Genetic Modifiers of Cystic Fibrosis Lung Disease Severity: Whole-Genome Analysis of 7,840 Patients.

Rationale: Lung disease is the major cause of morbidity and mortality in persons with cystic fibrosis (pwCF). Variability in CF lung disease has substantial non-CFTR (CF transmembrane conductance regulator) genetic influence. Identification of genetic modifiers has prognostic and therapeutic importance. Objectives: Identify genetic modifier loci and genes/pathways associated with pulmonary disease severity. Methods: Whole-genome sequencing data on 4,248 unique pwCF with pancreatic insufficiency and lung function measures were combined with imputed genotypes from an additional 3,592 patients with pancreatic insufficiency from the United States, Canada, and France. This report describes association of approximately 15.9 million SNPs using the quantitative Kulich normal residual mortality-adjusted (KNoRMA) lung disease phenotype in 7,840 pwCF using premodulator lung function data. Measurements and Main Results: Testing included common and rare SNPs, transcriptome-wide association, gene-level, and pathway analyses. Pathway analyses identified novel associations with genes that have key roles in organ development, and we hypothesize that these genes may relate to dysanapsis and/or variability in lung repair. Results confirmed and extended previous genome-wide association study findings. These whole-genome sequencing data provide finely mapped genetic information to support mechanistic studies. No novel primary associations with common single variants or rare variants were found. Multilocus effects at chr5p13 (SLC9A3/CEP72) and chr11p13 (EHF/APIP) were identified. Variant effect size estimates at associated loci were consistently ordered across the cohorts, indicating possible age or birth cohort effects. Conclusions: This premodulator genomic, transcriptomic, and pathway association study of 7,840 pwCF will facilitate mechanistic and postmodulator genetic studies and the development of novel therapeutics for CF lung disease.

Monocyte, neutrophil, and whole blood transcriptome dynamics following ischemic stroke.

BACKGROUND: After ischemic stroke (IS), peripheral leukocytes infiltrate the damaged region and modulate the response to injury. Peripheral blood cells display distinctive gene expression signatures post-IS and these transcriptional programs reflect changes in immune responses to IS. Dissecting the temporal dynamics of gene expression after IS improves our understanding of immune and clotting responses at the molecular and cellular level that are involved in acute brain injury and may assist with time-targeted, cell-specific therapy. METHODS: The transcriptomic profiles from peripheral monocytes, neutrophils, and whole blood from 38 ischemic stroke patients and 18 controls were analyzed with RNA-seq as a function of time and etiology after stroke. Differential expression analyses were performed at 0-24 h, 24-48 h, and >48 h following stroke. RESULTS: Unique patterns of temporal gene expression and pathways were distinguished for monocytes, neutrophils, and whole blood with enrichment of interleukin signaling pathways for different time points and stroke etiologies. Compared to control subjects, gene expression was generally upregulated in neutrophils and generally downregulated in monocytes over all times for cardioembolic, large vessel, and small vessel strokes. Self-organizing maps identified gene clusters with similar trajectories of gene expression over time for different stroke causes and sample types. Weighted Gene Co-expression Network Analyses identified modules of co-expressed genes that significantly varied with time after stroke and included hub genes of immunoglobulin genes in whole blood. CONCLUSIONS: Altogether, the identified genes and pathways are critical for understanding how the immune and clotting systems change over time after stroke. This study identifies potential time- and cell-specific biomarkers and treatment targets.

Genetic screening for anticancer genes highlights FBLN5 as a synthetic lethal partner of MYC.

