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Background: Colorectal cancer (CRC) is the most diagnosed cancer in men and the second most common cancer in women and remains associated with high morbidity and mortality in Saudi Arabia. The current understanding of genetic heterogeneity of CRC biology encourages the identification of the genetic causes of CRC in the Saudi population. Methods: In this study, we obtained 89 CRC patients’ tumor samples from Saudi Arabia and investigated the molecular alterations of the NRAS proto-oncogene, GTPase (NRAS) gene in the collected CRC tumor tissue samples to identify gene mutations using DNA sequencing using an automated DNA sequencer ABI 3730xl. The impact of mutations was analyzed using different bioinformatics tools including SwissModel, Missense3D, molecular dynamics simulations using YASARA DYNAMICS and Protein Variation Effect Analyzer (PROVEAN) tool. Results: We identified a novel mutation c.40 G > T, in one patient in whom valine was replaced by phenylalanine (V14F). Notably, we also identified another mutation in the same codon c.40 G > A where valine is replaced by isoleucine (V14I). Our in-silico analysis revealed that this novel mutation alters the binding affinity of the NRAS gene substantially, and as a result, could have lethal consequences on the downstream signaling genes and pathways including MAPK and PI3K involved in regulating CRC growth and progression. Conclusions: These findings provide insights into the molecular etiology of CRC in general and particularly in the Saudi population. Thus, these findings in NRAS mutation testing may also guide further treatment modalities, and more personalized therapy may be optimized.

Background: Colorectal cancer (CRC) liver metastasis (CRLM) is a clinical challenge, and optimizing treatment strategies is crucial for improving patient outcomes. This study aimed to identify gene expression signatures associated with CRLM for early diagnosis and improved treatment outcomes. Methods: We obtained RNA-seq data of 34 samples (17 colorectal tumor samples from metastasized liver and 17 samples from normal surrounding colonic epithelia) from the Gene Expression Omnibus (GEO) with accession number GSE50760 and analysed them using next-generation knowledge discovery (NGKD) tools such as GEO2R and web based gene set enrichment analysis (WebGestalt). Results: A total of 18808 genes were identified in the initial analysis which were further reduced to 2490 differentially expressed genes (DEGs) after applying different parameters using GEO2R tools. Furthermore, in the gene set enrichment analysis (GSEA), we analysed the biological processes, cellular components, and molecular functions. We analysed four pathways: KEGG, panther, reactome, and wikipathway cancer. In each analysis, we ascertained the most important top expressed and downregulated genes. Conclusions: We identified various gene sets that could be used as important prognostic and therapeutic markers, particularly in patients with advanced CRLM. Future studies in larger cohorts may further our research findings to establish the best prognostic biomarkers for early diagnosis and overall survival.

Background & aim: Congenital heart disease (CHD) is the most common cause of non-infectious deaths in infants worldwide. However, the molecular mechanisms underlying CHD remain unclear. Approximately 30 % of the causes are believed to be genetic mutations and chromosomal abnormalities. In this study, we aimed to identify the genetic causes of CHD in consanguineous families. Methods: Fourth-generation pedigrees with CHD were recruited. The main cardiac features of the patient included absence of the right pulmonary artery and a large dilated left pulmonary artery. To determine the underlying genetic cause, whole-exome sequencing was performed and subsequently confirmed using Sanger sequencing and different online databases to study the pathogenesis of the identified gene mutation. An in-silico homology model was created using the Alphafold homology model structure of GATA4 (AF-P43694-F1). The missense3D online program was used to evaluate the structural alterations. Results: We identified a deleterious mutation c.551T > C (p.Phe184Ser) in GATA4. GATA4 is a highly conserved zinc-finger transcription factor, and its continuous expression is essential for cardiogenesis during embryogenesis. The in-silico model suggested a compromised binding efficiency with other proteins. Several variant interpretation algorithms indicated that the F184S missense variant in GATA4 is damaging, whereas HOPE analysis indicated the functional impairment of DNA binding of transcription factors and zinc-ion binding activities of GATA4. Conclusion: The variant identified in GATA4 appears to cause recessive CHD in the family. In silico analysis suggested that this variant was damaging and caused multiple structural and functional aberrations. This study may support prenatal screening of the fetus in this family to prevent diseases in new generations.

