to improve the diagnostic accuracy and increase the reproducibility in the grading of OED.

Molecular Signatures of Tumour and Its Microenvironment for Precise Quantitative Diagnosis of Oral Squamous Cell Carcinoma: An International Multi-Cohort Diagnostic Validation Study

BACKGROUND

Heterogeneity in oral potentially malignant disorder (OPMD) poses a problem for accurate prognosis that impacts on treatment strategy and patient outcome. A holistic assessment based on gene expression signatures from both the tumour cells and their microenvironment is necessary to provide a more precise prognostic assessment than just tumour cell signatures alone.

METHODS

We reformulated our previously established multigene qPCR test, quantitative Malignancy Index Diagnostic System (qMIDS) with new genes involved in matrix/stroma and immune modulation of the tumour microenvironment. An algorithm calculates and converts a panel of 16 gene mRNA expression levels into a qMIDS index to quantify risk of malignancy for each sample.

RESULTS

The new qMIDS^V2 assay was validated in a UK oral squamous cell carcinoma (OSCC) cohort (n = 282) of margin and tumour core samples demonstrating significantly better diagnostic performance (AUC = 0.945) compared to previous qMIDS^V1 (AUC = 0.759). Performance of qMIDS^V2 were independently validated in Chinese (n = 35; AUC = 0.928) and Indian (n = 95; AUC = 0.932) OSCC cohorts. Further, 5-year retrospective analysis on an Indian dysplastic lesion cohort (n = 30) showed that qMIDS^V2 was able to significantly differentiate between lesions without transformation and those with malignant transformation.

CONCLUSIONS

This study validated a novel multi-gene qPCR test on a total of 535 tissue specimens from UK, China and India, demonstrating a rapid minimally invasive method that has a potential application for dysplasia risk stratification. Further study is required to establish if qMIDS^V2 could be used to improve OPMD patient management, guide treatment strategy and reduce oral cancer burden.

Identification of Biomarkers Associated with Cancerous Change in Oral Leukoplakia Based on Integrated Transcriptome Analysis

Objective

Oral leukoplakia (OLK) is the most common precancerous lesion in the oral cavity. This study aimed to explore key biomarkers for monitoring OLK for early diagnosis of oral squamous cell carcinoma (OSCC) and screen small-molecule drugs for the prevention of OSCC.

Method

The Gene Expression Omnibus (GEO) database was explored to extract two microarray datasets, namely, GSE85195 and GSE25099. The data of the normal group, OLK group, and OSCC group were analyzed by weighted gene coexpression network analysis (WGCNA) to identify the most significant gene module and differentially expressed genes (DEGs). The intersection genes were extracted as the key genes of OLK carcinogenesis. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed in the module. Connectivity Map and molecular docking were used to screen small-molecule drugs. The diagnostic values of four key genes were identified and verified in the GSE26549 dataset.

Results

WGCNA obtained the red module (r = −0.91, p < 0.05) with the strongest correlation with cancerous phenotype. GO enrichment analysis showed 60 pathways, including 28 biological processes, 11 cell components, and 21 molecular functions, and KEGG enrichment analysis showed 4 pathways (p < 0.05). In the differential expression analysis, there was no intersection between the upregulated genes and the red module genes. However, the intersection of the downregulated genes and the red module genes yielded 4 key genes: dopachrome tautomerase (DCT), keratin 3 (KRT3), keratin 76 (KRT76), and FAM3 metabolic regulation signal molecule B (FAM3B). The area under the curve of the diagnostic model constructed by these four genes was 0.963 (CI = 0.913–1.000). The sensitivity was 0.933, and the specificity was 0.923. The diagnostic model was successfully verified in GSE26549 (AUC = 0.745, CI = 0.638–0.851). Compared with the diagnostic models of the previous studies, the diagnostic efficiency of this model was the highest. The small-molecule drugs, selumetinib and benidipine, were selected according to the gene expression profile and showed binding activity when docking with the above molecules.

Conclusions

This study provides new targets and drugs for OLK. These targets could be used as the key diagnostic molecules for long-term follow-up of OLK. The small-molecule drugs selumetinib and benidipine could be used for the prevention and treatment of OSCC.

The role of SPP1 as a prognostic biomarker and therapeutic target in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies and has a low 5-year survival rate. Mounting evidence suggests that oral potentially malignant disorders, such as oral leukoplakia (OLK), may progress to HNSCC. Given that OLK and HNSCC are often insidious and asymptomatic, the identification of markers of OLK malignant transformation and therapeutic targets in HNSCC is critical. Using various online tools and publicly available gene expression datasets, the secreted phosphoprotein 1 gene (SPP1) was identified as a significant differentially expressed gene among OLK, HNSCC, and non-cancerous tissues. SPP1 mRNA levels were elevated in HNSCC tissues and were associated with cancer stage, tumor grade, and human papillomavirus infection status. High SPP1 mRNA levels were correlated with poor overall survival of HNSCC patients. In contrast, SPP1 mutations were not significantly associated with overall survival, although their frequency in HNSCC was very low (0.6%). Furthermore, SPP1 expression levels in HNSCC were positively correlated with the infiltration of CD4⁺ cells, macrophages, neutrophils, and dendritic cells. The study results suggest that SPP1 may represent a diagnostic and prognostic biomarker, as well as a potential therapeutic target in HNSCC.

