Quantification of miRNAs and Their Networks in the light of Integral Value Transformations

MicroRNAs (miRNAs) which are on average only 21-25 nucleotides long are key post-transcriptional regulators of gene expression in metazoans and plants. A proper quantitative understanding of miRNAs is required to comprehend their structures, functions, evolutions etc. In this paper, the nucleotide strings of miRNAs of three organisms namely Homo sapiens (hsa), Macaca mulatta (mml) and Pan troglodytes (ptr) have been quantified and classified based on some characterizing features. A network has been built up among the miRNAs for these three organisms through a class of discrete transformations namely Integral Value Transformations (IVTs), proposed by Sk. S. Hassan et al [1, 2]. Through this study we have been able to nullify or justify one given nucleotide string as a miRNA. This study will help us to recognize a given nucleotide string as a probable miRNA, without the requirement of any conventional biological experiment. This method can be amalgamated with the existing analysis pipelines, for small RNA sequencing data (designed for finding novel miRNA). This method would provide more confidence and would make the current analysis pipeline more efficient in predicting the probable candidates of miRNA for biological validation and filter out the improbable candidates

ORAL SUFFERING AND ANTIMICROBIAL SUSCEPTIBILITY OF

Staphylococcus aureus is a well recognized pathogen associated with a variety of clinical syndrome. The role of Staph aureus in some types of oral disease may be more important than previously recognized. The present study has been designed to investigate the prevalence of Staphylococcus aureus, MRSA and their rate of resistance to different anti staphylococcal antibiotics. For this study, Gurunanak Institute of Dental Science & Research (Kolkata), selected patients who were suffering from Staphylococcus aureus oral infection. Isolated Staphylococcus aureus was tested for Oxacillin (1 mcg) sensitivity and their antibiotic susceptibility was investigated by using eighteen antibiotics followed by Disk diffusion technique following CLSI method. Out of the 223 specimens collected, 109 (48.9%) were isolated. All the 109 (48.9%) specimens were studied in detail. 5.5 % of the isolates were shown to be methicillin resistant Staph. aureus (MRSA). Percentage (%) of resistance in commonly used oral antibiotics are ampicillin 98.1%, amoxycillin/clavulanic acid 73.3%, amoxycillin 45.0%, ofloxacin 48.6 % and ciprofloxacin 41.2%. The MRSA isolates showed multiple drug resistance (MDR), except linezolid and imipenem. In line with more recent surveys, this retrospective study suggests tha

Analysis of the whole transcriptome from gingivo-buccal squamous cell carcinoma reveals deregulated immune landscape and suggests targets for immunotherapy

<div><p>Background</p><p>Gingivo-buccal squamous cell carcinoma (GBSCC) is one of the most common oral cavity cancers in India with less than 50% patients surviving past 5 years. Here, we report a whole transcriptome profile on a batch of GBSCC tumours with diverse tobacco usage habits. The study provides an entire landscape of altered expression with an emphasis on searching for targets with therapeutic potential.</p><p>Methods</p><p>Whole transcriptomes of 12 GBSCC tumours and adjacent normal tissues were sequenced and analysed to explore differential expression of genes. Expression changes were further compared with those in TCGA head and neck cohort (n = 263) data base and validated in an independent set of 10GBSCC samples.</p><p>Results</p><p>Differentially expressed genes (n = 2176) were used to cluster the patients based on their tobacco habits, resulting in 3 subgroups. Immune response was observed to be significantly aberrant, along with cell adhesion and lipid metabolism processes. Different modes of immune evasion were seen across 12 tumours with up-regulation or consistent expression of <i>CD47</i>, unlike other immune evasion genes such as <i>PDL1</i>, <i>FUT4</i>, <i>CTLA4</i> and <i>BTLA</i> which were downregulated in a few samples. Variation in infiltrating immune cell signatures across tumours also indicates heterogeneity in immune evasion strategies. A few actionable genes such as <i>ITGA4</i>, <i>TGFB1</i> and <i>PTGS1/COX1</i> were over expressed in most samples.</p><p>Conclusion</p><p>This study found expression deregulation of key immune evasion genes, such as <i>CD47</i> and <i>PDL1</i>, and reasserts their potential as effective immunotherapeutic targets for GBSCC, which requires further clinical studies. Present findings reiterate the idea of using transcriptome profiling to guide precision therapeutic strategies.</p></div

Immune response alterations in tumor compared to normal tissues.