Abstract Background Lipodystrophy is a relatively rare, complex disease characterised by a deficiency of adipose tissue and can present as either generalised lipodystrophy (GLD) or partial lipodystrophy (PLD). The prevalence of this disease varies by region. This study aimed to identify the genetic variations associated with lipodystrophy in the southern part of Saudi Arabia. Methodology We conducted a retrospective study by recruiting nine patients from six families, recruiting the proband whole exome sequencing results or any other genetic test results, screening other family members using Sanger sequencing and analysing the carrier status of the latter. These patients were recruited from the Endocrinology and Diabetes Clinic at Jazan General Hospital and East Jeddah Hospital, both in the Kingdom of Saudi Arabia. Result Eight patients were diagnosed with GLD, and one was diagnosed with PLD. Of the six families, four were consanguineously married from the same tribe, while the remaining belonged to the same clan. The majority of GLD patients had an AGPAT2 c.158del mutation, but some had a BSCL2 c.942dup mutation. The single PLD case had a PPARG c.1024C > T mutation but no family history of the disease. In all families evaluated in this study, some family members were confirmed to be carriers of the mutation observed in the corresponding patient. Conclusion Familial screening of relatives of patients with rare, autosomal recessive diseases, such as lipodystrophy, especially when there is a family history, allows the implementation of measures to prevent the onset or reduced severity of disease and reduces the chances of the pathogenic allele being passed onto future generations. Creating a national registry of patients with genetic diseases and carriers of familial pathogenic alleles will allow the assessment of preventive measures and accelerate disease intervention via gene therapy.

Cancer research has advanced tremendously with the identification of causative genes, proteins, and signaling pathways. Numerous antitumor drugs have been designed and screened for cancer therapeutics; however, designing target-specific drugs for malignant cells with minimal side effects is challenging. Recently, energy-sensing- and homeostasis-associated molecules and signaling pathways playing a role in proliferation, apoptosis, autophagy, and angiogenesis have received increasing attention. Energy-metabolism-based studies have shown the contribution of energetics to cancer development, where tumor cells show increased glycolytic activity and decreased oxidative phosphorylation (the Warburg effect) in order to obtain the required additional energy for rapid division. The role of energy homeostasis in the survival of normal as well as malignant cells is critical; therefore, fuel intake and expenditure must be balanced within acceptable limits. Thus, energy-sensing enzymes detecting the disruption of glycolysis, AMP, ATP, or GTP levels are promising anticancer therapeutic targets. Here, we review the common energy mediators and energy sensors and their metabolic properties, mechanisms, and associated signaling pathways involved in carcinogenesis, and explore the possibility of identifying drugs for inhibiting the energy metabolism of tumor cells. Furthermore, to corroborate our hypothesis, we performed meta-analysis based on transcriptomic profiling to search for energy-associated biomarkers and canonical pathways.

Background: Genetic alterations in the perilipin (PLIN) family genes (PLIN1 to PLIN5) were infrequent in breast cancer (BC) where enhanced levels of PLIN1, PLIN3-5 were observed in the luminal A and luminal B subgroups, whereas increased PLIN2 expression was observed in the HER2-enriched and basal-like subgroups. However, the predictive value of PLIN1 for BC patient outcomes remains uncertain. In the present study, we aim to investigate the diagnostic, prognostic and treatment response roles of the PLIN1 gene expression in BC. Methods: We obtained microarray BC trancriptomic data of 320 tumor (T) and 62 normal (N) breast samples from five GEO data-series; GSE7904 (38 T:7N), GSE42568 (101 T: 15 N), GSE26910 (6 T:6N), GSE45827 (144 T:7N), and GSE10810 (31 T:27 N). The Welch t test was used to analyze the significant differences in gene expression including PLIN1 with fold change > ±2 and p-value 1) and log-rank p-values