BACKGROUND: When ectopically overexpressed, anticancer genes, such as TRAIL, PAR4 and ORCTL3, specifically destroy tumour cells without harming untransformed cells. Anticancer genes can not only serve as powerful tumour specific therapy tools but studying their mode of action can reveal mechanisms underlying the neoplastic transformation, sustenance and spread. METHODS: Anticancer gene discovery is normally accidental. Here we describe a systematic, gain of function, forward genetic screen in mammalian cells to isolate novel anticancer genes of human origin. Continuing with over 30,000 transcripts from our previous study, 377 cell death inducing genes were subjected to screening. FBLN5 was chosen, as a proof of principle, for mechanistic gene expression profiling, comparison pathways analyses and functional studies. RESULTS: Sixteen novel anticancer genes were isolated; these included non-coding RNAs, protein-coding genes and novel transcripts, such as ZNF436-AS1, SMLR1, TMEFF2, LINC01529, HYAL2, NEIL2, FBLN5, YPEL4 and PHKA2-processed transcript. FBLN5 selectively caused inhibition of MYC in COS-7 (transformed) cells but not in CV-1 (normal) cells. MYC was identified as synthetic lethality partner of FBLN5 where MYC transformed CV-1 cells experienced cell death upon FBLN5 transfection, whereas FBLN5 lost cell death induction in MCF-7 cells upon MYC knockdown. CONCLUSIONS: Sixteen novel anticancer genes are present in human genome including FBLN5. MYC is a synthetic lethality partner of FBLN5. Video Abstract.

Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study.

BACKGROUND: Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. METHODS: We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. RESULTS: We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. CONCLUSIONS: Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.

Multiomics-Identified Intervention to Restore Ethanol-Induced Dysregulated Proteostasis and Secondary Sarcopenia in Alcoholic Liver Disease.

BACKGROUND/AIMS: Signaling and metabolic perturbations contribute to dysregulated skeletal muscle protein homeostasis and secondary sarcopenia in response to a number of cellular stressors including ethanol exposure. Using an innovative multiomics-based curating of unbiased data, we identified molecular and metabolic therapeutic targets and experimentally validated restoration of protein homeostasis in an ethanol-fed mouse model of liver disease. METHODS: Studies were performed in ethanol-treated differentiated C2C12 myotubes and physiological relevance established in an ethanol-fed mouse model of alcohol-related liver disease (mALD) or pair-fed control C57BL/6 mice. Transcriptome and proteome from ethanol treated-myotubes and gastrocnemius muscle from mALD and pair-fed mice were analyzed to identify target pathways and molecules. Readouts including signaling responses and autophagy markers by immunoblots, mitochondrial oxidative function and free radical generation, and metabolic studies by gas chromatography-mass spectrometry and sarcopenic phenotype by imaging. RESULTS: Multiomics analyses showed that ethanol impaired skeletal muscle mTORC1 signaling, mitochondrial oxidative pathways, including intermediary metabolite regulatory genes, interleukin-6, and amino acid degradation pathways are ß-hydroxymethyl-butyrate targets. Ethanol decreased mTORC1 signaling, increased autophagy flux, impaired mitochondrial oxidative function with decreased tricarboxylic acid cycle intermediary metabolites, ATP synthesis, protein synthesis and myotube diameter that were reversed by HMB. Consistently, skeletal muscle from mALD had decreased mTORC1 signaling, reduced fractional and total muscle protein synthesis rates, increased autophagy markers, lower intermediary metabolite concentrations, and lower muscle mass and fiber diameter that were reversed by ß-hydroxymethyl-butyrate treatment. CONCLUSION: An innovative multiomics approach followed by experimental validation showed that ß-hydroxymethyl-butyrate restores muscle protein homeostasis in liver disease.

Chronically Elevated Exogenous Glucose Elicits Antipodal Effects on the Proteome Signature of Differentiating Human iPSC-Derived Pancreatic Progenitors.

The past decade revealed that cell identity changes, such as dedifferentiation or transdifferentiation, accompany the insulin-producing ß-cell decay in most diabetes conditions. Mapping and controlling the mechanisms governing these processes is, thus, extremely valuable for managing the disease progression. Extracellular glucose is known to influence cell identity by impacting the redox balance. Here, we use global proteomics and pathway analysis to map the response of differentiating human pancreatic progenitors to chronically increased in vitro glucose levels. We show that exogenous high glucose levels impact different protein subsets in a concentration-dependent manner. In contrast, regardless of concentration, glucose elicits an antipodal effect on the proteome landscape, inducing both beneficial and detrimental changes in regard to achieving the desired islet cell fingerprint. Furthermore, we identified that only a subgroup of these effects and pathways are regulated by changes in redox balance. Our study highlights a complex effect of exogenous glucose on differentiating pancreas progenitors characterized by a distinct proteome signature.

