Subset Of Genes Research Articles

A novel and innovative cancer classification framework through a consecutive utilization of hybrid feature selection

Cancer prediction in the early stage is a topic of major interest in medicine since it allows accurate and efficient actions for successful medical treatments of cancer. Mostly cancer datasets contain various gene expression levels as features with less samples, so firstly there is a need to eliminate similar features to permit faster convergence rate of classification algorithms. These features (genes) enable us to identify cancer disease, choose the best prescription to prevent cancer and discover deviations amid different techniques. To resolve this problem, we proposed a hybrid novel technique CSSMO-based gene selection for cancer classification. First, we made alteration of the fitness of spider monkey optimization (SMO) with cuckoo search algorithm (CSA) algorithm viz., CSSMO for feature selection, which helps to combine the benefit of both metaheuristic algorithms to discover a subset of genes which helps to predict a cancer disease in early stage. Further, to enhance the accuracy of the CSSMO algorithm, we choose a cleaning process, minimum redundancy maximum relevance (mRMR) to lessen the gene expression of cancer datasets. Next, these subsets of genes are classified using deep learning (DL) to identify different groups or classes related to a particular cancer disease. Eight different benchmark microarray gene expression datasets of cancer have been utilized to analyze the performance of the proposed approach with different evaluation matrix such as recall, precision, F1-score, and confusion matrix. The proposed gene selection method with DL achieves much better classification accuracy than other existing DL and machine learning classification models with all large gene expression dataset of cancer.

Uncertainty measurement for single cell RNA-seq data via Gaussian kernel: Application to unsupervised gene selection

A real-valued information system (RVIS) is an information system (IS) whose information values are real numbers. If the objects, attributes and information values of a RVIS change to cells, genes and gene expression values where gene expression data is single cell RNA-seq (scRNA) data, respectively, then this RVIS is referred to as a single cell gene space (scg-space). Unsupervised gene selection becomes very challenging due to a lack of decision information, which is to select the optimal gene subset that can maintain learning ability without decision information. However, little research has been done on unsupervised gene selection. Uncertainty measurement is a tool of gene selection. In view of this, this paper studies uncertainty measurement in an scg-space via Gaussian kernel and explores its application for unsupervised gene selection. In the first place, the distance between two cells in a given subspace is constructed. In the next place, the fuzzy Tcos-equivalence relation induced by this subspace is obtained employing Gaussian kernel. After that, measures of uncertainty for an scg-space are investigated. Lastly, gene selection algorithms in an scg-space are presented by using the proposed information entropy and information granularity. The presented algorithms are applied to clustering analyses of scRNA data. Multiple publicly available scRNA data sets are employed to evaluate the gene selection performances of the presented algorithms, while two commonly-used clustering methods, kmeans and AGNES, are utilized to obtain four metrics such as Silhouette Coefficient (SC), Davies–Bouldin Index (DBI), Fowlkes and Mallows Index (FMI), Normalized Mutual Information (NMI) . The clustering results demonstrated that the presented algorithms can lower significantly the number genes selected, achieve the better SC, DBI, FMI and NMI. They also show that the presented algorithms are superior to raw data and PCA and NMF regardless of using kmeans or AGNES clustering. This also indirectly demonstrates that the granulation measure and information entropy can effectively evaluate the uncertainty of an scg-space.

Enrichment of the Local Synaptic Translatome for Genetic Risk Associated With Schizophrenia and Autism Spectrum Disorder

BackgroundGenes that encode synaptic proteins or messenger RNA targets of the RNA-binding protein FMRP (fragile X messenger ribonucleoprotein) have been linked to schizophrenia and autism spectrum disorder (ASD) through the enrichment of genetic variants that confer risk for these disorders. FMRP binds many transcripts with synaptic functions and is thought to regulate their local translation, a process that enables rapid and compartmentalized protein synthesis required for development and plasticity. MethodsWe used summary statistics from large-scale genome-wide association studies of schizophrenia (74,776 cases, 101,023 controls) and ASD (18,381 cases, 27,969 controls) to test the hypothesis that the subset of synaptic genes that encode localized transcripts is more strongly associated with each disorder than nonlocalized transcripts. We also postulated that this subset of synaptic genes is responsible for associations attributed to FMRP targets. ResultsSchizophrenia associations were enriched in genes encoding localized synaptic transcripts compared to the remaining synaptic genes or to the remaining localized transcripts; this also applied to ASD associations, although only for transcripts observed after stimulation by fear conditioning. The genetic associations with either disorder captured by these gene sets were independent of those derived from FMRP targets. Schizophrenia association was related to FMRP interactions with messenger RNAs in somata, but not in dendrites, while ASD association was related to FMRP binding in either compartment. ConclusionsOur data suggest that synaptic transcripts capable of local translation are particularly relevant to the pathogenesis of schizophrenia and ASD, but they do not characterize the associations attributed to current sets of FMRP targets.