Breast and ovarian cancers are prevalent worldwide, with genetic factors such as BRCA1 and BRCA2 mutations playing a significant role. However, not all patients carry these mutations, making it challenging to identify risk factors. Researchers have turned to whole exome sequencing (WES) as a tool to identify genetic risk factors in BRCA-negative women. WES allows the sequencing of all protein-coding regions of an individual’s genome, providing a comprehensive analysis that surpasses traditional gene-by-gene sequencing methods. This technology offers efficiency, cost-effectiveness and the potential to identify new genetic variants contributing to the susceptibility to the diseases. Interpreting WES data for disease-causing variants is challenging due to its complex nature. Machine learning techniques can uncover hidden genetic-variant patterns associated with cancer susceptibility. In this study, we used the extreme gradient boosting (XGBoost) and random forest (RF) algorithms to identify BRCA-related cancer high-risk genes specifically in the Saudi population. The experimental results exposed that the RF method scored superior performance with an accuracy of 88.16% and an area under the receiver-operator characteristic curve of 0.95. Using bioinformatics analysis tools, we explored the top features of the high-accuracy machine learning model that we built to enhance our knowledge of genetic interactions and find complex genetic patterns connected to the development of BRCA-related cancers. We were able to identify the significance of HLA gene variations in these WES datasets for BRCA-related patients. We find that immune response mechanisms play a major role in the development of BRCA-related cancer. It specifically highlights genes associated with antigen processing and presentation, such as HLA-B, HLA-A and HLA-DRB1 and their possible effects on tumour progression and immune evasion. In summary, by utilizing machine learning approaches, we have the potential to aid in the development of precision medicine approaches for early detection and personalized treatment strategies.

Acute myeloid leukemia (AML) is hallmarked by the clonal proliferation of myeloid blasts. Mutations that result in the constitutive activation of the fms-like tyrosine kinase 3 (FLT3) gene, coding for a class III receptor tyrosine kinase, are significantly associated with this heterogeneous hematologic malignancy. The fms-related tyrosine kinase 3 ligand binds to the extracellular domain of the FLT3 receptor, inducing homodimer formation in the plasma membrane, leading to autophosphorylation and activation of apoptosis, proliferation, and differentiation of hematopoietic cells in bone marrow. In the present study, we evaluated the association of FLT3 as a significant biomarker for AML and tried to comprehend the effects of specific variations on the FLT3 protein’s structure and function. We also examined the effects of I836 variants on binding affinity to sorafenib using molecular docking. We integrated multiple bioinformatics tools, databases, and resources such as OncoDB, UniProt, COSMIC, UALCAN, PyMOL, ProSA, Missense3D, InterProScan, SIFT, PolyPhen, and PredictSNP to annotate the structural, functional, and phenotypic impact of the known variations associated with FLT3. Twenty-nine FLT3 variants were analyzed using in silico approaches such as DynaMut, CUPSAT, AutoDock, and Discovery Studio for their impact on protein stability, flexibility, function, and binding affinity. The OncoDB and UALCAN portals confirmed the association of FLT3 gene expression and its mutational status with AML. A computational structural analysis of the deleterious variants of FLT3 revealed I863F mutants as destabilizers of the protein structure, possibly leading to functional changes. Many single-nucleotide variations in FLT3 have an impact on its structure and function. Thus, the annotation of FLT3 SNVs and the prediction of their deleterious pathogenic impact will facilitate an insight into the tumorigenesis process and guide experimental studies and clinical implications.

A method, PhyloSignare, is presented to infer mutational signatures along a tumour evolutionary tree and is used to analyse somatic genomic variations in 61 lung cancer patients, providing insights into tumour evolution.

Abstract Mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 are oncogenic drivers to a variable extent in several tumors, including gliomas, acute myeloid leukemia (AML), cholangiocarcinoma, melanoma, and thyroid carcinoma. The pathobiological effects of these mutations vary considerably, impeding the identification of common expression profiles. We performed an expression meta-analysis between IDH-mutant (IDHmut) and IDH-wild-type (IDHwt) conditions in six human and mouse isogenic disease models. The datasets included colon cancer cells, glioma cells, heart tissue, hepatoblasts, and neural stem cells. Among differentially expressed genes (DEGs), serine protease 23 (PRSS23) was upregulated in four datasets, i.e., in human colon carcinoma cells, mouse heart tissue, mouse neural stem cells, and human glioma cells. Carbonic anhydrase 2 (CA2) and prolyl 3-hydroxylase 2 (P3H2) were upregulated in three datasets, and SOX2 overlapping transcript (SOX2-OT) was downregulated in three datasets. The most significantly overrepresented protein class was termed intercellular signal molecules. An additional DEG set contained genes that were both up- and downregulated in different datasets and included oxidases and extracellular matrix structural proteins as the most significantly overrepresented protein classes. In conclusion, this meta-analysis provides a comprehensive overview of the expression effects of IDH mutations shared between different isogenic disease models. The generated dataset includes biomarkers, e.g., PRSS23 that may gain relevance for further research or clinical applications in IDHmut tumors.

