Protein ANalysis THrough Evolutionary Relationships Research Articles

Computational Analysis of Single Nucleotide Polymorphisms in Human HIC1 Gene.

Background A putative tumor suppressor gene called HIC1 (hypermethylated in cancer) is situated at 17p13.3, a locus where the allelic loss occurs often in human malignancies, including breast cancer. Hypermethylated in cancer 1 protein is a protein that in humans is encoded by the HIC1 gene and it's aHomo sapiens(Human). This gene functions as a growth regulatory and tumor repressor gene. The molecular function of HIC1 gene includes DNA-binding transcription factor activity, sequence-specific DNA binding, DNA binding, histone deacetylase binding, protein binding, metal ion binding, nucleic acid binding, DNA-binding transcription repressor activity, RNA polymerase II-specific, DNA-binding transcription factor activity, RNA polymerase II-specific. The biological process of HIC1 gene includes multicellular organism development, negative regulation of Wnt signaling pathway, positive regulation of DNA damage response, signal transduction by p53 class mediator regulation of transcription, DNA-templated, negative regulation of transcription by RNA polymerase II, Wnt signaling pathway, transcription, DNA-templated, intrinsic apoptotic signaling pathway in response to DNA damage, cellular response to DNA damage stimulus. The study aimed to predict the stability and structure of the protein that will arise from single nucleotide polymorphisms (SNPs) in the human HIC1 gene. Methodology To investigate the possible negative effects associated with these SNPs, bioinformatic analysis is typically essential. The following tools were employed for forecasting harmful SNPs: scale-invariant feature transform (SIFT), Protein Analysis Through Evolutionary Relationships (PANTHER), nonsynonymous SNP by Protein Variation Effect Analyzer (PROVEAN), and nonsynonymous SNP by Single Nucleotide Polymorphism Annotation Platform (SNAP). Results The present study identified a total of 36 SNPs using the SIFT approach, which were shown to have functional significance. Twenty-six were determined to be tolerable, whereas 10 were shown to be detrimental. Out of 20 SNPs, seven (P370A, P646S, R654P, A476T, S400S, D666N, D7V) SNPs were predicted as "Possibly damaging" and seven (L9F, G468R, G490R, L482R, S12W, G489D, S12P) were identified as "probably benign", and six (R725G, G620S, A56V, E463D, D394N, L338V) were identified as "probably damaging" according to the predictions made by PANTHER tools. The majority of the pixels on the strip were red, indicating that the gene changes may have dangerous consequences. These results highlight the need for more research to fully comprehend how these mutations affect the hic1 protein's function, which is essential for the emergence of different types of cancer. Conclusion The current research has provided us with essential information about how SNPs might be used as a diagnostic marker for cancer, given that SNPs may be candidates for cellular changes caused by mutations linked to cancer.

Computational Exploration of Single-Nucleotide Polymorphisms in the Human hRAS Gene: Implications and Insights.

Background A group of genes called oncogenes includes the Harvey rat sarcoma virus (hRAS) gene. Along with hRAS, Kirsten rat sarcoma viral oncogene homolog (kRAS) and neuroblastoma RAS viral oncogene homolog(nRAS) genes belong to the Rat sarcoma (Ras) family of oncogenes. These three genes result in Rho guanosine triphosphate hydrolases (GTPases) as their protein product. Instructions for producing the protein hRAS, which is mainly involved in controlling cell division, are provided by the hRAS gene. The hRAS protein transfers signals from outside through a process called signal transduction.Because the hRAS protein is a GTPase, it changes the chemical guanosine-5'-triphosphate (GTP) into guanosine diphosphate (GDP). GTP and GDP molecules operate as switches to turn on and off the hRAS. This study aimed to anticipate the structure and stability of the protein resulting from missense single-nucleotide polymorphisms (SNPs) in the human hRAS genes. Methodology To investigate the possible negative effects associated with these SNPs, bioinformatic analysis is typically essential. The following tools were employed for forecasting harmful SNPs: Scale-Invariant Feature Transform (SIFT), Protein Analysis Through Evolutionary Relationships (PANTHER), non-synonymous SNP by Protein Variation Effect Analyzer (PROVEAN), and non-synonymous SNP by Single Nucleotide Polymorphism Annotation Platform (SNAP). Results The present study identified a total of 11 SNPs using the SIFT approach, which were shown to have functional significance. Only two of these 11 SNPs were determined to be tolerable, whereas nine were shown to be detrimental. Among the 11 SNPs analyzed, seven (Q61H, Q99H, K117R, A121D, A146V, R169W, R169Q) were classified as possibly damaging,and four (G13V, Q22K, Q61K, Q13V) were categorized as probably benign according to the predictions made by PANTHER tools. Therefore, the seven SNPs were identified as high-risk SNPs. Conclusions Given that SNPs have the potential to be candidates for cellular alterations brought on by mutations that are associated with cancer, this study provides vital information about how SNPs might be utilized as a diagnostic marker for cancer.