Deep Learning-Based Prediction of Alzheimer's Disease Using Microarray Gene Expression Data.

Alzheimer's disease is a genetically complex disorder, and microarray technology provides valuable insights into it. However, the high dimensionality of microarray datasets and small sample sizes pose challenges. Gene selection techniques have emerged as a promising solution to this challenge, potentially revolutionizing AD diagnosis. The study aims to investigate deep learning techniques, specifically neural networks, in predicting Alzheimer's disease using microarray gene expression data. The goal is to develop a reliable predictive model for early detection and diagnosis, potentially improving patient care and intervention strategies. This study employed gene selection techniques, including Singular Value Decomposition (SVD) and Principal Component Analysis (PCA), to pinpoint pertinent genes within microarray datasets. Leveraging deep learning principles, we harnessed a Convolutional Neural Network (CNN) as our classifier for Alzheimer's disease (AD) prediction. Our approach involved the utilization of a seven-layer CNN with diverse configurations to process the dataset. Empirical outcomes on the AD dataset underscored the effectiveness of the PCA-CNN model, yielding an accuracy of 96.60% and a loss of 0.3503. Likewise, the SVD-CNN model showcased remarkable accuracy, attaining 97.08% and a loss of 0.2466. These results accentuate the potential of our method for gene dimension reduction and classification accuracy enhancement by selecting a subset of pertinent genes. Integrating gene selection methodologies with deep learning architectures presents a promising framework for elevating AD prediction and promoting precision medicine in neurodegenerative disorders. Ongoing research endeavors aim to generalize this approach for diverse applications, explore alternative gene selection techniques, and investigate a variety of deep learning architectures.

Single-cell RNA sequencing reveals common and unique gene expression profiles in primary CD4+ T cells latently infected with HIV under different conditions.

The latent HIV reservoir represents the major barrier to a cure. One curative strategy is targeting diseased cells for elimination based on biomarkers that uniquely define these cells. Single-cell RNA sequencing (scRNA-seq) has enabled the identification of gene expression profiles associated with disease at the single-cell level. Because HIV provirus in many cells during latency is not entirely silent, it became possible to determine gene expression patterns in a subset of cells latently infected with HIV. The primary objective of this study was the identification of the gene expression profiles of single latently infected CD4+ T cells using scRNA-seq. Different conditions of latency establishment were considered. The identified profiles were then explored to prioritize the identified genes for future experimental validation. To facilitate gene prioritization, three approaches were used. First, we characterized and compared the gene expression profiles of HIV latency established in different environments: in cells that encountered an activation stimulus and then returned to quiescence, and in resting cells that were infected directly via cell-to-cell viral transmission from autologous activated, productively infected cells. Second, we characterized and compared the gene expression profiles of HIV latency established with viruses of different tropisms, using an isogenic pair of CXCR4- and CCR5-tropic viruses. Lastly, we used proviral expression patterns in cells from people with HIV to more accurately define the latently infected cells in vitro. Our analyses demonstrated that a subset of genes is expressed differentially between latently infected and uninfected cells consistently under most conditions tested, including cells from people with HIV. Our second important observation was the presence of latency signatures, associated with variable conditions when latency was established, including cellular exposure and responsiveness to a T cell receptor stimulus and the tropism of the infecting virus. Common signatures, specifically genes that encode proteins localized to the cell surface, should be prioritized for further testing at the protein level as biomarkers for the ability to enrich or target latently infected cells. Cell- and tropism-dependent biomarkers may need to be considered in developing targeting strategies to ensure that all the different reservoir subsets are eliminated.

RFX6 Maintains Gene Expression and Function of Adult Human Islet α-Cells.

Mutations in the gene encoding the transcription factor regulatory factor X-box binding 6 (RFX6) are associated with human diabetes. Within pancreatic islets, RFX6 expression is most abundant in islet α-cells, and α-cell RFX6 expression is altered in diabetes. However, the roles of RFX6 in regulating gene expression, glucagon output, and other crucial human adult α-cell functions are not yet understood. We developed a method for selective genetic targeting of human α-cells and assessed RFX6-dependent α-cell function. RFX6 suppression with RNA interference led to impaired α-cell exocytosis and dysregulated glucagon secretion in vitro and in vivo. By contrast, these phenotypes were not observed with RFX6 suppression across all islet cells. Transcriptomics in α-cells revealed RFX6-dependent expression of genes governing nutrient sensing, hormone processing, and secretion, with some of these exclusively expressed in human α-cells. Mapping of RFX6 DNA-binding sites in primary human islet cells identified a subset of direct RFX6 target genes. Together, these data unveil RFX6-dependent genetic targets and mechanisms crucial for regulating adult human α-cell function. Article Highlights

Transcriptome analysis of iron over-accumulating Arabidopsis genotypes uncover putative novel regulators of systemic and retrograde signaling.

