Bioinformatics Data Mining Research Articles

MFAP2 Promotes the Proliferation of Cancer Cells and Is Associated With a Poor Prognosis in Hepatocellular Carcinoma

Backgrounds:Microfibril-associated protein 2 (MFAP2) is an extracellular matrix protein that regulates the function of microfibrils by interacting with fibrillin. MFAP2 has been reported to play an important role in metabolic diseases and has been shown to be significantly overexpressed in head and neck squamous cell carcinoma and Hepatocellular carcinoma (HCC). However, the molecular function and prognostic value of MFAP2 have never been reported in HCC or other tumors.Methods:In the present study, expression characteristics of MFAP2 in HCC, its influence on the development of HCC, as well as its function and potential mechanism in HCC were verified by Quantitative reverse transcription-polymerase chain reaction, bioinformatics data mining and in vitro cell experiments.Results:MFAP2 was prominently high-expressed in HCC and associated with cancer stages. HCC patients with higher MFAP2 expression displayed lower overall survival (OS) and disease-specific survival(DSS), while there was no significant difference in recurrence-free survival (RFS). In vitro experiments showed that downregulation of MFAP2 inhibited proliferation, migration level of HCC cells. Transcription factors, DNA methyltransferases, immune factors may interact with MFAP2 mRNA to promote tumor progression in HCC.Conclusion:These findings suggest that MFAP2 may play a key role in the development of HCC. Therefore, MFAP2 may be a valuable prognostic marker and an effective anticancer target in HCC.

Function Prediction from Protein Primary Structure using Deep Learning LSTM Algorithm

Biological information of protein primary structure is responsible for finding the protein function, extracting features and function of a protein in the biology lab is challenging and time-consuming. Identification of protein function provides essential information for the treatment of various diseases and drug design. Therefore, extracting the protein knowledge from primary structure alone has been a diverse field in the study of bioinformatics data mining and computational biology. This study aimed to function prediction of protein primary structure using the LSTM methods. PRNP(prion protein )most of the nervous system tissues express by prion protein, this is generally to protease-resistant from disease, due to this reasons, the human codon PRNP is most closely associated with Alzheimer disease. The PRNP protein data trained with Hemo sapiens PRNP selection, classification was implemented with network layer perceptron. The learning algorithms are frame by the nervous system. The training results observation indicate that the learning success of prion protein classification leads positively.

MiR-132 controls pancreatic beta cell proliferation and survival through Pten/Akt/Foxo3 signaling

ObjectiveMicroRNAs (miRNAs) play an integral role in maintaining beta cell function and identity. Deciphering their targets and precise role, however, remains challenging. In this study, we aimed to identify miRNAs and their downstream targets involved in the regeneration of islet beta cells following partial pancreatectomy in mice. MethodsRNA from laser capture microdissected (LCM) islets of partially pancreatectomized and sham-operated mice were profiled with microarrays to identify putative miRNAs implicated in beta cell regeneration. Altered expression of the selected miRNAs, including miR-132, was verified by RT-PCR. Potential targets of miR-132 were selected through bioinformatic data mining. Predicted miR-132 targets were validated for their changed RNA, protein expression levels, and signaling upon miR-132 knockdown and/or overexpression in mouse MIN6 and human EndoC-βH1 insulinoma cells. The ability of miR-132 to foster beta cell proliferation in vivo was further assessed in pancreatectomized miR-132−/− and control mice. ResultsPartial pancreatectomy significantly increased the number of BrdU+/insulin+ islet cells. Microarray profiling revealed that 14 miRNAs, including miR-132 and -141, were significantly upregulated in the LCM islets of the partially pancreatectomized mice compared to the LCM islets of the control mice. In the same comparison, miR-760 was the only downregulated miRNA. The changed expression of these miRNAs in the islets of the partially pancreatectomized mice was confirmed by RT-PCR only in the case of miR-132 and -141. Based on previous knowledge of its function, we focused our attention on miR-132. Downregulation of miR-132 reduced the proliferation of MIN6 cells while enhancing the levels of pro-apoptotic cleaved caspase-9. The opposite was observed in miR-132 overexpressing MIN6 cells. Microarray profiling, RT-PCR, and immunoblotting of the latter cells demonstrated their downregulated expression of Pten with concomitant increased levels of pro-proliferative factors phospho-Akt and phospho-Creb and inactivation of pro-apoptotic Foxo3a via its phosphorylation. Downregulation of Pten was further confirmed in the LCM islets of pancreatectomized mice compared to the sham-operated mice. Moreover, overexpression of miR-132 correlated with increased proliferation of EndoC-βH1 cells. The regeneration of beta cells following partial pancreatectomy was lower in the miR-132/212−/− mice than the control littermates. ConclusionsThis study provides compelling evidence about the critical role of miR-132 for the regeneration of mouse islet beta cells through the downregulation of its target Pten. Hence, the miR-132/Pten/Akt/Foxo3 signaling pathway may represent a suitable target to enhance beta cell mass.

