Differential expression of mucin 1 and mucin 2 in colorectal cancer

AIM To determine tissue expression(mRNA, protein) of two types of mucins [mucin 1(MUC1) and mucin 2(MUC2)] in patients with colorectal cancer(CRC).METHODS Expression of membrane-bound mucin(MUC1) and secretory mucin(MUC2) in CRC(mRNA, protein) were analyzed in tissue material including fragments of tumorsobtained from CRC patients(n = 34), and fragments of normal colorectal tissue from the same patients(control). The analysis was conducted using real-time quantitative polymerase chain reaction(RT-qPCR)(transcripts), immunohistochemistry(IHC)(apomucins), and the modern approach for morphometric analysis of IHC reaction(HSV filter software). Results on tissue expression of both mucins(mRNA, protein) were compared to histological alterations in colorectal cancer samples and correlated with selected clinical data in the patients. The statistical analysis was conducted using Statistica PL v. 12.0 software.RESULTS Significantly higher expression of the MUC1 mRNA in the CRC, compared with the control and the borderline correlation of mRNA expression with MUC1 protein levels in colorectal samples was observed. The expression of apomucins concerned cell membranes(MUC1) and cytoplasm(MUC2) and occurred both in control tissues and in most cancerous samples. There were no significant relationships between MUC1(mRNA, protein) and the clinicopathological data of patients. MUC2 protein expression was significantly lower as compared to the control, while MUC2 mRNA expression was comparable in both groups. The MUC1/MUC2 ratio was significantly higher in CRC tissues than in the control. The higher expression of MUC2 was a feature of mucinous CRC subtypes, and characterized higher histological stage of tumors. Negative correlations have been obtained between MUC2 and the Ki-67 antigen, as well as between MUC2 and p53 protein expressions in CRC.CONCLUSION A combination of tissue overexpression of MUC1, reduced MUC2 expression, and high ratio of MUC1/MUC2 is a factor of poor prognosis in CRC patients. MUC2 tissue expression allows to differentiate mucinous and nonmucinous CRC subtypes.

Insulin-like growth factor-1 mRNA isoforms and insulinlike growth factor-1 receptor mRNA expression in chronic hepatitis C

AIM: to evaluate the expression of different insulinlike growth factor(IGF)-1 mRNA isoforms and IGF-1 receptor(IGF-1R) mRNA in hepatitis C virus(HCV)-infected livers. METHODS: Thirty-four liver biopsy specimens from chronic hepatitis C(CH-C) patients were obtained before anti-viral therapy. Inflammatory activity(grading) and advancement of fibrosis(staging) were evaluated using a modified point scale of METAVIR. The samples were analyzed using quantitative real-time PCR technique. From fragments of liver biopsies and control liver that were divided and ground in liquid nitrogen, RNA was isolated using RNeasy Fibrous Tissue Mini Kit according to the manufacturer's instruction. Expression levels of IGF-1 mRNA isoforms(IGF-1A, IGF-1B, IGF-1C, P1, and P2) and IGF-1R mRNA were determined through normalization of copy numbers in samples as related to reference genes: glyceraldehyde-3-phosphate dehydrogenase and hydroxymethylbilane synthase. Results on liver expression of the IGF-1 mRNA isoforms and IGF-1R transcript were compared to histological alterations in liver biopsies and with selected clinical data in the patients. Statistical analysis was performed using Statistica PL v. 9 software. RESULTS: The study showed differences in quantitative expression of IGF-1 mRNA variants in HCV-infected livers, as compared to the control. Higher relative expression of total IGF-1 mRNA and of IGF-1 mRNAs isoforms(P1, A, and C) in HCV-infected livers as compared to the control were detected. Within both groups, expression of the IGF-1A mRNA isoform significantly prevailed over expressions of B and C isoforms. Expression of P1 mRNA was higher than that of P2 only in CH-C. Very high positive correlations were detected between reciprocal expressions of IGF-1 mRNA isoforms P1 and P2(r = 0.876). Expression of P1 and P2 mRNA correlated with IGF-1A mRNA(r = 0.891; r = 0.821, respectively), with IGF-1B mRNA(r = 0.854; r = 0.813, respectively), and with IGF-1C mRNA(r = 0.839; r = 0.741, respectively). Expression of IGF-1A mRNA significantly correlated with isoform B and C mRNA(r = 0.956; r = 0.869, respectively), and B with C isoforms(r = 0.868)(P < 0.05 in all cases). Lower expression of IGF-1A and B transcripts was noted in the more advanced liver grading(G2) as compared to G1. Multiple negative correlations were detected between expression of various IGF-1 transcripts and clinical data(e.g., alpha fetoprotein, HCV RNA, steatosis, grading, and staging). Expression of IGF-1R mRNA manifested positive correlation with grading and HCV-RNA. CONCLUSION: Differences in quantitative expression of IGF-1 mRNA isoforms in HCV-infected livers, as compared to the control, suggest that HCV may induce alteration of IGF-1 splicing profile.