Expression profiles of PRKG1, SDF2L1 and PPP1R12A are predictive and prognostic factors for therapy response and survival in high-grade serous ovarian cancer.

High-grade serous ovarian cancer (HGS-EOCs) is generally sensitive to front-line platinum (Pt)-based chemotherapy although most patients at an advanced stage relapse with progressive resistant disease. Clinical or molecular data to identify primary resistant cases at diagnosis are not yet available. HGS-EOC biopsies from 105 Pt-sensitive (Pt-s) and 89 Pt-resistant (Pt-r) patients were retrospectively selected from two independent tumor tissue collections. Pathway analysis was done integrating miRNA and mRNA expression profiles. Signatures were further validated in silico on a cohort of 838 HGS-EOC cases from a published dataset. In all, 131 mRNAs and 5 miRNAs belonging to different functionally related molecular pathways distinguish Pt-s from Pt-r cases. Then, 17 out of 23 selected elements were validated by orthogonal approaches (SI signature). As resistance to Pt is associated with a short progression-free survival (PFS) and overall survival (OS), the prognostic role of the SI signature was assessed, and 14 genes associated with PFS and OS, in multivariate analyses (SII signature). The prognostic value of the SII signature was validated in a third extensive cohort. The expression profiles of SDF2L1, PPP1R12A and PRKG1 genes (SIII signature) served as independent prognostic biomarkers of Pt-response and survival. The study identified a prognostic molecular signature based on the combined expression profile of three genes which had never been associated with the clinical outcome of HGS-EOC. This may lead to early identification, at the time of diagnosis, of patients who would not greatly benefit from standard chemotherapy and are thus eligible for novel investigational approaches.

Genome-wide analysis of long non-coding RNAs (lncRNAs) in two contrasting rapeseed (Brassica napus L.) genotypes subjected to drought stress and re-watering.

BACKGROUND: Drought stress is a major abiotic factor that affects rapeseed (Brassica napus L.) productivity. Though previous studies indicated that long non-coding RNAs (lncRNAs) play a key role in response to drought stress, a scheme for genome-wide identification and characterization of lncRNAs' response to drought stress is still lacking, especially in the case of B. napus. In order to further understand the molecular mechanism of the response of B. napus to drought stress, we compared changes in the transcriptome between Q2 (a drought-tolerant genotype) and Qinyou8 (a drought-sensitive genotype) responding drought stress and rehydration treatment at the seedling stage. RESULTS: A total of 5546 down-regulated and 6997 up-regulated mRNAs were detected in Q2 compared with 7824 and 10,251 in Qinyou8, respectively; 369 down-regulated and 108 up- regulated lncRNAs were detected in Q2 compared with 449 and 257 in Qinyou8, respectively. LncRNA-mRNA interaction network analysis indicated that the co-expression network of Q2 was composed of 145 network nodes and 5175 connections, while the co-expression network of Qinyou8 was composed of 305 network nodes and 22,327 connections. We further identified 34 transcription factors (TFs) corresponding to 126 differentially expressed lncRNAs in Q2, and 45 TFs corresponding to 359 differentially expressed lncRNAs in Qinyou8. Differential expression analysis of lncRNAs indicated that up- and down-regulated mRNAs co-expressed with lncRNAs participated in different metabolic pathways and were involved in different regulatory mechanisms in the two genotypes. Notably, some lncRNAs were co-expressed with BnaC07g44670D, which are associated with plant hormone signal transduction. Additionally, some mRNAs co-located with XLOC_052298, XLOC_094954 and XLOC_012868 were mainly categorized as signal transport and defense/stress response. CONCLUSIONS: The results of this study increased our understanding of expression characterization of rapeseed lncRNAs in response to drought stress and re-watering, which would be useful to provide a reference for the further study of the function and action mechanisms of lncRNAs under drought stress and re-watering.

Rare genetic variants suggest dysregulation of signaling pathways in low- and high-risk patients developing severe ovarian hyperstimulation syndrome.

