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Worldwide, the incidence of oral tongue cancer is on the rise, adding to the existing burden due to prevailing low survival and high recurrence rates. This study uses high-throughput expression profiling to identify candidate markers of resistance/response in patients with oral tongue cancer. Analysis of primary and post-treatment samples (12 tumor and 8 normal) by the Affymetrix platform (HG U133 plus 2) identified 119 genes as differentially regulated in recurrent tumors. The study groups had distinct profiles, with induction of immune response and apoptotic pathways in the non-recurrent and metastatic/invasiveness pathways in the recurrent group. Validation was carried out in tissues by Quantitative Real-Time PCR (QPCR) (n=30) and immunohistochemistry (IHC) (n=35) and in saliva by QPCR (n=37). The markers, COL5A1, HBB, IGLA and CTSC individually and COL5A1 and HBB in combination had the best predictive power for treatment response in the patients. A subset of markers identified (COL5A1, ABCG1, MMP1, IL8, FN1) could be detected in the saliva of patients with oral cancers with their combined sensitivity and specificity being 0.65 and 0.87 respectively. The study thus emphasizes the extreme prognostic value of exploring markers of treatment resistance that are expressed in both tissue and saliva.

Human papillomavirus (HPV) associated head and neck squamous cell cancers (HNSCC) have become increasingly common in the West, but the same cannot be said about India. These cancers have a different biology and confer a better prognosis, however, its current role in the management of patients in India is not clearly defined. At the 35th Indian Cooperative Oncology Network conference held in September 2016, a panel of radiation, surgical and medical oncologists, pathologists, and basic scientists from across the country having experience in clinical research with respect to HPV in HNSCC reviewed the available literature from India. All the ideas and facts were thereafter collated in this report. Various topics of controversy in dealing with the diagnosis and management of HPV-associated HNSCC have been highlighted in this report in context to the Indian scenario. Furthermore, the prevalence of the same and its association with tobacco and high-risk sexual behavior has been touched on. Conclusively, a set of recommendations has been proposed by the panel to guide the practicing oncologists of the country while dealing with HPV-associated HNSCC.

20Oral tongue squamous cell carcinomas (OTSCC) are a homogenous group of 21 tumors characterized by aggressive behavior, early spread to lymph nodes and a 22 higher rate of regional failure. Additionally, the incidence of OTSCC among younger 23 population (<50yrs) is on a rise; many of who lack the typical associated risk factors 11, 2015; deletions were detected in chromosomes 6-9, and 11 in the tumors. Variants in CASP8 not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/028845 doi: bioRxiv preprint first posted online Oct.

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Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This study was conducted to validate the accuracy of Convolutional-Neural-Network (CNN) enabled m(mobile)-Health device deployed with FHWs for delineation of suspicious oral lesions (malignant/potentially-malignant disorders). The effectiveness of the device was tested in tertiary-care hospitals and low-resource settings in India. The subjects were screened independently, either by FHWs alone or along with specialists. All the subjects were also remotely evaluated by oral cancer specialist/s. The program screened 5025 subjects (Images: 32,128) with 95% (n = 4728) having telediagnosis. Among the 16% (n = 752) assessed by onsite specialists, 20% (n = 102) underwent biopsy. Simple and complex CNN were integrated into the mobile phone and cloud respectively. The onsite specialist diagnosis showed a high sensitivity (94%), when compared to histology, while telediagnosis showed high accuracy in comparison with onsite specialists (sensitivity: 95%; specificity: 84%). FHWs, however, when compared with telediagnosis, identified suspicious lesions with less sensitivity (60%). Phone integrated, CNN (MobileNet) accurately delineated lesions (n = 1416; sensitivity: 82%) and Cloud-based CNN (VGG19) had higher accuracy (sensitivity: 87%) with tele-diagnosis as reference standard. The results of the study suggest that an automated mHealth-enabled, dual-image system is a useful triaging tool and empowers FHWs for oral cancer screening in low-resource settings.

Laryngo-pharyngeal squamous cell carcinomas are one of the most common head and neck cancers. Despite the presence of a large body of information, molecular biomarkers are not currently used in the diagnosis, treatment and management of patients for this group of cancer. Here, we have profiled expression of genes and microRNAs of larynx and hypopharynx tumors using high-throughput sequencing experiments. We found that matrix metalloproteinases along with SCEL, CRNN, KRT4, SPINK5, and TGM3 among others have significantly altered expression in these tumors. Alongside gene expression, the microRNAs hsa-miR-139, hsa-miR-203 and the hsa-miR-424/503 cluster have aberrant expression in these cancers. Using target genes for these microRNAs, we found the involvement of pathways linked to cell cycle, p53 signaling, and viral carcinogenesis significant (P-values 10−13, 10−9 and 10−7 respectively). Finally, using an ensemble machine-learning tool, we discovered a unique 8-gene signature for this group of cancers that differentiates the group from the other tumor subsites of head and neck region. We investigated the role of promoter methylation in one of these genes, WIF1, and found no correlation between DNA methylation and down-regulation of WIF1. We validated our findings of gene expression, 8-gene signature and promoter methylation using q-PCR, data from TCGA and q-MSP respectively.Data presented in this manuscript has been submitted to the NCBI Geo database with the accession number GSE67994.