Swallowing in advanced oral cancers: A prospective observational study.

BACKGROUND: Advanced head and neck cancers are known to cause swallowing dysfunction due to anatomical and post-treatment changes. Literature is sparse on post-surgical and/or multi-modality therapy-associated swallowing function in advanced oral cancers. We conducted this study to longitudinally assess and compare the pre- and post-therapy swallowing dysfunction associated with locally advanced oral cancers. METHODS AND MATERIAL: A prospective observational longitudinal study was conducted at a tertiary cancer center from 2017 to 2018 including treatment-naive cT4a oral cancer patients (AJCC 7th edition). The assessment was done pre-surgery, post-surgery, and post-adjuvant setting as per the scales (Dysphagia score, Penetration aspiration scale, and Yale pharyngeal residue (vallecular and pyriform fossa). RESULTS: Of the 30 patients in the study, 47.4%, 47.4%, 52.6%, and 47.4% experienced deterioration of Dysphagia score, Penetration-Aspiration Scale (PAS), vallecula residue, and pyriform residue scores in the postoperative period. And 52.6%, 47.4%, 68.4%, and 57.9% had inferior dysphagia score, PAS, vallecula, and pyriform residue scores even 6 months after completion of adjuvant therapy. The dysphagia score correlated well with other objective assessment scores at different time points. CONCLUSION: Swallowing functions are significantly affected by surgery and adjuvant therapy and continue to be affected even 6 months after completion of treatment. Appropriate rehabilitation and intervention must be offered to patients to reduce this problem. Dysphagia scores can predict the swallowing status similar to other objective assessments.

Genome-Wide Analysis of Kidney Renal Cell Carcinoma: Exploring Differentially Expressed Genes for Diagnostic and Therapeutic Targets.

Kidney renal cell carcinoma (KIRC) is the most common type of renal cancer. Kidney malignancies have been ranked in the top 10 most frequently occurring cancers. KIRC is a prevalent malignancy with a poor prognosis. The disease has risen for the last 40 years, and robust biomarkers for KIRC are needed for precision/personalized medicine. In this bioinformatics study, we utilized genomic data of KIRC patients from The Cancer Genome Atlas for biomarker discovery. A total of 314 samples were used in this study. We identified many differentially expressed genes (DEGs) categorized as upregulated or downregulated. A protein-protein interaction network for the DEGs was then generated and analyzed using the Search Tool for the Retrieval of Interacting Genes plugin of Cytoscape. A set of 10 hub genes was selected based on the Maximum Clique Centrality score defined by the CytoHubba plugin. The elucidated set of genes, that is, CALCA, CRH, TH, CHAT, SLC18A3, FSHB, MYH6, CAV3, KCNA4, and GBX2, were then categorized as potential candidates to be explored as KIRC biomarkers. The survival analysis plots for each gene suggested that alterations in CHAT, CAV3, CRH, MYH6, SLC18A3, and FSHB resulted in decreased survival of KIRC patients. In all, the results suggest that genomic alterations in selected genes can be explored to inform biomarker discovery and for therapeutic predictions in KIRC.

Structure-based identification of potential inhibitors of ribosomal protein S6 kinase 1, targeting cancer therapy: a combined docking and molecular dynamics simulations approach.

Ribosomal protein S6 kinase 1 (S6K1), commonly known as P70-S6 kinase 1 (p70S6), is a key protein kinase involved in cellular signaling pathways that regulate cell growth, proliferation, and metabolism. Its significant role is reported in the PIK3/mTOR signaling pathway and is associated with various complex diseases, including diabetes, obesity, and different types of cancer. Due to its involvement in various physiological and pathological conditions, S6K1 is considered as an attractive target for drug design and discovery. One way to target S6K1 is by developing small molecule inhibitors that specifically bind to its ATP-binding site, preventing its activation and thus inhibiting downstream signaling pathways necessary for cell growth and survival. In this study, we have conducted a multitier virtual screening of a pool of natural compounds to identify potential S6K1 inhibitors. We performed molecular docking on IMPPAT 2.0 library and selected top hits based on their binding affinity, ligand efficiency, and specificity towards S6K1. The selected hits were further assessed based on different filters of drug-likeliness where two compounds (Hecogenin and Glabrene) were identified as potential leads for S6K1 inhibition. Both compounds showed appreciable affinity, ligand efficiency and specificity towards S6K1 binding pocket, drug-like properties, and stable protein-ligand complexes in molecular dynamics (MD) simulations. Finally, our study has suggested that Hecogenin and Glabrene can be potential S6K1 inhibitors which are presumably implicated in the therapeutic management of associated diseases such as diabetes, obesity, and varying types of cancer.Communicated by Ramaswamy H. Sarma.

