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Background: HPV status in a subset of HNSCC is linked with distinct treatment outcomes. Present investigation aims to elucidate the distinct clinicopathological features of HPV-positive and HPV-negative HNSCC and investigate their association with the HNSCC patient survival. Materials and methods: The total RNA of exosomes from HPV-positive (93VU147T) and HPV-negative (OCT-1) HNSCC cells was isolated, and the transcripts were estimated using Illumina HiSeq X. The expression of altered transcripts and their clinical relevance were further analyzed using publicly available cancer transcriptome data from The Cancer Genome Atlas (TCGA). Results: Transcriptomic analyses identified 3785 differentially exported transcripts (DETs) in HPV-positive exosomes compared to HPV-negative exosomes. DETs that regulate the protein machinery, cellular redox potential, and various neurological disorder-related pathways were over-represented in HPV-positive exosomes. TCGA database revealed the clinical relevance of altered transcripts. Among commonly exported abundant transcripts, SGK1 and MAD1L1 showed high expression, which has been correlated with poor survival in HNSCC patients. In the top 20 DETs of HPV-negative exosomes, high expression of FADS3, SGK3, and TESK2 correlated with poor survival of the HNSCC patients in the TCGA database. Conclusion: Overall, our study demonstrates that HPV-positive and HPV-negative cells' exosomes carried differential transcripts cargo that may be related to pathways associated with neurological disorders. Additionally, the altered transcripts identified have clinical relevance, correlating with patient survival in HNSCC, thereby highlighting their potential as biomarkers and as therapeutic targets. [ABSTRACT FROM AUTHOR]

Abstract Background HPV status in a subset of HNSCC is linked with distinct treatment outcomes. Present investigation aims to elucidate the distinct clinicopathological features of HPV-positive and HPV-negative HNSCC and investigate their association with the HNSCC patient survival. Materials and methods The total RNA of exosomes from HPV-positive (93VU147T) and HPV-negative (OCT-1) HNSCC cells was isolated, and the transcripts were estimated using Illumina HiSeq X. The expression of altered transcripts and their clinical relevance were further analyzed using publicly available cancer transcriptome data from The Cancer Genome Atlas (TCGA). Results Transcriptomic analyses identified 3785 differentially exported transcripts (DETs) in HPV-positive exosomes compared to HPV-negative exosomes. DETs that regulate the protein machinery, cellular redox potential, and various neurological disorder-related pathways were over-represented in HPV-positive exosomes. TCGA database revealed the clinical relevance of altered transcripts. Among commonly exported abundant transcripts, SGK1 and MAD1L1 showed high expression, which has been correlated with poor survival in HNSCC patients. In the top 20 DETs of HPV-negative exosomes, high expression of FADS3, SGK3, and TESK2 correlated with poor survival of the HNSCC patients in the TCGA database. Conclusion Overall, our study demonstrates that HPV-positive and HPV-negative cells’ exosomes carried differential transcripts cargo that may be related to pathways associated with neurological disorders. Additionally, the altered transcripts identified have clinical relevance, correlating with patient survival in HNSCC, thereby highlighting their potential as biomarkers and as therapeutic targets.

Simple Summary: The early detection of oral squamous cell carcinoma (OSCC) is crucial because the prognosis is significantly better when diagnosed in its initial stages as opposed to advanced ones. We investigate the use of clinical photographic images captured by common smartphones for the automatic detection of OSCC cases and the identification of suspicious cases necessitating an urgent biopsy. We study a cohort of 1470 patients and examined various deep learning methods for the early detection of OSCC and suspicious cases. Our results demonstrate the efficacy of these methods in predicting both tasks, providing a comprehensive understanding of the patient's condition. Moreover, we demonstrate that the models exhibit enhanced accuracy in differentiating specific patient groups, particularly those with lesions in the lingual mucosa, floor of the mouth, or posterior tongue. These results underscore the potential of leveraging clinical photographic images for the timely and accurate identification of OSCC, with a particular emphasis on specific anatomical locations. Oral squamous cell carcinoma (OSCC) accounts for more than 90% of oral malignancies. Despite numerous advancements in understanding its biology, the mean five-year survival rate of OSCC is still very poor at about 50%, with even lower rates when the disease is detected at later stages. We investigate the use of clinical photographic images taken by common smartphones for the automated detection of OSCC cases and for the identification of suspicious cases mimicking cancer that require an urgent biopsy. We perform a retrospective study on a cohort of 1470 patients drawn from both hospital records and online academic sources. We examine various deep learning methods for the early detection of OSCC cases as well as for the detection of suspicious cases. Our results demonstrate the efficacy of these methods in both tasks, providing a comprehensive understanding of the patient's condition. When evaluated on holdout data, the model to predict OSCC achieved an AUC of 0.96 (CI: 0.91, 0.98), with a sensitivity of 0.91 and specificity of 0.81. When the data are stratified based on lesion location, we find that our models can provide enhanced accuracy (AUC 1.00) in differentiating specific groups of patients that have lesions in the lingual mucosa, floor of mouth, or posterior tongue. These results underscore the potential of leveraging clinical photos for the timely and accurate identification of OSCC. [ABSTRACT FROM AUTHOR]

Background: Head and neck cancers are major public health problems, which can be detected much earlier by various screening methods. Head and neck cancers in India accounted for 30% of all cancers in males except Dibrugarh in Assam (49.6%). Since, no much study have been done on Head and Neck Cancers (HNCs) from this part of the country, this study was conducted to analyse the characteristics and trends of the different HNCs in a Tertiary Care Centre of Arunachal Pradesh, India. Materials and Methods: This is a retrospective observational study conducted in Tomo Riba Institute of Health and Medical Sciences, Naharlagun after obtaining institutional IEC & SRC clearance. Total 536 patients (370 males and 166 female) of head and neck (HNC) were reported in the Population based Cancer Registry (PBCR). The database collected from the PBCR (consists of 8 districts of Arunachal Pradesh) web portal included demographic and clinicopathological information, including age, sex, year of diagnosis, site and types of cancer, histopathological appearance and survival time. Patients were classified on the basis of primary histology morphology (PHM) into squamous cell carcinoma, and others. From mortality reports we calculated the median survival of the patients. Results: Our study showed that the male: female ratio was 2.2:1. Out of the 8 districts of Arunachal Pradesh, Papumpare district reported the highest incidence (44%) and mortality (50%) due to HNC. The median days of survival were 283days or 9.43 months. The commonest age group showing the highest incidence of HNC was the elderly from 61 years and above with a total of 121 cases (22.5%) followed by the age group from 56-60 years (17.7%). Esophageal cancer was the commonest cancer among these two age groups. Squamous cell carcinoma also showed the highest mortality contributing 47% of all the deaths registered. Conclusion: Esophageal cancer was the commonest cancer among these two age groups in our study. The burden of HNC is high, especially among the male population. Further research and policies on improving the uptake of available cancer screening are required for better cancer control and prevention. [ABSTRACT FROM AUTHOR]