Set Of Genes Research Articles

Molecular Differences With Therapeutic Implications in Early-Onset Compared With Average-Onset Biliary Tract Cancers.

Early-onset biliary tract cancer (eoBTC) is among the fast-growing subset of early-onset cancers, yet little is known about its biology. We sought to identify novel molecular characteristics of eoBTC in relation to average-onset BTC (aoBTC) using a real-world multiomics data set. The study comprised patients with BTC whose tumors underwent molecular analyses at Caris Life Sciences and were categorized by age (<50 years for eoBTC, ≥50 years for aoBTC). P values were adjusted for multiple testing and considered significant at Q < 0.05 (molecular comparisons) or Q < 0.25 (Gene Set Enrichment Analysis [GSEA]). Insurance claims data were used for survival analysis. The study included 5,587 patients with BTC (453 eoBTC, median age = 44 years and 5,134 aoBTC, median age = 68 years). FGFR2 fusion (15.7% in eoBTC v 5.9% in aoBTC) and NIPBL fusion (1.1% v 0%) were significantly more prevalent in eoBTC (both Q < 0.001). The interferon gamma-IFG score (fold change [FC], 1.1; Q = 0.01) and T-cell inflammation score (FC, 17.3; Q = 0.03) were significantly higher in aoBTC. On GSEA, angiogenesis was enriched in eoBTC (normalized enrichment score [NES] = 1.51; Q = 0.16), whereas IFG (NES = -1.58; Q = 0.06) and inflammatory response (NES = -1.46; Q = 0.18) were enriched in aoBTC. The median overall survival (OS) was 16.5 (eoBTC) versus 13.3 months (aoBTC), hazard ratio = 0.86, P = .004. The median OS by FGFR2 fusion (with fusion v without) was 21.7 versus 15.0 months (P = .47) for eoBTC and 18.6 versus 12.2 months (P < .001) for aoBTC. We identified crucial differences including higher prevalence of FGFR2 fusions in eoBTC and variations in immunotherapy-related markers. Better outcomes in eoBTC were affected by the FGFR2 fusion status. Our findings underscore the need for ensuring access to next-generation sequencing testing, including prompt identification of actionable targets.

Molecular characterization and expression patterns of MTP genes under heavy metal stress in mustard (Brassica juncea L.)

Members of the Metal Tolerance Protein (MTP) family are critical in mediating the transport and tolerance of divalent metal cations. Despite their significance, the understanding of MTP genes in mustard (Brassica juncea) remains limited, especially regarding their response to heavy metal (HM) stress. In our study, we identified MTP gene sets in Brassica rapa (17 genes), Brassica nigra (18 genes), and B. juncea (33 genes) using the HMMER (Cation_efflux; PF01545) and BLAST analysis. For the 33 BjMTPs, a comprehensive bioinformatics analysis covering the physicochemical properties, phylogenetic relationships, conserved motifs, protein structures, collinearity, spatiotemporal RNA-seq expression, GO enrichment, and expression profiling under six HM stresses (Mn2+, Fe2+, Zn2+, Cd2+, Sb3+, and Pb2+) were carried out. According to the findings of physicochemical characteristics, phylogenetic tree, and collinearity, the allopolyploid B. juncea’s MTP genes were inherited from its progenitors, B. rapa and B. nigra, with minimal gene loss during polyploidization. Members of the BjMTP family exhibited conserved motifs, promoter elements, and expression patterns across subgroups, consistent with the seven evolutionary branches (G1, G4–G9, and G12) of the MTPs. Further, spatiotemporal expression profiling under HM stresses successfully identified specific genes and crucial cis-regulatory elements associated with the response of BjMTPs to HM stresses. These findings may contribute to the genetic improvement of B. juncea for enhanced HM tolerance, facilitating the remediation of HM-contaminated areas.

Interferon-signaling pathways are upregulated in people with HIV with abnormal pulmonary diffusing capacity (DL CO ).