Supervised Dimension Reduction for Large-Scale "Omics" Data With Censored Survival Outcomes Under Possible Non-Proportional Hazards

The past two decades have witnessed significant advances in high-throughput "omics" technologies such as genomics, proteomics, metabolomics, transcriptomics and radiomics. These technologies have enabled simultaneous measurement of the expression levels of tens of thousands of features from individual patient samples and have generated enormous amounts of data that require analysis and interpretation. One specific area of interest has been in studying the relationship between these features and patient outcomes, such as overall and recurrence-free survival, with the goal of developing a predictive "omics" profile. Large-scale studies often suffer from the presence of a large fraction of censored observations and potential time-varying effects of features, and methods for handling them have been lacking. In this paper, we propose supervised methods for feature selection and survival prediction that simultaneously deal with both issues. Our approach utilizes continuum power regression (CPR) - a framework that includes a variety of regression methods - in conjunction with the parametric or semi-parametric accelerated failure time (AFT) model. Both CPR and AFT fall within the linear models framework and, unlike black-box models, the proposed prognostic index has a simple yet useful interpretation. We demonstrate the utility of our methods using simulated and publicly available cancer genomics data.

Oral epithelial dysplasia: Recognition, grading and clinical significance

Histopathological grading of epithelial dysplasia remains the principal laboratory method for assessing the risk of malignant transformation in oral potentially malignant disorders (OPMDs). Current views on the molecular pathogenesis and histological interpretation of the features of epithelial dysplasia are described, and the use of grading systems for epithelial dysplasia is discussed. Changes to the current 2017 WHO criteria for diagnosis are proposed with emphasis on the architectural features of epithelial dysplasia. The predictive values of three-grade and binary systems are summarised, and categories of epithelial dysplasia are reviewed, including lichenoid and verrucous lesions, keratosis of unknown significance, HPV-associated dysplasia, differentiated and basaloid epithelial dysplasia. The implications of finding epithelial dysplasia in an oral biopsy for clinical management are discussed from the pathologists' viewpoint.

Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology

BACKGROUND

This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.

METHODS

Patients with oral epithelial dysplasia at one hospital were selected as the 'training set' (n = 56) whilst those at another hospital were selected for the 'test set' (n = 66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni- and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature.

RESULTS

A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65, p = 0.0003].

CONCLUSIONS

This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility.

Improvement in the risk assessment of oral leukoplakia through morphology-related copy number analysis

Oral leukoplakia is the most common type of oral potentially malignant disorders and considered a precursor lesion to oral squamous cell carcinoma. However, a predictor of oral leukoplakia prognosis has not yet been identified. We investigated whether copy number alteration patterns may effectively predict the prognostic outcomes of oral leukoplakia using routinely processed paraffin sections. Comparison of copy number alteration patterns between oral leukoplakia with hyperplasia (HOL, n=22) and dysplasia (DOL, n=21) showed that oral leukoplakia with dysplasia had a higher copy number alteration rate (86%) than oral leukoplakia with hyperplasia (46%). Oral leukoplakia with dysplasia exhibited a wider range of genomic variations across all chromosomes compared with oral leukoplakia with hyperplasia. We also examined a retrospective cohort of 477 patients with oral leukoplakia with hyperplasia with detailed follow-up information. The malignant transformation (MT, n=19) and leukoplakia recurrence (LR, n=253) groups had higher frequencies of aneuploidy events and copy number loss rate than the free of disease (FD, n=205) group. Together, our results revealed the association between the degree of copy number alterations and the histological grade of oral leukoplakia and demonstrated that copy number alteration may be effective for prognosis prediction in oral leukoplakia patients with hyperplasia.

Early-Phase Interventional Trials in Oral Cancer Prevention

Simple Summary

Oral cancer is a devastating disease with increasing incidence worldwide. Oral epithelial dysplasia (OED) is a potentially malignant disorder and patients with OED are at increased risk of developing oral cancer. Current strategies for management of OED include surgery or close observation and both fail to address the underlying pathogenesis of the disease. There is an urgent need for evidence-based medical treatments for OED to prevent oral cancer development in this cohort. Chemoprevention trials to date have not delivered therapeutic agents for routine clinical practice. Historically, there has been significant heterogeneity in the design of oral cancer chemoprevention trials, with most failing to selectively recruit patients with biopsy-proven OED, which limits the usefulness of the findings in the OED population. The present paper aims to review the current evidence and the methodology of early-phase trials in oral cancer chemoprevention. Novel strategies in oral cancer chemoprevention will also be discussed.