Fc gamma receptor IIb in tumor-associated macrophages and dendritic cells drives poor prognosis of recurrent glioblastoma through immune-associated signaling pathways.

Background: Among central nervous system tumors, glioblastoma (GBM) is considered to be the most destructive malignancy. Recurrence is one of the most fatal aspects of GBM. However, the driver molecules that trigger GBM recurrence are currently unclear. Methods: The mRNA expression data and clinical information of GBM and normal tissues were collected from the Chinese Glioma Genome Atlas The Cancer Genome Atlas (TCGA), and REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT) cohorts. The DESeq2 R package was used to identify the differentially expressed genes between primary and recurrent GBM. ClueGO, Kyoto Encyclopedia of Genes and Genomes (KEGG), Biological Process in Gene ontology (GO-BP), and the Protein ANalysis THrough Evolutionary Relationships (PANTHER) pathway analyses were performed to explore the enriched signaling pathways in upregulated DEGs in recurrent GBM. A gene list that contained potential oncogenes that showed a significant negative correlation with patient survival from The Cancer Genome Atlas was used to further screen driver candidates for recurrent GBM. Univariate Cox proportional hazards regression analyses were used to investigate the risk score for the mRNA expression of the candidates. Single-cell RNA sequencing (scRNA-Seq) analyses were used to determine the cell type-specific distribution of Fc gamma receptor II b (FcγRIIb) in GBM. Immunohistochemistry (IHC) was used to confirm the FcγRIIb-positive cell populations in primary and paired recurrent GBM. Results: Through DEG analysis and overlap analysis, a total of 10 genes that are upregulated in recurrent GBM were screened. Using validation databases, FcγRIIb was identified from the 10 candidates that may serve as a driver for recurrent GBM. FCGR2B expression, not mutation, further showed a highly negative correlation with the poor prognosis of patients with recurrent GBM. Furthermore, scRNA-Seq analyses revealed that tumor-associated macrophage- and dendritic cell-specific FCGR2B was expressed. Moreover, FcγRIIb also showed a strong positive correlation coefficient with major immune-associated signaling pathways. In clinical specimens, FcγRIIb-positive cell populations were higher in recurrent GBM than in primary GBM. Conclusion: This study provides novel insights into the role of FcγRIIb in recurrent GBM and a promising strategy for treatment as an immune therapeutic target.

Identification of quantitative trait loci (QTLs) and candidate genes for seed shape and 100-seed weight in soybean [Glycine max (L.) Merr.].

Seed size and shape are important traits determining yield and quality in soybean. Seed size and shape are also desirable for specialty soy foods like tofu, natto, miso, and edamame. In order to find stable quantitative trait loci (QTLs) and candidate genes for seed shape and 100-seed weight, the current study used vegetable type and seed soybean-derived F2 and F2:3 mapping populations. A total of 42 QTLs were mapped, which were dispersed across 13 chromosomes. Of these, seven were determined to be stable QTLs and five of them were major QTLs, namely qSL-10-1, qSW-4-1, qSV-4-1, qSLW-10-1, and qSLH-10-1. Thirteen of the 42 QTLs detected in the current study were found at known loci, while the remaining 29 were discovered for the first time. Out of these 29 novel QTLs, 17 were major QTLs. Based on Protein Analysis Through Evolutionary Relationships (PANTHER), gene annotation information, and literature search, 66 genes within seven stable QTLs were predicted to be possible candidate genes that might regulate seed shape and seed weight in soybean. The current study identified the key candidate genes and quantitative trait loci (QTLs) controlling soybean seed shape and weight, and these results will be very helpful in marker-assisted breeding for developing soybean varieties with improved seed weight and desired seed shape.