Objective: Breast Cancer (BC) is one of the deadliest diseases in women, causing thousands of deaths annually despite the advent of high-throughput genomic platforms in the recent past. Microarray-based gene expression profiling with different statistical methods have been extensively used to understand the disease at the molecular level. We plan to apply Welch Satterthwaite t-test, Kaplan-Meier estimator plot and Huber Loss robust regression model on microarray data to improve the analysis and find biomarkers for future diagnosis, prognosis, and treatment. Methods: We retrieved microarray data (GSE10810 dataset) of 31 breast tumor samples and 27 normal breast samples from Gene Expression Omnibus (GEO, NCBI). Welch Satterthwaite t-test was applied to identify the most statistically significant genes, Huber loss robust regression model was applied to investigate the existing mathematical relations between tumor and control variables, and Kaplan-Meier Plotter was used to confirm their association with overall metastatic relapse-free survival of BC patients. Results: We identified 1837 differentially expressed genes, including 638 overexpressed (COL11A1, KIAA0101, S100P, GJB2, TOP2A, LINC01614, RRM2, INHBA, C15orf48 and CKS2) and 1199 under expressed (LEP, ADIPOQ, PLIN1, PCK1, PCOLCE2, ADH1B, LYVE1, FABP4, ABCA8, and CHRDL1) genes passing the threshold (fold change ± 2 and p value

Chromosomal imbalance is implicated in developmental delay (DD), congenital malformations (CM), and intellectual disability (ID), and, thus, precise identification of copy number variations (CNVs) is essential. We therefore aimed to investigate the genetic heterogeneity in Saudi children with DD/CM/ID. High-resolution array comparative genomic hybridization (array CGH) was used to detect disease-associated CNVs in 63 patients. Quantitative PCR was done to confirm the detected CNVs. Giemsa banding-based karyotyping was also performed. Array CGH identified chromosomal abnormalities in 24 patients; distinct pathogenic and/or variants of uncertain significance CNVs were found in 19 patients, and aneuploidy was found in 5 patients including 47,XXY (n = 2), 45,X (n = 2) and a patient with trisomy 18 who carried a balanced Robertsonian translocation. CNVs including 9p24p13, 16p13p11, 18p11 had gains/duplications and CNVs, including 3p23p14, 10q26, 11p15, 11q24q25, 13q21.1q32.1, 16p13.3p11.2, and 20q11.1q13.2, had losses/deletions only, while CNVs including 8q24, 11q12, 15q25q26, 16q21q23, and 22q11q13 were found with both gains or losses in different individuals. In contrast, standard karyotyping detected chromosomal abnormalities in ten patients. The diagnosis rate of array CGH (28%, 18/63 patients) was around two-fold higher than that of conventional karyotyping (15.87%, 10/63 patients). We herein report, for the first time, the extremely rare pathogenic CNVs in Saudi children with DD/CM/ID. The reported prevalence of CNVs in Saudi Arabia adds value to clinical cytogenetics.

Identifying cancer biomarkers is imperative, as upregulated genes offer a better microenvironment for the tumor; hence, targeted inhibition is preferred. The theme of our study is to predict molecular interactions between cancer biomarker proteins and selected natural compounds. We identified an overexpressed potential molecular target (AKT1) and computationally evaluated its inhibition by four dietary ligands (isoliquiritigenin, shogaol, tehranolide, and theophylline). The three-dimensional structures of protein and phytochemicals were retrieved from the RCSB PDB database (4EKL) and NCBI’s PubChem, respectively. Rational structure-based docking studies were performed using AutoDock. Results were analyzed based primarily on the estimated free binding energy (kcal/mol), hydrogen bonds, and inhibition constant, Ki, to identify the most effective anti-cancer phytomolecule. Toxicity and drug-likeliness prediction were performed using OSIRIS and SwissADME. Amongst the four phytocompounds, tehranolide has better potential to suppress the expression of AKT1 and could be used for anti-cancer drug development, as inhibition of AKT1 is directly associated with the inhibition of growth, progression, and metastasis of the tumor. Docking analyses reveal that tehranolide has the most efficiency in inhibiting AKT1 and has the potential to be used for the therapeutic management of cancer. Natural compounds targeting cancer biomarkers offer less rejection, minimal toxicity, and fewer side effects.