Impact of polymorphic transposable elements on transcription in lymphoblastoid cell lines from public data

BackgroundTransposable elements (TEs) are DNA sequences able to mobilize themselves and to increase their copy-number in the host genome. In the past, they have been considered mainly selfish DNA without evident functions. Nevertheless, currently they are believed to have been extensively involved in the evolution of primate genomes, especially from a regulatory perspective. Due to their recent activity they are also one of the primary sources of structural variants (SVs) in the human genome. By taking advantage of sequencing technologies and bioinformatics tools, recent surveys uncovered specific TE structural variants (TEVs) that gave rise to polymorphisms in human populations. When combined with RNA-seq data this information provides the opportunity to study the potential impact of TEs on gene expression in human.ResultsIn this work, we assessed the effects of the presence of specific TEs in cis on the expression of flanking genes by producing associations between polymorphic TEs and flanking gene expression levels in human lymphoblastoid cell lines. By using public data from the 1000 Genome Project and the Geuvadis consortium, we exploited an expression quantitative trait loci (eQTL) approach integrated with additional bioinformatics data mining analyses. We uncovered human loci enriched for common, less common and rare TEVs and identified 323 significant TEV-cis-eQTL associations. SINE-R/VNTR/Alus (SVAs) resulted the TE class with the strongest effects on gene expression. We also unveiled differential functional enrichments on genes associated to TEVs, genes associated to TEV-cis-eQTLs and genes associated to the genomic regions mostly enriched in TEV-cis-eQTLs highlighting, at multiple levels, the impact of TEVs on the host genome. Finally, we also identified polymorphic TEs putatively embedded in transcriptional units, proposing a novel mechanism in which TEVs may mediate individual-specific traits.ConclusionWe contributed to unveiling the effect of polymorphic TEs on transcription in lymphoblastoid cell lines.

NT5E/CD73 as Correlative Factor of Patient Survival and Natural Killer Cell Infiltration in Glioblastoma.

CD73, a cell-surface protein encoded by the gene NT5E, is overexpressed in glioblastoma (GBM), where it contributes to the tumor’s pathophysiology via the generation of immunosuppressive adenosine. Adenosinergic signaling, in turn, drives immunosuppression of natural killer (NK) cells through metabolic and functional reprogramming. The correlation of CD73 with patient survival in relation to GBM pathology and the intratumoral infiltration of NK cells has not been comprehensively studied before. Here, we present an analysis of the prognostic relevance of CD73 in GBM based on transcriptional gene expression from patient data from The Cancer Genome Atlas (TCGA) database. Utilizing bioinformatics data mining tools, we explore the relationship between GBM prognosis, NT5E expression, and intratumoral presence of NK cells. Our analysis demonstrates that CD73 is a negative prognostic factor for GBM and that presence of NK cells may associate with improved prognosis. Moreover, the interplay between expression of NT5E and specific NK genes hints to potential functional effects of CD73 on NK cell activation.

Genetic polymorphisms and transcription profiles associated with intracranial aneurysm: a key role for NOTCH3.