Electrochemical,spectroscopic,and molecular docking studies of the interaction between the anti-retroviral drug indinavir and dsDNA

In this study,an electrochemical DNA biosensor was developed using a straightforward methodology to investigate the interaction of indinavir with calf thymus double-stranded deoxyribonucleic acid(ctdsDNA)for the first time.The decrease in the oxidation signals of deoxyguanosine(dGuo)and deoxyadenosine(dAdo),measured by differential pulse voltammetry,upon incubation with different concentrations of indinavir can be attributed to the binding mode of indinavir to ct-dsDNA.The currents of the dGuo and dAdo peaks decreased linearly with the concentration of indinavir in the range of 1.0 e10.0 mg/mL.The limit of detection and limit of quantification for indinavir were 0.29 and 0.98 mg/mL,respectively,based on the dGuo signal,and 0.23 and 0.78 mg/mL,respectively,based on the dAdo signal.To gain further insights into the interaction mechanism between indinavir and ct-dsDNA,spectroscopic measurements and molecular docking simulations were performed.The binding constant(Kb)between indinavir and ct-dsDNA was calculated to be 1.64108 M1,based on spectrofluorometric measurements.The obtained results can offer insights into the inhibitory activity of indinavir,which could help to broaden its applications.That is,indinavir can be used to inhibit other mechanisms and/or hallmarks of viral diseases.

Application of Biochemical Tests and Machine Learning Techniques to Diagnose and Evaluate Liver Disease

Background: The liver function tests (LFTs) remain one of the most commonly employed clinical measures for the diagnosis of hepatobiliary disease. LFTs sometimes referred to as hepatic panel help to determine the health of liver, monitor the progression of a disease and measure the severity of a disease particularly scarring or cirrhosis of the liver. Aims: In this study, we present a new approach to evaluate the natural progression of liver disease through the assessment of eight biochemical parameters: serum total bilirubin (TB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), Alkaline phosphatase (ALP), total protein (TP), albumin (ALB), albumin/globulin (A/G) ratio, and alpha-fetoprotein (AFP) as well as two machine learning (ML) tools—Random Forest and CART to substantive the outcome. Methods: The study was carried out in a total of 100 subjects which included healthy controls (group I-25 patients), patients with acute hepatitis (group II-25 patients), chronic hepatitis (group III-25 patients) and hepatocellular carcinoma (group IV-25 patients) applying both biochemical and Machine Learning methods. Results: Of the eight parameters tested, all except ALP (p = 0.426), showed an overall discriminatory ability as judged by one-factor analysis of variance (p < 0.0001). We also assessed the differences among group means by least significance difference (LSD). The analysis showed that TB remained significantly elevated in groups II, III, and IV as compared to controls (p < 0.05). ALP did not have any discriminatory power among the four groups tested. ALT and AST were good discriminators only between the control groups and groups II and III. TP, ALB, and A/G ratio were decreased significantly in groups III and IV as compared to controls. Group III and IV were almost indistinguishable using these biochemical parameters except for AFP, which was found to be elevated only in group IV. The accuracy of classification into different liver patient groups using random Forest and CART was 94% and 95% respectively. Conclusion: Acute hepatitis (group II) shows a higher level of AST, ALT and ALP compared to chronic hepatitis (group III) and hepatocellular carcinoma (group IV). Two machine learning algorithms also predicted and supported the same biochemical results by correctly classifying liver disease patients. We also recommend that the AFP test can be performed if hepatocellular carcinoma is suspected.

