Evaluation of the significance of tumor stromal patterns and peri-tumoral inflammation in head and neck squamous cell carcinoma with special reference to the Yamamoto-Kohama classification.

INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide with 878,348 new cases. Cancer-associated fibroblasts (CAFs) are the predominant cell type in tumor stroma and are important promoters of tumor progression. OBJECTIVE: The aim of the study was to evaluate the pattern of desmoplastic stromal reaction and peri-tumoral inflammatory infiltrate with the histological grade and clinical data. MATERIALS AND METHODS: A total of 60 cases of HNSCC were included in the study. The hematoxylin and eosin (H and E)-stained sections from all cases were examined by two experienced pathologists for the grade, nature of stomal reaction (SR), peri-tumoral inflammatory infiltration, Yamamoto-Kohama classification grade, worst pattern of invasion (WPOI), depth of invasion (DOI), and other histopathological parameters. Correlation analysis was conducted using the Chi-square test. P- value less than 0.05 was considered statistically significant. RESULTS: Immature SR was not observed in any of the well-differentiated squamous cell carcinoma (SCC) cases. However, one (3.7%) case of moderately differentiated SCC and two (28.6%) cases of poorly differentiated SCC showed signs of immature SR. In the case of the higher grades of the YK classification, specifically grades 4C and 4D, a more profound depth of tumor cell invasion, equal to or exceeding 10 mm, was evident in six (66.67%) and two (28.57%) cases, respectively. Additionally, among the seven (11.7%) cases classified as poorly differentiated carcinoma, three (42.85%) displayed a WPOI score of 5. CONCLUSION: SR and the tumor invasive pattern in HNSCC are related to prognosis and may indicate tumor aggressiveness.

Comparison of the 7th and revised 8th UICC editions (2020) for oral squamous cell carcinoma: How does the reclassification impact staging and survival?

Since its introduction in 1968, the TNM (tumor, node, metastasis) classification established by the International Union Against Cancer has provided a consistent framework for staging of oral squamous cell carcinoma (OSCC). The introduction of the 8th edition in 2017 brought about significant modifications, encompassing the integration of depth of invasion (DOI) and extranodal extension (ENE) into the T and N classifications. Further, the UICC the criteria for the T3 and T4a categories were amended in 2020. This study aimed to evaluate the impact of reclassification on staging and, subsequently, the survival of patients with OSCC. Primary OSCCs from 391 patients were classified according to the 7th and revised 8th UICC editions (2020). Stage migration was assessed, and stage-specific progression-free survival (PFS) and overall survival (OS) were evaluated using the Kaplan-Meier method. The log-rank test was used to compare the different stages. Cox-proportional hazard modeling was used to compare the two editions. Incorporating the DOI into the T classification resulted in an upstaging of 77 patients, constituting 19.69% of the cohort. In addition, 49 (12.53%) patients experienced an upstaging when considering ENE in the N classification. Consequently, 103 patients underwent upstaging in UICC staging, accounting for 21.74% of cases. Upstaging mainly occurred from stage III to IVA (26.92%) and from stage IVA to IVB (31.78%). Upon comparing the categories in survival analysis, significant differences in OS and PFS were especially observed between stage IVB and lower stages. When examining the hazard ratios, it became evident that UICC 8 stage IVB is burdened by a 5.59-fold greater risk of disease progression than stage I. Furthermore, UICC 8 stage IVB exhibits a 3.83 times higher likelihood of death than stage I disease. We demonstrated significant stage migration from the 7th to the revised 8th UICC edition. Overall, incorporating DOI and ENE into the T and N classifications represents a substantial clinical advancement, leading to a more accurate staging of OSCC patients. Both staging systems exhibited statistically significant discrimination between stages; however, the 8th UICC edition allowed for a more precise categorization of patients based on their prognosis and led to enhanced hazard discrimination, particularly within higher stages.

Identification of High-Risk Human Papillomavirus DNA, p16, and E6/E7 Oncoproteins in Laryngeal and Hypopharyngeal Squamous Cell Carcinomas.