On account of its competence to accept and donate electrons, iron (Fe) is an essential element across all forms of life, including plants. Maintaining Fe homeostasis requires precise orchestration of its uptake, trafficking, and translocation in order to meet the demand for Fe sinks such as plastids. Plants harboring defects in the systemic Fe transporter OPT3 (OLIGOPEPTIDE TRANSPORTER 3) display constitutive Fe deficiency responses and accumulate toxic levels of Fe in their leaves. Similarly, ectopic expression of IRONMAN (IMA) genes, encoding a family of phloem-localized signaling peptides, triggers the uptake and accumulation of Fe by inhibiting the putative Fe sensor BRUTUS. This study aims at elucidating the mechanisms operating between OPT3-mediated systemic Fe transport, activation of IMA genes in the phloem, and activation of Fe uptake in the root epidermis. Transcriptional profiling of opt3-2 mutant and IMA1/IMA3 overexpressing (IMA Ox) lines uncovered a small subset of genes that were consistently differentially expressed across all three genotypes and Fe-deficient control plants, constituting potential novel regulators of cellular Fe homeostasis. In particular, expression of the the F-box protein At1g73120 was robustly induced in all genotypes, suggesting a putative function in the posttranslational regulation of cellular Fe homeostasis. As further constituents of this module, two plastid-encoded loci that putatively produce transfer ribonucleic acid (tRNA)-derived small ribonucleic acids are possibly involved in retrograde control of root Fe uptake.

Dalbergia odorifera undergoes massive molecular shifts in response to waterlogging combined with salinity.

Field and greenhouse studies attempting to describe the molecular responses of plant species under waterlogging (WL) combined with salinity (ST) are almost nonexistent. We integrated transcriptional, metabolic, and physiological responses involving several crucial transcripts and common differentially expressed genes and metabolites in fragrant rosewood (Dalbergia odorifera) leaflets to dissect plant-specific molecular responses and patterns under WL combined with ST (SWL). We discovered that the synergistic pattern of the transcriptional response of fragrant rosewood under SWL was exclusively characterized by the number of regulated transcripts. The response patterns under SWL based on transcriptome and metabolome regulation statuses revealed different patterns (additive, dominant, neutral, minor, unilateral, and antagonistic) of transcripts or metabolites that were commonly regulated or expressed uniquely under SWL. Under SWL, the synergistic transcriptional response of several functional gene subsets was positively associated with several metabolomic and physiological responses related to the shutdown of the photosynthetic apparatus and the extensive degradation of starch into saccharides through α-amylase, β-amylase, and α-glucosidase or plastoglobuli accumulation. The dissimilarity between the regulation status and number of transcripts in plants under combined stresses led to nonsynergistic responses in several physiological and phytohormonal traits. As inferred from the impressive synergistic transcriptional response to morpho-physiological changes, combined stresses exhibited a gradually decreasing effect on the changes observed at the molecular level compared to those in the morphological one. Here, by characterizing the molecular responses and patterns of plant species under SWL, our study considerably improves our understanding of the molecular mechanisms underlying combined stress.

The Interaction between Histone Lysine Methyltransferase GLP and EZH2

Recent studies have implicated that H3K9 lysine methyltransferases (KMTs) and polycomb repressive complex2 (PRC2) act in a cross-talk. However, a connection between GLP, one of the well-known H3K9 KMTs and the EZH2, one of the core members of PRC2, has not been established. Here we not only demonstrated that there was interaction between the GLP and the EZH2 proteins in vivo, but also provided evidence that the activity of EZH2 was effected by down-regulation of GLP. In light of these observations, western blotting, co-immunoprecipitation and qRT-PCR were performed to explore in GLP siRNA KGN cells. The specific interaction between GLP and EZH2 was demonstrated with co-immunoprecipitation. Our results also indicate that the decreased level of GLP participate in the modulation of EZH2 function in vivo.Taken together, our findings identified that an unanticipated interplay between the two histone lysine methyltransferases, which is implicated in regulating of a subset of developmental genes.