PURPOSE: To investigate if rare gene variants in women with severe ovarian hyperstimulation syndrome (OHSS) provide clues to the mechanisms involved in the syndrome. METHODS: Among participants in a prospective randomized study (Toftager et al. 2016), six women with predicted low and six women with predicted high risk of OHSS developing severe OHSS (grades 4 and 5, Golan classification) were selected. In the same cohort, six plus six matched controls developing no signs of OHSS (Golan grade 0) were selected. Whole-exome sequencing was performed. Analysis using a predefined in silico OHSS gene panel, variant filtering, and pathway analyses was done. RESULTS: We found no convincing monogenetic association with the development of OHSS using the in silico gene panel. Pathway analysis of OHSS variant lists showed substantial overlap in highly enriched top pathways (p value range p < 0.0001 and p > 9.8E-17) between the low- and high-risk group developing severe OHSS, i.e., "the integrin-linked kinase (ILK) signaling pathway" and the "axonal guidance signaling pathway," both being connected to vasoactive endothelial growth factor (VEGF) and endothelial function. CONCLUSION: Rare variants in OHSS cases with two distinct risk profiles enrich the same signaling pathways linked to VEGF and endothelial function. Clarification of the mechanism as well as potentially defining genetic predisposition of the high vascular permeability is important for future targeted treatment and prevention of OHSS; the potential roles of ILK signaling and the axonal guidance signaling need to be validated by functional studies.

Epigenome-wide exploratory study of monozygotic twins suggests differentially methylated regions to associate with hand grip strength.

Hand grip strength is a measure of muscular strength and is used to study age-related loss of physical capacity. In order to explore the biological mechanisms that influence hand grip strength variation, an epigenome-wide association study (EWAS) of hand grip strength in 672 middle-aged and elderly monozygotic twins (age 55-90 years) was performed, using both individual and twin pair level analyses, the latter controlling the influence of genetic variation. Moreover, as measurements of hand grip strength performed over 8 years were available in the elderly twins (age 73-90 at intake), a longitudinal EWAS was conducted for this subsample. No genome-wide significant CpG sites or pathways were found, however two of the suggestive top CpG sites were mapped to the COL6A1 and CACNA1B genes, known to be related to muscular dysfunction. By investigating genomic regions using the comb-p algorithm, several differentially methylated regions in regulatory domains were identified as significantly associated to hand grip strength, and pathway analyses of these regions revealed significant pathways related to the immune system, autoimmune disorders, including diabetes type 1 and viral myocarditis, as well as negative regulation of cell differentiation. The genes contributing to the immunological pathways were HLA-B, HLA-C, HLA-DMA, HLA-DPB1, MYH10, ERAP1 and IRF8, while the genes implicated in the negative regulation of cell differentiation were IRF8, CEBPD, ID2 and BRCA1. In conclusion, this exploratory study suggests hand grip strength to associate with differentially methylated regions enriched in immunological and cell differentiation pathways, and hence merits further investigations.

Integrated analysis of SNP, CNV and gene expression data in genetic association studies.

Integrative approaches that combine multiple forms of data can more accurately capture pathway associations and so provide a comprehensive understanding of the molecular mechanisms that cause complex diseases. Association analyses based on single nucleotide polymorphism (SNP) genotypes, copy number variant (CNV) genotypes, and gene expression profiles are the 3 most common paradigms used for gene set/pathway enrichment analyses. Many work has been done to leverage information from 2 types of data from these 3 paradigms. However, to the best of our knowledge, there is no work done before to integrate the 3 paradigms all together. In this article, we present an integrated analysis that combine SNP, CNV, and gene expression data to generate a single gene list. We present different methods to compare this gene list with the other 3 possible lists that result from the combinations of the following pairs of data: SNP genotype with gene expression, CNV genotype with gene expression, and SNP genotype with CNV genotype. The comparison is done using 3 different cancer datasets and 2 different methods of comparison. Our results show that integrating SNP, CNV, and gene expression data give better association results than integrating any pair of 3 data.

Cytokine Release and Focal Adhesion Proteins in Normal Thyroid Cells Cultured on the Random Positioning Machine.

