We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. Comprehensive, integrated molecular analysis identifies molecular relationships across a large diverse set of human cancers, suggesting future directions for exploring clinical actionability in cancer treatment.

Primary management for head and neck cancers, including squamous cell carcinoma (SCC), involves surgical resection with negative cancer margins. Pathologists guide surgeons during these operations by detecting cancer in histology slides made from the excised tissue. In this study, 381 digitized, histological whole-slide images (WSI) from 156 patients with head and neck cancer were used to train, validate, and test an inception-v4 convolutional neural network. The proposed method is able to detect and localize primary head and neck SCC on WSI with an AUC of 0.916 for patients in the SCC testing group and 0.954 for patients in the thyroid carcinoma testing group. Moreover, the proposed method is able to diagnose WSI with cancer versus normal slides with an AUC of 0.944 and 0.995 for the SCC and thyroid carcinoma testing groups, respectively. For comparison, we tested the proposed, diagnostic method on an open-source dataset of WSI from sentinel lymph nodes with breast cancer metastases, CAMELYON 2016, to obtain patch-based cancer localization and slide-level cancer diagnoses. The experimental design yields a robust method with potential to help create a tool to increase efficiency and accuracy of pathologists detecting head and neck cancers in histological images.

Hyperspectral imaging (HSI) and radiomics have the potential to improve the accuracy of tumor malignancy prediction and assessment. In this work, we extracted radiomic features of fresh surgical papillary thyroid carcinoma (PTC) specimen that were imaged with HSI. A total of 107 unique radiomic features were extracted. This study includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. With the dilated hyperspectral images, the shape feature of least axis length was able to predict the tumor aggressiveness with a high accuracy. The HSI-based radiomic method may provide a useful tool to aid oncologists in determining tumors with intermediate to high risk and in clinical decision making.

The purpose of this study is to explore the feasibility of using hyperspectral imaging (HSI) for automatic detection of head and neck squamous cell carcinoma (SCC) in histologic images. Histologic slides from 14 patients with SCC of the larynx, hypopharynx, and buccal mucosa were scanned to train and test an Inception-based two-dimensional convolutional neural network (CNN). The average accuracy, sensitivity and specificity of the HSI patch-based CNN classification were 0.80, 0.82 and 0.78, respectively. The hyperspectral microscopic imaging and proposed classification method provide an automatic tool to aid pathologists in detecting SCC on histologic slides.

Surgery is a major treatment method for squamous cell carcinoma (SCC). During surgery, insufficient tumor margin may lead to local recurrence of cancer. Hyperspectral imaging (HSI) is a promising optical imaging technique for in vivo cancer detection and tumor margin assessment. In this study, a fully convolutional network (FCN) was implemented for tumor detection and margin assessment in hyperspectral images of SCC. The FCN was trained and tested with hyperspectral images of 25 ex vivo SCC surgical specimens from 20 different patients. The network was evaluated per patient and achieved pixel-level tissue classification with an average AUC of 0.88, 0.83 accuracy, 0.84 sensitivity and 0.70 specificity. The 95% Hausdorff distance of assessed tumor margin in 17 patients was less than 2 mm, and the classification time of each tissue specimen took less than 10 seconds. The proposed method potentially facilitates intraoperative tumor margin assessment and improves surgical outcomes.

Papillary thyroid carcinoma (PTC) is primarily treated by surgical resection. During surgery, surgeons often need intraoperative frozen analysis and pathologic consultation in order to detect PTC. In some cases pathologists cannot determine if the tumor is aggressive until the operation has been completed. In this work, we have taken tumor classification a step further by determining the tumor aggressiveness of fresh surgical specimens. We employed hyperspectral imaging (HSI) in combination with multiparametric radiomic features to complete this task. The study cohort includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. A total of 67 features were extracted from this data. Using machine learning classification methods, we were able to achieve an AUC of 0.85. Our study shows that hyperspectral imaging and multiparametric radiomic features could aid in the pathological detection of tumor aggressiveness using fresh surgical spemens obtained during surgery.

Background: We examined the prognostic value of a panel of biomarkers in patients with squamous cell carcinoma of the head and neck (SCCHN) who were human immunodeficiency virus (HIV) positive (HIV-positive head and neck cancer) and HIV negative (HIV-negative head and neck cancer). Methods: Tissue microarrays (TMAs) were constructed using tumors from 41 disease site-matched and age-matched HIV-positive head and neck cancer cases and 44 HIV-negative head and neck cancer controls. Expression of tumor biomarkers was assessed by immunohistochemistry (IHC) and correlations examined with clinical variables. Results: Expression levels of the studied oncogenic and inflammatory tumor biomarkers were not differentially regulated by HIV status. Among patients with HIV-positive head and neck cancer, laryngeal disease site (P =.003) and Clavien-Dindo classification IV (CD4) counts <200 cells/μL (P =.01) were associated with poor prognosis. Multivariate analysis showed that p16 positivity was associated with improved overall survival (OS; P <.001) whereas increased expression of transforming growth factor-beta (TGF-β) was associated with poor clinical outcome (P =.001). Conclusion: Disease site has significant effect on the expression of biomarkers. Expression of tumor TGF-β could be a valuable addition to the conventional risk stratification equation for improving head and neck cancer disease management strategies.