Functional analysis and screening small molecules to RpfF protein in Xanthomonas oryzae involved in rice bacterial blight disease

Xanthomonas oryzae pv.oryzae(Xoo) is an important rice pathogen.This is a vascular pathogen entering the plant via the hydathodes causing rice bacterial blight.It has been known that most regulation of pathogenicity factor F(RpfF) genes in Xanthomonas regulates virulence in response to the diffusible signal factor(DSF).The RpfF recognized as an attractive drug target in bacterial rice blight disease.In this study,we performed the gene-gene interaction of RpfF and pathway functional analysis.3 D structure of RpfF protein was predicted using a homology modelling tool Swiss-Model and refined by molecular dynamics(MD) simulation.The refined model protein was predicted structural assessment using various tools such as PROCHECK,ERRAT,and VERIFY-3 D.We have collected 2 500 rifampicin analogues from Zinc Database by virtual screening.The screened compounds were docked into the active site of the RpfF protein using AutoDock Vina in PyRx Virtual Screening Tool.Furthermore,docking result and in silico ADMET analysis described that the compounds ZINC03056414,ZINC03205310,ZINC08673779,ZINC09100848,ZINC09729566,ZINC11415953,ZINC12810788,ZINC24989313,ZINC27441787 and ZINC32739565 have best binding energies and less toxicity than reference compound.This study revealed that the active site residues such as HIS-118,HIS-147,THR-148,ARG-179,ASP-207,ARG-240 and THR-244 are key roles in the pathogenicity.It could be beneficial in the design of small molecule therapeutics or the treatment of rice bacterial blight disease.

Designing Genetic Regulatory Networks Using Fuzzy Petri Nets Approach

In this paper, we have successfully presented a fuzzy Petri net （FPN） model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the FPN, we present an alternative approach that is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. In this paper, a novel model with a new concept of hidden fuzzy transition （HFT） to design the genetic regulatory network is developed. We have built the FPN model and classified the input data in terms of time point and obtained the output data, so the system can be viewed as the two-input and one output system. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. The experimental results show the proposed approach is feasible and acceptable to design the genetic regulatory network and investigate the dynamical behaviors of gene network.

Dysregulated TCA Cycle Pathway in Endometrial Cancer

Background:Numerous questions regarding metabolism alterations in endometrial cancer remain unanswered.Methods:We used the Mann-Whitney test to identify significantly downregulated genes in Cluster II,which were then subject to Ingenuity Pathway Analysis and Gene Ontology(GO)enrichment analysis.We next compared the expression levels of several key enzymes between the CTNNB1 mutant and wide-type patients to correlate“TCA Cycle”alterations with CTNNB1 mutation status.Finally,we performed a Spearman correlation between the TCA Cycle genes and the immune checkpoint molecule to understand the relationship between TCA Cycle dysfunction and immune response.All statistical tests were two-sided.Results:A total of 603 genes were significantly downregulated in Cluster II.Pathway analysis showed that metabolic pathways were frequently dysregulated,and GO analysis demonstrated that metabolic processes were commonly retarded.In particular,TCA Cycle is the most significantly altered metabolic pathway(P=1.45×10-07),with one-third of the enzymes altered.The TCA Cycle pathway activity and the expression levels of several key enzymes were significantly lower in CTNNB1 mutant patients,compared to CTNNB1 wide-type patients.In addition,the TCA Cycle pathway activity and the expression levels of pathway genes were significantly and positively correlated with PD-L1 gene expression.Conclusion:This study systematically characterizes a subset of endometrioid endometrial cancer patients with dysregulated TCA Cycle pathway,which may contribute to immune resistance in endometrial cancer.

Reversible phosphorylation of the 26S proteasome

The 26S proteasome at the center of the ubiquitin- proteasome system （UPS） is essential for virtually all cellular processes of eukaryotes. A common miscon- ception about the proteasome is that, once made, it remains as a static and uniform complex with sponta- neous and constitutive activity for protein degradation. Recent discoveries have provided compelling evidence to support the exact opposite insomuch as the 26S proteasome undergoes dynamic and reversible phos- phorylation under a variety of physiopathological con- ditions. In this review, we summarize the history and current understanding of proteasome phosphorylation, and advocate the idea of targeting proteasome kinases/ phosphatases as a new strategy for clinical interven- tions of several human diseases.