Intracranial aneurysm (IA) incidence is about 1~2%. However, the specific mechanisms of IA onset and development need further study. Our objective was to discover novel IA-related genes to determine possible etiologies further. We performed next-generation sequencing on nineteen Chinese patients with familial IA and one patient with sporadic IA. We obtained mRNA expression data of 129 samples from Gene Expression Omnibus (GEO) and made statistical computing to discover differentially expressed genes (DEGs). The screened IA-related gene NOTCH3 was determined by bioinformatic data mining. We verified the IA-related indicators of NOTCH3. Association was found between IA and the NOTCH3 SNPs rs779314594, rs200504060 and rs2285981. Levels of NOTCH3 mRNA were lower in IA tissue than in control tissue, but higher in peripheral blood neutrophils from IA patients than in neutrophils from controls. Levels of NOTCH3 protein were lower in IA tissue than in cerebral artery tissue. NOTCH3 also decreased the expression of angiogenesis factors in human umbilical vein endothelial cells. Variation in NOTCH3 and alteration of its expression in cerebral artery or neutrophils may contribute to IA. Our findings also describe a bioinformatic-experimental approach that may prove useful for probing the pathophysiology of other complex diseases.

332-LB: Mir-132 Controls Pancreatic Beta-Cell Proliferation and Survival through the Pten/Akt/Foxo3 Signaling

Aim and Hypothesis: microRNAs (miRNAs) play an integral role in maintaining beta cell function and identity. We aimed to identify miRNAs and their downstream targets involved in regeneration of islet beta cells following partial pancreatectomy (pP) in mice. Methods: RNA from laser capture microdissected islets of pP and sham-operated mice were profiled with microarrays to identify miRNAs implicated in control of beta cell regeneration. Altered expression of selected miRNAs, including miR-132, was verified by RT-PCR. Potential targets of miR-132 were selected through bioinformatic data mining. Predicted miR-132 targets were validated for their changed RNA and protein expression levels and signaling upon miR-132 knockdown and overexpression in mouse MIN6 cells and human EndoC-βH1 insulinoma cells. The ability of miR-132 to foster beta cell proliferation in vivo was further assessed in pP miR-132-/-and control mice. Results: pP significantly increased the number of BrdU+/insulin+ positive islet cells. Microarray profiling revealed 14 miRNAs, including miR-132, to be significantly upregulated in LCM islets of partially pancreatectomized mice and confirmed by RT-PCR. Downregulation of miR-132 in MIN6 cells reduced proliferation while enhancing the levels of pro-apoptotic cleaved caspase-9. Microarray profiling, RT-PCR and immunoblotting revealed downregulated expression of Pten, with concomitant increased levels of pro-proliferative factors as well as inactivation of pro-apoptotic Foxo3. Overexpression of miR-132 in human insulinoma cells EndoC-βH1 validated the findings. In vivo regeneration of beta cells was reduced in pP miR-132-/- mice compared to control mice. Conclusions: Our study provides compelling evidence for miR-132 being critical for regeneration of mouse islet beta cells in vivo through downregulation of its target Pten. Hence, the miR-132/Pten/Akt/Foxo3 signaling pathway may represent a suitable target to enhance beta cell regeneration. Disclosure S. Kersting: None. H. Mziaut: None. Funding German Center for Diabetes Research (to S.K.)

MicroRNA-200b is downregulated and suppresses metastasis by targeting LAMA4 in renal cell carcinoma

