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Suresh, A.

Publications and source records attributed to Suresh, A..

28 records · Page 2Linked to original sources
bioRxiv2022

Establishment and characterization of novel autologous pair primary cultures from two Indian non-habitual tongue carcinoma patients

Oral tongue squamous cell carcinoma (OTSCC) is one of the major causes of fatality in India owing to very high percentages of patients with smoking and chewing habits. Being highly heterogeneous in nature, every patient poses a different challenge clinically. To better understand disease progression, knowledge of cross talk between tumor stroma and the tumor cells becomes indispensable. Patient-derived in vitro cell line models are helpful to understand the complexity of diseases. However, they have very low efficiency of establishment from the tumor samples, especially the cancer associated fibroblasts (CAFs). In the present study, two novel autologous pairs have been immortalized spontaneously from non-habitual, HPV-positive patients, presented with tongue squamous cell carcinoma. The epithelial and fibroblast primary lines had typical polygonal and spindle shaped morphology, respectively. Positive staining with Pan-cytokeratin (PanCK) and Fibroblast Specific Protein (FSP-1) further confirmed their epithelial and fibroblast origin. Unique Short Tandem Repeat (STR) profile of the cultures confirmed their novelty, while the similarity of the STR profiles between the epithelial and fibroblast cells from the same patient, confirmed their autologous nature. DNA analysis revealed aneuploidy of the established cultures. Increase in the tumorigenic potential of the established epithelial cultures upon treatment with CAF-conditioned medium proved the "CAF-ness" of the established fibroblast cells. The established cultures are the first of their kind which would serve as an useful platform in understanding the cross talk between tumor-stroma and tumor, along with studying tongue cancer progression.

cancer biology↗
bioRxiv2020

Effect of Variations in the Conserved Residues E371 and S359 on the Structural Dynamics of Protein Z Dependent Protease Inhibitor (ZPI): A Molecular Dynamic Simulation Study

Protein Z (PZ) dependent protease inhibitor (ZPI) is a natural anticoagulant inhibiting blood coagulation proteases fXa and fXIa. Despite being a member of the serpin superfamily, it possesses unique structural features such as activation by PZ that regulate its inhibitory function. It is well known that effecient protease inhibition by serpins is dependent on the dynamics of its reactive center loop (RCL). In order to understand the RCL dynamics of ZPI, we performed Molecular Dynamics (MD) simulation on ZPI and its E371 and S359 variants located at important conserved functional sites. Unexpectedly, the RCL of E371 variants, such as E371K, E371R, and E371Q, were shown to be very stable due to compensatory interactions at the proximal end of RCL. Interestingly, RCL flexibility was shown to be enhanced in the double mutant K318-E371 due to the repulsive effect of increased negative charge on top of the breach region. Principal component analysis (PCA) coupled with residue wise interaction network (RIN) revealed correlated motion between the RCL and the PZ binding regions in the WT. Whereas the analysis revealed a loss of regulation in correlated motion between RCL and PZ binding hotspot Tyr240 in the double mutant. Additionally, the S359F and S359I mutations also resulted in increased RCL flexibility owing to the disruption of stabilizing hydrogen bonding interaction at the N terminal end of S5A. Thus, the current study proposes that the overall stabilizing interactions of S5A is a major regulator of proper loop movement of ZPI for protease inhibition and therefore its activity. The results would be beneficial to engineer activity compromised ZPI mutants as a prophylactic agent for the treatment of hemophilia.

biophysics↗
bioRxiv2020

Three Essential Resources to Improve Differential Scanning Fluorimetry (DSF) Experiments

Differential Scanning Fluorimetry (DSF) is a method that enables rapid determination of a proteins apparent melting temperature (Tma). Owing to its high throughput, DSF has found widespread application in fields ranging from structural biology to chemical screening. Yet DSF has developed two opposing reputations: one as an indispensable laboratory tool to probe protein stability, another as a frustrating platform that often fails. Here, we aim to reconcile these disparate reputations and help users perform more successful DSF experiments with three resources: an updated, interactive theoretical framework, practical tips, and online data analysis. We anticipate that these resources, made available online at DSFworld (https://gestwickilab.shinyapps.io/dsfworld/), will broaden the utility of DSF.