Human papillomavirus (HPV) was proven to play a significant role in cancer development in the oropharynx. However, its role in the development of laryngeal (LSCC) and hypopharyngeal squamous cell carcinoma (HPSCC) remains to be clarified. High-risk HPV (HR-HPV) viral proteins E6 and E7 are considered to be pertinent to HPV-related carcinogenesis. Hence, our aim was to estimate LSCC and HPSCC for HR-HPV DNA, p16, and E6/E7 oncoprotein status by using molecular virology and immunohistochemistry methods. The prevalence of HPV16 infection was 22/41 (53.7%) and 20/31 (64.5%) for LSCC and HPSCC, accordingly. The majority of HPV16+ tumor samples were stage III or IV. In most samples, the presence of either HPV16 E6 or HPV16 E7 viral protein in dysplastic or tumor cells was confirmed using immunohistochemistry. Our results suggest a high prevalence of HPV16 as a primary HR-HPV type in LSCC and HPSCC. The lack of HPV E6/E7 oncoproteins in some tumor samples may suggest either the absence of viral integration or the presence of other mechanisms of tumorigenesis. The utilization of p16 IHC as a surrogate marker of HR-HPV infection is impractical in LSCC and HPSCC.

Small RNA sequencing to differentiate lung squamous cell carcinomas from metastatic lung tumors from head and neck cancers.

Distinguishing lung squamous cell carcinoma (LSQCC) from a solitary metastatic lung tumor (MSQCC) from head and neck squamous cell carcinoma (HNSQCC) presents a difficult diagnostic challenge even after detailed pathological assessment. Treatment options and estimated survival outcomes after pulmonary resection differ between patients with LSQCC and MSQCC. This study aimed to investigate whether microRNA (miRNA) profiling by RNA sequencing of HNSQCC, MSQCC, and LSQCC was useful for differential diagnosis of MSQCC and LSQCC. RNA sequencing was performed to identify bioinformatically significant miRNAs from a formalin-fixed paraffin-embedded (FFPE) block from a derivation set. MiRNA levels were confirmed by validation sets using FFPE samples and serum extracellular vesicles from patients. Step-wise discriminant analysis and canonical discriminant analysis identified 13 miRNAs by which the different expression patterns of LSQCC, MSQCC, and HNSQCC groups were demonstrated. Six miRNAs (miR-10a/28/141/320b/3120) were assessed in validation sets, and 4 miRNAs (miR-10a/28/141/3120) were significantly upregulated in LSQCCs compared with MSQCCs and HNSQCCs. Serum extracellular vesicles from LSQCC patients demonstrated significantly elevated miR-10a (p = .042), miR-28 (p = .041), and miR-3120 (p = .047) levels compared with those from MSQCC patients. RNA sequencing is useful for differential diagnosis of LSQCC and MSQCC, and the expression level of miR-10a, miR-28, and miR-3120 in serum extracellular vesicles are promising noninvasive tools for this purpose.

Oropharyngeal squamous cell carcinoma: p16/p53 immunohistochemistry as a strong predictor of HPV tumour status.

AIMS: Oropharyngeal squamous cell carcinomas (OPSCC) related to human papillomavirus (HPV) infection have a better prognosis than those without HPV infection. Although p16INK4a overexpression is used as a surrogate marker for HPV infection, 5-20% of p16-positive OPSCC are described as being unrelated to HPV infection, with worse overall survival compared to OPSCC-related HPV. There is therefore a risk of undertreating a proportion of OPSCC patients falsely considered to be HPV-driven because of p16 positivity. TP53 mutations are highly prevalent in OPSCC driven by mutagens in tobacco and alcohol. We describe herein a combined p16/p53 algorithm to predict HPV tumour status in OPSCC. METHODS AND RESULTS: A total of 110 OPSCC were identified in the database of the pathology department and were studied using p16 and p53 immunohistochemistry. For p16-positive or p16-negative/wild-type patterns-p53 (WT-p53) cases (n = 63), DNA in-situ hybridisation for high-risk HPV was performed, and if negative the HPV status was controlled by HPV DNA polymerase chain reaction (PCR) (n = 19). A significant association between TP53 mutation and pattern of p53 expression was found (WT-p53, seven of 16, P < 0.001). The p16-positive/WT-p53 was significantly associated with HPV+ tumour status (p16-positive/WT-p53, 50 of 110, P < 0.001). Interestingly, a subset of p16-positive OPSCC was unrelated to HPV (13.5%, eight of 59), and showed mutant-type staining of p53 expression. CONCLUSIONS: The p16 protein immunopositivity in conjunction with the mutant-type pattern of p53 staining helped to reclassify a subset of p16-positive OPSCC as OPSCC-unrelated HPV. This approach could be routinely applied by pathologists involved in the management of OPSCC, because of their potential therapeutic implications.