BACKGROUND/AIMS: Spaceflight impacts on the function of the thyroid gland in vivo. In vitro normal and malignant thyrocytes assemble in part to multicellular spheroids (MCS) after exposure to the random positioning machine (RPM), while a number of cells remain adherent (AD). We aim to elucidate possible differences between AD and MCS cells compared to 1g-controls of normal human thyroid cells. METHODS: Cells of the human follicular epithelial thyroid cell line Nthy-ori 3-1 were incubated for up to 72 h on the RPM. Afterwards, they were investigated by phase-contrast microscopy, quantitative real-time PCR and by determination of cytokines released in their supernatants. RESULTS: A significant up-regulation of IL6, IL8 and CCL2 gene expression was found after a 4h RPM-exposure, when the whole population was still growing adherently. MCS and AD cells were detected after 24 h on the RPM. At this time, a significantly reduced gene expression in MCS compared to 1g-controls was visible for IL6, IL8, FN1, ITGB1, LAMA1, CCL2, and TLN1. After a 72 h RPM-exposure, IL-6, IL-8, and TIMP-1 secretion rates were increased significantly. CONCLUSION: Normal thyrocytes form MCS within 24 h. Cytokines seem to be involved in the initiation of MCS formation via focal adhesion proteins.

Arsenic exposure from drinking water is associated with decreased gene expression and increased DNA methylation in peripheral blood.

BACKGROUND: Exposure to inorganic arsenic increases the risk of cancer and non-malignant diseases. Inefficient arsenic metabolism is a marker for susceptibility to arsenic toxicity. Arsenic may alter gene expression, possibly by altering DNA methylation. OBJECTIVES: To elucidate the associations between arsenic exposure, gene expression, and DNA methylation in peripheral blood, and the modifying effects of arsenic metabolism. METHODS: The study participants, women from the Andes, Argentina, were exposed to arsenic via drinking water. Arsenic exposure was assessed as the sum of arsenic metabolites in urine (U-As), using high performance liquid-chromatography hydride-generation inductively-coupled-plasma-mass-spectrometry, and arsenic metabolism efficiency was assessed by the urinary fractions (%) of the individual metabolites. Genome-wide gene expression (N=80 women) and DNA methylation (N=93; 80 overlapping with gene expression) in peripheral blood were measured using Illumina DirectHyb HumanHT-12 v4.0 and Infinium Human-Methylation 450K BeadChip, respectively. RESULTS: U-As concentrations, ranging 10-1251µg/L, was associated with decreased gene expression: 64% of the top 1000 differentially expressed genes were down-regulated with increasing U-As. U-As was also associated with hypermethylation: 87% of the top 1000CpGs were hypermethylated with increasing U-As. The expression of six genes and six individual CpG sites were significantly associated with increased U-As concentration. Pathway analyses revealed enrichment of genes related to cell death and cancer. The pathways differed somewhat depending on arsenic metabolism efficiency. We found no overlap between arsenic-related gene expression and DNA methylation for individual genes. CONCLUSIONS: Increased arsenic exposure was associated with lower gene expression and hypermethylation in peripheral blood, but with no evident overlap.

The prostate cancer immunome: In silico functional analysis of antigenic proteins from microarray profiling with IgG.

The study of the immunome of prostate cancer (PCa) and characterization of autoantibody signature from differentially reactive antigens can uncover disease stage proteins, reveal enriched networks and even expose aberrant cellular mechanisms during the disease process. By conducting plasma IgG profiling on protein microarrays presenting 5449 unique human proteins expressed in 15 417 E. coli human cDNA expression clones, we elucidated 471 (21 higher reactive in PCa) differentially reactive antigens in 50 PCa versus 49 patients with benign prostate hyperplasia (BPH) at initial diagnosis. Functional analyzes show that the immune-profile of PCa compared to BPH control samples is significantly enriched in features targeting Cellular assembly, Cell death and pathways involved in Cell cycle, translation, and assembly of proteins as EIF2 signaling, PCa related genes as AXIN1 and TP53, and ribosomal proteins (e.g. RPS10). An overlap of 61 (out of 471) DIRAGs with the published 1545 antigens from the SEREX database has been found, however those were higher reactive in BPH. Clinical relevance is shown when antibody-reactivities against eight proteins were significantly (p < 0.001) correlated with Gleason-score. Herewith we provide a biological and pathophysiological characterization of the immunological layer of cancerous (PCa) versus benign (BPH) disease, derived from antibody profiling on protein microarrays.