Abstract

The increasing breadth of molecular targets, promise of immune-targeted therapies and repurposed agents have heightened interest in cancer prevention. While, to date, testing of oral cancer chemoprevention strategies has failed to deliver therapeutic agents for routine clinical practice, there remains an urgent need for further clinical research to overcome this hurdle. Patients at the greatest risk of disease stand to benefit the most from inclusion in clinical trials; therefore, there is a need to carefully define this population using validated clinical and molecular markers. Safety, tolerability and the efficacy of interventions is assessed through carefully selected endpoints. These endpoints may include pharmacodynamic, clinical, histological and on-target molecular modifications as an individual or as a composite endpoint. Early-phase trials provide an area of opportunity to explore novel and repurposed agents in the setting of oral cancer chemoprevention, eventually leading to phase III trials with clinical endpoints such as transformation and clinical outcome; these studies are large, lengthy and expensive and should be reserved for the most promising of agents. This paper will explore current evidence in oral cancer chemoprevention, drug repurposing, selection of appropriate endpoints for early-phase trials and novel therapeutic angles in oral cancer chemoprevention.

Overview of oral cavity squamous cell carcinoma: Risk factors, mechanisms, and diagnostics

Oral cavity squamous cell carcinoma (OCSCC) is the most common malignancy of the oral cavity. The substantial risk factors for OCSCC are the consumption of tobacco products, alcohol, betel quid, areca nut, and genetic alteration. However, technological advancements have occurred in treatment, but the survival decreases with late diagnosis; therefore, new methods are continuously being investigated for treatment. In addition, the rate of secondary tumor formation is 3-7% yearly, which is incomparable to other malignancies and can lead to the disease reoccurrence. Oral cavity cancer (OCC) arises from genetic alterations, and a complete understanding of the molecular mechanism involved in OCC is essential to develop targeted treatments. This review aims to update the researcher on oral cavity cancer, risk factors, genetic alterations, molecular mechanism, classification, diagnostic approaches, and treatment.

A novel 4-gene signature model simultaneously predicting malignant risk of oral potentially malignant disorders and oral squamous cell carcinoma prognosis

OBJECTIVE

Oral squamous cell carcinoma (OSCC) is often diagnosed at late stage with a poor prognosis. The study hereunder aimed to construct a multi-gene model to simultaneously promote early diagnosis of OSCC by evaluating malignant risk of oral potentially malignant disorders (OPMDs) and predict prognosis.

MATERIALS AND METHODS

3 GEO datasets including OPMDs and OSCC samples were obtained for overlapping differentially expressed genes (DEGs) being screened. The predictive model was built with optimal DEGs by SVM algorithm, estimated by receiver operator characteristic curves and validated for double prediction via oral cancer-free survival (for malignant risk of OPMDs) and overall survival time (for OSCC) analysis respectively compared to other models. The protein expression of biomarkers in the model was validated in human samples by immunohistochemistry.

RESULTS

A novel predictive model of 4-gene signature was built based on 12 common DEGs revealed from 3 GEO datasets. It could well distinguish OSCC from OPMDs and normal tissues. Both oral cancer-free survival and overall survival time analysis were significantly poorer in high-risk patients than in low-risk ones in Kaplan Meier survival curve respectively. The protein expression of biomarkers in OSCC was with significant difference compared to normal and OPMDs.

CONCLUSIONS

The novel 4-gene signature model presents strong ability in simultaneous prediction of the malignant risk of OPMDs and OSCC progression, potentially benefiting both the early diagnosis and therapeutic outcomes of OSCC.

Early changes in the immune microenvironment of oral potentially malignant disorders reveal an unexpected association of M2 macrophages with oral cancer free survival

Understanding the dynamics of the immune microenvironment is critical to the development of immuno-based strategies for the prevention of oral potentially malignant disorders transformation to oral squamous cell carcinoma (OSCC). We used laser capture microdissection and RNA-sequencing to profile the expression of 13 matched pairs of epithelial versus stromal compartments from normal mucosa, hyperplasia, dysplasia, and invasive tumors in the 4-nitroquinolein (4-NQO) murine model of oral carcinogenesis. Genes differentially expressed at each step of transformation were defined. Immune cell deconvolution and enrichment scores of various biological processes including immune-related ones were computed. Immunohistochemistry was also performed to characterize the immune infiltrates by T-cells (T-cells CD3+, helper CD4+, cytotoxic CD8+, regulatory FoxP3+), B-cells (B220+), and macrophages (M1 iNOS+, M2 CD163+) at each histological step. Enrichment of three independent M2 macrophages signatures were computed in 86 oral leukoplakia with available clinical outcome. Most gene expression changes were observed in the stromal compartment and related to immune biological processes. Immune cell deconvolution identified infiltration by the macrophage population as the most important quantitatively especially at the stage of dysplasia. In 86 patients with oral leukoplakia, three M2 macrophages signatures were independently associated with improved oral cancer-free survival. This study provides a better understanding of the dynamics of the immune microenvironment during oral carcinogenesis and highlights an unexpected association of M2 macrophages gene expression signatures with oral cancer free survival in patients with oral leukoplakia.