Quantitative Proteomic Analysis of Non-Tobacco Associated Oral Squamous Cell Carcinoma Reveals Deregulation of Cytoskeletal and Apoptotic Proteins

The exact etiology of non-tobacco associated oral squamous cell carcinoma (NT-OSCC) is still unknown. The lack of established biomarkers for oral NT-OSCC has resulted in less effective management and poor prognosis. Here, we report for the first time a panel of potential markers identified from the quantitative proteomic analysis of NT-OSCC using two-dimensional gel-electrophoresis (2D-GE) using matrix-assisted laser desorption/ionization - time of flight (MALDI-TOF) coupled with mass spectrometry (MS) and further analysis using protein analysis through evolutionary relationships (PANTHER) database. To quantitatively analyze the proteomic profile of non-tobacco associated oral squamous cell carcinoma. Twenty fresh tissue samples were collected from healthy controls and NT-OSCC, ten each, and were subjected to proteomic analysis. Sample quantification for the presence of protein was done using Bradford assay and bovine serum albumin was used as a standard protein to obtain the standard graph. Fractionation of protein was done using sodium dodecyl sulphate - polyacrylamide gel electrophoresis (SDS-PAGE) and they were separated based on their molecular weight. MS analysis was done and the purified peptides were analysed using MALDI-TOF. PANTHER database for functional classification and pathway analysis was done for identification of protein expression. Our approach of combining 2D-GE with MS identified four candidate proteins including keratin, alpha-1-antitrypsin (AAT), S100 and serpin B5 with significant differential expression in NT-OSCC as compared with healthy controls. The results showed that the levels of these proteins were significantly upregulated in NT-OSCC when compared to the healthy controls that suggests that these proteins can be used as candidate targets for NT-OSCC therapeutics. The differentially expressed proteins are found to be involved in apoptotic signalling pathways, cytoskeletal dynamics and are known to play a critical role in oral tumorigenesis. Put together, the results provide available baseline information for understanding the development and progression of NT-OSCC. These identified proteins on further validation may be used as potential biomarkers in future for early detection and predicting therapeutic outcome of patients with NT-OSCC.

Role of epigallocatechin-3- gallate in the regulation of known and novel microRNAs in breast carcinoma cells.

Breast cancer comprises 30% of all cancer cases among the world’s women population. MicroRNAs are small, endogenous, non-coding RNAs that regulate cell proliferating and apoptotic pathways by modulating expressions of related genes. Phytochemicals like epigallocatechin-3-gallate (EGCG) are known to have a chemotherapeutic effect on cancer often through the regulation of microRNAs. The aim is to find out the key known and novel miRNAs, which are controlled by EGCG in breast cancer cell line MDA-MB-231. Next-generation sequencing (NGS) revealed 1,258 known and 330 novel miRNAs from untreated and 83 μM EGCG (IC50 value of EGCG) treated cells. EGCG modulated 873 known and 47 novel miRNAs in the control vs. treated sample. The hypothesis of EGCG being a great modulator of miRNAs that significantly control important cancer-causing pathways has been established by analyzing with Kyoto Encyclopedia of Genes and Genomes (KEGG) and Protein Analysis Through Evolutionary Relationships (PANTHER) database. Validation of known and novel miRNA expression differences in untreated vs. treated cells was done using qPCR. From this study, a few notable miRNAs were distinguished that can be used as diagnostics as well as prognostic markers for breast cancer.

Exploring the mutational landscape of genes associated with inherited retinal disease using large genomic datasets: identifying loss of function intolerance and outlying propensities for missense changes

BackgroundLarge databases permit quantitative description of genes in terms of intolerance to loss of function (‘haploinsufficiency’) and prevalence of missense variants. We explored these parameters in inherited retinal disease (IRD)...

Toxocara canis- and Toxocara cati-Induced Neurotoxocarosis Is Associated with Comprehensive Brain Transcriptomic Alterations.