PyPAn: An Automated Graphical User Interface for Protein Sequence and Structure Analyses.

BACKGROUND: Protein sequence and structure analyses have been essential components of bioinformatics and structural biology. They provide a deeper insight into the physicochemical properties, structure, and subsequent functions of a protein. Advanced computational approaches and bioinformatics utilities help solve several issues related to protein analysis. Still, beginners and non-professional may struggle when encountering a wide variety of computational tools and the sheer number of input parameter variables required by each tool. METHODS: We introduce a free-to-access graphical user interface (GUI) named PyPAn 'Python-based Protein Analysis' for varieties of protein sequence/structure analyses. PyPAn serves as a universal platform to analyze protein sequences, structure, and their properties. PyPAn facilitates onboard analysis of each task in just a single click. It can be used to calculate the physicochemical properties, including instability index and molar extinction coefficient, for a protein. PyPAn is one of the few computational tools that allow users to generate a Ramachandran plot and calculate solvent accessibility and the radius of gyration (Rg) of proteins at once. In addition, it can refine the protein model along with computation and minimization of its energy. RESULTS: PyPAn can generate a recommendation for an appropriate structure modelling method to employ for a query protein sequence. PyPAn is one of the few, if not the only, Python-based computational GUI tools with an array of options for the user to employ as they see fit. CONCLUSION: PyPAn aims to unify many successful academically significant proteomic applications and is freely available for academic and industrial research uses at https://hassanlab.org/pypan.

Genomic Variations in the Structural Proteins of SARS-CoV-2 and Their Deleterious Impact on Pathogenesis: A Comparative Genomics Approach.

A continual rise in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection causing coronavirus disease (COVID-19) has become a global threat. The main problem comes when SARS-CoV-2 gets mutated with the rising infection and becomes more lethal for humankind than ever. Mutations in the structural proteins of SARS-CoV-2, i.e., the spike surface glycoprotein (S), envelope (E), membrane (M) and nucleocapsid (N), and replication machinery enzymes, i.e., main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) creating more complexities towards pathogenesis and the available COVID-19 therapeutic strategies. This study analyzes how a minimal variation in these enzymes, especially in S protein at the genomic/proteomic level, affects pathogenesis. The structural variations are discussed in light of the failure of small molecule development in COVID-19 therapeutic strategies. We have performed in-depth sequence- and structure-based analyses of these proteins to get deeper insights into the mechanism of pathogenesis, structure-function relationships, and development of modern therapeutic approaches. Structural and functional consequences of the selected mutations on these proteins and their association with SARS-CoV-2 virulency and human health are discussed in detail in the light of our comparative genomics analysis.

InstaDock: A single-click graphical user interface for molecular docking-based virtual high-throughput screening.

Exploring protein-ligand interactions is a subject of immense interest, as it provides deeper insights into molecular recognition, mechanism of interaction and subsequent functions. Predicting an accurate model for a protein-ligand interaction is a challenging task. Molecular docking is a computational method used for predicting the preferred orientation, binding conformations and the binding affinity of a ligand to a macromolecular target, especially protein. It has been applied in 'virtual high-throughput screening' of chemical libraries containing millions of compounds to find potential leads in drug design and discovery. Here, we have developed InstaDock, a free and open access Graphical User Interface (GUI) program that performs molecular docking and high-throughput virtual screening efficiently. InstaDock is a single-click GUI that uses QuickVina-W, a modified version of AutoDock Vina for docking calculations, made especially for the convenience of non-bioinformaticians and for people who are not experts in using computers. InstaDock facilitates onboard analysis of docking and visual results in just a single click. To sum up, InstaDock is the easiest and more interactive interface than ever existing GUIs for molecular docking and high-throughput virtual screening. InstaDock is freely available for academic and industrial research purposes via https://hassanlab.org/instadock.