People with HIV (PWH) are at greater risk of developing lung diseases even when they are antiretroviral therapy (ART)-adherent and virally suppressed. The most common pulmonary function abnormality in PWH is that of impaired diffusing capacity of the lungs for carbon monoxide (DL CO ), which is an independent risk factor for increased mortality in PWH. Earlier work has identified several plasma biomarkers of inflammation and immune activation to be associated with decreased DL CO . However, the underpinning molecular mechanisms of HIV-associated impaired DL CO are largely unknown. Cross-sectional pilot study with PWH with normal DL CO (values greater than or equal to the lower limit of normal, DL CO ≥ LLN, N = 9) or abnormal DL CO (DL CO < LLN, N = 9). We compared the gene expression levels of over 900 inflammation and immune exhaustion genes in PBMCs from PWH with normal vs. abnormal DL CO using the NanoString technology. We found that 26 genes were differentially expressed in the impaired DL CO group. These genes belong to 4 categories: 1. Nine genes in inflammation and immune activation pathways, 2. seven upregulated genes that are direct targets of the interferon signaling pathway, 3. seven B-cell specific genes that are downregulated, and 4. three miscellaneous genes. These results were corroborated using the bioinformatics tools DAVID (Database for Annotation, Visualization and Integrated Discovery) and GSEA (Gene Sets Enrichment Analysis). The data provides preliminary evidence for the involvement of sustained interferon signaling as a molecular mechanism for impaired DL CO in PWH.

Pan-cancer analysis of SERPINE1 with a concentration on immune therapeutic and prognostic in gastric cancer.

The serine protease inhibitor clade E member 1 (SERPINE1) is a key modulator of the plasminogen/plasminase system and has been demonstrated to promote tumor progression and metastasis in various tumours. However, although much literature has explored the cancer-promoting mechanism of SERPINE1, the pan-cancer analyses of its predictive value and immune response remain unexplored. The differential expression, and survival analysis of SERPINE1 expression in multiple cancers were analysed using The Cancer Genome Atlasand Genotype-Tissue Expression database. Kaplan-Meier (K-M) plotter and survival data analysis were used to analyze the prognostic value of SERPINE1 expression, including overall survival (OS), disease-specific survival, disease-free interval and progression-free interval and investigated the relationship of SERPINE1 expression with microsatellite instability. We further analysed the correlation between the expression of SERPINE1 and immune infiltration. The Kyoto Encyclopaedia of Genes and Genomes pathway was used for enrichment analysis, and the Gene Set Enrichment Analysis (GSEA) database was used to perform pathway analysis. Finally, invitro experiments demonstrated that knockdown or overexpression of SERPINE1 could alter the proliferation and migration of gastric cancer (GC) cells. The results indicated that SERPINE1 expression levels different significantly between cancer and normal tissues, meanwhile, it was highly expressed in various cancers. By analysing online data, it has been observed that the gene SERPINE1 exhibits heightened expression levels across a variety of human cancers, significantly impacting patient survival rates. Notably, the presence of SERPINE1 was strongly associated with decrease OS and disease-free survival in individuals diagnosed with GC. Furthermore, an observed link indicates that higher levels of SERPINE expression are associated with increased infiltration of immune cells in GC. Finally, invitro experiments showed that knockdown or overexpression of SERPINE1 inhibited the growth, and migration, of GC cells. SERPINE1expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in GC. This study shows that SERPINE1 is an oncogene that participates in regulating the immune infiltration and affecting the prognosis of patients in multiple cancers, especially in GC. These findings underscore the importance of further investigating the role of SERPINE1 in cancer progression and offer a promising direction for the development of new therapeutic strategies.

Exploring the Potential Mechanisms of Action of Gentiana Veitchiorum Hemsl. Extract in the Treatment of Cholestasis using UPLC-MS/MS, Systematic Network Pharmacology, and Molecular Docking.