Toxocara canis and Toxocara cati are globally occurring zoonotic roundworms of dogs and cats. Migration and persistence of Toxocara larvae in the central nervous system of paratenic hosts including humans may cause clinical signs of neurotoxocarosis (NT). As pathomechanisms of NT and host responses against Toxocara larvae are mostly unknown, whole-genome microarray transcription analysis was performed in cerebra and cerebella of experimentally infected C57Bl/6J mice as paratenic host model at days 14, 28, 70, 98, and 120 post-infection. Neuroinvasion of T. cati evoked 220 cerebral and 215 cerebellar differentially transcribed genes (DTGs), but no particular PANTHER (Protein ANalysis THrough Evolutionary Relationships) pathway was affected. In T. canis-infected mice, 1039 cerebral and 2073 cerebellar DTGs were identified. Statistically significant dysregulations occurred in various pathways, including cholesterol biosynthesis, apoptosis signaling, and the Slit/Robo mediated axon guidance as well as different pathways associated with the immune and defense response. Observed dysregulations of the cholesterol biosynthesis, as well as the Alzheimer disease-amyloid secretase pathway in conjunction with previous histopathological neurodegenerative findings, may promote the discussion of T. canis as a causative agent for dementia and/or Alzheimer’s disease. Furthermore, results contribute to a deeper understanding of the largely unknown pathogenesis and host-parasite interactions during NT, and may provide the basis for prospective investigations evaluating pathogenic mechanisms or designing novel diagnostic and therapeutic approaches.

Meta-Analysis and Bioinformatics Detection of Susceptibility Genes in Diabetic Nephropathy.

The latest meta-analysis of genome-wide linkage studies (GWLS) identified nine cytogenetic locations suggestive of a linkage with diabetic nephropathy (DN) due to type 1 diabetes mellitus (T1DM) and seven locations due to type 2 diabetes mellitus (T2DM). In order to gain biological insight about the functional role of the genes located in these regions and to prioritize the most significant genetic loci for further research, we conducted a gene ontology analysis with an over representation test for the functional annotation of the protein coding genes. Protein analysis through evolutionary relationships (PANTHER) version 16.0 software and Cytoscape with the relevant plugins were used for the gene ontology analysis, and the overrepresentation test and STRING database were used for the construction of the protein network. The findings of the over-representation test highlight the contribution of immune related molecules like immunoglobulins, cytokines, and chemokines with regard to the most overrepresented protein classes, whereas the most enriched signaling pathways include the VEGF signaling pathway, the Cadherin pathway, the Wnt pathway, the angiogenesis pathway, the p38 MAPK pathway, and the EGF receptor signaling pathway. The common section of T1DM and T2DM results include the significant over representation of immune related molecules, and the Cadherin and Wnt signaling pathways that could constitute potential therapeutic targets for the treatment of DN, irrespective of the type of diabetes.

Cadherin and Wnt signaling pathways as key regulators in diabetic nephropathy.

AimA recent meta-analysis of genome-wide linkage studies (GWLS) has identified multiple genetic regions suggestive of linkage with DN harboring hundreds of genes. Moving this number of genetic loci forward into biological insight is truly the next step. Here, we approach this challenge with a gene ontology (GO) analysis in order to yield biological and functional role to the genes, an over-representation test to find which GO terms are enriched in the gene list, pathway analysis, as well as protein network analysis.MethodGO analysis was performed using protein analysis through evolutionary relationships (PANTHER) version 14.0 software and P-values less than 0.05 were considered statistically significant. GO analysis was followed by over-representation test for the identification of enriched terms. Statistical significance was calculated by Fisher’s exact test and adjusted using the false discovery rate (FDR) for correction of multiple tests. Cytoscape with the relevant plugins was used for the construction of the protein network and clustering analysis.ResultsThe GO analysis assign multiple GO terms to the genes regarding the molecular function, the biological process and the cellular component, protein class and pathway analysis. The findings of the over-representation test highlight the contribution of cell adhesion regarding the biological process, integral components of plasma membrane regarding the cellular component, chemokines and cytokines with regard to protein class, while the pathway analysis emphasizes the contribution of Wnt and cadherin signaling pathways.ConclusionsOur results suggest that a core feature of the pathogenesis of DN may be a disturbance in Wnt and cadherin signaling pathways, whereas the contribution of chemokines and cytokines need to be studied in additional studies.