<p>(A) Heatmap shows diverse expression levels (log fold change of FPKM values) of immune evasion genes. Orange values in color bar shows up regulation while values in blue show down regulation. The panel below shows proliferation scores per samples with green color intensity indicating higher proliferation score and numbers indicates % CCP score. The right-side panel indicates fold change values (FPKM) in TCGA HNSCC cohort (n = 263) for each gene. In case of TCGA HNCC tissues, Green color denotes downregulation while red color shows upregulation in the right-side panel. (B) The barplot shows how relative composition of immune cells is altered across 12 pairs of tumor compared to its control tissues. Plot was derived from the <i>CIBERSORT</i> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0183606#pone.0183606.ref009" target="_blank">9</a>] estimated data output from FPKM normalized expression data. Every color stands for a type of immune cell and height of each colored bar represents relative frequency of an immune cell type. In the plot, 2N and 2D indicate normal and tumour tissues of tumour-normal paired S2sample, respectively. Similar nomenclature was used for tumour and normal tissues of other samples.</p

Hierarchical clustering of GBSCC tumours by 2176 deregulated gene expressions.

<p>Hierarchical clusters were constructed based on log2 transformed expression values of 1002 upregulated (represented by colours of negative values in heatmap) and 1174 downregulated genes (represented by colours of positive values in heatmap). Across all 12 tumours there is a gross similarity in deregulation pattern, with some exceptions. As a result, 3 distinct sample clusters were noticed. The coloured panel below, represent subject's smoking (orange) and/or chewing tobacco (red) and/or alcohol abuse (green)status.</p

Schematic view of fusion events.

<p>(A) ANO1-PLA2G16 fusion gene which retains exon 16 along with upstream exons of ANO1 and exon 3 along with downstream exons of PLA2G16 in tumour tissue (i.e. 23D) of the tumour-normal paired S23 sample. (B) S100A9-KRT17 fusion gene deduced from coding regions up to exon 3 of S100A9 and exon 1 to all other downstream exons of KRT17 in tumour tissue (i.e. 2D) of the tumour-normal paired S2 sample.</p

Expression deregulation of miRNA and target mRNAs.

<p>(A) Bar plots show log₂fold change in expression of miRNAs (hsa-miR-18b, hsa-miR-1293and hsa-miR-21) and their target, TIMP3. Scatter plots show negative correlation of TIMP3 expression with hsa-miR-18b and hsa-miR-21expression. Negative correlation was not observed between TIMP3 and hsa-miR-1293. Negative values of log₂fold change indicate upregulated expression whereas positive log₂fold change values indicate downregulation. (B) Bar plot showslog₂fold change of expression of miRNAs (hsa-miR-126 and hsa-miR-7) and their target, IRS1. Scatter plot shows negative correlation of IRS1 expression with hsa-miR-126 and hsa-miR-7expression. Negative values of log₂fold change indicate upregulated expression whereas positive fold change values indicate downregulation.</p

A Quest for miRNA Bio-Marker: A Track Back Approach from Gingivo Buccal Cancer to Two Different Types of Precancers

<div><p>Deregulation of miRNA expression may contribute to tumorigenesis and other patho-physiology associated with cancer. Using TLDA, expression of 762 miRNAs was checked in 18 pairs of gingivo buccal cancer-adjacent control tissues. Expression of significantly deregulated miRNAs was further validated in cancer and examined in two types of precancer (leukoplakia and lichen planus) tissues by primer-specific TaqMan assays. Biological implications of these miRNAs were assessed bioinformatically. Expression of <i>hsa-miR-1293, hsa-miR-31, hsa-miR-31*</i> and <i>hsa-miR-7</i> were significantly up-regulated and those of <i>hsa-miR-206, hsa-miR-204</i> and <i>hsa-miR-133a</i> were significantly down-regulated in all cancer samples. Expression of only <i>hsa-miR</i>-31 was significantly up-regulated in leukoplakia but none in lichen planus samples. Analysis of expression heterogeneity divided 18 cancer samples into clusters of 13 and 5 samples and revealed that expression of 30 miRNAs (including the above-mentioned 7 miRNAs), was significantly deregulated in the cluster of 13 samples. From database mining and pathway analysis it was observed that these miRNAs can significantly target many of the genes present in different cancer related pathways such as “proteoglycans in cancer”, <i>PI3K-AKT</i> etc. which play important roles in expression of different molecular features of cancer. Expression of <i>hsa-miR-31</i> was significantly up-regulated in both cancer and leukoplakia tissues and, thus, may be one of the molecular markers of leukoplakia which may progress to gingivo-buccal cancer.</p></div