Gentiana veitchiorum Hemsl. (GV) has a long history in Tibetan medicine for treating hepatobiliary disease cholestasis. However, the mechanisms mediating its efficacy in treating cholestasis have yet to be determined. To elucidate the mechanisms of action of GV in the treatment of cholestasis, an integrated approach combining ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis with network pharmacology was established. A comprehensive analysis of the chemical composition of GV was achieved by UPLC-MS/MS. Subsequently, a network pharmacology method that integrated target prediction, a protein-protein interaction (PPI) network, gene set enrichment analysis, and a component- target-pathway network was established, and finally, molecular docking and experiments in vitro were conducted to verify the predicted results. Twenty compounds that were extracted from GV were identified by UPLC-MS/MS analysis. Core proteins such as AKT1, TNF, and IL6 were obtained through screening in the Network pharmacology PPI network. The Kyoto Encyclopedia of the Genome (KEGG) pathway predicted that GV could treat cholestasis by acting on signaling pathways such as TNF/IL-17 / PI3K-Akt. Network pharmacology suggested that GV might exert a therapeutic effect on cholestasis by regulating the expression levels of inflammatory mediators, and the results were further confirmed by the subsequent construction of an LPS-induced RAW 264.7 cell model. In this study, UPLC-MS/MS analysis, network pharmacology, and experiment validation were used to explore potential mechanisms of action of GV in the treatment of cholestasis.

Identification of candidate genes and molecular mechanisms related to asthma progression using bioinformatics.

Asthma is a heterogeneous disorder. This study aimed to identify changes in gene expression and molecular mechanisms associated with moderate to severe asthma. Differentially expressed genes (DEGs) were analyzed in GSE69683 dataset among moderate asthma and its controls as well as between severe asthma and moderate asthma. Key module genes were identified via co-expression analysis, and the molecular mechanism of the module genes was explored through enrichment analysis and gene set enrichment analysis (GSEA). GSE89809 was used to verify the characteristic genes related to moderate and severe asthma. Accordingly, 2540 DEGs were present between moderate asthma and the control group, while 6781 DEGs existed between severe asthma and moderate asthma. These genes were identified into 14 co-expression modules. Module 7 had the highest positive correlation with severe asthma and was recognized to be a key module by STEM. Enrichment analysis demonstrated that the module genes were mainly involved in oxidative stress-related signaling pathways. The expression of HSPA1A, PIK3CG and PIK3R6 was associated with moderate asthma, while MAPK13 and MMP9 were associated with severe asthma. The AUC values were verified by GSE89809. Additionally, 322 drugs were predicted to target five genes. These results identified characteristic genes related to moderate and severe asthma and their corresponding molecular mechanisms, providing a basis for future research.

Gene expression patterns associated with PFOA exposure in Czech Young men and women

Perfluorooctanoic acid (PFOA), a member of per- and polyfluoroalkyl substances (PFASs), has been widely used in manufacturing for decades. Currently, PFOA is strictly regulated, but due to its high stability and persistence, it is detected in both environmental as well as in human matrices. To elucidate mechanisms of PFOA toxicity in humans, we determined the genome-wide transcriptomic changes of peripheral blood mononuclear cells (PBMC) responding to PFOA exposure in a sex-stratified analysis. This work employed samples from 145 female and 143 male participants of the CELSPAC: YA study to characterize PFOA-associated transcripts in a broader context using computational analysis. PFOA-associated gene expression differed significantly between men and women, as only 2% of mapped genes were expressed in both sexes. Disease-specific enrichment analysis revealed cancer and immune-related disease terms as those most enriched in male and female populations. Patterns of enriched terms within the gene set enrichment analysis indicated three main targets of PFOA toxicity: i) lipid metabolism for women; ii) cell cycle regulation for men; and iii) immune system response for both sexes. In summary, our genome-wide transcriptomics analysis described sex-specific differences in PFOA-associated gene expression and provided evidence about biological pathways underlying PFOA toxicity in humans.

Novel inhibition of central carbon metabolism pathways by Rac and Cdc42 inhibitor MBQ-167 and paclitaxel.