Objective: Databases and softwares are important to manage modern high-throughput laboratories and store clinical and genomic information for quality assurance. Commercial softwares are expensive with proprietary code issue while academic versions have adaptation issue. Our aim was to develop an adaptable in-house software that can stores specimen and disease-associated genetic information in biobank to facilitate translational research. Methods: Prototype was designed as per the research requirements and computational tools were used to develop software under three tiers; Visual Basic and ASP.net for presentation tier, SQL server for data tier, and Ajax and JavaScript for business tier. We retrieved specimens from biobank using this software and performed microarray based transcriptomic analysis to detect differentialy expressed genes (DEGs) with FC ±2 and P-value

Atherosclerosis is a chronic inflammation characterized by macrophage infiltration, lipid deposition, and arterial wall thickening. Prevention of atherosclerosis by nutraceuticals is gaining attention. Myricetin, a dietary flavonol, is claimed to possess anti-atherosclerosis properties. We studied myricetin’s effect on the atherosclerosis-associated molecular mechanism. Cytotoxicity and proliferation testing to check the viability of myricetin-treated THP-1 macrophages and monocyte migration study in the presence and absence of myricetin was performed. The whole transcriptome analysis was conducted using the Affymetrix microarray platform. The Partek genomics suite for detecting differentially expressed genes (DEGs) and ingenuity pathway analysis was used to identify canonical pathways. Cytotoxicity assays exhibited no significant toxicity in THP-1 macrophages treated with different myricetin concentrations (10–200 μM). Genome-wide expression profiling revealed 58 DEGs (53 upregulated and 5 downregulated) in myricetin-treated THP-1 macrophages. Pathway analysis revealed inhibition of LXR/RXR activation and angiogenesis inhibition by thrombospondin-1 and activated phagocytosis in myricetin-treated THP-1 macrophages. The cytotoxicity assay shows myricetin as a safe phytochemical. In vitro and in silico pathway studies on THP-1 macrophages showed that they can inhibit THP-1 monocyte migration and alter the cholesterol efflux mediated via LXR/RXR signaling. Therefore, myricetin could help in the prevention of cell infiltration in atherosclerotic plaque with reduced risk of stroke or brain damage.

Cardiovascular disease (CVD) is causing high mortality worldwide (World Health Organization-WHO, 2015). Atherosclerosis, the hardening and narrowing of arteries caused by the accumulation of fatty acids and lipids (cholesterol plaques), is a main reason of stroke, myocardial infarction, and angina. Present therapies for cardiovascular disease basically use statins such as β-Hydroxy β-methylglutaryl-CoA, with

Hashimoto's thyroiditis (HT) is present in the background of around 30% of papillary thyroid carcinomas (PTCs). The genetic predisposition effect of this autoimmune condition is not thoroughly understood. We analyzed the microarray expression profiles of 13 HT, eight PTCs with (w/) coexisting HT, six PTCs without (w/o) coexisting HT, six micro PTCs (mPTCs), and three normal thyroid (TN) samples. Based on a false discovery rate (FDR)-adjusted p-value ≤ 0.05 and a fold change (FC) > 2, four comparison groups were defined, which were HT vs. TN; PTC w/ HT vs. TN; PTC w/o HT vs. TN; and mPTC vs. TN. A Venn diagram displayed 15 different intersecting and non-intersecting differentially expressed gene (DEG) sets, of which a set of 71 DEGs, shared between the two comparison groups HT vs. TN ∩ PTC w/ HT vs. TN, harbored the relatively largest number of genes related to immune and inflammatory functions; oxidative stress and reactive oxygen species (ROS); DNA damage and DNA repair; cell cycle; and apoptosis. The majority of the 71 DEGs were upregulated and the most upregulated DEGs included a number of immunoglobulin kappa variable genes, and other immune-related genes, e.g., CD86 molecule (CD86), interleukin 2 receptor gamma (IL2RG), and interferon, alpha-inducible protein 6 (IFI6). Upregulated genes preferentially associated with other gene ontologies (GO) were, e.g., STAT1, MMP9, TOP2A, and BRCA2. Biofunctional analysis revealed pathways related to immunogenic functions. Further data analysis focused on the set of non-intersecting 358 DEGs derived from the comparison group of HT vs. TN, and on the set of 950 DEGs from the intersection of all four comparison groups. In conclusion, this study indicates that, besides immune/inflammation-related genes, also genes associated with oxidative stress, ROS, DNA damage, DNA repair, cell cycle, and apoptosis are comparably more deregulated in a data set shared between HT and PTC w/ HT. These findings are compatible with the conception of a genetic sequence where chronic inflammatory response is accompanied by deregulation of genes and biofunctions associated with oncogenic transformation. The generated data set may serve as a source for identifying candidate genes and biomarkers that are practical for clinical application.