Targeting the genetic landscape of oral potentially malignant disorders has the potential as a preventative strategy in oral cancer

This study reviews the molecular landscape of oral potentially malignant disorders (OPMD). We examine the impact of tumour heterogeneity, the spectrum of driver mutations (TP53, CDKN2A, TERT, NOTCH1, AJUBA, PIK3CA, CASP8) and gene transcription on tumour progression. We comment on how some of these mutations impact cellular senescence, field cancerization and cancer stem cells. We propose that OPMD can be monitored more closely and more dynamically through the use of liquid biopsies using an appropriate biomarker of transformation. We describe new gene interactions through the use of a systems biology approach and we highlight some of the first studies to identify functional genes using CRISPR-Cas9 technology. We believe that this information has translational implications for the use of re-purposed existing drugs and/or new drug development. Further, we argue that the use of digital technology encompassing clinical and laboratory-based data will create relevant datasets for machine learning/artificial intelligence. We believe that therapeutic intervention at an early molecular premalignant stage should be an important preventative strategy to inhibit the development of oral squamous cell carcinoma and that this approach is applicable to other aerodigestive tract cancers.

Development of a Gene-Based Prediction Model for Recurrence of Colorectal Cancer Using an Ensemble Learning Algorithm

It is difficult to determine which patients with stage I and II colorectal cancer are at high risk of recurrence, qualifying them to undergo adjuvant chemotherapy. In this study, we aimed to determine a gene signature using gene expression data that could successfully identify high risk of recurrence among stage I and II colorectal cancer patients. First, a synthetic minority oversampling technique was used to address the problem of imbalanced data due to rare recurrence events. We then applied a sequential workflow of three methods (significance analysis of microarrays, logistic regression, and recursive feature elimination) to identify genes differentially expressed between patients with and without recurrence. To stabilize the prediction algorithm, we repeated the above processes on 10 subsets by bagging the training data set and then used support vector machine methods to construct the prediction models. The final predictions were determined by majority voting. The 10 models, using 51 differentially expressed genes, successfully predicted a high risk of recurrence within 3 years in the training data set, with a sensitivity of 91.18%. For the validation data sets, the sensitivity of the prediction with samples from two other countries was 80.00% and 91.67%. These prediction models can potentially function as a tool to decide if adjuvant chemotherapy should be administered after surgery for patients with stage I and II colorectal cancer.

Tissue biomarkers for predicting the risk of oral cancer in patients diagnosed with oral leukoplakia: A systematic review

OBJECTIVES

We performed a systematic review to evaluate the published biomarkers related to oral leukoplakia (OL), aiming to identify the biomarkers that indicate any future risk of cancer in patients with oral leukoplakia.

METHODS

A search strategy was developed for three main electronic databases: PubMed, Cochrane Library, and EBSCO, and also for Google Scholar, until February 28, 2020. The study selection was performed in a two-phase process aiming at studies assessing tissue biomarkers for "malignant transformation of OL." Risk of bias analysis of included studies was performed using the Quality in Prognosis Studies Tool.

RESULTS

From 3,130 articles initially identified by searching databases, a total of 46 studies were included in this systematic review, with a combined sample of 3,783 patients, of whom 1,047 presented with malignant transformation of a previously diagnosed OL as reported by the authors. The cancer incidence in the whole group was 27.6% (range: 5.4% to 54.1%). The studies were derived from different geographic areas, including Asia (n = 21), Europe (n = 15), North America (n = 9), and Oceania (n = 1). There were 49 different molecular biomarkers evaluated in the 46 included studies: p53 and podoplanin proteins were the most frequently reported, followed by abnormalities at particular chromosomal loci (e.g., LOH). Risk of bias analysis revealed concerns associated with "measurement of prognostic factor," "study confounding" and "statistical analysis and reporting."

CONCLUSIONS

Substantial heterogeneity and lack of standardized reporting of data among the studies were identified. The most promising biomarkers reported to have a significant association with the malignant transformation in OL included podoplanin and chromosomal loci abnormalities. A critical examination of the follow-up studies on OL published so far indicated that tissue biomarkers that could predict the risk of oral cancer in patients with OL are still in a discovery phase.

Unified methods for feature selection in large-scale genomic studies with censored survival outcomes

MOTIVATION

One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous datasets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards (PH), which is unlikely to hold for each feature. When applied to genomic features exhibiting some form of non-proportional hazards (NPH), these methods could lead to an under- or over-estimation of the effects. We propose a broad array of marginal screening techniques that aid in feature ranking and selection by accommodating various forms of NPH. First, we develop an approach based on Kullback-Leibler information divergence and the Yang-Prentice model that includes methods for the PH and proportional odds (PO) models as special cases. Next, we propose R2 measures for the PH and PO models that can be interpreted in terms of explained randomness. Lastly, we propose a generalized pseudo-R2 index that includes PH, PO, crossing hazards and crossing odds models as special cases and can be interpreted as the percentage of separability between subjects experiencing the event and not experiencing the event according to feature measurements.

RESULTS

We evaluate the performance of our measures using extensive simulation studies and publicly available datasets in cancer genomics. We demonstrate that the proposed methods successfully address the issue of NPH in genomic feature selection and outperform existing methods.

AVAILABILITY AND IMPLEMENTATION

R code for the proposed methods is available at github.com/lburns27/Feature-Selection.