Triple negative breast cancer (TNBC) represents a therapeutic challenge where standard chemotherapy is limited to paclitaxel. MBQ-167, a clinical stage small molecule inhibitor that targets Rac and Cdc42, inhibits tumor growth and metastasis in mouse models of TNBC. Herein, we investigated the efficacy of MBQ-167 in combination with paclitaxel in TNBC pre-clinical models, as a prelude to safety trials of this combination in advanced breast cancer patients. Individual MBQ-167 or combination therapy with paclitaxel was more effective at reducing TNBC cell viability and increasing apoptosis compared to paclitaxel alone. In orthotopic mouse models of human TNBC (MDA-MB-231 and MDA-MB-468), individual MBQ-167, paclitaxel, or the combination reduced mammary tumor growth with similar efficacy, with no apparent liver toxicity. However, paclitaxel single agent treatment significantly increased lung metastasis, while MBQ-167, single or combined, reduced lung metastasis. In the syngeneic 4T1/BALB/c model, combined MBQ-167 and paclitaxel decreased established lung metastases by ~80%. To determine the molecular basis for the improved efficacy of the combined treatment on metastasis, 4T1 tumor extracts from BALB/c mice treated with MBQ-167, paclitaxel, or the combination were subjected to transcriptomic analysis. Gene set enrichment identified specific downregulation of central carbon metabolic pathways by the combination of MBQ-167 and Paclitaxel but not individual compounds. Biochemical validation, by immunoblotting and metabolic Seahorse analysis, shows that combined MBQ-167 and paclitaxel reduces glycolysis. This study provides a strong rationale for the clinical testing of MBQ-167 in combination with paclitaxel as a potential therapeutic for TNBC and identifies a unique mechanism of action.

Growth factor-loaded ovarian extracellular matrix hydrogels promote in vivo ovarian niche regeneration and enhance fertility in premature ovarian insufficiency preclinical models

Premature ovarian insufficiency (POI) means menopause before 40 years of age affecting about 1% of women. Approaches based on cell therapy and the paracrine effects of stem cells or bioproducts such as platelet-rich plasma have been proposed, but concerns remain about undesired systemic effects, as well as the need to optimize delivery methods through bioengineering methods. This study explores the efficacy of decellularized bovine ovarian cortex extracellular matrix (OvaECM) hydrogels alone and as a growth factor (GF) carrier (OvaECM+GF) in a chemotherapy-induced POI murine model. In vitro assays showed a gradual release of GF from the OvaECM sustained for two weeks. Chemotherapy drastically reduced follicle numbers, but OvaECM+GF treatment restored pre-antral follicle development. Moreover, this treatment notably regenerated the ovarian microenvironment by increasing cell proliferation and microvessel density while reducing chemotherapy-induced apoptosis and fibrosis. Whole-ovary RNA sequencing and gene set enrichment analysis revealed an upregulation of regeneration-related genes and a downregulation of apoptotic pathways. The OvaECM+GF treatment also yielded significantly better outcomes following ovarian stimulation and in vitro fertilization. After two consecutive crossbreeding cycles, OvaECM+GF-treated mice showed normal reproductive function. This research showcases the biocompatibility and efficacy of OvaECM to reverse POI in mice, setting a foundation to explore innovative bioengineering-based POI therapies. Statement of significancePremature ovarian insufficiency (POI) affects about 1% of women worldwide, causing early menopause before 40 years old. Current treatments alleviate symptoms but do not restore ovarian function. This study explores an innovative approach using ovarian cortex extracellular matrix hydrogels to deliver growth factors into the murine ovarian niche and reverse POI. In vitro release kinetic assays demonstrated a gradual and sustained release of growth factors. In a POI-induced mouse model, intraovarian injections of the hydrogel encapsulating growth factors restored pre-antral follicle development, increased cell proliferation, reduced apoptosis and fibrosis, and improved ovarian response and in vitro fertilization outcomes. Long-term benefits included larger litter sizes. This innovative technique shows promise in regenerating the ovarian environment and improving reproductive outcomes.

Lung-MAP Next Generation Sequencing Analysis of Advanced Squamous Cell Lung Cancers (SWOG S1400)