The Impact of a High Fat Diet on AD‐risk Associated Genes in a Mouse Model of Alzheimer’s Disease

AbstractBackgroundOver 80% of individuals with AD have a co‐morbid metabolic disease, defined as obesity, glucose intolerance, or diabetes. Both metabolic disease and a HF diet cause the release of inflammatory factors, increases AD risk, and alters the expression of hippocampal microvascular genes. Work has increased in identifying specific networks and the genes that drive these networks in AD. We hypothesize that AD causes baseline changes in a specific cluster of genes and when a HF diet is introduced, it further drives alterations of a sub‐population of genes to drive the worsening of AD pathology.MethodMale wild type (WT) and AppNL‐F knock‐in mice were given a low fat (LF; 10% fat) or high fat (HF; 60% fat; metabolic disease model) diet for 1 month. Weekly weights and end of study visceral fat weight were taken. The hippocampus was rapidly extracted and flash frozen for bulk RNA sequencing and differential gene expression analysis.ResultOn an LF diet, AppNL‐F mice had a greater body weight gain and greater visceral fat compared to WT controls. HF diet increased body weight and visceral fat in WT mice. There was surprisingly no difference between AppNL‐F mice on a LF diet and HF diet in body weight gain and visceral fat. There were 760 significant hippocampal gene alterations between AD and WT mice. Within the WT controls on a LF vs HF diet, there were 213 gene alterations and within the AD model on a LF vs HF diet, there were 31 gene alterations.ConclusionAppNL‐F mice on both a LF and HF diet gained equivalent amounts of weight, displaying an altered metabolic profile due to AD alone. While AD alone caused most of the gene alterations, a HF diet further drove alterations in a subset of genes. This work increases our understanding of the contribution of a HF diet to metabolic disease and alterations in AD‐risk associated hippocampal genes to uncover potential modifiable targets. We are currently examining specific clusters of genes and how they are linked to AD pathology, increased inflammation, and vascular dysfunction, and sequencing hippocampal samples from female mice to examine sex differences.

Virulence-related genotypic differences among Bacillus cereus ocular and gastrointestinal isolates and the relationship to endophthalmitis pathogenesis.

Bacillus cereus (Bc) can cause self-limiting gastrointestinal infections, but when infecting the eye, can cause rapid and irreversible blindness. This study investigated whether clinical ocular and gastrointestinal Bc isolates differed in terms of virulence-related genotypes and endophthalmitis virulence. Twenty-eight Bc ocular, gastrointestinal, and laboratory reference isolates were evaluated. Hemolysis assays were performed to assess potential differences in hemolytic activity. The presence of twenty Bc virulence-related genes was assessed by PCR. A subset of ocular and gastrointestinal isolates differing in PCR positivity for 5 virulence genes was compared to strain ATCC14579 in an experimental murine model of endophthalmitis. At 8 hours post infection, retinal function was evaluated by electroretinography, and intraocular bacterial concentrations were determined by plate counts. Gastrointestinal Bc isolates were more hemolytic than the Bc ocular isolates and ATCC14579 (p < 0.0001). Bc ocular isolates were more frequently PCR-positive for capK, cytK, hblA, hblC, and plcR compared to the gastrointestinal isolates (p ≤ 0.0002). In the endophthalmitis model, mean A-wave retention did not differ significantly between eyes infected with ATCC14579 and eyes infected with the selected ocular or gastrointestinal isolates (p ≥ 0.3528). Similar results were observed for mean B-wave retention (p ≥ 0.0640). Only one diarrheal isolate showed significantly greater B-wave retention when compared to ATCC14579 (p = 0.0303). No significant differences in mean A-wave (p ≥ 0.1535) or B-wave (p ≥ 0.0727) retention between the selected ocular and gastrointestinal isolates were observed. Intraocular concentrations of ATCC14579 were significantly higher than the selected ocular isolate and 3 of the gastrointestinal isolates (p ≤ 0.0303). Intraocular concentrations of the selected ocular isolate were not significantly different from the gastrointestinal isolates (p ≥ 0.1923). Among the subset of virulence-related genes assessed, 5 were significantly enriched among the ocular isolates compared to gastrointestinal isolates. While hemolytic activity was higher among gastrointestinal isolates, retinal function retention and intraocular growth was not significantly different between the selected ocular and gastrointestinal isolates. These results suggest that Bc strains causing gastrointestinal infections, while differing from ocular isolates in hemolytic activity and virulence-related gene profile, are similarly virulent in endophthalmitis.

The H2Bub1-deposition complex is required for human and mouse cardiogenesis.

De novo variants affecting monoubiquitylation of histone H2B (H2Bub1) are enriched in human congenital heart disease. H2Bub1 is required in stem cell differentiation, cilia function, post-natal cardiomyocyte maturation and transcriptional elongation. However, how H2Bub1 affects cardiogenesis is unknown. We show that the H2Bub1-deposition complex (RNF20-RNF40-UBE2B) is required for mouse cardiogenesis and for differentiation of human iPSCs into cardiomyocytes. Mice with cardiac-specific Rnf20 deletion are embryonic lethal and have abnormal myocardium. We then analyzed H2Bub1 marks during differentiation of human iPSCs into cardiomyocytes. H2Bub1 is erased from most genes at the transition from cardiac mesoderm to cardiac progenitor cells but is preserved on a subset of long cardiac-specific genes. When H2Bub1 is reduced in iPSC-derived cardiomyocytes, long cardiac-specific genes have fewer full-length transcripts. This correlates with H2Bub1 accumulation near the center of these genes. H2Bub1 accumulation near the center of tissue-specific genes was also observed in embryonic fibroblasts and fetal osteoblasts. In summary, we show that normal H2Bub1 distribution is required for cardiogenesis and cardiomyocyte differentiation, and suggest that H2Bub1 regulates tissue-specific gene expression by increasing the amount of full-length transcripts.

