SInC: An accurate and fast error-model based simulator for SNPs, Indels and CNVs coupled with a read generator for short-read sequence data

We report SInC (SNV, Indel and CNV) simulator and read generator, an open-source tool capable of simulating biological variants taking into account a platform-specific error model. SInC is capable of simulating and generating single- and paired-end reads with user-defined insert size with high efficiency compared to the other existing tools. SInC, due to its multi-threaded capability during read generation, has a low time footprint. SInC is currently optimised to work in limited infrastructure setup and can efficiently exploit the commonly used quad-core desktop architecture to simulate short sequence reads with deep coverage for large genomes. Sinc can be downloaded from https://sourceforge.net/projects/sincsimulator/

Functional genomics screen with pooled shRNA library and gene expression profiling with extracts of Azadirachta indica identify potential pathways for therapeutic targets in head and neck squamous cell carcinoma

Tumor suppression by the extracts of Azadirachta indica (neem) works via anti-proliferation, cell cycle arrest, and apoptosis, demonstrated previously using cancer cell lines and live animal models. However, very little is known about the molecular targets and pathways that neem extracts and their associated compounds act through. Here, we address this using a genome-wide functional pooled shRNA screen on head and neck squamous cell carcinoma cell lines treated with crude neem leaf extracts, known for their anti-tumorigenic activity. We analyzed differences in global clonal sizes of the shRNA-infected cells cultured under no treatment and treatment with neem leaf extract conditions, assayed using next-generation sequencing. We found 225 genes affected the cancer cell growth in the shRNA-infected cells treated with neem extract. Pathway enrichment analyses of whole-genome gene expression data from cells temporally treated with neem extract revealed important roles played by the TGF-β pathway and HSF-1-related gene network. Our results indicate that neem extract affects various important molecular signaling pathways in head and neck cancer cells, some of which may be therapeutic targets for this devastating tumor

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

Selection of the right reference gene(s) is crucial in the analysis and interpretation of gene expression data. The aim of the present study was to discover and validate a minimal set of internal control genes in head and neck tumor studies. We analyzed data from multiple sources (in house whole-genome gene expression microarrays, previously published quantitative real-time PCR (qPCR) data and RNA-seq data from TCGA) to come up with a list of 18 genes (discovery set) that had the lowest variance, a high level of expression across tumors, and their matched normal samples. The 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. Finally, we validated their expression using qPCR in an additional set of tumor:matched normal samples that resulted in five genes (RPL30, RPL27, PSMC5, MTCH1, and OAZ1), out of which RPL30 and RPL27 were most stable and were abundantly expressed across the tissues. Our data suggest that RPL30 or RPL27 in combination with either PSMC5 or MTCH1 or OAZ1 can be used as a minimal set of control genes in head and neck tumor gene expression studies

Customisation of the Exome Data Analysis Pipeline Using a Combinatorial Approach

The advent of next generation sequencing (NGS) technologies have revolutionised the way biologists produce, analyse and interpret data. Although NGS platforms provide a cost-effective way to discover genome-wide variants from a single experiment, variants discovered by NGS need follow up validation due to the high error rates associated with various sequencing chemistries. Recently, whole exome sequencing has been proposed as an affordable option compared to whole genome runs but it still requires follow up validation of all the novel exomic variants. Customarily, a consensus approach is used to overcome the systematic errors inherent to the sequencing technology, alignment and post alignment variant detection algorithms. However, the aforementioned approach warrants the use of multiple sequencing chemistry, multiple alignment tools, multiple variant callers which may not be viable in terms of time and money for individual investigators with limited informatics know-how. Biologists often lack the requisite training to deal with the huge amount of data produced by NGS runs and face difficulty in choosing from the list of freely available analytical tools for NGS data analysis. Hence, there is a need to customise the NGS data analysis pipeline to preferentially retain true variants by minimising the incidence of false positives and make the choice of right analytical tools easier. To this end, we have sampled different freely available tools used at the alignment and post alignment stage suggesting the use of the most suitable combination determined by a simple framework of pre-existing metrics to create significant datasets

Artificial intelligence and real-world data for drug and food safety - A regulatory science perspective