IntroductionSquamous cell cancer (SqCC) is a lung cancer subtype with few targeted therapy options. Molecular characterization, i.e., by next generation sequencing (NGS), is needed to identify potential targets. Lung-MAP SWOG S1400 enrolled patients with previously treated stage IV or recurrent SqCC to assess NGS biomarkers for therapeutic substudies. MethodsTumors underwent NGS using Foundation Medicine’s FoundationOne research platform, which sequenced the exons and/or introns of 313 cancer-related genes. Mutually Exclusive Gene Set Analysis (MEGSA) and Selected Events Linked by Evolutionary Conditions across human Tumors (SELECT) were performed to identify mutually exclusive and co-occurring gene alterations. Comparisons were performed with data on 495 lung SqCC downloaded from The Cancer Genome Atlas. Cox proportional hazards models were used to examine associations between genetic variants and survival. ResultsNGS data are reported for 1672 patients enrolled on S1400 between 2014 and 2019. MEGSA identified two non-overlapping sets of mutually exclusive alterations with a false discovery rate < 15%: NFE2L2, KEAP1 and PARP4; and CDKN2A and RB1. PARP4, a relatively uncharacterized gene, showed three frequent mutations suggesting functional significance: 3116T>C (I1039T), 3176A>G (Q1059R) and 3509C>T (T1170I). NFE2L2 and KEAP1 alterations when taken together were associated with poorer survival. ConclusionsAs the largest dataset to-date of lung SqCC profiled on a clinical trial, the S1400 NGS dataset establishes a rich resource for biomarker discovery. Mutual exclusivity of PARP4 and NFE2L2 or KEAP1 alterations suggests that PARP4 may have an uncharacterized role in a key pathway known to impact oxidative stress response and treatment resistance.

UBE2D3 regulated by WTAP-mediated m6A modification inhibits temozolomide chemosensitivity in glioblastoma.

To explore how the ubiquitin-conjugating enzyme E2D3 (UBE2D3) influences temozolomide (TMZ) resistance in glioblastoma (GBM), and to clarify the association between UBE2D3 and WTAP. The UBE2D3 protein expression in GBM tissues were detected using immunohistochemistry (IHC) through tissue microarrays. The potential pathways of UBE2D3 in TCGA-GBM were predicted via Gene Set Enrichment Analysis (GSEA). To investigate UBE2D3's role in TMZ resistance, GBM cells were transduced with UBE2D3 shRNA or overexpression lentivirus, followed by assessments of CCK-8, flow cytometry, comet assay, and western blot analysis. Furthermore, a subcutaneous tumor model was established in nude mice using U87 cells transduced with interfering lentivirus to observe tumor growth and assess cell apoptosis using TUNEL staining. Mechanically, m6A content analysis, m6A methylated RNA immunoprecipitation quantitative PCR, reporter gene assay, mRNA stability measurements, RNA immunoprecipitation, quantitative Real-Time PCR, and Western blot assays were carried out to verify the role of WTAP/IGF2BP1 in regulating UBE2D3 expression. UBE2D3 exhibited elevated expression levels in GBM tissues compared with normal brain tissues and was associated with the DNA repair signaling pathway. In both in vitro and in vivo studies, it was demonstrated that TMZ treatment combined with reduced UBE2D3 expression further suppressed U87 cell viability and tumor growth, with a notable increase in apoptosis rate and DNA damage. Conversely, the overexpression of UBE2D3 had the opposite impact. Furthermore, our findings revealed that WTAP promotes the m6A modification of UBE2D3 via an IGF2BP1-dependent mechanism. The WTAP-IGF2BP1 axis regulates UBE2D3 stability in an m6A-dependent manner, influencing tumor malignancy and TMZ chemosensitivity in GBM via the DNA repair signaling pathway.

Identification of effective diagnostic genes and immune cell infiltration characteristics in small cell lung cancer by integrating bioinformatics analysis and machine learning algorithms.

To identify potential diagnostic markers for small cell lung cancer (SCLC) and investigate the correlation with immune cell infiltration. GSE149507 and GSE6044 were used as the training group, while GSE108055 served as validation group A and GSE73160 served as validation group B. Differentially expressed genes (DEGs) were identified and analyzed for functional enrichment. Machine learning (ML) was used to identify candidate diagnostic genes for SCLC. The area under the receiver operating characteristic curves was applied to assess diagnostic efficacy. Immune cell infiltration analyses were carried out. There were 181 DEGs identified. The gene ontology analysis showed that DEGs were enriched in 455 functional annotations, some of which were associated with immunity. The kyoto encyclopedia of genes and genomes analysis revealed that there were 9 signaling pathways enriched. The disease ontology analysis indicated that DEGs were related to 116 diseases. The gene set enrichment analysis results displayed multiple items closely related to immunity. ZWINT and NRCAM were screened using ML and further validated as diagnostic genes. Significant differences were observed in SCLC with normal lung tissue samples among immune cell infiltration characteristics. Strong associations were found between the diagnostic genes and immune cell infiltration. This study identified 2 diagnostic genes, ZWINT and NRCAM, that were related to immune cell infiltration by integrating bioinformatics analysis and ML algorithms. These genes could serve as potential diagnostic biomarkers and provide possible molecular targets for immunotherapy in SCLC.