Investigation of long interspersed element-1 retrotransposons as potential risk factors for idiopathic temporal lobe epilepsy.

To determine if long interspersed element-1 (L1) retrotransposons convey risk for idiopathic temporal lobe epilepsy (TLE). Surgically resected temporal cortex from individuals with TLE (N=33) and postmortem temporal cortex from individuals with no known neurological disease (N=33) were analyzed for L1 content by Restriction Enzyme Based Enriched L1Hs sequencing (REBELseq). Expression of three KCNIP4 splice variants was assessed by droplet digital PCR (ddPCR). Protein ANalysis THrough Evolutionary Relationships (PANTHER) was used to determine ontologies and pathways for lists of genes harboring L1 insertions. We identified novel L1 insertions specific to individuals with TLE, and others specific to controls. Although there were no statistically significant differences between cases and controls in the numbers of known and novel L1 insertions, PANTHER analyses of intragenic L1 insertions showed statistically significant enrichments for epilepsy-relevant gene ontologies in both cases and controls. Gene ontologies "neuron projection development" and "calcium ion transmembrane transport" were among those found only in individuals with TLE. We confirmed novel L1 insertions in several genes associated with seizures/epilepsy, including a de novo somatic L1 retrotransposition in KCNIP4 that occurred after neural crest formation in one patient. However, ddPCR results suggest this de novo L1 did not alter KCNIP4 mRNA expression. Given current data from this small cohort, we conclude that L1 elements, either rare heritable germline insertions or de novo somatic retrotranspositions, may contribute only minimally to overall genetic risk for idiopathic TLE. We suggest that further studies in additional patients and additional brain regions are warranted.

Investigation of Genes Associated With Atherosclerosis in Patients With Systemic Lupus Erythematosus.

Objectives In this study, we aimed to identify patients with systemic lupus erythematosus (SLE) who are genetically at risk for developing atherosclerosis.Patients and methods Between November 2014 and May 2016, a total of 38 patients with SLE (36 females, 2 males; mean age: 37.6 years; range, 18 to 71 years) and 32 healthy females (mean age: 31.5 years; range, 19 to 54 years) were included in the study. Carotid intima-media thickness (CIMT) was measured using high-resolution B-mode ultrasonography. SurePrint G3 Human Gene Expression 8x60K Microarray kit was used in our study. Genes showing differences in expression between the groups were identified by using GeneSpring GX 10.0 program. Pathway analyses of gene expressions were performed using Ingenuity Pathways Analysis (IPA). Gene ontology analyses were performed using the Protein Analysis Through Evolutionary Relationships (PANTHER).Results Clinical findings of SLE patients were mainly photosensitivity (71.1%), arthritis (63.2%), lupus nephritis (55.3%), thrombocytopenia (26.3%), and autoimmune hemolytic anemia (21.1%). A total of 155 genes showing expression level difference were detected between SLE patients and healthy controls. In molecular network analysis, 28.2% of all genes were found to be directly or indirectly associated with atherosclerosis and cardiovascular disease.ConclusionIn SLE patients, many genes are expressed differently from healthy individuals. Expression of these genes is important in the pathogenesis of SLE. Genes identified differently in gene expression analysis can help us to identify SLE patients at risk for atherosclerosis in the Turkish population.

The presence of an embryo affects day 14 uterine transcriptome depending on the nutritional status in sheep. b. Immune system and uterine remodeling

Transcriptomics and bioinformatics were used to investigate the potential interactions of undernutrition and the presence of the conceptus at the time of maternal recognition of pregnancy on uterine immune system and remodeling. Adult Rasa Aragonesa ewes were allocated to one of two planes of nutrition for 28 days: maintenance energy intake (control; 5 cyclic, 6 pregnant ewes) providing 7.8 MJ of metabolisable energy and 0.5 maintenance intake (undernourished; 6 cyclic, 7 pregnant ewes) providing 3.9 MJ of metabolisable energy per ewe. Uterine gene expression was measured using Agilent 15 K Sheep Microarray chip on day 14 of estrus or pregnancy. Functional bioinformatics analyses were performed using PANTHER (Protein ANalysis THrough Evolutionary Relationships) Classification System. Pregnancy affected the expression of 18 genes in both control and undernourished ewes, underscoring the relevance for embryo-maternal interactions. Immune system evidenced by classical interferon stimulated genes were activated in control and -in a lesser extent-in undernourished pregnant vs cyclic ewes. Genes involved in uterine remodeling such as protein metabolism were also upregulated with the presence of an embryo in control and undernourished ewes. However, relevant genes for the adaptation of the uterus to the embryo were differentially expressed between pregnant vs cyclic ewes both in control and undernourished groups. Undernutrition alone led to an overall weak activation of immune system pathways both in cyclic and pregnant ewes. Data revealed that cellular and immune adaptations of the uterus to pregnancy are dependent on the nutritional status.

