Sanga Mitra

HNOCDB: A comprehensive database of genes and miRNAs relevant to head and neck and oral cancer

In spite of the wide prevalence of head, neck and oral cancer, HNOC, there is no integrated database on genes and miRNAs associated with all the carcinoma subtypes of HNOC. The objective is to compile a multilayered and comprehensive database of HNOC as a user-friendly resource for researchers devising novel therapeutic strategies. We present HNOCDB, the head, neck and oral cancer database, with the following key features: (i) it tabulates all the different categories of HNOC separately under appropriate subtype-names, and then puts them together in a table headlined All; (ii) the oncogenes/oncomiRs that cause HNOC are listed; their mutations, methylations and polymorphisms loci are marked, and the variations in their expression profiles relative to the normal are recorded; (iii) HNOCDB contains a chromosomal map of HNOC genes and miRNA; (iv) contains references that experimentally validate the reason for the inclusion of the genes and the miRNAs in HNOCDB. HNOCDB is freely accessible for academic and non-profit users via http://gyanxet.com/hno.html.

Anomalous altered expressions of downstream gene-targets in TP53-miRNA pathways in head and neck cancer

The prevalence of head and neck squamous cell carcinoma, HNSCC, continues to grow. Change in the expression of TP53 in HNSCC affects its downstream miRNAs and their gene targets, anomalously altering the expressions of the five genes, MEIS1, AGTR1, DTL, TYMS and BAK1. These expression alterations follow the repression of TP53 that upregulates miRNA-107, miRNA- 215, miRNA-34 b/c and miRNA-125b, but downregulates miRNA-155. The above five so far unreported genes are the targets of these miRNAs. Meta-analyses of microarray and RNA-Seq data followed by qRT-PCR validation unravel these new ones in HNSCC. The regulatory roles of TP53 on miRNA-155 and miRNA-125b differentiate the expressions of AGTR1 and BAK1in HNSCC vis-à-vis other carcinogenesis. Expression changes alter cell cycle regulation, angiogenic and blood cell formation, and apoptotic modes in affliction. Pathway analyses establish the resulting systems-level functional and mechanistic insights into the etiology of HNSCC.

Eukaryotic tRNA paradox

tRNAs are widely believed to segregate into two classes, I and II. Computational analysis of eukaryotic tRNA entries in Genomic tRNA Database, however, leads to new, albeit paradoxical, presence of more than a thousand class-I tRNAs with uncharacteristic long variable arms (V-arms), like in class-II. Out of 62,202 tRNAs from 69 eukaryotes, as many as 1431 class-I tRNAs have these novel extended V-arms, and we refer to them as paradoxical tRNAs (pxtRNAs). A great majority of these 1431 pxtRNA genes are located in intergenic regions, about 18% embedded in introns of genes or ESTs, and just one in 3′UTR. A check on the conservations of 2D and 3D base pairs for each position of these pxtRNAs reveals a few variations, but they seem to have almost all the known features (already known identity and conserved elements of tRNA). Analyses of the A-Box and B-Box of these pxtRNA genes in eukaryotes display salient deviations from the previously annotated conserved features of the standard promoters, whereas the transcription termination signals are just canonical and non-canonical runs of thymidine, similar to the ones in standard tRNA genes. There is just one such pxtRNAProAGG gene in the entire human genome, and the availability of data allows epigenetic analysis of this human pxtRNAProAGG in three different cell lines, H1 hESC, K562, and NHEK, to assess the level of its expression. Histone acetylation and methylation of this lone pxtRNAProAGG gene in human differ from that of the nine standard human tRNAProAGG genes. The V-arm nucleotide sequences and their secondary structures in pxtRNA differ from that of class-II tRNA. Considering these differences, hypotheses of alternative splicing, non-canonical intron and gene transfer are examined to partially improve the Cove scores of these pxtRNAs and to critically question their antecedence and novelty.

Eukaryotic tRNAs fingerprint invertebrates vis-à-vis vertebrates

During translation, aminoacyl-tRNA synthetases recognize the identities of the tRNAs to charge them with their respective amino acids. The conserved identities of 58,244 eukaryotic tRNAs of 24 invertebrates and 45 vertebrates in genomic tRNA database were analyzed and their novel features extracted. The internal promoter sequences, namely, A-Box and B-Box, were investigated and evidence gathered that the intervention of optional nucleotides at 17a and 17b correlated with the optimal length of the A-Box. The presence of canonical transcription terminator sequences at the immediate vicinity of tRNA genes was ventured. Even though non-canonical introns had been reported in red alga, green alga, and nucleomorph so far, fairly motivating evidence of their existence emerged in tRNA genes of other eukaryotes. Non-canonical introns were seen to interfere with the internal promoters in two cases, questioning their transcription fidelity. In a first of its kind, phylogenetic constructs based on tRNA molecules delineated and built the trees of the vast and diverse invertebrates and vertebrates. Finally, two tRNA models representing the invertebrates and the vertebrates were drawn, by isolating the dominant consensus in the positional fluctuations of nucleotide compositions.