Unique expression and critical role of metallothionein 3 in the control of osteoclastogenesis and osteoporosis.

Bone homeostasis is maintained by an intricate balance between osteoclasts and osteoblasts, which becomes disturbed in osteoporosis. Metallothioneins (MTs) are major contributors in cellular zinc regulation. However, the role of MTs in bone cell regulation has remained unexplored. Single-cell RNA sequencing analysis discovered that, unlike the expression of other MT members, the expression of MT3 was unique to osteoclasts among various macrophage populations and was highly upregulated during osteoclast differentiation. This unique MT3 upregulation was validated experimentally and supported by ATAC sequencing data analyses. Downregulation of MT3 by gene knockdown or knockout resulted in excessive osteoclastogenesis and exacerbated bone loss in ovariectomy-induced osteoporosis. Transcriptome sequencing of MT3 knockdown osteoclasts and gene set enrichment analysis indicated that the oxidative stress and redox pathways were enriched, which was verified by MT3-dependent regulation of reactive oxygen species (ROS). In addition, MT3 deficiency increased the transcriptional activity of SP1 in a manner dependent on intracellular zinc levels. This MT3-zinc-SP1 axis was crucial for the control of osteoclasts, as zinc chelation and SP1 knockdown abrogated the promotion of SP1 activity and osteoclastogenesis by MT3 deletion. Moreover, SP1 bound to the NFATc1 promoter, and overexpression of an inactive SP1 mutant negated the effects of MT3 deletion on NFATc1 and osteoclastogenesis. In conclusion, MT3 plays a pivotal role in controlling osteoclastogenesis and bone metabolism via dual axes involving ROS and SP1. The present study demonstrated that MT3 elevation is a potential therapeutic strategy for osteolytic bone disorders, and it established for the first time that MT3 is a crucial bone mass regulator.

Archaeal mevalonate pathway in the uncultured bacterium Candidatus Promineifilum breve belonging to the phylum Chloroflexota.

The archaeal mevalonate pathway is a recently discovered modified version of the eukaryotic mevalonate pathway. This pathway is widely conserved in archaea, except for some archaeal lineages possessing the eukaryotic or other modified mevalonate pathways. Although the pathway seems almost exclusive to the domain Archaea, the whole set of homologous genes of the pathway is found in the metagenome-assembled genome sequence of an uncultivated bacterium, Candidatus Promineifilum breve, of the phylum Chloroflexota. To prove the existence of the archaea-specific pathway in the domain Bacteria, we confirmed the activities of the enzymes specific to the pathway, phosphomevalonate dehydratase and anhydromevalonate phosphate decarboxylase, because only these two enzymes are absent in closely related Chloroflexota bacteria that possess a different type of modified mevalonate pathway. The activity of anhydromevalonate phosphate decarboxylase was evaluated by carotenoid production via the archaeal mevalonate pathway reconstituted in Escherichia coli cells, whereas that of phosphomevalonate dehydratase was confirmed by an in vitro assay using the recombinant enzyme after purification and iron-sulfur cluster reconstruction. Phylogenetic analyses of some mevalonate pathway-related enzymes suggest an evolutionary route for the archaeal mevalonate pathway in Candidatus P. breve, which probably involves horizontal gene transfer events.IMPORTANCEThe recent discovery of various modified mevalonate pathways in microorganisms, such as archaea and Chloroflexota bacteria, has shed light on the complexity of the evolution of metabolic pathways, including those involved in primary metabolism. The fact that the archaeal mevalonate pathway, which is almost exclusive to the domain Archaea, exists in a Chloroflexota bacterium provides valuable insights into the molecular evolution of the mevalonate pathways and associated enzymes. Putative genes probably involved in the archaeal mevalonate pathway have also been found in the metagenome-assembled genomes of Chloroflexota bacteria. Such genes can contribute to metabolic engineering for the bioproduction of valuable isoprenoids because the archaeal mevalonate pathway is known to be an energy-saving metabolic pathway that consumes less ATP than other mevalonate pathways do.