Pathway analysis in attention deficit hyperactivity disorder: An ensemble approach.

Despite a wealth of evidence for the role of genetics in attention deficit hyperactivity disorder (ADHD), specific and definitive genetic mechanisms have not been identified. Pathway analyses, a subset of gene-set analyses, extend the knowledge gained from genome-wide association studies (GWAS) by providing functional context for genetic associations. However, there are numerous methods for association testing of gene sets and no real consensus regarding the best approach. The present study applied six pathway analysis methods to identify pathways associated with ADHD in two GWAS datasets from the Psychiatric Genomics Consortium. Methods that utilize genotypes to model pathway-level effects identified more replicable pathway associations than methods using summary statistics. In addition, pathways implicated by more than one method were significantly more likely to replicate. A number of brain-relevant pathways, such as RhoA signaling, glycosaminoglycan biosynthesis, fibroblast growth factor receptor activity, and pathways containing potassium channel genes, were nominally significant by multiple methods in both datasets. These results support previous hypotheses about the role of regulation of neurotransmitter release, neurite outgrowth and axon guidance in contributing to the ADHD phenotype and suggest the value of cross-method convergence in evaluating pathway analysis results. © 2016 Wiley Periodicals, Inc.

Sex differences in mechanisms of pain hypersensitivity.

The introduction of sex-as-a-biological-variable policies at funding agencies around the world has led to an explosion of very recent observations of sex differences in the biology underlying pain. This review considers evidence of sexually dimorphic mechanisms mediating pain hypersensitivity, derived from modern assays of persistent pain in rodent animal models. Three well-studied findings are described in detail: the male-specific role of spinal cord microglia, the female-specific role of calcitonin gene-related peptide (CGRP), and the female-specific role of prolactin and its receptor. Other findings of sex-specific molecular involvement in pain are subjected to pathway analyses and reveal at least one novel hypothesis: that females may preferentially use Th1 and males Th2 T cell activity to mediate chronic pain.

A critical appreciation of pathway analysis in atherosclerotic disease. Cellular phenotypic plasticity as an illustrative example.

The rapid advancements in genome-scale (omics) techniques has created significant opportunities to investigate complex disease mechanisms in tissues and cells. Nevertheless, interpreting -omics data can be challenging, and pathway enrichment analysis is a frequently used method to identify candidate molecular pathways that drive gene expression changes. With a growing number of -omics studies dedicated to atherosclerosis, there has been a significant increase in studies and hypotheses relying on enrichment analysis. This brief review discusses the benefits and limitations of pathway enrichment analysis within atherosclerosis research. We highlight the challenges of identifying complex biological processes, such as cell phenotypic switching, within -omics data. Additionally, we emphasize the need for more comprehensive and curated gene sets that reflect the biological complexity of atherosclerosis. Pathway enrichment analysis is a valuable tool for gaining insights into the molecular mechanisms of atherosclerosis. Nevertheless, it is crucial to remain aware of the intrinsic limitations of this approach. By addressing these weaknesses, enrichment analysis in atherosclerosis can lead to breakthroughs in identifying the mechanisms of disease progresses, the identification of key driver genes, and consequently, advance personalized patient care.

Transcriptome Profiling Analysis of Breast Cancer Cell MCF-7 Treated by Sesamol.