Integrating depth of invasion in T classification improves the prognostic performance of the American Joint Committee on Cancer primary tumor staging system for cutaneous squamous cell carcinoma of the head and neck.

BACKGROUND: The last revision of the American Joint Committee on Cancer (AJCC) Cancer Staging Manual included a specific system for cutaneous squamous cell carcinoma (CSCC) of the head and neck. Here, we assessed the prognostic performance of six candidate modified T-classification models in head and neck CSCC patients. METHODS: Analysis of 916 patients with head and neck CSCC given treatment with curative intent at The University of Texas MD Anderson Cancer Center between 1995 and 2019 was performed. The main outcome was disease-specific survival (DSS), and the impact of depth of invasion (DOI) was analyzed using multivariable regression models. Candidate models were developed using the optimal DOI cut points for each AJCC T classification based on goodness of fit of the model and the simplicity of the model. Staging systems were compared using Harrell's concordance index. RESULTS: Median age was 70 years (range, 19-97years) and median follow-up time of 22 months (range, 1-250months). The median DOI was 6.0 mm (range, 0.1-70.0 mm). The five-year DSS rate was 80.7% (95%CI, 77.4-83.7%). We found significant association between DOI (hazard ratio, 1.21 [95%CI: 1.01-1.43]) and DSS on multivariable analysis. Based on a low Akaike information criterion score, improvement in the concordance index, and Kaplan-Meier curves, model 6 surpassed the AJCC staging system. CONCLUSIONS: Incorporation of DOI in the current AJCC staging system improves discrimination of T classifications in head and neck CSCC patients. LAY SUMMARY: The current staging system for head and neck cutaneous squamous cell carcinoma demonstrates wide prognostic variability and provides suboptimal risk stratification. Incorporation of depth of invasion in the T-classification system improves risk prediction and patient counseling. PRECIS: We propose improved head and neck cutaneous squamous cell carcinoma T staging that will include depth of invasion and should be considered in future versions of the American Joint Committee on Cancer after external validation.

Study of morphological and textural features for classification of oral squamous cell carcinoma by traditional machine learning techniques.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is the most prevalent form of oral cancer. Very few researches have been carried out for the automatic diagnosis of OSCC using artificial intelligence techniques. Though biopsy is the ultimate test for cancer diagnosis, analyzing a biopsy report is a very much challenging task. To develop computer-assisted software that will diagnose cancerous cells automatically is very important and also a major need of the hour. AIM: To identify OSCC based on morphological and textural features of hand-cropped cell nuclei by traditional machine learning methods. METHODS: In this study, a structure for semi-automated detection and classification of oral cancer from microscopic biopsy images of OSCC, using clinically significant and biologically interpretable morphological and textural features, are examined and proposed. Forty biopsy slides were used for the study from which a total of 452 hand-cropped cell nuclei has been considered for morphological and textural feature extraction and further analysis. After making a comparative analysis of commonly used methods in the segmentation technique, a combined technique is proposed. Our proposed methodology achieves the best segmentation of the nuclei. Henceforth the features extracted were fed into five classifiers, support vector machine, logistic regression, linear discriminant, k-nearest neighbors and decision tree classifier. Classifiers were also analyzed by training time. Another contribution of the study is a large indigenous cell level dataset of OSCC biopsy images. RESULTS: We achieved 99.78% accuracy applying decision tree classifier in classifying OSCC using morphological and textural features. CONCLUSION: It is found that both morphological and textural features play a very important role in OSCC diagnosis. It is hoped that this type of framework will help the clinicians/pathologists in OSCC diagnosis.

Predictive classifier for intensive treatment of head and neck cancer.