Functional genomics of AP-2\u03b1 and AP-2\u03b3 in cancers: in silico study

BackgroundAmong all causes of death, cancer is the most prevalent and is only outpaced by cardiovascular diseases. Molecular theory of carcinogenesis states that apoptosis and proliferation are regulated by groups of tumor suppressors or oncogenes. Transcription factors are example of proteins comprising representatives of both cancer-related groups. Exemplary family of transcription factors which exhibits dualism of function is Activating enhancer-binding Protein 2 (AP-2). Scientific reports concerning their function in carcinogenesis depend on particular family member and/or tumor type which proves the issue to be unsolved. Therefore, the present study examines role of the best-described AP-2 representatives, AP-2α and AP-2γ, through ontological analysis of their target genes and investigation what processes are differentially regulated in 21 cancers using samples deposited in Genomic Data Analysis Center (GDAC) Firehose.MethodsExpression data with clinical annotation was collected from TCGA-dedicated repository GDAC Firehose. Transcription factor targets were obtained from Gene Transcription Regulation Database (GTRD), TRANScription FACtor database (TRANSFAC) and Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRRUST). Monocle3 R package was used for global samples profiling while Protein ANalysis THrough Evolutionary Relationships (PANTHER) tool was used to perform gene ontology analysis.ResultsWith RNA-seq data and Monocle3 or PANTHER tools we outlined differences in many processes and signaling pathways, separating tumor from normal tissues or tumors from each other. Unexpectedly, a number of alterations in basal-like breast cancer were identified that distinguished it from other subtypes, which could bring future clinical benefits.ConclusionsOur findings indicate that while the AP-2α/γ role remains ambiguous, their activity is based on processes that underlie the cancer hallmarks and their expression could have potential in diagnosis of selected tumors.

Transcriptome Analyses of Candida albicans Biofilms, Exposed to Arachidonic Acid and Fluconazole, Indicates Potential Drug Targets.

Candida albicans is an opportunistic yeast pathogen within the human microbiota with significant medical importance because of its pathogenic potential. The yeast produces highly resistant biofilms, which are crucial for maintaining infections. Though antifungals are available, their effectiveness is dwindling due to resistance. Alternate options that comprise the combination of existing azoles and polyunsaturated fatty acids, such as arachidonic acid (AA), have been shown to increase azoles susceptibility of C. albicans biofilms; however, the mechanisms are still unknown. Therefore, transcriptome analysis was conducted on biofilms exposed to sub-inhibitory concentrations of AA alone, fluconazole alone, and AA combined with fluconazole to understand the possible mechanism involved with the phenomenon. Protein ANalysis THrough Evolutionary Relationships (PANTHER) analysis from the differentially expressed genes revealed that the combination of AA and fluconazole influences biological processes associated with essential processes including methionine synthesis and those involved in ATP generation, such as AMP biosynthesis, fumarate metabolism and fatty acid oxidation. These observations suggests that the interference of AA with these processes may be a possible mechanisms to induce increased antifungal susceptibility.

Changes in the Salivary Proteome Associated With Canine Pyometra.