biochemistry↗
bioRxiv2020

EZcalcium: Open Source Toolbox for Analysis of Calcium Imaging Data

Fluorescence calcium imaging using a range of microscopy approaches, such as 2-photon excitation or head-mounted miniscopes, is one of the preferred methods to record neuronal activity and glial signals in various experimental settings, including acute brain slices, brain organoids, and behaving animals. Because changes in the fluorescence intensity of genetically encoded or chemical calcium indicators correlate with action potential firing in neurons, data analysis is based on inferring such spiking from changes in pixel intensity values across time within different regions of interest. However, the algorithms necessary to extract biologically relevant information from these fluorescent signals are complex and require significant expertise in programming to develop robust analysis pipelines. For decades, the only way to perform these analyses was for individual laboratories to write their own custom code. These routines were typically not well annotated and lacked intuitive graphical user interfaces (GUIs), which made it difficult for scientists in other laboratories to adopt them. Although the panorama is changing with recent tools like CaImAn, Suite2P and others, there is still a barrier for many laboratories to adopt these packages, especially for potential users without sophisticated programming skills. As 2-photon microscopes are becoming increasingly affordable, the bottleneck is no longer the hardware, but the software used to analyze the calcium data in an optimal manner and consistently across different groups. We addressed this unmet need by incorporating recent software solutions for motion correction, segmentation, signal extraction and deconvolution of calcium imaging data into an open-source, easy to use, GUI-based, intuitive and automated data analysis software, which we named EZcalcium.

neuroscience↗
bioRxiv2019

PARP1 as a biomarker for early detection and intraoperative tumor delineation in epithelial cancers - first-in-human results

Major determining factors for survival of patients with oral, oropharyngeal, and esophageal cancer are early detection, the quality of surgical margins, and the contemporaneous detection of residual tumor. Intuitively, the exposed location at the epithelial surface qualifies these tumor types for utilization of visual aids to assist in discriminating tumor from healthy surrounding tissue. Here, we explored the DNA repair enzyme PARP1 as imaging biomarker and conducted optical imaging in animal models, human tissues and as part of a first-in-human clinical trial. Our data suggests that PARP1 is a quantitative biomarker for oral, oropharyngeal, and esophageal cancer and can be visualized with PARPi-FL, a fluorescently labeled small molecule contrast agent for topical or intravenous delivery. We show feasibility of PARPi-FL-assisted tumor detection in esophageal cancer, oropharyngeal and oral cancer. We developed a contemporaneous PARPi-FL topical staining protocol for human biospecimens. Using fresh oral cancer tissues within 25 min of biopsy, tumor and margin samples were correctly identified with >95% sensitivity and specificity without terminal processing. PARPi-FL imaging can be integrated into clinical workflows, potentially providing instantaneous assessment of the presence or absence of microscopic disease at the surgical margin. Additionally, we showed first-in-human PARPi-FL imaging in oral cancer. In aggregate, our preclinical and clinical studies have the unifying goal of verifying the clinical value of PARPi-FL-based optical imaging for early detection and intraoperative margin assignment.

clinical trials↗
bioRxiv2019

lncRNAKB: A comprehensive knowledgebase of long non-coding RNAs

We have assembled a comprehensive long non-coding RNA knowledgebase (lncRNAKB) of 77,199 annotated human lncRNAs (224,286 transcripts) by methodically integrating widely used lncRNAs resources. To facilitate functional characterization of lncRNAs, we employed Genotype-Tissue Expression (GTEx) project to provide tissue-specific gene expression profiles of lncRNAs in 31 solid organ tissues. Additional information includes network analysis to identify co-expressed gene modules to potentially delineate lncRNA function. Tissue-specificity, phylogenetic conservation scores and coding potential for lncRNAs are included. Finally, using whole genome sequencing data from GTEx, expression quantitative trait loci (cis-eQTL) regulated lncRNAs were calculated in all tissues. lncRNAKB is available at http://www.lncrnakb.org.