BACKGROUND: This study was designed to test the hypothesis that the effectiveness of intensive treatment for locoregionally advanced head and neck cancer (LAHNC) depends on the proportion of patients' overall event risk attributable to cancer. METHODS: This study analyzed 22,339 patients with LAHNC treated in 81 randomized trials testing altered fractionation (AFX; Meta-Analysis of Radiotherapy in Squamous Cell Carcinomas of Head and Neck [MARCH] data set) or chemotherapy (Meta-Analysis of Chemotherapy in Head and Neck Cancer [MACH-NC] data set). Generalized competing event regression was applied to the control arms in MARCH, and patients were stratified by tertile according to the ω score, which quantified the relative hazard for cancer versus competing events. The classifier was externally validated on the MACH-NC data set. The study tested for interactions between the ω score and treatment effects on overall survival (OS). RESULTS: Factors associated with a higher ω score were a younger age, a better performance status, an oral cavity site, higher T and N categories, and a p16-negative/unknown status. The effect of AFX on OS was greater in patients with high ω scores (hazard ratio [HR], 0.92; 95% confidence interval [CI], 0.85-0.99) and medium ω scores (HR, 0.91; 95% CI, 0.84-0.98) versus low ω scores (HR, 0.97; 95% CI, 0.90-1.05; P for interaction = .086). The effect of chemotherapy on OS was significantly greater in patients with high ω scores (HR, 0.81; 95% CI, 0.75-0.88) and medium ω scores (HR, 0.86; 95% CI, 0.78-0.93) versus low ω scores (HR, 0.96; 95% CI, 0.86-1.08; P for interaction = .011). CONCLUSIONS: LAHNC patients with a higher risk of cancer progression relative to competing mortality, as reflected by a higher ω score, selectively benefit from more intensive treatment.

The 8th TNM classification for oral squamous cell carcinoma: What is gained, what is lost, and what is missing.

OBJECTIVES: The 8th TNM edition remarkably changed the classification of T and N categories for oral squamous cell carcinoma (OSCC). The present study aims at evaluating the improvement in prognostic power compared to the 7th edition, pros and cons of the modifications, and parameters deserving consideration for further implementations. MATERIALS AND METHODS: All OSCCs treated with upfront surgery at our institution between 2002 and 2017 were included. Demographics, clinical-pathological and treatment variables were retrieved. All tumors were classified according to both the 7th and 8th TNM edition, and patients were grouped according to the shift in T category and stage. Survivals were calculated with the Kaplan-Meier method. Univariate and multivariate analysis were carried out. Receiver Operating Characteristics (ROC) curve analyses were performed to find the best cut-off of DOI (in patients with DOI > 10 mm) and number of involved nodes (in positive neck patients). RESULTS: 244 patients were included. T, N categories, and stage changed in 59.2%, 20.5%, and 49.1% patients, respectively; 41.5% of patients were upstaged. The new T classification well depicted prognosis according to OS. Five-year overall (OS), disease-specific, recurrence-free (RFS) survivals were 60.5%, 70.9%, 59.8%, respectively. According to ROC curves, DOI > 20 mm and 4 positive nodes were the best cutoffs for OS and RFS. CONCLUSION: The novelties introduced in 8th TNM edition were positive. DOI > 20 mm for T4 definition and number of positive nodes (0, <4, 4 or more) for N classification emerged as the most urgent factors to be implemented.

Discovery and Validation of a CT-Based Radiomic Signature for Preoperative Prediction of Early Recurrence in Hypopharyngeal Carcinoma.

PURPOSE: In the clinical management of hypopharyngeal squamous cell carcinoma (HSCC), preoperative identification of early recurrence (≤2 years) after curative resection is essential. Thus, we aimed to develop a CT-based radiomic signature to predict early recurrence in HSCC patients preoperatively. METHODS: In total, 167 HSCC patients who underwent partial surgery were enrolled in this retrospective study and divided into two groups, i.e., the training cohort (n = 133) and the validation cohort (n = 34). Each individual was followed up for at least for 2 years. Radiomic features were extracted from CT images, and the radiomic signature was built with the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) model. The associations of preoperative clinical factors with early recurrence were evaluated. A radiomic signature-combined model was built, and the area under the curve (AUC) was used to explore their performance in discriminating early recurrence. RESULTS: Among the 1415 features, 335 of them were selected using the variance threshold method. Then, the SelectKBest method was further used for the selection of 31 candidate features. Finally, 11 out of 31 optimal features were identified with the LASSO algorithm. In the LR classifier, the AUCs of the training and validation sets in discriminating early recurrence were 0.83 (95% CI: 0.76-0.90) (sensitivity 0.8 and specificity 0.83) and 0.83 (95% CI: 0.67-0.99) (sensitivity 0.69 and specificity 0.71), respectively. CONCLUSIONS: Using the radiomic signature, we developed a radiomic signature to preoperatively predict early recurrence in patients with HSCC, which may serve as a potential noninvasive tool to guide personalized treatment.

Human Papillomavirus Testing in Head and Neck Squamous Cell Carcinoma in 2020: Where Are We Now and Where Are We Going?