CONTACT

karthik.devarajan@fccc.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular, genomic and mutational landscape of oral leukoplakia

Oral leukoplakia (OLK) and its more aggressive clinical variant proliferative verrucous leukoplakia (PVL) remain enigmatic disorders clinically and histopathologically. Despite decades of research into both, there has been only incremental advancement in our understanding of their aetiology and pathogenesis and only minimal improvement in effective management strategies. Currently, no specific prognostic genetic or molecular marker has been reported for leukoplakia. There is, however, an emerging body of evidence characterising the genomic and transcriptomic profile of OLK. Regardless of the significance of cellular and architectural features of OLK and PVL, it is clear from studies reported in this review that new emerging evidence points to the presence of premalignant molecular subtypes of leukoplakia which require further investigation. This up-to-date review explores the contemporary genomic, transcriptomic and mutational landscape of leukoplakia broadly, discusses concepts that may not be widely recognised or accepted and purposefully highlights studies with juxtaposed findings in an effort to challenge dogma. It also highlights the urgent need for a concerted international effort of original collaborative research which will only occur by pooling collective efforts, resources and intellect to define the molecular fingerprint of this enigmatic disorder, in the hope it will better inform diagnosis, stratification and treatment.

Gene expression changes associated with malignant transformation of oral potentially malignant disorders

BACKGROUND

A large number of oral squamous cell carcinomas (OSCCs) are believed to be preceded by oral potentially malignant disorders (OPMD) that have an increased likelihood of malignant transformation compared to clinically normal mucosa. This study was performed to identify differentially expressed genes between OPMDs that underwent malignant transformation (MT) and those that did not, termed "non-transforming" (NT) cases.

METHODS

Total RNA was extracted from formalin-fixed paraffin-embedded tissue biopsies of 20 OPMD cases with known clinical outcomes (10 MT vs. 10 NT). Samples were assessed for quantity, quality and integrity of RNA prior to sequencing. Analysis for differential gene expression between MT and NT was performed using statistical packages in R. Genes were considered to be significantly differentially expressed if the False Discovery Rate corrected P-value was < 0.05.

RESULTS

RNA yield was variable but RNA purity was good (A260/A280 > 1.90). Analysis of RNA-Sequencing outputs revealed 41 genes (34 protein-coding; 7 non-coding) that were significantly differentially expressed between MT and NT cases. The log2 fold change for the statistically significant differentially expressed genes ranged from -2.63 to 2.48, with 23 protein-coding genes being downregulated and 11 protein-coding genes being upregulated in MT cases compared to NT cases.

CONCLUSION

Several candidate genes that may play a role in malignant transformation of OPMD have been identified. Experiments to validate these candidates are underway. It is anticipated that this work will contribute to better understanding of the etiopathogenesis of OPMD and development of novel biomarkers.

Gene Expression Clustering and Selected Head and Neck Cancer Gene Signatures Highlight Risk Probability Differences in Oral Premalignant Lesions

BACKGROUND

Oral premalignant lesions (OPLs) represent the most common oral precancerous conditions. One of the major challenges in this field is the identification of OPLs at higher risk for oral squamous cell cancer (OSCC) development, by discovering molecular pathways deregulated in the early steps of malignant transformation. Analysis of deregulated levels of single genes and pathways has been successfully applied to head and neck squamous cell cancers (HNSCC) and OSCC with prognostic/predictive implications. Exploiting the availability of gene expression profile and clinical follow-up information of a well-characterized cohort of OPL patients, we aim to dissect tissue OPL gene expression to identify molecular clusters/signatures associated with oral cancer free survival (OCFS).

MATERIALS AND METHODS

The gene expression data of 86 OPL patients were challenged with: an HNSCC specific 6 molecular subtypes model (Immune related: HPV related, Defense Response and Immunoreactive; Mesenchymal, Hypoxia and Classical); one OSCC-specific signature (13 genes); two metabolism-related signatures (3 genes and signatures raised from 6 metabolic pathways associated with prognosis in HNSCC and OSCC, respectively); a hypoxia gene signature. The molecular stratification and high versus low expression of the signatures were correlated with OCFS by Kaplan-Meier analyses. The association of gene expression profiles among the tested biological models and clinical covariates was tested through variance partition analysis.

RESULTS

Patients with Mesenchymal, Hypoxia and Classical clusters showed an higher risk of malignant transformation in comparison with immune-related ones (log-rank test, p = 0.0052) and they expressed four enriched hallmarks: "TGF beta signaling" "angiogenesis", "unfolded protein response", "apical junction". Overall, 54 cases entered in the immune related clusters, while the remaining 32 cases belonged to the other clusters. No other signatures showed association with OCFS. Our variance partition analysis proved that clinical and molecular features are able to explain only 21% of gene expression data variability, while the remaining 79% refers to residuals independent of known parameters.

CONCLUSIONS

Applying the existing signatures derived from HNSCC to OPL, we identified only a protective effect for immune-related signatures. Other gene expression profiles derived from overt cancers were not able to identify the risk of malignant transformation, possibly because they are linked to later stages of cancer progression. The availability of a new well-characterized set of OPL patients and further research is needed to improve the identification of adequate prognosticators in OPLs.