Forkhead Box Protein K1 Promotes Chronic Kidney Disease by Driving Glycolysis in Tubular Epithelial Cells.

Renal tubular epithelial cells (TECs) undergo an energy-related metabolic shift from fatty acid oxidation to glycolysis during chronic kidney disease (CKD) progression. However, the mechanisms underlying this burst of glycolysis remain unclear. Herein, a new critical glycolysis regulator, the transcription factor forkhead box protein K1 (FOXK1) that is expressed in TECs during renal fibrosis and exhibits fibrogenic and metabolism-rewiring capacities is reported. Genetic modification of the Foxk1 locus in TECs alters glycolytic metabolism and fibrotic lesions. A surge in the expression of a set of glycolysis-related genes following FOXK1 protein activation contributes to the energy-related metabolic shift. Nuclear-translocated FOXK1 forms condensate through liquid-liquid phase separation (LLPS) to drive the transcription of target genes. Core intrinsically disordered regions within FOXK1 protein are mapped and validated. A therapeutic strategy is explored by targeting the Foxk1 locus in a murine model of CKD by the renal subcapsular injection of a recombinant adeno-associated virus 9 vector encoding Foxk1-short hairpin RNA. In summary, the mechanism of a FOXK1-mediated glycolytic burst in TECs, which involves the LLPS to enhance FOXK1 transcriptional activity is elucidated.

Hybrid Adaptive Threshold Segmentation for predicting Breast Cancer

Breast cancer is a leading cause of death for women in many parts of the world. The disease is often misdiagnosed until it has progressed beyond the point of effective treatment. Therefore, early detection of the disease would aid in reducing mortality and other associated risks. Microarray gene expression data is difficult to identify and interpret, making it challenging to evaluate and choose the most relevant set of genes for use as breast cancer markers. Our research utilized Matlab 2018a and the Breast Cancer Wisconsin Diagnostic dataset to develop a mixed machine-learning model for fast breast cancer prediction. Here, we apply various machine learning techniques including random forest classification, logistic regression, support vector machine and Naive Bayes, as well as to a dataset to make predictions about their development and eventual size. The success percentage for the eXtreme Gradient Boosting classifier compared to various machine learning approaches is 99.78%. This new approach to prediction has the potential to revolutionize the detection, analysis and prognosis of breast cancer.

Integrative mRNA and miRNA Expression Profiles from Developing Zebrafish Head Highlight Brain-Preference Genes and Regulatory Networks.

Zebrafish is an emerging animal model for studying molecular mechanism underlying neurodevelopmental disorder due to its advantage characters. miRNAs are small non-coding RNAs that play a key role in brain development. Understanding of dynamic transcriptional and post-transcriptional molecules and their regulation during the head development is important for the study of neurodevelopmental disorder. In this study, we performed the high-throughput sequencing of mRNAs and miRNAs in developing zebrafish head from pharyngula to early larval stages and carried out bioinformatic analysis including differential expression and functional enrichment as well as joint analysis of miRNAs and mRNAs, and also compared with other related public sequencing datasets to aid our interpretation. A large number of differential expression genes with a large fold change were detected during the head development. Further clustering and functional enrichment analyses indicated that genes in late stage were most related with synaptic signaling. Overlap test analysis showed a significant enrichment of brain-preference and synapse-associated gene set in the head transcriptome compared with the whole embryo transcriptome. We also constructed miRNA-mRNA network for those brain-preference genes and focused on those densely connected network components. CRISPR-Cas9-mediated snap25b mutants led to embryonic development defects and decreases locomotor activity. Altogether, the present study provides developmental profiles of head-enriched mRNAs and miRNAs at three critical windows for nervous system development, which may contribute to the study of neurodevelopmental disorder.

Immune infiltration and prognosis in gastric cancer: role of NAD+ metabolism-related markers.