The present study evaluated for the first time changes in the saliva proteome in bitches with pyometra through a high-throughput quantitative proteomic analysis. The aims were to explore whether saliva composition could reflect the physiopathological changes occurring in canine pyometra and to identify potential biomarkers of the disease. Saliva samples from six healthy (H) and six bitches with pyometra (P) were analyzed using tandem mass tags–based approach. Additionally, 15 samples were used for the validation of changes in haptoglobin (Hp) concentration in saliva of dogs with pyometra. Proteomic analysis quantified 707 proteins in saliva. Comparison of the two groups revealed 16 unique proteins significantly modulated in saliva, with S100A calcium-binding protein 12 (S100A12), vimentin, and Hp the most up-regulated in canine pyometra. According to PANTHER (Protein Analysis Through Evolutionary Relationships) classification tool, these proteins are mainly related to proinflammatory mediators, acute-phase proteins, and sepsis. In conclusion, it can be stated that there are changes in various proteins in saliva in canine pyometra reflecting different physiopathological changes occurring in this disease. These proteins could be a source of potential non-invasive biomarkers for this disease that should be confirmed in future studies.

P0044THE BIOLOGICAL AND FUNCTIONAL CHARACTERISATION OF GENES RESPONSIBLE FOR MONOGENIC DISORDERS OF THE KIDNEY

Abstract Background and Aims Single mutations in over 620 genes are known as drivers of approximately 330 monogenic disorders of the kidney. These disorders are estimated to account for up to 10% of chronic kidney disease cases. Due to their disease-causing nature, these genes are particularly clinically relevant targets for molecular analysis, but, so far, there has been no systematic analysis of their expression profile and biological functions in the human kidney. We aimed to characterise and compare the genes responsible for monogenic disorders of the kidney with other non-monogenic protein-coding genes. Method We used RNA-sequencing profile of 430 kidneys to explore the characteristics of 530 monogenic genes whose expression was available for analysis in the dataset. The property of genes was characterised using in silico databases such as Genome Reference Consortium Human Build 37 (GRCh37), Drug Gene Interaction database (DGIdb) and the Human Protein Atlas (HPA). The PANTHER (protein analysis through evolutionary relationships) database was used to determine the biological network of interactions between the monogenic genes. A Fast Gene Set Enrichment Analysis (FGSEA) was carried out using single-cell RNA-sequencing data for eight cell types of the kidney from Young et al. Finally, we carried out a two-stage mendelian randomisation to discover a causal link between gene expression and estimated glomerular filtration rate (eGFR) and blood pressure (BP). We used the summary statistics from UK Biobank and the CKDGen consortium for BP and eGFR respectively. Results The expression of monogenic genes was both higher and more specific to the kidney, than other protein-coding kidney genes. The pathway analysis found both fetal and organ development to be overrepresented in this set of genes, when compared to non-monogenic kidney genes. We also found that monogenic genes are significantly overrepresented for cell-type specific expression in the proximal tubule and underrepresented in podocytes. Our Mendelian randomisation analysis identified a causal effect between the expression of 50 monogenic genes and either eGFR, systolic or diastolic blood pressure. Conclusion Our studies revealed differences in the renal expression profile of monogenic genes and protein-coding genes. The proximal tubule segment of the nephron is a particularly enriched segment of the nephron for monogenic disorders. Kidney expression of 50 of the monogenic genes is causally related to changes in eGFR and blood pressure in the general population.

Proteomics and functional study reveal marginal zone B and B1 cell specific protein as a candidate marker of multiple myeloma.

Multiple myeloma (MM) is a plasma cell‑associated cancer and accounts for 13%of all hematological malignancies, worldwide. MM still remains an incurable plasma cell malignancy with a poor prognosis due to a lack of suitable markers. Therefore, discovering novel markers and targets for diagnosis and therapeutics of MM is essential. The present study aims to identify markers associated with MM malignancy using patient‑derived MM mononuclear cells (MNCs). Label‑free quantitative proteomics analysis revealed a total of 192differentially regulated proteins, in which 79proteins were upregulated and 113proteins were found to be downregulated in MM MNCs as compared to non‑hematological malignant samples. The identified differentially expressed candidate proteins were analyzed using various bioinformatics tools, including Ingenuity Pathway Analysis (IPA), Protein Analysis THrough Evolutionary Relationships (PANTHER), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Database for Annotation, Visualization and Integrated Discovery (DAVID) to determine their biological context. Among the 192candidate proteins, marginal zoneBandB1 cell specific protein (MZB1) was investigated in detail using the RPMI-8226 cell line model of MM. The functional studies revealed that higher expression of MZB1 is associated with promoting the progression of MM pathogenesis and could be established as a potential target for MM in the future.