Viral/plasmid captures in Crenarchaea

tRNA genes are the integration sites of viral/plasmid genomes into their hosts chromosomes by homologous recombination catalyzed by integrases. The crossover between viral/plasmid and host genomes leaves 3′-fractional tRNA motif as tell-tale marker of integration on host-chromosome. This 3′-fractional tRNA motif on host genome is our retrenched tRNA (rtRNA). To track integration in Crenarchaea, host rtRNAs, and conserved features in viral/plasmid tRNA motifs and in integrases were identified. The viral-integrase has a conserved 24-nucleotide long motif, GTATTATGTTTACTCAATAGAGAA in the N-terminal region. Upstream of the viral tRNA motif has a conserved poly-cytosine region and a hairpin secondary structure. Corresponding to a host tRNA, we observe up to two rtRNAs on crenarchaeal chromosome. The length of the rtRNA is not random. The fraction of tRNA excised off in rtRNA is either 61.8, or 50, or 38.2, or 23.6%. Thus, the integration fragments the tRNA nonrandomly dividing it approximately in ratios 3:2, or 1:1, or 2:3, or 1:3. More than 79% of rtRNAs have lengths that are excised 38.2% off tRNA. It turns out that 38.2% excision implies that the ratio of the length of tRNA to its rtRNA is just 1.618, the golden ratio. Hence, the vast majority of rtRNAs are at or near the golden ratio. Evidence emerges of new extremophile viral entities.

Novel Hybrid Encodes both Continuous and Split tRNA Genes

Abstract tRNAs are mostly transcribed from un-fragmented genes, but occasionally also from split genes, with separated 5′ and 3′ halves. A reanalysis of the existing data on Staphylothermus marinus and Staphylothermus hellenicus hints of a novel hybrid gene that encodes both an un-fragmented and a 5′-split-half together in one. The corresponding 3′-complementgene is located elsewhere on the genome. As un-fragmented, the hybrid gene transcribes to tRNAlys(TTT). But as 5′-half, it trans-splices with its 3′-complement-half to tRNAlys(CTT), the tRNA missed so far. This hybrid of the split and the un-fragmented in one suggests a deeper synergy between the two, and hints of co-evolution. Furthermore, in a subtle contrast to the widely held idea of conservation of 3′-half, it is precisely the 3′-half that varies in these two tRNAs; the 5′-half remains conserved.

Chapter 9 – Transfer RNA in Cancer

Abstract Cancer cell proliferation depends on protein abundances that are aided by transfer RNAs, tRNAs. Messenger RNAs, mRNAs, of cancer-specific oncogenes and the simultaneous generation of their respective tRNAs bear on the complex carcinogenic imprint in transcription and translation. Beyond translation, tRNA-derived fragments, derivatives of either mature or precursor tRNAs, represent a novel and potentially important group of noncoding RNAs implicated in oncogenic or tumor suppressive pathways. Recent trend revolves around the usage of tRNA as antitumor drug target.

Chapter 27 – A Comparative Evaluation of Emerging Databases and Tools for Cancer Noncoding RNAs

Abstract Biological databases play a central role in translational research, including the roles of noncoding RNAs (ncRNAs) involved in cancers. This chapter provides a brief overview of available databases related to ncRNAs, such as microRNAs (miRNAs), long noncoding RNAs (lncRNAs), transfer RNAs (tRNAs), and circular RNAs (circRNAs), altered in multicancer panel as well as the major tools used for identification, annotation, and analyses of small ncRNA data in cancer. We present an open-access database, ncRNAiC (Noncoding RNAs in Cancer), where the alteration statuses of ncRNAs in 19 types of cancers are provided.

Perspective on long noncoding RNA functionality

Long non-coding RNAs or lncRNAs, are non-protein coding transcripts longer than 200 nucleotides, distinguishing them from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. As the number of lncRNAs-genes has gone above and beyond the number of protein coding genes in human, lncRNAs have begun to gain widespread attention in recent years, as a result the need to identify them as well as determine their functions has gained precedence.

Decrypting ENCODEd epigenetic marks of human tRN-A-RS genes in normal, stem and cancer cell lines.

Screening large-scale ENCODE data of 625 cytoplasmic transfer RNA (tRNAs) and 37 aminoacyl tRNA synthetase (AARSs) human genes, we deconstruct the array of relations between 10 histone marks affecting 15 chromatin states; their tissue specificity and variations and interchange amongst normal, cancerous and stem cells. The histone marks of RNA Pol II transcribed AARS genes share, but also contrast with that on RNA Pol III transcribed tRNA genes. tRNAs with identical/similar sequences may be in significantly varying states even within the same cell line; the chromatin scaffold, where the tRNA gene resides, is the key determinant. Hepatocellular carcinoma cell line has dominant H3K27me3, and singular clustering of other marks. Leukaemic cell line has hyperactive genes. The quiescence of the stem cells is encoded in the markers. Leaving aside the important exceptions in stem cells and elsewhere, tRNAs with cove scores above 50 have active markers and precise sets of transcription factors, and are usually well conserved compared to the low-scoring ones. Pseudo tRNAs are in heterochromatin/repressed state with anomalous exceptions in cancer cells. We motivate that Epigenetic-Phishing hacks the translation apparatus through the chromatin states governed by the histone marks of tRNA and AARS genes, and speculate on their therapeutic implications in cancer and on stem cells.