Essential gene expression pattern of head and neck squamous cell carcinoma revealed by tumor-specific expression rule based on single-cell RNA sequencing

Head and neck squamous cell carcinoma (HNSCC) has been widely reported and considered as one of the most threatening diseases to human health. Derived from complicated tissue subtypes, HNSCC has diverse symptoms and pathogenesis. They make the identification of the core carcinogenic factors of such diseases at the multi-cell level difficult. With the development of single-cell sequencing technologies, the effects of non-malignant cells on traditional bulk sequencing data can be eliminated directly. On the basis of fresh single-cell RNA-seq data, we set up a computational filtering strategy for tumor cell identification in an expression rule manner. This strategy can reveal the accurate expression distinction between tumor cells and adjacent tumor microenvironment, which are all supported by literature reports. Validated by several independent datasets, these rule genes can further group HNSCC patients with significant difference on survival risks. Thus, the establishment of our computational approach may not only provide an efficient tool to identify malignant cells in the tumor ecosystem but also deepen our understanding of tumor heterogeneity and tumorigenesis.

Deep learning-based model for predicting progression in patients with head and neck squamous cell carcinoma

PURPOSE

This study endeavors to build a deep learning (DL)-based model for predicting disease progression in head and neck squamous cell carcinoma (HNSCC) patients by integrating multi-omics data.

METHODS

RNA sequencing, miRNA sequencing, and methylation data from The Cancer Genome Atlas (TCGA) were used as input for autoencoder, a DL approach. An autoencoder-based prognosis model for PFS was built by SVM algorithm and tested in three confirmation sets. Predictive performance of the model was compared to two alternative approaches. Differential expression analysis for mRNAs, microRNAs (miRNA) and methylation was conducted. Moreover, functional annotation of differentially expressed genes (DEGs) was achieved through function enrichment analysis.

RESULT

The DL-based prognosis model identified two subgroups of patients with significantly different PFS, and showcased a good model fitness (C-index = 0.73). The two identified PFS subtypes were successfully validated in three confirmation sets. The DL-based model was more accurate and efficient than principal component analysis (PCA) or individual Cox-PH-based models. There were 348 DEGs, 23 differentially expressed miRNAs and 55 differentially methylated genes between the two PFS subtypes. These genes were significantly involved in several immune-related biological processes and primary immunodeficiency, cell adhesion molecules (CAMs), B cell receptor signaling and leukocyte transendothelial migration pathways.

CONCLUSION

The DL-based model introduced in this study is reliable and robust in predicting disease progression in HNSCC patients. A number of pathways and genes targets are unraveled to be implicated in cancer progression. Utility of this model would facilitate development of more individualized therapy for HNSCC patients and improve prognosis.

Adaptive ERK signalling activation in response to therapy and in silico prognostic evaluation of EGFR-MAPK in HNSCC

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) patients frequently develop treatment resistance to cetuximab, a monoclonal antibody against EGFR, as well as radiotherapy. Here we addressed extracellular signal-regulated kinase 1/2 (ERK1/2) regulation by cetuximab or fractionated irradiation (IR) and conducted in silico prognostic evaluation of the EGFR-MAPK axis in HNSCC.

METHODS

Expression of ERK1/2 phosphorylation (pERK1/2) was determined in HNSCC cell lines, which were treated with cetuximab or fractionated-IR. Furthermore, the effect of fractionated IR on pERK1/2 was confirmed in an ex vivo HNSCC tissue culture model. Expression and prognostic significance of EGFR-ERK axis was evaluated in a cohort of radiotherapy plus cetuximab-treated HNSCC. Correlations among EGFR-MAPK signalling components and association between transcript and protein expression profiles and patient survival in HNSCC were analysed using publicly available databases.

RESULTS

ERK1/2 phosphorylation was rebounded by prolonged cetuximab administration and was induced by fractionated IR, which could be suppressed by a MEK inhibitor as a radiosensitiser. In silico assessments suggested that EGFR-MAPK cascade genes and proteins could predict HNSCC patients' survival as a prognostic signature.

CONCLUSIONS

Activation of ERK1/2 signalling contributes to the cellular defence of HNSCC against cetuximab and fractionated IR treatment. EGFR-MAPK axis has a prognostic significance in HNSCC.

Oral potentially malignant disorders: A scoping review of prognostic biomarkers

This scoping review aimed to map evidence regarding biomarkers for malignant transformation of oral potentially malignant disorders (OPMD). Seventy-three longitudinal studies investigating prognostic biomarkers for OPMD malignant transformation were included, encompassing 5612 disorders and 108 biomarkers, of which 72 were investigated by immunohistochemistry. Most biomarkers were assessed in one or two studies, while five (p53, Ki-67, podoplanin, p16, and DNA ploidy) were analyzed in five or more studies. All studies investigating podoplanin (n = 8) reported a significant association between positive/high immunoexpression and malignant transformation. Similarly, all studies assessing DNA ploidy (n = 5) found that aneuploidy or gross genomic aberrations were significantly associated with malignant transformation. Included studies often presented mixed data from different OPMD subtypes, inadequate description of population characteristics, and lack of adjusted analysis for confounding factors. One hundred and eight biomarkers were identified and, from these, podoplanin immunoexpression and DNA ploidy were considered promising candidates for future long-term clinical research.