Identification of Conserved Regulatory Elements in Mammalian Promoter Regions:A Case Study Using the PCK1 Promoter

A systematic phylogenetic footprinting approach was performed to identify conserved transcription factor binding sites （TFBSs） in mammalian promoter regions using human, mouse and rat sequence alignments. We found that the score distributions of most binding site models did not follow the Gaussian distribution required by many statistical methods. Therefore, we performed an empirical test to establish the optimal threshold for each model. We gauged our computational predictions by comparing with previously known TFBSs in the PCK1 gene promoter of the cytosolic isoform of phosphoenolpyruvate carboxykinase, and achieved a sensitivity of 75% and a specificity of approximately 32% Almost all known sites overlapped with predicted sites, and several new putative TFBSs were also identified. We validated a predicted SP1 binding site in the control of PCK1 transcription using gel shift and reporter assays. Finally, we applied our computational approach to the prediction of putative TFBSs within the promoter regions of all available RefSeq genes. Our full set of TFBS predictions is freely available at http：//bfgl.anri.barc.usda.gov/tfbsConsSites.

Genome-Wide Analysis of Epigenetic Modifications

In plants and animals, gene expression can be altered by changes that do not alter the sequence of nucleotides in DNA but rather modify the chemical structure of either the DNA or the histones that interact with the DNA. These so-called epigenetic modifications are not transient, but persist through cell divisions. Rapidly advancing technologies, such as next-generation DNA sequencing, have dramatically increased our ability to survey epigenetic markers throughout an entire genome. These techniques are revealing in great detail that the many forms and stages of cancer are characterized by a massive number of epigenetic changes. Interpreting such epigenetic marks in cell differentiation and in carcinogenesis is computationally challenging. We review several examples of epigenetic data analysis and discuss the need for computational methods that will enable us to learn from the data the relationships between different kinds of histone modifications and DNA methylation.

Convergent Usage of Amino Acids in Human Cancers as A Reversed Process of Tissue Development

Genome-and transcriptome-wide amino acid usage preference across different species is a well-studied phenomenon in molecular evolution,but its characteristics and implication in cancer evolution and therapy remain largely unexplored.Here,we analyzed large-scale transcriptome/proteome profiles,such as The Cancer Genome Atlas(TCGA),the Genotype-Tissue Expression(GTEx),and the Clinical Proteomic Tumor Analysis Consortium(CPTAC),and found that compared to normal tissues,different cancer types showed a convergent pattern toward using biosynthetically low-cost amino acids.Such a pattern can be accurately captured by a single index based on the average biosynthetic energy cost of amino acids,termed energy cost per amino acid(ECPA).With this index,we further compared the trends of amino acid usage and the contributing genes in cancer and tissue development,and revealed their reversed patterns.Finally,focusing on the liver,a tissue with a dramatic increase in ECPA during development,we found that ECPA represents a powerful biomarker that could distinguish liver tumors from normal liver samples consistently across 11 independent patient cohorts and outperforms any index based on single genes.Our study reveals an important principle underlying cancer evolution and suggests the global amino acid usage as a system-level biomarker for cancer diagnosis.

Profiling of immune features to predict immunotherapy efficacy

Immune checkpoint blockade(ICB)therapies exhibit substantial clinical benefit in different cancers,but relatively low response rates in the majority of patients highlight the need to understand mutual relationships among immune features.Here,we reveal overall positive correlations among immune checkpoints and immune cell populations.Clinically,patients benefiting from ICB exhibited increases for both immune stimulatory and inhibitory features after initiation of therapy,suggesting that the activation of the immune microenvironment might serve as the biomarker to predict immune response.As proof-of-concept,we demonstrated that the immune activation score(ISD)based on dynamic alteration of interleukins in patient plasma as early as two cycles(4-6 weeks)after starting immunotherapy can accurately predict immunotherapy efficacy.Our results reveal a systematic landscape of associations among immune features and provide a noninvasive,cost-effective,and time-efficient approach based on dynamic profiling of pre-and on-treatment plasma to predict immunotherapy efficacy.