BackgroundMetastasis is the primary cause of tumor death in renal cell carcinoma (RCC). Improved diagnostic markers of metastasis are critically needed for RCC. MicoRNAs are demonstrated to be stable and significant biomarkers for several malignancies. In this study, we aimed to explore the metastasis related microRNAs and its mechanism in RCC. MethodsThe relationship between microRNAs expression and prognosis and metastasis of RCC patients were explored by data mining through expression profiles from The Cancer Genome Atlas (TCGA). A total of 80 RCC tissues and adjacent normal kidney tissues were obtained from Department of Urology, Peking University First Hospital. Expression of microRNA-200b (miR-200b) in RCC tissues and cell lines were determined by bioinformatic data mining and quantitative real-time PCR (qRT-PCR). The effects of miR-200b on cell proliferation, migration and invasion were determined by cell counting kit-8 and colony formation assay, wound healing assay and Boyden chamber assay. Mouse cell-derived xenograft and patient-derived xenograft model were also performed to evaluate the effects of miR-200b on tumor growth and metastasis in vivo. The molecular mechanism of miR-200b function was investigated using bioinformatic target predication and high-throughput cDNA sequencing (RNA-seq) and validated by luciferase reporter assay, qRT-PCR, Western blot and immunostaining in vitro and in vivo. FindingsOur findings indicates that miR-200b is frequently downregulated and have potential utility as a biomarker of metastasis and prognosis in RCC. Interestingly, ectopic expression of miR-200b in the Caki-1 and OSRC-2 cell lines suppresses cell migration and invasion in vitro as well as tumor metastases in vivo. However, miR-200b has no effect on cell proliferation in vitro and tumor growth in vivo. In addition, bioinformatics target predication and RNA-seq results reveals that Laminin subunit alpha 4 (LAMA4) is one target of miR-200b and significantly inhibited by miR-200b in vitro and in vivo. InterpretationThese results demonstrate a previously undescribed role of miR-200b as a suppressor of tumor metastasis in RCC by directly destabilizing LAMA4 mRNA.

Exploring the Evolution of Virulence Factors through Bioinformatic Data Mining.

The molecular evolution of virulence factors is a central theme in our understanding of bacterial pathogenesis and host-microbe interactions. Using bioinformatics and genome data mining, recent studies have shed light on the evolution of important virulence factor families and the mechanisms by which they have adapted and diversified in function. This perspective highlights three complementary approaches useful for studying the molecular evolution of virulence factors: identification and analysis of virulence factor homologs, detection of adaptations or functional shifts, and computational prediction of novel virulence factor families. Each of these research directions is associated with distinct questions, approaches, and challenges for future work. Moving forward, bioinformatics will continue to play a critical role in exploring the evolution of virulence factors, including those that target humans. By reconstructing past processes and events, we will be able to better interpret newly sequenced microbial genomes and detect future pathoadaptations.

Abrogation of Pancreatic Cancer Using a Brain Malady Drug

Pancreatic cancer is the fourth preeminent cause of cancer-related deaths with a poor prognosis. Desmoplasia and drug resistance are few of the pivotal hurdles in pancreatic cancer management. Unlike breast cancer, awareness about pancreatic cancer still lacks in all the aspects. Our extensive bioinformatic and clinical data mining led us to notice an abnormal upregulation of a membrane protein Sphingosine-1-Phosphate Receptor-1 (S1PR1) in pancreatic cancer. S1PR1 is an important lipid signalling receptor whose ligand is a bioactive lipid, Sphingosine-1-phosphate. We were curious to know what happens to the cancer cell if we block this active lipid signaling. So, we targeted this protein using its antagonist, FTY720, which is already in the market for a known brain disorder called multiple sclerosis. FDA accreditation and known ADMET patters prompted us to choose this pre-existing drug. Accordingly, time-consuming clinical trials could be bypassed leading to rapid repurposing for pancreatic cancer. Our in vitro studies on numerous pancreatic cancer cell lines displayed a dose-dependent increase in cell death with low toxicity on normal cells. Although, gemcitabine is the first line chemotherapeutic drug for pancreatic cancer, the emergence of resistance among the patients was observed which leads to metastasis. In particular, combination therapy is an imminent approach to tackle the trouble of drug resistance. Indeed, an amalgamation of FTY720 and gemcitabine showed the enhanced anticancer effects on ex vivo experiments. Furthermore, two animal models showed the conspicuous abatement in tumor chunk as a result of blended drug treatment for 30 days. Besides, reduction of significant cell proliferation markers in the tumor microenvironment was observed. We found that FTY720 alone and also in commixture with gemcitabine effectively ameliorated the activity of PP2A which is the known target of FTY720. STAT3 is a transcription factor, which plays a remarkable role in carcinogenesis. We also observed a reduced S1PR1-STAT3 loop in vivo along with its downstream survival proteins due to strong affinity of FTY720 on the S1PR1 receptor. Since the combination of FTY720+Gem showed an astonishing role in abatement of tumor size than solitary treatment, the exact role of this combination strategy was explained by exploring the role of FTY720, which may act as a trooper for gemcitabine to cross the desmoplasia, an enlarged collagen area. As expected, we found a reduction in desmoplastic markers in the FTY720 treatment group. It infers that FTY720 loosens up the tumor tissue so that gemcitabine can readily reach the cancer cells. In conclusion, we propose that FTY720 can be a propitious molecule in pancreatic cancer management in combination with other chemotherapeutic drugs. Support or Funding Information University Grants Commision, Government of India and Department of Biotechnology, Government of India. The Mechanism of action of the combination therapy in pancreatic cancer. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Multi-targeting chemoprevention of Chinese herb formula Yanghe Huayan decoction on experimentally induced mammary tumorigenesis

