Currently, molecular markers are not used when determining the prognosis and treatment strategy for patients with hepatocellular carcinoma (HCC). In the present study, we proposed that the identification of common pro‐oncogenic pathways in primary tumors (PT) and adjacent non‐malignant tissues (AT) typically used to predict HCC patient risks may result in HCC biomarker discovery. We examined the genome‐wide mRNA expression profiles of paired PT and AT samples from 321 HCC patients. The workflow integrated differentially expressed gene selection, gene ontology enrichment, computational classification, survival predictions, image analysis and experimental validation methods. We developed a 24‐ribosomal gene‐based HCC classifier (RGC), which is prognostically significant in both PT and AT. The RGC gene overexpression in PT was associated with a poor prognosis in the training (hazard ratio = 8.2, P = 9.4 × 10−6) and cross‐cohort validation (hazard ratio = 2.63, P = 0.004) datasets. The multivariate survival analysis demonstrated the significant and independent prognostic value of the RGC. The RGC displayed a significant prognostic value in AT of the training (hazard ratio = 5.0, P = 0.03) and cross‐validation (hazard ratio = 1.9, P = 0.03) HCC groups, confirming the accuracy and robustness of the RGC. Our experimental and bioinformatics analyses suggested a key role for c‐MYC in the pro‐oncogenic pattern of ribosomal biogenesis co‐regulation in PT and AT. Microarray, quantitative RT‐PCR and quantitative immunohistochemical studies of the PT showed that DKK1 in PT is the perspective biomarker for poor HCC outcomes. The common co‐transcriptional pattern of ribosome biogenesis genes in PT and AT from HCC patients suggests a new scalable prognostic system, as supported by the model of tumor‐like metabolic redirection/assimilation in non‐malignant AT. The RGC, comprising 24 ribosomal genes, is introduced as a robust and reproducible prognostic model for stratifying HCC patient risks. The adjacent non‐malignant liver tissue alone, or in combination with HCC tissue biopsy, could be an important target for developing predictive and monitoring strategies, as well as evidence‐based therapeutic interventions, that aim to reduce the risk of post‐surgery relapse in HCC patients.

BackgroundEpstein-Barr virus (EBV) encodes six nuclear transformation-associated proteins that induce extensive changes in cellular gene expression and signaling and induce B-cell transformation. The role of HIF1A in EBV-induced B-cell immortalization has not been previously studied.Methods and FindingsUsing Western blotting and Q-PCR, we found that HIF1A protein is stabilized in EBV-transformed lymphoblastoid cells. Western blotting, GST pulldown assays, and immunoprecipitation showed that EBV-encoded nuclear antigens EBNA-5 and EBNA-3 bind to prolylhydroxylases 1 and 2, respectively, thus inhibiting HIF1A hydroxylation and degradation. Immunostaining and Q-PCR showed that the stabilized HIF1A translocates to the nucleus, forms a heterodimer with ARNT, and transactivates several genes involved in aerobic glycolysis. Using biochemical assays and Q-PCR, we also found that lymphoblastoid cells produce high levels of lactate, lactate dehydrogenase and pyruvate.ConclusionsOur data suggest that activation of the aerobic glycolytic pathway, corresponding to the Warburg effect, occurs in EBV-transformed lymphoblastoid cells, in contrast to mitogen-activated B-cells.

The possible formation of three-stranded RNA and DNA hybrid structures (R-loops) in thousands of functionally important guanine-rich genic and inter-genic regions could suggest their involvement in transcriptional regulation and even development of diseases. Here, we introduce the first freely available R-loop prediction program called Quantitative Model of R-loop Forming Sequence (RLFS) finder (QmRLFS-finder), which predicts RLFSs in nucleic acid sequences based on experimentally supported structural models of RLFSs. QmRLFS-finder operates via a web server or a stand-alone command line tool. This tool identifies and visualizes RLFS coordinates from any natural or artificial DNA or RNA input sequences and creates standards-compliant output files for further annotation and analysis. QmRLFS-finder demonstrates highly accurate predictions of the detected RLFSs, proposing new perspective to further discoveries in R-loop biology, biotechnology and molecular therapy. QmRLFS-finder is freely available at http://rloop.bii.a-star.edu.sg/?pg=qmrlfs-finder.