Background: Oculocutaneous albinism (OCA) is an autosomal recessive disorder of low or missing pigmentation in the eyes, hair, and skin. Multiple types of OCA, including Hermansky-Pudlak syndrome 6 (HPS6), are distinguished by their genetic cause and pigmentation pattern. HPS6 is characterized by OCA, nose bleeding due to platelet dysfunction, and lysosome storage defect. To date, 25 disease-associated mutations have been reported in the HPS6 gene. Methods: DNA was extracted from proband, and whole-exome sequencing (WES) was performed using the Illumina NovaSeq platform. Bioinformatic analysis was done with a custom-designed filter pipeline to detect the causative variant. We did Sanger sequencing to confirm the candidate variant and segregation analysis, and protein-based structural analysis to evaluate the functional impact of variants. Result: Proband-based WES identified two novel homozygous mutations in HPS6 (double mutation, c.1136C>A and c.1789delG) in an OCA suspect. Sanger sequencing confirmed the WES results. Although no platelet and/or lysosome storage defect was detected in the patient or family, an oculocutaneous albinism diagnosis was established based on the HPS6 mutations. Structural analysis revealed the transformation of abnormalities at protein level for both nonsense and frameshift mutations in HPS6. Conclusion: To the best of our knowledge, the double mutation in HPS6 (p.Ser379Ter and p.Ala597GlnfsTer16) represents novel pathogenic variants, not described previously, which we report for the first time in the Saudi family. In silico analyses showed a significant impact on protein structure. WES should be used to identify HPS6 and/or other disease-associated genetic variants in Saudi Arabia, particularly in consanguineous families.

Abstract Background Breast cancer brain metastases (BCBM) develop in about 20–30% of breast cancer (BC) patients. BCBM are associated with dismal prognosis not at least due to lack of valuable molecular therapeutic targets. The aim of the study was to identify new molecular biomarkers and targets in BCBM by using complementary state-of-the-art techniques. Methods We compared array expression profiles of three BCBM with 16 non-brain metastatic BC and 16 primary brain tumors (prBT) using a false discovery rate (FDR) p 2. Biofunctional analysis was conducted on the differentially expressed probe sets. High-density arrays were employed to detect copy number variations (CNVs) and whole exome sequencing (WES) with paired-end reads of 150 bp was utilized to detect gene mutations in the three BCBM. Results The top 370 probe sets that were differentially expressed between BCBM and both BC and prBT were in the majority comparably overexpressed in BCBM and included, e.g. the coding genes BCL3, BNIP3, BNIP3P1, BRIP1, CASP14, CDC25A, DMBT1, IDH2, E2F1, MYCN, RAD51, RAD54L, and VDR. A number of small nucleolar RNAs (snoRNAs) were comparably overexpressed in BCBM and included SNORA1, SNORA2A, SNORA9, SNORA10, SNORA22, SNORA24, SNORA30, SNORA37, SNORA38, SNORA52, SNORA71A, SNORA71B, SNORA71C, SNORD13P2, SNORD15A, SNORD34, SNORD35A, SNORD41, SNORD53, and SCARNA22. The top canonical pathway was entitled, role of BRCA1 in DNA damage response. Network analysis revealed key nodes as Akt, ERK1/2, NFkB, and Ras in a predicted activation stage. Downregulated genes in a data set that was shared between BCBM and prBT comprised, e.g. BC cell line invasion markers JUN, MMP3, TFF1, and HAS2. Important cancer genes affected by CNVs included TP53, BRCA1, BRCA2, ERBB2, IDH1, and IDH2. WES detected numerous mutations, some of which affecting BC associated genes as CDH1, HEPACAM, and LOXHD1. Conclusions Using complementary molecular genetic techniques, this study identified shared and unshared molecular events in three highly aberrant BCBM emphasizing the challenge to detect new molecular biomarkers and targets with translational implications. Among new findings with the capacity to gain clinical relevance is the detection of overexpressed snoRNAs known to regulate some critical cellular functions as ribosome biogenesis.