High risk human papillomavirus (HPV) has transformed head and neck oncology in the past several decades. Now that we have recognized that HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) is a unique cancer type with distinct clinicopathologic features and favorable prognosis, it has become essential to test patients in routine practice. We have progressed greatly in our knowledge of this disease and gone, over the past two to three decades, from doing testing in highly variable amounts and methods to, now, with the help of national and international guidelines and patient staging requirements, to a situation where almost all patients with OPSCC are getting accurate classification through at least p16 immunohistochemistry. However, we are still struggling with how to accurately test specimens from cervical lymph nodes, and, in particular, on fine needle aspiration. In addition, many patients with non-oropharyngeal SCC are getting clinically unnecessary p16 and/or HPV-specific testing. The trends suggest progressive improvement in practices, but many practical questions still remain. On the horizon are myriad non-tissue-based tests, such as HPV serology and plasma DNA, DNA-based testing of fine needle aspirate fluid, computerized analysis of digitized pathology and radiology images, and machine learning from clinical and pathologic features, that may render pathologists largely obsolete for establishing HPV status for our patients' tumors. This review takes a brief look back in time to where we have been, then characterizes current practices in 2020 and lingering questions, and, finally, looks ahead into the possible future of HPV testing in patients with head and neck SCC.

Analysis of specific survival and local control through a recursive partitioning analysis in patients with head and neck carcinoma. / Análisis de la supervivencia específica y el control local mediante un análisis de partición recursiva en pacientes con carcinomas de cabeza y cuello.

INTRODUCTION AND OBJECTIVES: Recursive partitioning analysis (RPA) is a technique that allows prognostic classification in oncological patients. The aim of the present study is to analyse by means of an RPA a cohort of patients with squamous carcinomas of the head and neck (SCHN). METHODS: 5,226 SCHN were retrospectively analysed with an RPA, considering the specific survival and local control of the disease as dependent variables. A cohort of patients was used for the creation of the classification model, and another cohort was used to carry out its internal validation. RESULTS: Considering specific survival as a dependent variable we obtained a classification tree with 14 terminal nodes that were grouped into 5 categories, including as partition variables the local and regional extent of the tumour, and the location of the tumour. When considering the local control of the disease as a dependent variable we obtained a classification tree with 10 terminal nodes that were grouped into 4 categories, including as partition variables the local extension and location of the tumour, the type of treatment performed, the age of the patient, and if it was a first tumour or a subsequent neoplasm. The validation study confirmed the prognostic capacity of the models developed with the RPA. One of the advantages of the RPA is that it allows the identification of groups of patients with specific behaviour. CONCLUSION: RPA is shown to be an effective technique for the prognostic classification of patients with a SCHN.

Selection of Head and Neck Cancer Patients for Intensive Therapy.

PURPOSE: Previous studies have found that patients with head and neck cancer (HNC) with a higher relative hazard for recurrence versus competing mortality (ω+ ratio) are more likely to benefit from intensive therapy. Nomograms to predict this ratio (ω scores) can be useful to guide clinical management; however, comorbidity and other risk factors are frequently lacking from trial samples. METHODS AND MATERIALS: In this study of 7117 US veterans, we evaluated the ability of a ω score nomogram developed from clinical trial data to stratify patients with HNC treated with radiation therapy by their relative risk of cancer progression versus competing mortality. We then fit generalized competing event models to determine the effect of comorbidity and other covariates on the ω+ ratio. RESULTS: The ω score was effective in stratifying patients with HNC according to their risk for cancer recurrence relative to competing mortality, especially among patients aged >70 years. Patients with ω score ≥0.80 were more likely to receive intensive therapy compared with patients with a ω score <0.80 (66 vs. 54%; P < .001). On multivariable generalized competing event regression, T2-4 category (relative hazard ratio [RHR], 1.08; 95% confidence interval [CI], 1.01-1.16), N2-3 category (RHR, 1.07; 95% CI, 1.01-1.15), and being employed (RHR, 1.11; 95% CI, 1.03-1.20) were associated with increased ω+ ratio, and increasing age (RHR, 0.83; 95% CI, 0.78-0.89), Charlson comorbidity index ≥2 (RHR, 0.85; 95% CI, 0.79-0.91), being a current smoker (RHR, 0.90; 95% CI, 0.84-0.96), and lower body mass index (RHR, 0.89; 95% CI, 0.84-0.95) were associated with a decreased ω+ ratio. CONCLUSIONS: The ω scores are effective in stratifying patients with HNC and are correlated with the intensity of treatment given. The ω scores incorporating comorbidity and other risk factors could help identify patients with HNC most likely to benefit from intensive therapy.