Poorly differentiated thyroid carcinoma (PDTC) characteristics and the efficacy of radioactive iodine (RAI) therapy as an adjuvant treatment in a tertiary cancer care center.

BACKGROUND: Poorly differentiated thyroid cancer (PDTC) is biologically more aggressive. Surgery remains the mainstay of treatment. The utility of radioactive iodine (RAI) after surgery is unclear. METHODS: In this retrospective study, patients treated between Jan 2012 and Dec 2017 were included. The demographic, clinical and treatment-related details, including RAI ablation, were recorded and their survival analyzed. RESULTS: Thirty-five patients fulfilled the eligibility criteria. Majority was treatment naïve at presentation. All patients underwent surgery followed by RAI ablation, with a cumulative median dose of 220 mCi (range 40-1140). Sixteen patients received more than one radioiodine treatment for distant metastases. Incomplete resection, age > 45 years and the presence of distant metastasis influenced survival the most. The 3-year PFS of patients with PDTC was 69%. CONCLUSION: All patients in our series showed uptake and responded to treatment. Further use of molecular markers and functional molecular imaging would better our understanding of this entity.

Outcome of patients following neo-adjuvant chemotherapy for unresectable cervical nodes in head and neck squamous cell carcinomas.

BACKGROUND: This study was undertaken to assess the effects of neo-adjuvant chemotherapy (NACT) on patients with head and neck squamous cell carcinoma (HNSCC) having advanced unresectable cervical nodal metastasis. METHODOLOGY: A retrospective cohort study was conducted to assess the response of unresectable nodes to NACT in a pragmatic manner. Patients were grouped according to the response noted and the treatment offered after chemotherapy. The median survival amongst the patients in these groups was compared. RESULTS: The study included 51 patients. Oral cavity was the commonest site (67.2%). Favourable nodal response was seen in 64.7% of the patients. Up to 87.9% of the nodal responders were amenable to curative intent therapy. The overall survival of patients undergoing surgery, definitive chemoradiotherapy, palliative chemotherapy and palliative radiotherapy was 24, 13, 10 and 9 months, respectively. CONCLUSION: NACT may be utilized in HNSCC with advanced inoperable nodal disease to make them amenable to definitive therapy.

Depth of invasion, size and number of metastatic nodes predicts extracapsular spread in early oral cancers with occult metastases.

OBJECTIVE: Presence of extracapsular spread (ECS) significantly decreases survival in oral cancer patients. Considering its prognostic impact, we have studied the incidence and factors predicting ECS in clinically node negative early oral cancers. MATERIALS AND METHODS: We performed a retrospective chart review of 354 treatment naïve clinically node negative early oral cancer patients operated between 2012 and 2014. Chi-square test and logistic regression were used for identifying predictors of ECS, while cox-regression test was used for survival analysis. RESULTS: The incidence of occult nodal metastasis was 28.5% (101/354). Among them, ECS was seen in 15.3%(54/354) patients. The incidence of ECS in T1 and T2 lesion was 13.4% (21/157) and 16.8% (33/197), respectively. The overall incidence of ECS was 48% and 29% in lymph nodes smaller than 10 mm and 5 mm respectively. We found that tumor depth of invasion (>5 mm; p-0.027) and node (metastatic) size >15 mm (p-0.018) were significant predictors of ECS. p N2b disease was seen in 41/354 (11.6%) of which 31/354 (8.7%) had ECS, i.e. 75.6% of pN2b patients been ECS positive (p-0.000). The 3-year OS of patients without nodal metastasis, nodal metastasis without ECS and nodal metastasis with ECS was 88.4%, 66.9% and 59.2% (p-0.000) respectively. CONCLUSION: A significant number of patients with metastatic nodal size less than 1 cm have ECS which suggests aggressive behavior of the primary tumor. Thus, elective neck dissection is the only way of detecting ECS in these patients which may warrant treatment intensification.