Usefulness of Circulating Methylated p16 as a Noninvasive Molecular Biomarker for Hepatitis C-Related Hepatocellular Carcinoma with Normal Serum Alpha-Fetoprotein Levels

Background

Screening of hepatocellular carcinoma (HCC) is challenged especially in patients with normal alpha-fetoprotein (AFP) levels. Aberrant p16 methylation has been implicated in HCC.

Objectives and Aims

This study aimed to assess serum methylated p16 (MP16) expression levels and to evaluate MP16 diagnostic performance in HCC detection among HCV-infected Egyptian patients with normal AFP levels.

Methods

MP16 levels were quantified using real-time PCR in 230 serum samples (30 healthy controls, 95 with HCV-HCC, 40 with chronic hepatitis C "CHC" and 65 with HCV cirrhosis). Diagnostic performance of MP16 for diagnosis of HCC was done using receiver operator characteristic curve analysis.

Results

Serum MP16 levels were significantly higher in HCC than CHC, cirrhosis, and healthy subjects and significantly higher in HCC with normal AFP levels than those with higher AFP. ROC curves revealed promising diagnostic performance for MP16 in discriminating HCC with normal AFP levels from non-HCC cases. This predictive ability improved by combining MP16 and AFP (AUC of 0.872 with 100% sensitivity, 76.5% specificity, 79.1% positive predictive value, 100% negative predictive value, and 87.5% accuracy).

Conclusion

MP16 can be a potential noninvasive molecular biomarker for HCC detection in patients with hepatic mass(es) and normal AFP levels especially in those where liver biopsy and radiological imaging cannot be done.

DNA aneuploidy and tissue architecture in oral potentially malignant disorders with epithelial dysplasia assessed by a 10 locus FISH panel

Subjectivity in oral dysplasia grading has prompted evaluation of molecular-based tests to predict malignant transformation. Aneuploidy detected by DNA image-based cytometry (ICM) is currently the best predictor but fails to detect certain high risk lesions. A novel multiplex fluorescence in situ hybridization (FISH) panel was used to explore possible explanations by detecting aneuploidy at the single cell level. FISH was compared to reference standard DNA ICM in 19 oral lesions with epithelial dysplasia and used to characterize the cellular architecture. Copy number variation at 3q28, 7p11.2, 8q24.3, 11q13.3 and 20q13.12 and matched chromosome specific loci were assessed by dual-color FISH to assess numerical and spatial patterns of copy number increase and gene amplification. FISH revealed wide variation in copy number at different loci. Only low level copy number gain was present and often in only a small proportion of cells, although usually with all or all but one locus (9/12). Four cases showed gene amplification, one at two loci. Some probes revealed an internal presumed clonal structure within lesions not apparent in routine histological examination. Both methods produced similar diagnostic results with concordance in detection of aneuploidy by both methods in 17 out of 19 samples (89%). We have shown that oral dysplastic lesions may contain very few aneuploid cells at a cellular level, high copy number gain is rare and changes appear to arise from large chromosomal fragment duplications. Single stem lines are relatively homogeneous for loci with copy number gain but there is a subclonal structure revealed by gene amplification in some lesions.

Visualization of mucosal field in HPV positive and negative oropharyngeal squamous cell carcinomas: combined genomic and radiology based 3D model

The aim of this study was to visualize the tumor propagation and surrounding mucosal field in radiography-based 3D model for advanced stage HNSCC and combine it with HPV genotyping and miRNA expression characterization of the visualized area. 25 patients with T1-3 clinical stage HNSCC were enrolled in mapping biopsy sampling. Biopsy samples were evaluated for HPV positivity and miR-21-5p, miR-143, miR-155, miR-221-5p expression in Digital Droplet PCR system. Significant miRNA expression differences of HPV positive tumor tissue biopsies were found for miR-21-5p, miR-143 and miR-221-5p compared to the HPV negative tumor biopsy series. Peritumoral mucosa showed patchy pattern alterations of miR-21-5p and miR-155 in HPV positive cases, while gradual change of miR-21-5p and miR-221-5p was seen in HPV negative tumors. In our study we found differences of the miRNA expression patterns among the HPV positive and negative tumorous tissues as well as the surrounding mucosal fields. The CT based 3D models of the cancer field and surrounding mucosal surface can be utilized to improve proper preoperative planning. Complex evaluation of HNSCC tissue organization field can elucidate the clinical and molecular differentiation of HPV positive and negative cases, and enhance effective organ saving therapeutic strategies.

World Workshop on Oral Medicine VII: Prognostic biomarkers in oral leukoplakia: A systematic review of longitudinal studies

OBJECTIVE

To identify the prognostic biomarker candidates for stratification and long-term surveillance of oral leukoplakia progressing to cancer via a systematic literature review.

MATERIALS AND METHODS

Systematic searches with no date restrictions were conducted on March 29, 2018, targeting the databases PubMed (Ovid), EMBASE (Ovid), EBM (Ovid), and Web of Science (ISI). Bias was assessed using the Quality in Prognosis Studies tool. Biomarkers were stratified based on hallmarks of cancer.