Long noncoding RNA MALAT1; A novel and potential therapeutic target for Alzheimer’s disease

AbstractBackgroundAlzheimer disease (AD) is the most common form of dementia, characterized pathologically by amyloid plaques and neurofibrillary tangles. Despite considerable advances in the knowledge of AD pathogenesis, we know little about preventing or delaying the ongoing neurodegenerative process, indicating that there remain critical gaps in our understanding of disease mechanisms and opportunities for new treatment approaches. Long noncoding RNAs (lncRNAs) are larger than 200 nucleotides, structurally resemble mRNAs but do not encode proteins. LncRNAs participate in regulation of several physiological and pathophysiological processes by modulating gene expression and have been documented in several neurodegenerative diseases. Among them, metastasis associated lung adenocarcinoma transcript 1 (MALAT1) is a highly abundant and evolutionary conserved lncRNA and regulates a subset of genes involved in synaptic plasticity, cognitive function and memory.MethodTo test the hypothesis that lncRNA MALAT1 plays an important role in AD pathology, we quantified expression levels of lncRNA MALAT1 in the brains of age‐matched AD patients and cognitively normal controls (Non‐AD) by QRT‐PCR and RNAScope in situ hybridization assays, respectively. We further examined the lncRNA MALAT1 expressions and AD‐related neuropathology in the brains of 5XFAD transgenic mouse model of AD and their WT littermates using dual RNAScope/Immunofluorescence technique.ResultWe observed reduced expressions of lncRNA MALAT1 in the hippocampus of AD brains compared to the non‐AD control brains. Next, we found marked reduced expression of lncRNA MALAT1 in the brain of 5xFAD mice compared to non‐transgenic mice. Interestingly, decreased expression levels of lncRNA MALAT1 are correlated with AD‐related neuropathology and memory deficits in 5xFAD mice.ConclusionThese findings provided compelling evidence that AD is associated with altered expression of lncRNA MALAT1 which may influence several pathways related to neural damage and memory deficits in AD. Because expression patterns, interacting proteins, pathways, and biological functions of lncRNA MALAT1 are remain largely unexplored in AD, understanding how lncRNA MALAT1 regulates AD‐related neuropathology may allow development of effective therapies for this incurable disease.

CTCF deletion alters the pluripotency and DNA methylation profile of human iPSCs

Pluripotent stem cells are characterized by their differentiation potential toward endoderm, mesoderm, and ectoderm. However, it is still largely unclear how these cell-fate decisions are mediated by epigenetic mechanisms. In this study, we explored the relevance of CCCTC-binding factor (CTCF), a zinc finger-containing DNA-binding protein, which mediates long-range chromatin organization, for directed cell-fate determination. We generated human induced pluripotent stem cell (iPSC) lines with deletions in the protein-coding region in exon 3 of CTCF, resulting in shorter transcripts and overall reduced protein expression. Chromatin immunoprecipitation showed a considerable loss of CTCF binding to target sites. The CTCF deletions resulted in slower growth and modest global changes in gene expression, with downregulation of a subset of pluripotency-associated genes and neuroectodermal genes. CTCF deletion also evoked DNA methylation changes, which were moderately associated with differential gene expression. Notably, CTCF-deletions lead to upregulation of endo-mesodermal associated marker genes and epigenetic signatures, whereas ectodermal differentiation was defective. These results indicate that CTCF plays an important role in the maintenance of pluripotency and differentiation, especially towards ectodermal lineages.

BAP18 acting as a novel peroxisome proliferator-activated receptor α co-regulator contributes to hepatocellular carcinoma progression