BackgroundDevelopment of safe and effective chemopreventive agents is a winning strategy in reducing the morbidity and mortality of breast cancer. The current study was to investigate the mechanism-based chemopreventive potential of a Chinese herb formula Yanghe Huayan (YHHY) Decoction on the classical 7,12-dimethylbenz(a)anthracene (DMBA) induced rat mammary carcinogenesis model.MethodsFemale Sprague-Dawley rats at 42 days of age were orally administered with a human equivalent dose of YHHY Decoction at 0.02 ml/g (10 mg/ml) once daily, starting 1 wk. before and 4 wks following DMBA treatment. Mammary tumor occurrence was monitored every day. The length of time before palpable tumor is examined is defined as tumor-free survival time. High performance liquid chromatography (HPLC) analyses were adopted to identify major chemical compositions of the decoction. Following bioinformatics data mining and experimental analyses were performed to demonstrate the underlying mechanism of action.ResultsDMBA animals receiving YHHY Decoction exhibited a significant delay (P = 0.014) and in some animals prevention (P = 0.046) of tumor occurrence without obvious toxicity. Oncogenic myc activation was significantly suppressed in the DMBA-induced rats by the YHHY treatment. Eight major chemical compositions of the decoction were identified and were shown to interfere with multiple tumorigenic pathways simultaneously in the mammary tumors, including inducing tumor apoptosis and up-regulating pro-apoptotic protein Bax and down-regulating anti-apoptotic protein Bcl-2; suppressing abnormal cell proliferation and the MAPK/ERK, PI3K/AKT signalings; blocking neo-angiogenesis and the VEGF/KDR signaling, and inhibiting oxidative stress in the mammary tumors.ConclusionThe multi-components and multi-targeting properties of the YHHY Decoction support its use as a potent chemopreventive drug in breast cancer.

Developments beyond blood group serology in the genomics era.

Blood group serology and single nucleotide polymorphism-based genotyping platforms are accurate but do not provide a comprehensive cover for all 36 blood group systems and do not cover the antigen diversity observed among population groups. This review examines the extent to which genomics is shaping blood group serology. Resources for genomics include the Human Reference Genome Sequence assembly; curated blood group tables listing variants; public databases providing information on genetic variants from world-wide studies; and massively parallel sequencing technologies. Blood group genomic studies span the spectrum, from bioinformatic data mining of huge data sets containing whole genome and whole exome information to laboratory investigations utilising targeted sequencing approaches. Blood group predictions based on genome sequencing and genomic studies are proving accurate, and have shown utility in both research and reference settings. Overall, studies confirm the potential for blood group genomics to reshape donor and patient transfusion management strategies to provide more compatible blood transfusions.

Inhibition of LOXL2 Enhances the Radiosensitivity of Castration-Resistant Prostate Cancer Cells Associated with the Reversal of the EMT Process.