RESULTS

Inclusion criteria were met by 25 of 3,415 studies. A range of biomarkers were evaluated experimentally for risk stratification, prognosis, and surveillance of oral leukoplakia in tissue, blood, and saliva. However, the studies were highly heterogeneous and require further validation. Biomarkers reported in these studies included inflammatory or oxidative markers, growth factors, ion channels, genetic and cellular regulatory factors, and epigenetic biomarkers. Studies tended to include small sample sizes, under-reported or variably reported histopathological data, did not address potential confounding, reported limited/variable follow-up data, or lacked a control group. Inclusion of subsets from chemoprevention trials may have introduced bias regarding reported malignant transformation rates and accuracy of prognostic biomarkers.

CONCLUSIONS

This review identified insufficient longitudinal evidence to support validated prognostic biomarkers for oral leukoplakia. Further studies are needed to identify molecular targets with the potential to mitigate risk of malignant transformation.

Ovatodiolide Suppresses Oral Cancer Malignancy by Down-Regulating Exosomal Mir-21/STAT3/β-Catenin Cargo and Preventing Oncogenic Transformation of Normal Gingival Fibroblasts

Oral squamous cell carcinoma (OSCC) is among the most commonly diagnosed malignancies in the world. Patients with OSCC often develop treatment resistance, resulting in a poor prognosis. Mounting evidence indicates that interactions between cancerous cells and other components of the tumor microenvironment (TME) determine their response to treatment. Herein, we examined the role of cancer stem cell-derived extracellular vesicles (CSC_EVs) generated from CAL27 and SCC-15 OSCC cells in the development of cisplatin (CDDP) resistance. We demonstrated that CSC_EVs enhance CDDP resistance, clonogenicity, and the tumorsphere formation potential of OSCC cells. Our bioinformatics analyses revealed that OSCC_EVs are enriched with microRNA (miR)-21-5p and are associated with increased metastasis, stemness, chemoresistance, and poor survival in patients with OSCC. Mechanistically, enhanced activity of CSC_EVs was positively correlated with upregulated β-catenin, phosphatidylinositol-3 kinase (PI3K), signal transducer and activator of transcription 3 (STAT3), mammalian target of rapamycin (mTOR), and transforming growth factor (TGF)-β1 messenger (m)RNA and protein expression levels. CSC_EVs also conferred a cancer-associated fibroblast (CAF) phenotype on normal gingival fibroblasts (NGFs), with the resultant CAFs enhancing the oncogenicity of OSCC cells. Interestingly, treatment with ovatodiolide (OV), the bioactive component of Anisomeles indica, suppressed OSCC tumorigenesis by reducing the cargo content of EVs derived from CSCs, suppressing self-renewal, and inhibiting the NGF-CAF transformation by disrupting EV-TME interactions. Moreover, by suppressing miR-21-5p, STAT3, and mTOR expressions in CSC_EVs, OV re-sensitized CSCs to CDDP and suppressed OSCC tumorigenesis. In vivo, treatment with OV alone or in combination with CDDP significantly reduced the tumor sphere-forming ability and decreased EV cargos containing mTOR, PI3K, STAT3, β-catenin, and miR-21-5p. In summary, our findings provide further strong evidence of OV’s therapeutic effect in OSCC.

Deep learning-based survival prediction of oral cancer patients

The Cox proportional hazards model commonly used to evaluate prognostic variables in survival of cancer patients may be too simplistic to properly predict a cancer patient’s outcome since it assumes that the outcome is a linear combination of covariates. In this retrospective study including 255 patients suitable for analysis who underwent surgical treatment in our department from 2000 to 2017, we applied a deep learning-based survival prediction method in oral squamous cell carcinoma (SCC) patients and validated its performance. Survival prediction using DeepSurv, a deep learning based-survival prediction algorithm, was compared with random survival forest (RSF) and the Cox proportional hazard model (CPH). DeepSurv showed the best performance among the three models, the c-index of the training and testing sets reaching 0.810 and 0.781, respectively, followed by RSF (0.770/0.764), and CPH (0.756/0.694). The performance of DeepSurv steadily improved with added features. Thus, deep learning-based survival prediction may improve prediction accuracy and guide clinicians both in choosing treatment options for better survival and in avoiding unnecessary treatments.

Molecular Biomarkers Related to Oral Carcinoma: Clinical Trial Outcome Evaluation in a Literature Review

Backgrounds

The objective of the present research was to systematically revise the international literature about the genetic biomarkers related to oral cancer (OC) evaluating the recent findings in clinical studies.

Methods

A comprehensive review of the current literature was conducted according to the PRISMA guidelines by accessing the NCBI PubMed database. The authors conducted the search of articles in the English language published from 2008 to 2018. The present systematic review included only papers with significant results about correlation between wound healing, genetic alteration, and OC. Prognostic capacity of genetic markers was not evaluated in vivo.

Results

The first analysis with filters recorded about 1884 published papers. Beyond reading and consideration of suitability, only 20 and then 8 papers, with case report exclusion, were recorded for the revision.

Conclusion

All the researches recorded the proteomic and genetic alterations in OC human biopsy cells. The gene modification level in the different studies, compared with samples of healthy tissues, has always been statistically significant, but it is not possible to associate publications with each other because each job is based on the measurement of different biomarkers and gene targets. Further investigations should be required in order to state scientific evidence about a clear advantage of using these biomarkers for diagnostic purpose.