Hepatocellular carcinoma (HCC) is a common malignancy worldwide with a poor prognosis. The therapeutic outcomes of HCC patients are urgently needed to be improved, and predictive biomarkers for the optimal treatment selection remains to be further defined. In the present study, our results showed that BPTF-associated protein of 18 KDa (BAP18) was highly expressed in HCC tissues. In cultured HCC cells, BAP18 regulated a subset of down-stream genes involved in different functions, particularly including peroxisome proliferator-activated receptor (PPAR) pathway and lipid metabolism. Furthermore, BAP18 co-activated PPARα-mediated transactivation and facilitated the recruitment of nucleosome acetyltransferase of H4 (NuA4)/tat interacting protein 60 (TIP60) complex, thereby increasing histone H4 acetylation on stearoyl-CoA desaturase 1 (SCD1) loci. In addition, BAP18 promoted HCC cell proliferation, increased intracellular lipid levels and enhanced cell survival under the metabolic stress conditions, such as glucose limitation or tyrosine kinase inhibitors (TKIs) treatment. Importantly, higher BAP18 expression was positively correlated with the postoperative recurrence and the poor disease-free survival in clinical patients receiving sorafenib treatment. Altogether, we discovered that BAP18 plays an oncogenic role in the survival and proliferation of HCC cells, and BAP18 may serve as a predictive biomarker for adjunct TKIs treatment in patients with HCC, and further facilitate the precise treatment.

Proposed Two-Steps Procedure of Classification High Dimensional Data with Regularized Logistic Regression

The field of Bioinformatics has developed in response to the rapid increase in biological data, particularly high-dimensional gene expression data. Bioinformatics utilizes optimization, computational science, and statistical methods to effectively address challenges in the field of molecular biology. Numerous genes (variables) in gene expression are irrelevant to their study. Gene selection has been demonstrated to be an effective means of enhancing the performance of numerous methods of classification. The job of acquiring significant variables via the use of ranking variable selection (RVS) techniques and then picking the most effective classifier is an enormous challenge in the context of high-dimensional data. in this study, we proposed a new ranking filter method using smooth clipped absolute deviation depending on the resampling technique (RSVS) to obtain a proficient subset of genes with strong classification abilities. This is achieved by merging A screening technique employed as a filtering method in conjunction with Regularized Logistic Regression, such as LASSO,ALASSO,ENET, and MCP. The study involved the utilization of both simulated and real datasets to conduct an empirical evaluation of the proposed approach. The findings indicated that the proposed method outperformed other established methods. it was tested using three publicly data sets about Cancer. The Results demonstrate that the suggested approach is highly effective and viable, thus showing a strong level of performance with regards to accuracy, geometric mean, and the area under the curve. Furthermore, The findings suggest that the genes most often chosen are physiologically associated with the specific form of cancer. Therefore, the method that has been suggested has potential advantages for the classification of cancer via the use of DNA gene expression data within a clinical setting.

Transcription factors in microcephaly.

Higher cognition in humans, compared to other primates, is often attributed to an increased brain size, especially forebrain cortical surface area. Brain size is determined through highly orchestrated developmental processes, including neural stem cell proliferation, differentiation, migration, lamination, arborization, and apoptosis. Disruption in these processes often results in either a small (microcephaly) or large (megalencephaly) brain. One of the key mechanisms controlling these developmental processes is the spatial and temporal transcriptional regulation of critical genes. In humans, microcephaly is defined as a condition with a significantly smaller head circumference compared to the average head size of a given age and sex group. A growing number of genes are identified as associated with microcephaly, and among them are those involved in transcriptional regulation. In this review, a subset of genes encoding transcription factors (e.g., homeobox-, basic helix-loop-helix-, forkhead box-, high mobility group box-, and zinc finger domain-containing transcription factors), whose functions are important for cortical development and implicated in microcephaly, are discussed.

Genetic Variants in Canonical Wnt Signaling Pathway Associated with Pediatric ITP