bioinformatics↗
bioRxiv2019

IKAP - Identifying K mAjor cell Population groups in single-cell RNA-seq analysis

In single-cell RNA-seq analysis, clustering cells into groups and differentiating cell groups by marker genes are two separate steps for investigating cell identity. However, results in clustering greatly affect the ability to differentiate between cell groups. We develop IKAP - an algorithm identifying major cell groups that improves differentiating by tuning parameters for clustering. Using multiple datasets, we demonstrate IKAP improves identification of major cell types and facilitates cell ontology curation.

bioinformatics↗
bioRxiv2017

A minimal set of internal control genes for gene expression studies in head and neck squamous cell carcinoma

BackgroundSelection of the right reference gene(s) is crucial in the analysis and interpretation of gene expression data. In head and neck cancer, studies evaluating the efficacy of internal reference genes are rare. Here, we present data for a minimal set of candidates as internal control genes for gene expression studies in head and neck cancer.\n\nMethodsWe analyzed data from multiple sources (in house whole-genome gene expression microarrays, n=21; TCGA RNA-seq, n=42, and published gene expression studies in head and neck tumors from literature) to come up with a set of genes (discovery set) for their stable expression across tumor and normal tissues. We then performed independent validation of their expression using qPCR in 14 tumor:normal pairs. Genes in the discovery set were ranked using four different algorithms (BestKeeper, geNorm, NormFinder, and comparative delta Ct) and a web-based comparative tool, RefFinder, for their stability and variance in expression across tissues.\n\nResultsOur analyses resulted in 18 genes (discovery set) that had lowest variance and high level of expression across tumor and normal samples. Independent experimental validation and analyses with multiple tools resulted in top ranked five genes (RPL30, RPL27, PSMC5, OAZ1 and MTCH1) out of which, RPL30 (60S ribosomal protein L30) and RPL27 (60S ribosomal protein L27), performed best and were abundantly expressed across tumor and normal tissues.\n\nConclusionsRPL30 and RPL27 are stably expressed in HNSCC and should be used as internal control genes in gene expression in head and neck tumors studies.

cancer biology↗
bioRxiv2016

High-risk human papillomavirus in oral cavity squamous cell carcinoma

PurposeThe prevalence of human papillomavirus (HPV) in oral cavity squamous cell carcinoma (OSCC) varies significantly based on assay sensitivity and patient geography. Accurate detection is essential to understand the role of HPV in disease prognosis and management of patients with OSCC.\n\nMethodsWe generated and integrated data from multiple analytes (HPV DNA, HPV RNA, and p16), assays (immunohistochemistry, PCR, qPCR and digital PCR) and molecular changes (somatic mutations and DNA methylation) from 153 OSCC patients to correlate p16 expression, HPV DNA, and HPV RNA with HPV incidence and patient survival.\n\nResultsHigh prevalence (33-58%) of HPV16/18 DNA did not correlate with the presence of transcriptionally active viral genomes (15%) in tumors. Eighteen percent of the tumors were p16 positive. and only 6% were both HPV DNA and RNA positive. Most tumors with relatively high-copy HPV DNA, and/or HPV RNA, but not with HPV DNA alone (irrespective of copy number), were wild-type for TP53 and CASP8 genes. In our study, p16 protein, HPV DNA and HPV RNA, either alone or in combinations, did not correlate with patient survival. Nine HPV-associated genes stratified the virus +ve from the -ve tumor group with high confidence (p<0.008) when HPV DNA copy number and/or HPV RNA were considered to define HPV positivity and not HPV DNA alone irrespective of their copy number (p < 0.2).\n\nConclusionsIn OSCC, the presence of both HPV RNA and p16 are rare. HPV DNA alone is not an accurate measure of HPV positivity and therefore not informative. Moreover, HPV DNA, RNA or p16 dont correlate with outcome.

cancer biology↗