Development and validation of radiomic signatures of head and neck squamous cell carcinoma molecular features and subtypes.

BACKGROUND: Radiomics-based non-invasive biomarkers are promising to facilitate the translation of therapeutically related molecular subtypes for treatment allocation of patients with head and neck squamous cell carcinoma (HNSCC). METHODS: We included 113 HNSCC patients from The Cancer Genome Atlas (TCGA-HNSCC) project. Molecular phenotypes analyzed were RNA-defined HPV status, five DNA methylation subtypes, four gene expression subtypes and five somatic gene mutations. A total of 540 quantitative image features were extracted from pre-treatment CT scans. Features were selected and used in a regularized logistic regression model to build binary classifiers for each molecular subtype. Models were evaluated using the average area under the Receiver Operator Characteristic curve (AUC) of a stratified 10-fold cross-validation procedure repeated 10 times. Next, an HPV model was trained with the TCGA-HNSCC, and tested on a Stanford cohort (N = 53). FINDINGS: Our results show that quantitative image features are capable of distinguishing several molecular phenotypes. We obtained significant predictive performance for RNA-defined HPV+ (AUC = 0.73), DNA methylation subtypes MethylMix HPV+ (AUC = 0.79), non-CIMP-atypical (AUC = 0.77) and Stem-like-Smoking (AUC = 0.71), and mutation of NSD1 (AUC = 0.73). We externally validated the HPV prediction model (AUC = 0.76) on the Stanford cohort. When compared to clinical models, radiomic models were superior to subtypes such as NOTCH1 mutation and DNA methylation subtype non-CIMP-atypical while were inferior for DNA methylation subtype CIMP-atypical and NSD1 mutation. INTERPRETATION: Our study demonstrates that radiomics can potentially serve as a non-invasive tool to identify treatment-relevant subtypes of HNSCC, opening up the possibility for patient stratification, treatment allocation and inclusion in clinical trials. FUND: Dr. Gevaert reports grants from National Institute of Dental & Craniofacial Research (NIDCR) U01 DE025188, grants from National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (NIBIB), R01 EB020527, grants from National Cancer Institute (NCI), U01 CA217851, during the conduct of the study; Dr. Huang and Dr. Zhu report grants from China Scholarship Council (Grant NO:201606320087), grants from China Medical Board Collaborating Program (Grant NO:15-216), the Cyrus Tang Foundation, and the Zhejiang University Education Foundation during the conduct of the study; Dr. Cintra reports grants from São Paulo State Foundation for Teaching and Research (FAPESP), during the conduct of the study.

Molecular prognosticators in clinically and pathologically distinct cohorts of head and neck squamous cell carcinoma-A meta-analysis approach.

Head and neck squamous cell carcinomas (HNSCC) includes multiple subsites that exhibit differential treatment outcome, which is in turn reflective of tumor stage/histopathology and molecular profile. This study hypothesized that the molecular profile is an accurate prognostic adjunct in patients triaged based on clinico-pathological characteristics. Towards this effect, publically available micro-array datasets (n = 8), were downloaded, classified based on HPV association (n = 83) and site (tongue n = 88; laryngopharynx n = 53; oropharynx n = 51) and re-analyzed (Genespring; v13.1). The significant genes were validated in respective cohorts in The Cancer Genome Atlas (TCGA) for correlation with clinico-pathological parameters/survival. The gene entities (n = 3258) identified from HPV based analysis, when validated in TCGA identified the subset specifically altered in HPV+ HNSCC (n = 63), with three genes showing survival impact (RPP25, NUDCD2, NOVA1). Site-specific meta-analysis identified respective differentials (tongue: 3508, laryngopharynx: 4893, oropharynx: 2386); validation in TCGA revealed markers with high incidence (altered in >10% of patients) in tongue (n = 331), laryngopharynx (n = 701) and oropharynx (n = 404). Assessment of these genes in clinical sub-cohorts of TCGA indicated that early stage tongue (MTFR1, C8ORF33, OTUD6B) and laryngeal cancers (TWISTNB, KLHL13 and UBE2Q1) were defined by distinct prognosticators. Similarly, correlation with perineural/angiolymophatic invasion, identified discrete marker panels with survival impact (tongue: NUDCD1, PRKC1; laryngopharynx: SLC4A1AP, PIK3CA, AP2M1). Alterations in ANO1, NUDCD1, PIK3CA defined survival in tongue cancer patients with nodal metastasis (node+ECS-), while EPS8 is a significant differential in node+ECS- laryngopharyngeal cancers. In oropharynx, wherein HPV is a major etiological factor, distinct prognosticators were identified in HPV+ (ECHDC2, HERC5, GGT6) and HPV- (GRB10, EMILIN1, FNDC1). Meta-analysis in combination with TCGA validation carried out in this study emphasized on the molecular heterogeneity inherent within HNSCC; the feasibility of leveraging this information for improving prognostic efficacy is also established. Subject to large scale clinical validation, the marker panel identified in this study can prove to be valuable prognostic adjuncts.