Background: Breast cancer is a highly malignant tumor that affects a large number of women worldwide. Sesamol, a natural compound, has been shown to exhibit inhibitory effects on various tumors, including breast cancer. However, the underlying mechanism of its action has not been fully explored. In this study, we aimed to investigate the effect of sesamol on the transcriptome of MCF-7 breast cancer cells, in order to better understand its potential as an anti-cancer agent. Methods: The transcriptome profiles of MCF-7 breast cancer cells treated with sesamol were analyzed using Illumina deep-sequencing. The differentially expressed genes (DEGs) between the control and sesamol-treated groups were identified, and GO and KEGG pathway analyses of these DEGs were conducted using ClueGO. Protein-protein interaction (PPI) network of DEGs was mapped on STRING database and visualized by Cytoscape software. Hub genes in the network were screened by Cytohubba plugin of Cytoscape. Prognostic values of hub genes were analyses by the online Kaplan-Meier plotter and validated by qRT-PCR in MCF-7 cells. Results: The results of the study showed that sesamol treatment had a significant effect on the transcriptome of MCF-7 cells, with a total of 351 DEGs identified. Functional enrichment analyses of DEGs revealed their involvement in extracellular matrix (ECM) remodeling, fatty acid metabolism and monocyte chemotaxis. The protein-protein interaction (PPI) network analysis of DEGs resulted in the identification of 10 hub genes, namely IGF2, MMP1, MSLN, CXCL10, WT1, ITGAL, PLD1, MME, TWIST1, and FOXA2. Survival analysis showed that MMP1 and ITGAL were significantly associated with overall survival (OS) and recovery-free survival (RFS) in breast cancer patients. Conclusion: Sesamol may play important roles in extracellular matrix (ECM) remodeling, fatty acid metabolism and cell cycle of MCF-7.

Genome-wide identification of long non-coding RNAs and their potential functions in radish response to salt stress.

Long non-coding RNAs (lncRNAs) are increasingly recognized as cis- and trans-acting regulators of protein-coding genes in plants, particularly in response to abiotic stressors. Among these stressors, high soil salinity poses a significant challenge to crop productivity. Radish (Raphanus sativus L.) is a prominent root vegetable crop that exhibits moderate susceptibility to salt stress, particularly during the seedling stage. Nevertheless, the precise regulatory mechanisms through which lncRNAs contribute to salt response in radish remain largely unexplored. In this study, we performed genome-wide identification of lncRNAs using strand-specific RNA sequencing on radish fleshy root samples subjected to varying time points of salinity treatment. A total of 7,709 novel lncRNAs were identified, with 363 of them displaying significant differential expression in response to salt application. Furthermore, through target gene prediction, 5,006 cis- and 5,983 trans-target genes were obtained for the differentially expressed lncRNAs. The predicted target genes of these salt-responsive lncRNAs exhibited strong associations with various plant defense mechanisms, including signal perception and transduction, transcription regulation, ion homeostasis, osmoregulation, reactive oxygen species scavenging, photosynthesis, phytohormone regulation, and kinase activity. Notably, this study represents the first comprehensive genome-wide analysis of salt-responsive lncRNAs in radish, to the best of our knowledge. These findings provide a basis for future functional analysis of lncRNAs implicated in the defense response of radish against high salinity, which will aid in further understanding the regulatory mechanisms underlying radish response to salt stress.

XGBG: A Novel Method for Identifying Ovarian Carcinoma Susceptible Genes Based on Deep Learning.

Ovarian carcinomas (OCs) represent a heterogeneous group of neoplasms consisting of several entities with pathogenesis, molecular profiles, multiple risk factors, and outcomes. OC has been regarded as the most lethal cancer among women all around the world. There are at least five main types of OCs classified by the fifth edition of the World Health Organization of tumors: high-/low-grade serous carcinoma, mucinous carcinoma, clear cell carcinoma, and endometrioid carcinoma. With the improved knowledge of genome-wide association study (GWAS) and expression quantitative trait locus (eQTL) analyses, the knowledge of genomic landscape of complex diseases has been uncovered in large measure. Moreover, pathway analyses also play an important role in exploring the underlying mechanism of complex diseases by providing curated pathway models and information about molecular dynamics and cellular processes. To investigate OCs deeper, we introduced a novel disease susceptible gene prediction method, XGBG, which could be used in identifying OC-related genes based on different omics data and deep learning methods. We first employed the graph convolutional network (GCN) to reconstruct the gene features based on both gene feature and network topological structure. Then, a boosting method is utilized to predict OC susceptible genes. As a result, our model achieved a high AUC of 0.7541 and an AUPR of 0.8051, which indicates the effectiveness of the XGPG. Based on the newly predicted OC susceptible genes, we gathered and researched related literatures to provide strong support to the results, which may help in understanding the pathogenesis and mechanisms of the disease.