Discovering Therapeutic Protein Targets for Bladder Cancer Using Proteomic Data Analysis.

Bladder cancer accounts for almost 54% of urinary system cancer and is the second most frequent cause of death in genitourinary malignancies after prostate cancer. About 70% of bladder tumors are non-muscle-invasive, and the rest are muscle-invasive. Recurrence of the tumor is the common feature of bladder cancer. Chemotherapy is a conventional treatment for MIBC, but it cannot improve the survival rate of these patients sufficiently. Therefore, researchers must develop new therapies. Antibody-based therapy is one of the most important strategies for the treatment of solid tumors. Selecting a suitable target is the most critical step for this strategy. The aim of this study is to detect therapeutic cell surface antigen targets in bladder cancer using data obtained by proteomic studies. Isobaric tag for relative and absolute quantitation (iTRAQ) analysis had identified 131 overexpressed proteins in baldder cancer tissue and reverse-phase proteomic array (RPPA) analysis had been done for 343 tumor tissues and 208 antibodies. All identified proteins from two studies (131+208 proteins) were collected and duplicates were removed (331 unique proteins). Gene ontology study was performed using gene ontology (GO) and protein analysis through evolutionary relationships (PANTHER) databases. The Human Protein Atlas database was used to search the protein class and subcellular location of membrane proteins obtained from the PANTHER analysis. Membrane proteins that could be suitable therapeutic targets for bladder cancer were selected. These included: Epidermal growth factor receptor (EGFR), Her2, Kinase insert domain receptor (KDR), Heat shock protein 60 (HSP60), HSP90, Transferrin receptor (TFRC), Activin A Receptor Like Type 1 (ACVRL1), and cadherin 2 (CDH2). Monoclonal antibodies against these proteins or their inhibitors were used for the treatment of different cancers in preclinical and clinical trials. These monoclonal antibodies and inhibitor molecules and also their combination can be used for the treatment of bladder cancer.

Glucagon-like peptide-1 receptor and sarcoglycan delta genetic variants can affect cardiovascular risk in chronic kidney disease patients under hemodialysis

BackgroundChronic kidney disease (CKD) patients under hemodialysis show a higher risk of cardiovascular (CV) mortality and morbidity than the general population. This study aims to identify genetic markers that could explain the increased CV risk in hemodialysis. Methods A total of 245 CKD patients under hemodialysis were recruited and followed up for 5 years to record CV events. Genetic analysis was performed using single-nucleotide polymorphisms (SNPs) genotyping by Infinium Expanded Multi-Ethnic Genotyping Array (Illumina, San Diego, CA, USA) comparing patients with and without a history of CV events [161 cardiovascular diseases (CVDs) and 84 no CVDs]. The fixation index (Fst) measure was used to identify the most differentiated SNPs, and gene ontology analysis [Protein Analysis THrough Evolutionary Relationships (PANTHER) and Ingenuity Pathway Analysis (IPA)] was applied to define the biological/pathological roles of the associated SNPs. Partitioning tree analysis interrogated the genotype–phenotype relationship between discovered genetic variants and CV phenotypes. Cox regression analysis measured the effect of these SNPs on new CV events during the follow-up (FU).ResultsFst analysis identified 3218 SNPs that were significantly different between CVD and no CVD. Gene ontology analysis identified two of these SNPs as involved in cardiovascular disease pathways (Ingenuity Pathway) and heart development (Panther) and belonging to 2 different genes: Glucagon-like peptide-1 receptor (GLP1R) and Sarcoglycan delta (SGCD). The phenotype–genotype analysis found a higher percentage of CVD patients carrying the GLP1R rs10305445 allele A (P = 0.03) and lower percentages of CVD patients carrying the SGCD rs145292439 allele A (P = 0.038). Moreover, SGCD rs145292439 was associated with higher levels of high-density lipoprotein (P = 0.015). Cox analysis confirmed the increased frequency of CV events during the 5-year FU in patients carrying GLP1R rs1035445 allele A but it did not show any significant association with SGCD rs145292439.ConclusionsThis study identified GLP1R rs10305445 and SCGD rs145292439 as potential genetic markers that may explain the higher risk of CVD in hemodialysis patients.