Addition of tumour infiltration depth and extranodal extension improves the prognostic value of the pathological TNM classification for early-stage oral squamous cell carcinoma.

AIMS: In the 8th edition of the American Joint Committee on Cancer TNM staging manual, tumour infiltration depth and extranodal extension are added to the pathological classification for oral squamous cell carcinoma. The currently available 8th TNM validation studies lack patients with conservative neck treatment, and changes in the classification especially affect patients with small tumours. The aim of this study was to determine the potential impact of the changes in the 8th edition pTNM classification on the prognosis and treatment strategy for oral squamous cell carcinoma in a well-defined series of pT1-T2 patients with long-term follow-up. METHODS AND RESULTS: Two hundred and eleven first primary pT1-T2 oral squamous cell carcinoma patients, with surgical resection as primary treatment, were analysed retrospectively. One hundred and seventy-three patients underwent a neck dissection, and 38 patients had frequent clinical neck assessments. Long-term follow-up (median 64 months) and reassessed tumour infiltration depth were available. Classification according to the 8th edition criteria resulted in 36% total upstaging with the T classification and 16% total upstaging with the N classification. T3-restaged patients (n = 30, 14%) had lower 5-year disease-specific survival rates than T2-staged patients (81% versus 67%, P = 0.042). Postoperative (chemo)radiotherapy could have been considered in another seven (3%) patients on the basis of the 8th edition criteria. CONCLUSIONS: Addition of tumour infiltration depth and extranodal extension in the 8th TNM classification leads to the identification of oral squamous cell carcinoma patients with a worse prognosis who might benefit from an improved postoperative treatment strategy.

HPV detection and genotyping of head and neck cancer biopsies by molecular testing with regard to the new oropharyngeal squamous cell carcinoma classification based on HPV status.

Recently, both the World Health Organization/International Agency for Research on Cancer (WHO/IARC) and the American Joint Committee on Cancer (AJCC) have classified oropharyngeal squamous cell carcinoma (OPSCC) on the basis of HPV status. For this purpose, the WHO/IARC recommended direct molecular HPV testing. In practice, formalin-fixed, paraffin-embedded (FFPE) biopsy specimens are frequently the only available samples. We herein compared in parallel two commercially available molecular assays that were first designed for cervical HPV detection and genotyping: Inno-Lipa HPV Genotyping Extra II (IL) and Anyplex II HPV28 (AP28). A total of 55 samples were tested. By IL assay, chosen as reference assay, 27 (49.1%) biopsies were positive for HPV16, 10 (18.2%) were positive for HPV but negative for HPV16, and 18 (32.7%) were negative for HPV. A valid result with AP28 was obtained for 51 biopsy samples (92.7%). Among 37 HPV positive samples by IL, 33 (89.2%) were positive by AP28. The agreement between both assays was good (Cohen's κ = 0.78). Among the six discrepancies between assays, always associated with low HPV16 viral load, four biopsies positive for HPV16 by IL could not be detected by AP28. Taken together, these observations demonstrate that both assays could be used in routine HPV detection and genotyping on FFPE biopsy samples of head and neck tumours.

A Proposal to Revise the Histopathologic Grading System of Early Oral Tongue Cancer Incorporating Tumor Budding.