In 2013, the Global Coalition for Regulatory Science Research (GCRSR) was established with members from over ten countries (www.gcrsr.net). One of the main objectives of GCRSR is to facilitate communication among global regulators on the rise of new technologies with regulatory applications through the annual conference Global Summit on Regulatory Science (GSRS). The 11th annual GSRS conference (GSRS21) focused on "Regulatory Sciences for Food/Drug Safety with Real-World Data (RWD) and Artificial Intelligence (AI)." The conference discussed current advancements in both AI and RWD approaches with a specific emphasis on how they impact regulatory sciences and how regulatory agencies across the globe are pursuing the adaptation and oversight of these technologies. There were presentations from Brazil, Canada, India, Italy, Japan, Germany, Switzerland, Singapore, the United Kingdom, and the United States. These presentations highlighted how various agencies are moving forward with these technologies by either improving the agencies' operation and/or preparing regulatory mechanisms to approve the products containing these innovations. To increase the content and discussion, the GSRS21 hosted two debate sessions on the question of "Is Regulatory Science Ready for AI?" and a workshop to showcase the analytical data tools that global regulatory agencies have been using and/or plan to apply to regulatory science. Several key topics were highlighted and discussed during the conference, such as the capabilities of AI and RWD to assist regulatory science policies for drug and food safety, the readiness of AI and data science to provide solutions for regulatory science. Discussions highlighted the need for a constant effort to evaluate emerging technologies for fit-for-purpose regulatory applications. The annual GSRS conferences offer a unique platform to facilitate discussion and collaboration across regulatory agencies, modernizing regulatory approaches, and harmonizing efforts

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Survival

p { margin-bottom: 0.25cm; direction: ltr; line-height: 120%; text-align: left; }a:link { } <p> Oral tongue squamous cell carcinomas (OTSCC) are a homogenous group of head and neck tumors characterized with aggressive behavior among younger age group of patients. In this report, we have analysed genetic, transcriptomic, and epigenetic variants across genomes of 50 oral tongue primary tumors along with the human papilloma virus infection to find significant association with disease free survival. Our data identified somatic mutations in the genes <i>NOTCH2</i>, <i>TP53</i> and LOH in <i>11p</i>, and DNA methylation in <i>SLC38A8</i> to be significantly associated with better disease free survival in HPV positive patients (<i>P</i> = 0.000175), but not in HPV negative patients (<i>P</i> = 0.974). We validated the latter using patients without HPV infection from TCGA (<i>P</i> = 0.679, N = 15 for TCGA_OralTongue; <i>P</i> = 0.262, N = 43 for all TCGA_HNSCC patients).</p

A Minimal DNA Methylation Signature in Oral Tongue Squamous Cell Carcinoma Links Altered Methylation with Tumor Attributes.

<h3>Abstract</h3><p>Oral tongue squamous cell carcinomas (OTSCCs) are a homogenous group of aggressive tumors in the head and neck region that spread early to lymph nodes and have a higher incidence of regional failure. Additionally, there is a rising incidence of oral tongue cancer in younger populations. Studies on functional DNA methylation changes linked with altered gene expression are critical for understanding the mechanisms underlying tumor development and metastasis. Such studies also provide important insight into biomarkers linked with viral infection, tumor metastasis and patient survival in OTSCC. Therefore, we performed genome-wide methylation analysis of tumors (N = 52) and correlated altered methylation with differential gene expression. The minimal tumor-specific DNA 5-methycytosine (5mc) signature identified genes near 16 different differentially methylated regions (DMRs), which were validated using genomic data from The Cancer Genome Atlas (TCGA) cohort. In our cohort, hypermethylation of miR-10b was significantly associated with the differential expression of its target genes NR4A3 and BCL2L11 (P = 0.0125 and P = 0.014 respectively), which was inversely correlated with disease-free survival (P = 9E-15 and P = 2E-15 respectively) in patients. Finally, differential methylation in FUT3, TRIM5, TSPAN7, MAP3K8, RPS6KA2, SLC9A9 and NPAS3 genes was found to be predictive of certain clinical and epidemiological parameters.</p><b>IMPLICATIONS:</b><br>This study reveals a functional minimal methylation profile in oral tongue tumors with associated risk habits, clinical and epidemiological outcomes. In addition, NR4A3 down-regulation and correlation with patient survival suggests a potential target for therapeutic intervention in oral tongue tumors. Data from the current study are deposited in the NCBI Geo database (Accession number GSE75540)