Background: Chronic myeloid leukemia (CML) is initiated in bone marrow due to chromosomal translocation t(9;22) leading to fusion oncogene BCR-ABL. Targeting BCR-ABL by tyrosine kinase inhibitors (TKIs) has changed fatal CML into an almost curable disease. Despite that, TKIs lose their effectiveness due to disease progression. Unfortunately, the mechanism of CML progression is poorly understood and common biomarkers for CML progression are unavailable. This study was conducted to find novel biomarkers of CML progression by employing whole-exome sequencing (WES). Materials and Methods: WES of accelerated phase (AP) and blast crisis (BC) CML patients was carried out, with chronic-phase CML (CP-CML) patients as control. After DNA library preparation and exome enrichment, clustering and sequencing were carried out using Illumina platforms. Statistical analysis was carried out using SAS/STAT software version 9.4, and R package was employed to find mutations shared exclusively by all AP-/BC-CML patients. Confirmation of mutations was carried out using Sanger sequencing and protein structure modeling using I-TASSER followed by mutant generation and visualization using PyMOL. Results: Three novel genes (ANKRD36, ANKRD36B and PRSS3) were mutated exclusively in all AP-/BC-CML patients. Only ANKRD36 gene mutations (c.1183_1184 delGC and c.1187_1185 dupTT) were confirmed by Sanger sequencing. Protein modeling studies showed that mutations induce structural changes in ANKRD36 protein. Conclusions: Our studies show that ANKRD36 is a potential common biomarker and drug target of early CML progression. ANKRD36 is yet uncharacterized in humans. It has the highest expression in bone marrow, specifically myeloid cells. We recommend carrying out further studies to explore the role of ANKRD36 in the biology and progression of CML.

Abstract Background Genome-wide association studies (GWAS) have become a mainstay of biological research concerned with discovering genetic variation linked to phenotypic traits and diseases. Both discrete and continuous traits can be analyzed in GWAS to discover associations between single nucleotide polymorphisms (SNPs) and traits of interest. Associations are typically determined by estimating the significance of the statistical relationship between genetic loci and the given trait. However, the prioritization of bona fide, reproducible genetic associations from GWAS results remains a central challenge in identifying genomic loci underlying common complex diseases. Evolutionary-aware meta-analysis of the growing GWAS literature is one way to address this challenge and to advance from association to causation in the discovery of genotype-phenotype relationships. Description We have created an evolutionary GWAS resource to enable in-depth query and exploration of published GWAS results. This resource uses the publically available GWAS results annotated in the GRASP2 database. The GRASP2 database includes results from 2082 studies, 177 broad phenotype categories, and ~8.87 million SNP-phenotype associations. For each SNP in e-GRASP, we present information from the GRASP2 database for convenience as well as evolutionary information (e.g., rate and timespan). Users can, therefore, identify not only SNPs with highly significant phenotype-association P-values, but also SNPs that are highly replicated and/or occur at evolutionarily conserved sites that are likely to be functionally important. Additionally, we provide an evolutionary-adjusted SNP association ranking (E-rank) that uses cross-species evolutionary conservation scores and population allele frequencies to transform P-values in an effort to enhance the discovery of SNPs with a greater probability of biologically meaningful disease associations. Conclusion By adding an evolutionary dimension to the GWAS results available in the GRASP2 database, our e-GRASP resource will enable a more effective exploration of SNPs not only by the statistical significance of trait associations, but also by the number of studies in which associations have been replicated, and the evolutionary context of the associated mutations. Therefore, e-GRASP will be a valuable resource for aiding researchers in the identification of bona fide, reproducible genetic associations from GWAS results. This resource is freely available at http://www.mypeg.info/egrasp .