Introduction Radiotherapy is the mainstay in the treatment of prostate cancer. However, significant radioresistance of castration-resistant prostate cancer (CRPC) cells constitutes a main obstacle in the treatment of this disease. By using bioinformatic data mining methods, LOXL2 was found to be upregulated in both androgen-independent prostate cancer cell lines and radioresistant tumor samples collected from patients with prostate cancer. We speculate that LOXL2 may play an important role in the radioresistance of CRPC cells. Methods The effect of LOXL2 knockdown on the radiosensitivity of androgen-independent prostate cancer cells lines was measured by the clonogenic assay and xenograft tumor experiments under in vitro and in vivo conditions, respectively. In studies on the mechanism, we focused on the EMT phenotype changes and cell apoptosis changes induced by LOXL2 knockdown in DU145 cells. The protein levels of three EMT biomarkers, namely, E-cadherin, vimentin, and N-cadherin, were measured by western blotting and immunohistochemical staining. Cell apoptosis after irradiation was measured by flow cytometry and caspase-3 activity assay. Salvage experiment was also conducted to confirm the possible role of EMT in the radiosensitization effect of LOXL2 knockdown in CRPC cells. Results LOXL2 knockdown in CRPC cells enhanced cellular radiosensitivity under both in vitro and in vivo conditions. A significant reversal of EMT was observed in LOXL2-silenced DU145 cells. Cell apoptosis after irradiation was significantly enhanced by LOXL2 knockdown in DU145 cells. Results from the salvage experiment confirmed the key role of EMT process reversal in the radiosensitization effect of LOXL2 knockdown in DU145 cells. Conclusions LOXL2 plays an important role in the development of cellular radioresistance in CRPC cells. Targeting LOXL2 may be a rational avenue to overcome radioresistance in CRPC cells. A LOXL2-targeting strategy for CRPC treatment warrants detailed investigation in the future.

Downregulation of CLDN7 due to promoter hypermethylation is associated with human clear cell renal cell carcinoma progression and poor prognosis

BackgroundMetastasis is the primary cause of death in renal cell carcinoma (RCC). Loss of cell-to-cell adhesion, including tight junctions (TJs) is the initial step in the process of metastasis. Claudin-7 (CLDN7) is a major component of TJs. However, the clinical significance and its regulation of kidney tumorigenesis remain poorly understood.MethodsA total of 120 fresh clear cell RCC (ccRCC) specimens and 144 primary RCC and adjacent nonmalignant renal paraffin specimens were obtained from Department of Urology, Peking University First Hospital. Expression of CLDN7 in ccRCC tissues and cell lines were determined using bioinformatic data mining, quantitative real-time PCR (qRT-PCR), Western blotting and immunostaining. The clinical significance of CLDN7 expression and promoter DNA methylation status was analyzed in ccRCC patients from Peking University First Hospital and The Cancer Genome Atlas. Additionally, the methylation specific-PCR, bisulfite genomic sequencing and demethylation analysis of CLDN7 were performed. Biological functions of CLDN7 were investigated by examining cell proliferation using MTS assays and EdU incorporation assays, cell migration by in vitro wound healing assays and transwell migration assays, cell invasion by transwell invasion assays, and cell apoptosis by flow cytometry. Mouse model experiments were performed to confirm the effects of CLDN7 on tumor growth and metastasis in vivo. The molecular mechanism of CLDN7 function was investigated using gene-set enrichment analysis (GSEA) and high-throughput cDNA sequencing (RNA-Seq) and confirmed by qRT-PCR, Western blot and immunostaining in vitro and in vivo.ResultsOur findings revealed that CLDN7 is frequently downregulated via hypermethylation of its promoter in ccRCC. CLDN7 can help predict aggressive tumor status and poor prognosis in ccRCC patients. Interestingly, hypermethylation of the CLDN7 promoter was related to advanced ccRCC status and poor prognosis. Moreover, overexpression of CLDN7 induced cell apoptosis, suppressed proliferation, migration and invasion abilities of ccRCC cells both in vitro and in vivo. Additionally, GSEA and RNA-Seq results showed that CLDN7 had negative effects in cancer-associated signaling pathways and (epithelial-mesenchymal transition) EMT-related pathways. These results were validated by qRT-PCR, Western blot and immunostaining.ConclusionsWe have demonstrated a previously undescribed role of CLDN7 as a ccRCC suppressor and suggest that loss of CLDN7 potentiates EMT and tumor progression. CLDN7 may serve as a functional tumor suppressor in tumor progression and a potential biomarker and target in patients with ccRCC.