Introduction : Pediatric immune thrombocytopenia (ITP) is thought to develop when a triggering event inappropriately activates an autoimmune anti-platelet response in the context of predisposing genetic factors. Inborn errors of immunity are increasingly being identified in cases of chronic, refractory autoimmune cytopenias. We sought to identify genetic variants associated with predisposition to 1) primary or secondary pediatric ITP of any disease duration versus healthy controls and 2) chronic ITP (cITP) versus disease that spontaneously resolves in &amp;lt; 1 year (sr-ITP). Methods : DNA and clinical data were derived from 8 sites from the Pediatric ITP Consortium of North America's (ICON) biorepository. Samples were genotyped using the Illumina Global Screening Array BeadChip. Genotypes were imputed using the Michigan Imputation Server HRC reference panel. Genetic variants that passed standard quality metrics and had a MAF ≥1% were retained. Control samples (n=8,372) were obtained from the National Longitudinal Study of Adolescent to Adult Health (Add Health) cohort. Logistic regression models were used to estimate adjusted odds ratios (aORs) comparing (1) ITP and control cohorts and (2) cITP and sr-ITP cohorts. Models assumed additive allelic effects and accounted for the top 3 principal components. Genome-wide significance was defined as P &amp;lt;5 × 10 -8 and suggestive of genome-wide significance, P &amp;lt;1 x 10 -5. Results : Six-hundred ten unique patient samples were genotyped. Nineteen (3.1%) did not pass quality control, leaving 591 for analysis. This cohort included 307 (52.0%) cITP patients, 209 (35.4%) sr-ITP patients, and 75 (12.7%) individuals without complete follow-up data to allow for classification of cITP or sr-ITP. The ITP cohort was 50.1% male, 50.1% non-Hispanic (NH) white, 29.4% Hispanic, 6.1% NH Black, 3.1% NH Asian, and 11.3% Other/Unknown. Compared with healthy controls, we identified 6 loci associated with ITP at genome-wide significance (Figure 1). Located within the intronic region of SLC24A4 rs75650997 was associated with an increased risk of ITP compared with controls (aOR: 2.38, P=3.9x10 -8). An intronic variant, rs2165798, in NAV2 was inversely associated with ITP (aOR: 0.52, P=3.2x10 -11). A variant in NKD1 rs4785216, was inversely associated with ITP (aOR: 0.43, P=8.86x10 -15).Another intergenic variant, rs4785426, in close proximity to NKD1 was also inversely associated with ITP (aOR: 0.48, P=1.84x10 -16) . An additional 20 variants met suggestive of genome-wide significance. When comparing sr-ITP and cITP patients, no SNVs (single nucleotide variant) reached genome-wide significance, but one variant, rs117609649, in ABCC4 met suggestive of genome-wide significance (aOR: 0.26, P=4.49x10 -7). Discussion : This is the largest, unbiased genetic study of pediatric ITP patients. The analysis comparing ITP versus healthy controls identified 20 suggestive SNVs and 6 which met genome-wide significance. Several of the top SNVs identified in this study affect Wnt/β-catenin signaling. Wnt-signaling impacts the development and regulation of immune cell populations including dendritic cells, macrophages, NK cells, B cells, and T cells. NAV2 activates Wnt/β-catenin signaling. NAV2 variants have been implicated in autoimmune conditions including Celiac disease and rheumatoid arthritis. NKD1 inhibits the canonical Wnt/β-catenin signaling pathway. The cumulative impact of these variants on Wnt activity in ITP should be evaluated in the future. No genetic variants met genome-wide significance in a comparison of sr-ITP and cITP patients. Collectively, these findings suggest there may be genetic variants implicated in ITP risk, but those genetic features are not specific to sr-ITP or cITP. A focused analysis of 632 genes that cause inborn errors of immunity (IEI) is ongoing. This includes gene burden testing and analysis of pathogenic variants within this gene subset. Variants in IEI genes will also be evaluated in a sub-population of patients with Evans syndrome. Conclusion : ITP is highly heterogenous in its presentation, disease course, and response to therapy. Mirroring its clinical behavior, the genetic contribution to ITP development is complex. This study identified potential SNVs associated with ITP, but not specific to sr-ITP or cITP. Variants in genes that affect the canonical Wnt-signaling pathway may play a role in ITP risk.

Exceptional Response to BTK Inhibitors in Aggressive Lymphomas Linked to Chronic Selective Autophagy