Meningiomas are the most common primary brain tumors bearing in a minority of cases an aggressive phenotype. Although meningiomas are stratified according to their histology and clinical behavior, the underlying molecular genetics predicting aggressiveness are not thoroughly understood. We performed whole transcript expression profiling in 10 grade I and four grade II meningiomas, three of which invaded the brain. Microarray expression analysis identified deleted in colorectal cancer (DCC) as a differentially expressed gene (DEG) enabling us to cluster meningiomas into DCC low expression (3 grade I and 3 grade II tumors), DCC medium expression (2 grade I and 1 grade II tumors), and DCC high expression (5 grade I tumors) groups. Comparison between the DCC low expression and DCC high expression groups resulted in 416 DEGs (p-value2). The most significantly downregulated genes in the DCC low expression group comprised DCC, phosphodiesterase 1C (PDE1C), calmodulin-dependent 70kDa olfactomedin 2 (OLFM2), glutathione S-transferase mu 5 (GSTM5), phosphotyrosine interaction domain containing 1 (PID1), sema domain, transmembrane domain (TM) and cytoplasmic domain, (semaphorin) 6D (SEMA6D), and indolethylamine N-methyltransferase (INMT). The most significantly upregulated genes comprised chromosome 5 open reading frame 63 (C5orf63), homeodomain interacting protein kinase 2 (HIPK2), and basic helix-loop-helix family, member e40 (BHLHE40). Biofunctional analysis identified as predicted top upstream regulators beta-estradiol, TGFB1, Tgf beta complex, LY294002, and dexamethasone and as predicted top regulator effectors NFkB, PIK3R1, and CREBBP. The microarray expression data served also for a comparison between meningiomas from female and male patients and for a comparison between brain invasive and non-invasive meningiomas resulting in a number of significant DEGs and related biofunctions. In conclusion, based on its expression levels, DCC may constitute a valid biomarker to identify those benign meningiomas at risk for progression.

Patau Syndrome (PS), characterized as a lethal disease, allows less than 15% survival over the first year of life. Most deaths owe to brain and heart disorders, more so due to septal defects because of altered gene regulations. We ascertained the cytogenetic basis of PS first, followed by molecular analysis and docking studies. Thirty-seven PS cases were referred from the Department of Pediatrics, King Abdulaziz University Hospital to the Center of Excellence in Genomic Medicine Research, Jeddah during 2008 to 2018. Cytogenetic analyses were performed by standard G-band method and trisomy13 were found in all the PS cases. Studies have suggested that genes of chromosome 13 and other chromosomes are associated with PS. We, therefore, did molecular pathway analysis, gene interaction, and ontology studies to identify their associations. Genomic analysis revealed important chr13 genes such as FOXO1, Col4A1, HMGBB1, FLT1, EFNB2, EDNRB, GAS6, TNFSF1, STARD13, TRPC4, TUBA3C, and TUBA3D, and their regulatory partners on other chromosomes associated with cardiovascular disorders, atrial and ventricular septal defects. There is strong indication of involving FOXO1 (Forkhead Box O1) gene—a strong transcription factor present on chr13, interacting with many septal defects link genes. The study was extended using molecular docking to find a potential drug lead for overexpressed FOXO1 inhibition. The phenothiazine and trifluoperazine showed efficiency to inhibit overexpressed FOXO1 protein, and could be potential drugs for PS/trisomy13 after validation.

The S100A8 and epidermal growth factor receptor (EGFR) proteins are proto-oncogenes that are strongly expressed in a number of cancer types. EGFR promotes cellular proliferation, differentiation, migration and survival by activating molecular pathways. Involvement of proinflammatory S100A8 in tumor cell differentiation and progression is largely unclear and not studied in kidney cancer (KC). S100A8 and EGFR are potential therapeutic biomarkers and anticancer drug targets for KC. In this study, we explored molecular mechanisms of interaction profiles of both molecules with potential anticancer drugs. We undertook transcriptional profiling in Saudi KCs using Affymetrix HuGene 1.0 ST arrays. We identified 1478 significantly expressed genes, including S100A8 and EGFR overexpression, using cut-off p value

Toxicity induced by radiation therapy is a curse for cancer patients undergoing treatment. It is imperative to understand and define an ideal condition where the positive effects notably outweigh the negative. We used a microarray meta-analysis approach to measure global gene-expression before and after radiation exposure. Bioinformatic tools were used for pathways, network, gene ontology and toxicity related studies. We found 429 differentially expressed genes at fold change >2 and p-value