Proteomic analysis of 2-monochloropropanediol (2-MCPD) and 2-MCPD dipalmitate toxicity in rat kidney and liver in a 28-days study

2-monochloropropanediol (2-MCPD), 3-monochloropropanediol (3-MCPD) and their fatty acid esters have recently been identified as heat-induced contaminants in fat- and salt-containing foodstuff. Toxicity of 3-MCPD has been studied previously in some detail. Disturbance of glycolysis and cellular redox functions appear to be involved in 3-MCPD toxicity. By contrast, only very few toxicological data are available for 2-MCPD or 2-MCPD esters, especially at the molecular level. This study was therefore aimed to provide a comprehensive overview of proteomic alterations induced in rat kidney and liver by 2-MCPD and 2-MCPD dipalmitate, a representative 2-MCPD fatty acid ester. Sub-toxic doses of 10 mg/kg body weight 2-MCPD, or equimolar doses of 2-MCPD dipalmitate were applied in a 28-day in vivo gavage oral toxicity study in male rats. Two-dimensional gel electrophoresis and mass-spectrometric protein identification using material from 5 animals per treatment group were employed together with bioinformatic data mining to obtain information about the molecular basis of the observed proteomic alterations. Obtained data indicate toxic consequences of 2-MCPD exposure in the kidney and provide evidence that 2-MCPD exerts its cellular effects in rat kidney by mechanisms different from 3-MCPD.

Interplay between base excision repair protein XRCC1 and ALDH2 predicts overall survival in lung and liver cancer patients

BackgroundTo deliver efficacious personalised cancer treatment, it is essential to characterise the cellular metabolism as well as the genetic stability of individual tumours. In this study, we describe a new axis between DNA repair and detoxification of aldehyde derivatives with important implications for patient prognosis and treatment.MethodsWestern blot and qPCR analyses were performed in relevant non-transformed and cancer cell lines from lung and liver tissue origin in combination with bioinformatics data mining of The Cancer Genome Atlas database from lung and hepatocellular cancer patients.ResultsUsing both biochemical and bioinformatics approaches, we revealed an association between the levels of expression of the aldehyde detoxifying enzyme aldehyde dehydrogenase 2 (ALDH2) and the key DNA base excision repair protein XRCC1. Across cancer types, we found that if one of the corresponding genes exhibits a low expression level, the level of the other gene is increased. Surprisingly, we found that low ALDH2 expression levels associated with high XRCC1 expression levels are indicative for a poor overall survival, particularly in lung and liver cancer patients. In addition, we found that Mithramycin A, a XRCC1 expression inhibitor, efficiently kills cancer cells expressing low levels of ALDH2.ConclusionsOur data suggest that lung and liver cancers require efficient single-strand break repair for their growth in order to benefit from a low aldehyde detoxification metabolism. We also propose that the ratio of XRCC1 and ALDH2 levels may serve as a useful prognostic tool in these cancer types.

Benchmarking relief-based feature selection methods for bioinformatics data mining

Modern biomedical data mining requires feature selection methods that can (1) be applied to large scale feature spaces (e.g. ‘omics’ data), (2) function in noisy problems, (3) detect complex patterns of association (e.g. gene-gene interactions), (4) be flexibly adapted to various problem domains and data types (e.g. genetic variants, gene expression, and clinical data) and (5) are computationally tractable. To that end, this work examines a set of filter-style feature selection algorithms inspired by the ‘Relief’ algorithm, i.e. Relief-Based algorithms (RBAs). We implement and expand these RBAs in an open source framework called ReBATE (Relief-Based Algorithm Training Environment). We apply a comprehensive genetic simulation study comparing existing RBAs, a proposed RBA called MultiSURF, and other established feature selection methods, over a variety of problems. The results of this study (1) support the assertion that RBAs are particularly flexible, efficient, and powerful feature selection methods that differentiate relevant features having univariate, multivariate, epistatic, or heterogeneous associations, (2) confirm the efficacy of expansions for classification vs. regression, discrete vs. continuous features, missing data, multiple classes, or class imbalance, (3) identify previously unknown limitations of specific RBAs, and (4) suggest that while MultiSURF∗ performs best for explicitly identifying pure 2-way interactions, MultiSURF yields the most reliable feature selection performance across a wide range of problem types.