Diffuse large B cell lymphoma (DLBCL) is an aggressive cancer that is profoundly heterogeneous, both molecularly and phenotypically, presenting a challenge for precision medicine. Inhibitors of Bruton tyrosine kinase (BTK) block B cell receptor (BCR)-dependent NF-κB signaling and are particularly effective in DLBCL with mutations in the BCR subunit CD79B and MYD88 (MCD DLBCL). MCD tumors are enriched for a multiprotein supercomplex, termed the My-T-BCR, that is nucleated by MYD88 L265P, TLR9 and the BCR, and serves as a central hub of NF-κB signaling. The integrity of the My-T-BCR complex is rapidly compromised following BTK inhibition, but the molecular mechanisms responsible for the dissolution of this molecular machine have not been elucidated. To investigate the underlying mechanisms regulating the My-T-BCR, we used genome wide CRISPR-Cas9 screens in MCD DLBCL cell line models treated with the BTK inhibitors (BTKi) and compared the results to screens with inhibitors of SYK, IKK, mTOR, and BRD4. We identified several drug resistance genes encoding known negative regulators of BCR, NF-κB, and PI3 kinase signaling that were recurrently inactivated by mutation and/or deletion in DLBCL biopsies. Unexpectedly, we identified multiple autophagy-related genes involved autophagosome formation ( ATG9A, ATG101, ATG13, RB1CC1 and ATG14) and autophagosome membrane expansion ( ATG2A, WIPI2, WDR45) that strongly counteracted the toxicity of BTKi (≥3 SD). Notably, these autophagy genes did not promote resistance to the mTOR inhibitors, which induces classical autophagy. To gain further insight, we generated BTKi-resistant cell lines deficient in ATG9A or ATG101 (ATG KO) and performed genome-wide CRISPR screens and RNA-seq with or without BTKi. In doing so, we observed 11 ATG genes that displayed epistatic interactions, no longer conferring BTKi resistance in ATG KO MCD cells (p≤0.05). We also observed the buffering of many NF-κB negative regulators (p≤0.001) and the increased sensitivity to loss of NF-κB positive regulators (p≤0.05). Furthermore, gene expression studies showed a marked decrease of BCR, MYD88 and NF-κB signatures in control BTKi-treated cells, whereas ATG KOs demonstrated a rescue of these same gene signatures and displayed higher levels of nuclear NF-κB localization upon BTKi treatment. MCD patients display the highest levels of NF-κB gene expression compared to other genetic subtypes. Interestingly, MCD patients also displayed the lowest gene expression profile for a subset of the ATG genes (p≤2.7x10 -6), suggesting that this pathway may be counter-selected during MCD pathogenesis. As autophagy promotes the lysosomal degradation of proteins, and disruption of autophagy promoted NF-κB signaling in MCD cell lines, we assessed global protein levels and localization of proteins to the My-T-BCR in ATG KO cells using mass spectrometry. Selective autophagy receptors TAX1BP1, NBR1 and p62 were significantly upregulated in ATG KOs and displayed significant enrichment of proximity to MYD88 L265Pin ATG KOs (p≤0.01), suggesting MYD88 L265P is targeted for degradation by selective autophagy. To test this, we engineered MCD cell lines with dual fluorescent autophagy reporters (GFP-RFP fusions) for TAX1BP1, NBR1, p62, or MYD88 L265P. Each reporter displayed an accumulation of GFP relative to RFP in ATG KOs or upon treatment with the autophagy blocking v-ATPase inhibitor bafilomycin. To identify genes that modulate selective autophagy of MYD88 L265P, we performed a CRISPR screen in MCD cells stably expressing a MYD88 L265P-RFP-GFP reporter. We observed deletion of the same epistatic interactors of ATG9A in BTKi survival screens also blocked MYD88 L265P autophagic degradation. Conversely, deletion of BTK, mTORC1-related genes and IRF4 were all among the top-ranked genes that promoted MYD88 L265P autophagic degradation. We validated these findings using chemical inhibitors of each gene alone or in combination and observed synergy for the promotion of MYD88 L265P autophagic degradation. Collectively, we identified a non-canonical form of selective autophagy that chronically degrades MYD88 L265P, is counter-selected in MCD tumors, and is promoted by BTK inhibitors. Our findings help to elucidate the exceptional benefit of BTK-targeted therapies in the MCD DLBCL subtype and offer a rationally designed combination therapy regimen to specifically degrade this mutant allele of MYD88.

Molecular analyses of zebrafish V0v spinal interneurons and identification of transcriptional regulators downstream of Evx1 and Evx2 in these cells

BackgroundV0v spinal interneurons are highly conserved, glutamatergic, commissural neurons that function in locomotor circuits. We have previously shown that Evx1 and Evx2 are required to specify the neurotransmitter phenotype of these cells. However, we still know very little about the gene regulatory networks that act downstream of these transcription factors in V0v cells.MethodsTo identify candidate members of V0v gene regulatory networks, we FAC-sorted wild-type and evx1;evx2 double mutant zebrafish V0v spinal interneurons and expression-profiled them using microarrays and single cell RNA-seq. We also used in situ hybridization to compare expression of a subset of candidate genes in evx1;evx2 double mutants and wild-type siblings.ResultsOur data reveal two molecularly distinct subtypes of zebrafish V0v spinal interneurons at 48 h and suggest that, by this stage of development, evx1;evx2 double mutant cells transfate into either inhibitory spinal interneurons, or motoneurons. Our results also identify 25 transcriptional regulator genes that require Evx1/2 for their expression in V0v interneurons, plus a further 11 transcriptional regulator genes that are repressed in V0v interneurons by Evx1/2. Two of the latter genes are hmx2 and hmx3a. Intriguingly, we show that Hmx2/3a, repress dI2 interneuron expression of skor1a and nefma, two genes that require Evx1/2 for their expression in V0v interneurons. This suggests that Evx1/2 might regulate skor1a and nefma expression in V0v interneurons by repressing Hmx2/3a expression.ConclusionsThis study identifies two molecularly distinct subsets of zebrafish V0v spinal interneurons, as well as multiple transcriptional regulators that are strong candidates for acting downstream of Evx1/2 to specify the essential functional characteristics of these cells. Our data further suggest that in the absence of both Evx1 and Evx2, V0v spinal interneurons initially change their neurotransmitter phenotypes from excitatory to inhibitory and then, later, start to express markers of distinct types of inhibitory spinal interneurons, or motoneurons. Taken together, our findings significantly increase our knowledge of V0v and spinal development and move us closer towards the essential goal of identifying the complete gene regulatory networks that specify this crucial cell type.