The World Health Organization (WHO) grading system has a low prognostic value for early-stage oral tongue squamous cell carcinoma; greater prognostic power has been shown with tumor budding analysis. In this study, we combined tumor budding analysis with histopathologic grading according to WHO 2017. In our proposal, a revised grade I tumor is defined as a "well differentiated cohesive tumor"; revised grade II as a "moderately differentiated and/or slightly dissociated tumor"; and revised grade III as a "poorly differentiated and/or dissociated tumor." We evaluated the prognostic value of this proposed grading system in a multicenter cohort of 311 cases of early oral tongue squamous cell carcinoma. The proposed grading system showed significant prognostic value in multivariable analysis for disease-specific survival with a hazard ratio of 3.86 and a 95% confidence interval of 1.36-10.9 (P=0.001). For disease-free survival, the proposed grading system showed good predictive power in multivariable analysis (hazard ratio, 2.07; 95% confidence interval, 1.00-4.27; P=0.009). The conventional WHO grading system showed a low prognostic value for disease-specific survival and disease-free survival (P>0.05). In conclusion, the prognostic power of the WHO histopathologic grading improved significantly with incorporation of tumor budding. Our proposed grading system can be easily included in pathology reports.

Identification and validation of novel microenvironment-based immune molecular subgroups of head and neck squamous cell carcinoma: implications for immunotherapy.

Background: Targeting the immune checkpoint pathway has demonstrated antitumor cytotoxicity in treatment-refractory head and neck squamous cell carcinoma (HNSC). To understand the molecular mechanisms underpinning its antitumor response, we characterized the immune landscape of HNSC by their tumor and stromal compartments to identify novel immune molecular subgroups. Patients and methods: A training cohort of 522 HNSC samples from the Cancer Genome Atlas profiled by RNA sequencing was analyzed. We separated gene expression patterns from tumor, stromal, and immune cell gene using a non-negative matrix factorization algorithm. We correlated the expression patterns with a set of immune-related gene signatures, potential immune biomarkers, and clinicopathological features. Six independent datasets containing 838 HNSC samples were used for validation. Results: Approximately 40% of HNSCs in the cohort (211/522) were identified to show enriched inflammatory response, enhanced cytolytic activity, and active interferon-γ signaling (all, P < 0.001). We named this new molecular class of tumors the Immune Class. Then we found it contained two distinct microenvironment-based subtypes, characterized by markers of active or exhausted immune response. The Exhausted Immune Class was characterized by enrichment of activated stroma and anti-inflammatory M2 macrophage signatures, WNT/transforming growth factor-ß signaling pathway activation and poor survival (all, P < 0.05). An enriched proinflammatory M1 macrophage signature, enhanced cytolytic activity, abundant tumor-infiltrating lymphocytes, high human papillomavirus (HPV) infection, and favorable prognosis were associated with Active Immune Class (all, P < 0.05). The robustness of these immune molecular subgroups was verified in the validation cohorts, and Active Immune Class showed potential response to programmed cell death-1 blockade (P = 0.01). Conclusions: This study revealed a novel Immune Class in HNSC; two subclasses characterized by active or exhausted immune responses were also identified. These findings provide new insights into tailoring immunotherapeutic strategies for different HNSC subgroups.

Three distinct genomic subtypes of head and neck squamous cell carcinoma associated with clinical outcomes.

OBJECTIVES: Heterogeneity of head and neck squamous cell carcinomas (HNSCCs) results in unpredictable outcomes for patients with similar stages of cancer. Beyond the role of human papilloma virus (HPV), no validated molecular marker of HNSCCs has been established. Thus, clinically relevant molecular subtypes are needed to optimize HNSCC therapy. The purpose of this study was to identify subtypes of HNSCC that have distinct biological characteristics associated with clinical outcomes and to characterize genomic alterations that best reflect the biological and clinical characteristics of each subtype. MATERIALS AND METHODS: We analyzed gene expression profiling data from pan-SCC tissues including cervical SCC, esophageal SCC, lung SCC, and HNSCC (n = 1346) to assess the similarities and differences among SCCs and to identify molecular subtypes of HNSCC associated with prognosis. Subtype-specific gene expression signatures were identified and used to construct predictive models. The association of the subtypes with prognosis was validated in two independent cohorts of patients. RESULTS: Pan-SCC analysis identified three novel subtypes of HNSCC. Subtype 1 had the best prognosis and was similar to cervical SCC, whereas subtype 3 had the worst prognosis and was similar to lung SCC. Subtype 2 had a moderate prognosis. The 600-gene signature associated with the three subtypes significantly predicted prognosis in two independent validation cohorts. These three subtypes also were associated with potential benefit of immunotherapy. CONCLUSION: We identified three clinically relevant HNSCC molecular subtypes. Independent prospective studies to assess the clinical utility of the subtypes and associated gene signature are warranted.