Downregulation of miR-130a, antagonized doxorubicin-induced cardiotoxicity via increasing the PPAR\u03b3 expression in mESCs-derived cardiac cells

Doxorubicin (Dox) is a widely used powerful chemotherapeutic component for cancer treatment. However, its clinical application has been hampered due to doxorubicin-induced cardiomyopathy upon the cessation of chemotherapy. Previous studies revealed that PPARγ plays a crucial protective role in cardiomyocytes. Modulation of miRNA expression is an applicable approach for prohibition of toxicity induction. Therefore, the aim of present study is uprising of PPARγ transcript levels via manipulation of miRNAs to limit Dox-induced cardiotoxicity in mESCs-derived cardiac cells, as in vitro model cell to provide a simple direct approach for further clinical therapies. Based on bioinformatics data mining, eventually miR-130a was selected to target PPARγ. This miRNA is highly expressed in heart. The expression of miR-130a increases sharply upon Dox treatment while specific antagomiR-130a reverses Dox-induced reduced expression of PPARγ, cellular apoptosis, and inflammation. Our data strongly suggest that antagomiR-130a limits Dox-induced cellular toxicity via PPARγ upregulation and may have clinical relevance to limit in vivo Dox toxicity.

A Survey of Data Mining and Deep Learning in Bioinformatics.

The fields of medicine science and health informatics have made great progress recently and have led to in-depth analytics that is demanded by generation, collection and accumulation of massive data. Meanwhile, we are entering a new period where novel technologies are starting to analyze and explore knowledge from tremendous amount of data, bringing limitless potential for information growth. One fact that cannot be ignored is that the techniques of machine learning and deep learning applications play a more significant role in the success of bioinformatics exploration from biological data point of view, and a linkage is emphasized and established to bridge these two data analytics techniques and bioinformatics in both industry and academia. This survey concentrates on the review of recent researches using data mining and deep learning approaches for analyzing the specific domain knowledge of bioinformatics. The authors give a brief but pithy summarization of numerous data mining algorithms used for preprocessing, classification and clustering as well as various optimized neural network architectures in deep learning methods, and their advantages and disadvantages in the practical applications are also discussed and compared in terms of their industrial usage. It is believed that in this review paper, valuable insights are provided for those who are dedicated to start using data analytics methods in bioinformatics.

Gene-to-Gene Network Analysis of the Mediation of Plant Innate Immunity by the Eliciting Plant Response-Like 1 (Epl1) Elicitor of Trichoderma formosa.

A new clade, Trichoderma formosa, secretes eliciting plant response-like 1 (Epl1), a small peptide elicitor that stimulates plant immunity. Nicotiana benthamiana pretreated with Epl1 for 3 days developed immunity against Tomato mosaic virus (ToMV) infection. The transcriptome profiles of T. formosa and N. benthamiana were obtained by deep sequencing; the transcript of Epl1 is 736 nt in length and encodes a 12-kDa peptide. Identifying critical genes in Epl1-mediated immunity was challenging due to high similarity between the transcriptome expression profiles of Epl1-treated and ToMV-infected N. benthamiana samples. Therefore, an efficient bioinformatics data mining approach was used for high-throughput transcriptomic assays in this study. We integrated gene-to-gene network analysis into the ContigViews transcriptome database, and genes related to jasmonic acid and ethylene signaling, salicylic acid signaling, leucine-rich repeats, transcription factors, and histone variants were hubs in the gene-to-gene networks. In this study, the Epl1 of T. formosa triggers plant immunity against various pathogen infections. Moreover, we demonstrated that high-throughput data mining and gene-to-gene network analysis can be used to identify critical candidate genes for further studies on the mechanisms of plant immunity.