(2012) Genetic and epigenetic analysis of non-small cell lung cancer with NotImicroarrays, Epigenetics, 7:5, 502-513,

Wastewater-based surveillance for SARS-CoV-2 has been used for the early warning of transmission or objective trending of the population-level disease prevalence. Here, we describe a new use-case of conducting targeted wastewater surveillance to complement clinical testing for case identification in a small community at risk of COVID-19 transmission. On 2 July 2020, a cluster of COVID-19 cases in two unrelated households residing on different floors in the same stack of an apartment building was reported in Singapore. After cases were conveyed to healthcare facilities and six healthy household contacts were quarantined in their respective apartments, wastewater surveillance was implemented for the entire residential block. SARS-CoV-2 was subsequently detected in wastewaters in an increasing frequency and concentration, despite the absence of confirmed COVID-19 cases, suggesting the presence of fresh case/s in the building. Phone interviews of six residents in quarantine revealed that no one was symptomatic (fever/ respiratory illness). However, when nasopharyngeal swabs from six quarantined residents were tested by PCR tests, one was positive for SARS-CoV-2. The positive case reported episodes of diarrhea and the case's stool sample was also positive for SARS-CoV-2, explaining the SARS-CoV-2 spikes observed in wastewaters. After the case was conveyed to a healthcare facility, wastewaters continued to yield positive signals for five days, though with a decreasing intensity. This was attributed to the return of recovered cases, who had continued to shed the virus. Our findings demonstrate the utility of wastewater surveillance as a non-intrusive tool to monitor high-risk COVID-19 premises, which is able to trigger individual tests for case detection, highlighting a new use-case for wastewater testing.

R-loops are three-stranded RNA:DNA hybrid structures essential for many normal and pathobiological processes. Previously, we generated a quantitative R-loop forming sequence (RLFS) model, quantitative model of R-loop-forming sequences (QmRLFS) and predicted ∼660 000 RLFSs; most of them located in genes and gene-flanking regions, G-rich regions and disease-associated genomic loci in the human genome. Here, we conducted a comprehensive comparative analysis of these RLFSs using experimental data and demonstrated the high performance of QmRLFS predictions on the nucleotide and genome scales. The preferential co-localization of RLFS with promoters, U1 splice sites, gene ends, enhancers and non-B DNA structures, such as G-quadruplexes, provides evidence for the mechanical linkage between DNA tertiary structures, transcription initiation and R-loops in critical regulatory genome regions. We introduced and characterized an abundant class of reverse-forward RLFS clusters highly enriched in non-B DNA structures, which localized to promoters, gene ends and enhancers. The RLFS co-localization with promoters and transcriptionally active enhancers suggested new models for in cis and in trans regulation by RNA:DNA hybrids of transcription initiation and formation of 3D-chromatin loops. Overall, this study provides a rationale for the discovery and characterization of the non-B DNA regulatory structures involved in the formation of the RNA:DNA interactome as the basis for an emerging quantitative R-loop biology and pathobiology.

Epstein-Barr virus (EBV), like other DNA tumor viruses, induces an S-phase in the natural host cell, the human B lymphocyte. This is linked with blast transformation. It is believed that the EBVencoded nuclear antigen 6 (EBNA-6) is involved in the regulation of cell cycle entry. However, the possible mechanism of this regulation is not approached. In our current study, we found that EBNA-6 binds to a MRPS18-2 protein, and targets it to the nucleus. We found that MRPS18-2 binds to both hypo-and hyperphosphorylated forms of Rb protein specifically. This binding targets the small pocket of pRb, which is a site of interaction with E2F1. The MRPS18-2 competes with the binding of E2F1 to pRb, thereby raising the level of free E2F1. Our experimental data suggest that EBNA-6 may play a major role in the entry of EBV infected B cells into the S phase by binding to and raising the level of nuclear MRPS18-2, protein. This would inhibit pRb binding to E2F1 competitively and lift the block preventing S-phase entry.cell transformation ͉ cell cycle ͉ surface plasmon resonance ͉ S-phase entry

BackgroundMany different genetic alterations are observed in cancer cells. Individual cancer genes display point mutations such as base changes, insertions and deletions that initiate and promote cancer growth and spread. Somatic hypermutation is a powerful mechanism for generation of different mutations. It was shown previously that somatic hypermutability of proto-oncogenes can induce development of lymphomas.Methodology/Principal FindingsWe found an exceptionally high incidence of single-base mutations in the tumor suppressor genes RASSF1 and RBSP3 (CTDSPL) both located in 3p21.3 regions, LUCA and AP20 respectively. These regions contain clusters of tumor suppressor genes involved in multiple cancer types such as lung, kidney, breast, cervical, head and neck, nasopharyngeal, prostate and other carcinomas. Altogether in 144 sequenced RASSF1A clones (exons 1–2), 129 mutations were detected (mutation frequency, MF = 0.23 per 100 bp) and in 98 clones of exons 3–5 we found 146 mutations (MF = 0.29). In 85 sequenced RBSP3 clones, 89 mutations were found (MF = 0.10). The mutations were not cytidine-specific, as would be expected from alterations generated by AID/APOBEC family enzymes, and appeared de novo during cell proliferation. They diminished the ability of corresponding transgenes to suppress cell and tumor growth implying a loss of function. These high levels of somatic mutations were found both in cancer biopsies and cancer cell lines.Conclusions/SignificanceThis is the first report of high frequencies of somatic mutations in RASSF1 and RBSP3 in different cancers suggesting it may underlay the mutator phenotype of cancer. Somatic hypermutations in tumor suppressor genes involved in major human malignancies offer a novel insight in cancer development, progression and spread.