Purpose: Aberrant mTOR pathway and somatostatin receptor signaling are implicated in thyroid cancer and offer potential therapeutic targets. We assessed the clinical efficacy of everolimus and Pasireotide long-acting release (LAR) in radioiodine-refractory differentiated thyroid cancer (DTC) and medullary thyroid cancer (MTC). Patients and methods: Adults with progressive MTC and DTC untreated or treated with no more than one systemic agent were eligible. The trial was designed to establish the most promising regimen and the optimal combination sequence. Patients were randomized to start treatment with single agent everolimus (10 mg QD; Arm A), pasireotide-LAR (60 mg intramuscular injection, Q4 weeks; Arm B), or the combination (Arm C). At initial progression (PFS1), patients on Arm A or B switched to the combination and continued until progression (PFS2). Efficacy was measured by RECIST criteria. Results: Study enrolled 42 patients: median age 65 years; female 17 (40.5%); White 31 (73.8%), African American 6 (14.3%), others 5 (11.9); DTC 32 (76.2%); MTC 10 (23.8%). There was no objective response by RECIST criteria across the three arms. Median and 1-year PFS1 rates were 8.3, 1.8, 8.1 months and 49.9%, 36.4%, 25.0% for Arms A, B, C, respectively. Median and 1-year PFS2 rates were 26.3, 17.5, 8.1 months and 78.4%, 70.0%, 25% for Arms A, B, C, respectively. The most frequent adverse events were anemia, stomatitis, fatigue, hyperglycemia, and hypercholesterolemia. Conclusions: The combination of everolimus and pasireotide-LAR showed promising efficacy over single agent. The delayed combination of everolimus and pasireotide-LAR following progression on single agent everolimus appeared intriguing as a combination strategy.

Purpose We investigated the efficacy and underlying molecular mechanism of a novel chemopreventive strategy combining epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) with cyclooxygenase-2 inhibitor (COX-2I). Experimental Design We examined the inhibition of tumor cell growth by combined EGFR-TKI (erlotinib) and COX-2I (celecoxib) treatment using head and neck cancer (HNC) cell lines and a preventive xenograft model. We studied the antiangiogenic activity of these agents and examined the affected signaling pathways by immunoblotting analysis in tumor cell lysates and immunohistochemistry (IHC) and enzyme immunoassay (EIA) analyses on the mouse xenograft tissues and blood, respectively. Biomarkers in these signaling pathways were studied by IHC, EIA, and an antibody array analysis in samples collected from participants in a phase I chemoprevention trial of erlotinib and celecoxib. Results The combined treatment inhibited HNC cell growth significantly more potently than either single agent alone in cell line and xenograft models, and resulted in greater inhibition of cell cycle progression at G1 phase than either single drug. The combined treatment modulated the EGFR and mTOR signaling pathways. A phase I chemoprevention trial of combined erlotinib and celecoxib revealed an overall pathologic response rate of 71% at time of data analysis. Analysis of tissue samples from participants consistently showed downregulation of EGFR, pERK and pS6 levels after treatment, which correlated with clinical response. Conclusion Treatment with erlotinib combined with celecoxib offers an effective chemopreventive approach through inhibition of EGFR and mTOR pathways, which may serve as potential biomarkers to monitor the intervention of this combination in the clinic.

Epidermal growth factor receptor (EGFR) and COX-2 inhibitors synergistically inhibit head and neck squamous cell carcinoma tumorigenesis in preclinical studies. We conducted a phase I and pharmacokinetic study with the erlotinib and celecoxib combination in patients with advanced premalignant lesions. Thirty-six subjects with oral leukoplakia, mild, moderate, or severe dysplasia, or carcinoma in situ were screened for study participation; 12 consented and received therapy for a median of 5.38 months. Erlotinib was escalated following a standard 3+3 design at 50, 75, and 100 mg orally daily and celecoxib was fixed at 400 mg twice daily for 6 months. Biopsy of lesions and cytobrush of normal mucosa were performed at baseline, 3, 6, and 12 months. Erlotinib pharmacokinetics were analyzed in 10 subjects. The maximum tolerated dose of erlotinib with celecoxib 400 mg BID was 50 mg per day with skin rash being the main observed toxicity. Overall histologic response rate was 63% (complete response, 43%; partial response, 14%; stable disease, 29%; and disease progression, 14%). With median follow-up of 36 months, mean time to progression to higher-grade dysplasia or carcinoma was 25.4 months. Downregulation of EGFR and p-ERK in follow-up biopsies correlated with response to treatment. Larger average erlotinib V/F (approximately 308 L) and CL/F (8.3 L/h) compared with previous studies may be related to relatively large average bodyweights. Average erlotinib t1/2 was 25.6 hours. Encouraging responses to the celecoxib and erlotinib combination correlated with EGFR pathway inhibition. Although erlotinib-related rash was the main limitation to dose escalation, the intervention was well tolerated.