This study endeavored to develop a nicotinamide adenine dinucleotide (NAD+) metabolism-related biomarkers in gastric cancer (GC), which could provide a theoretical foundation for prognosis and therapy of GC patients. In this study, differentially expressed genes (DEGs1) between GC and paraneoplastic tissues were overlapped with NAD+ metabolism-related genes (NMRGs) to identify differentially expressed NMRGs (DE-NMRGs). Then, GC patients were divided into high and low score groups by gene set variation analysis (GSVA) algorithm for differential expression analysis to obtain DEGs2, which was overlapped with DEGs1 for identification of intersection genes. These genes were further analyzed using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses to obtain prognostic genes for constructing a risk model. Enrichment and immune infiltration analyses further investigated investigate the different risk groups, and qRT-PCR validated the prognostic genes. Initially, we identified DE-NMRGs involved in NAD biosynthesis, with seven (DNAJB13, CST2, THPO, CIDEA, ONECUT1, UPK1B and SNCG) showing prognostic significance in GC. Subsequent, a prognostic model was constructed in which the risk score, derived from the expression profiles of these genes, along with gender, emerged as robust independent predictors of patient outcomes in GC. Enrichment analysis linked high-risk patients to synaptic membrane pathways and low-risk to the CMG complex pathway. Tumor immune infiltration analysis revealed correlations between risk scores and immune cell abundance, suggesting a relationship between NAD+ metabolism and immune response in GC. The prognostic significance of our identified genes was validated by qRT-PCR, which confirmed their upregulated expression in GC tissue samples. In this study, seven NAD+ metabolism-related markers were established, which is of great significance for the development of prognostic molecular biomarkers and clinical prognosis prediction for gastric cancer patients.

Identification of Key Efferocytosis-Related Genes and Mechanisms in Diabetic Retinopathy.

This study aimed to explore the key efferocytosis-related genes in diabetic retinopathy (DR) and their regulatory mechanisms. Public DR-related gene expression datasets, GSE160306 (training) and GSE60436 (validation), were downloaded. Differentially expressed efferocytosis-related genes (DEERGs) were analyzed using differential expression analysis and weighted gene co-expression network analysis. Functional enrichment analysis was conducted. Moreover, efferocytosis-related signature genes were identified using machine learning analysis, and their expression levels and diagnostic value were analyzed. Furthermore, nomograms were constructed; immune cell infiltration was analyzed; and gene set enrichment analysis, transcriptional regulation analysis, and small-molecule drug (SMD) prediction of efferocytosis-related signature genes were performed. In total, 36 DEERGs were identified in DR, and were markedly enriched in multiple functions, such as visual system development. Through further machine learning analysis, two efferocytosis-related signature genes, Ferritin Light Chain (FTL) and Fc Gamma Binding Protein (FCGBP), were identified, and were found to be upregulated in DR samples and showed high diagnostic performance for DR. A nomogram constructed using FTL and FCGBP accurately predicted the risk of DR. Moreover, the level of infiltration of immature B cells was positively correlated with FTL and FCGBP expression levels. Multiple transcription factors (TFs), such as CCCTC-Binding Factor (CTCF) and KLF Transcription Factor 9 (KLF9), were found to interact with both FTL and FCGBP. In addition, FTL can be targeted by miRNAs, such as miR-22-3p, and FCGBP can be targeted by miR-7973. In addition, both FTL and FCGBP can be targeted by SMDs, such as bisphenol A. Key efferocytosis-related genes, such as FTL and FCGBP, may promote DR development. Detecting or targeting FTL and FCGBP may aid in the prevention, diagnosis, and treatment of DR.

Genomics and proteomics to determine novel molecular subtypes and predict the response to immunotherapy and the effect of bevacizumab in glioblastoma

Glioblastoma (GBM) is a highly aggressive, infiltrative malignancy that cannot be completely cured by current treatment modalities, and therefore requires more precise molecular subtype signatures to predict treatment response for personalized precision therapy. Expression subtypes of GBM samples from the Cancer Genome Atlas (TCGA) were identified using BayesNM and compared with existing molecular subtypes of GBM. Biological features of the subtypes were determined by single-sample gene set enrichment analysis. Genomic and proteomic data from GBM samples were combined and Genomic Identification of Significant Targets in Cancer analysis was used to screen genes with recurrent somatic copy-number alterations phenomenon. The immune environment among subtypes was compared by assessing the expression of immune molecules and the infiltration of immune cells. Molecular subtypes adapted to immunotherapy were identified based on Tumor Immune Dysfunction and Exclusion (TIDE) score. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was performed on the expression profiles of S2, S3 and S4 in TCGA-GBM and RPPA to determine the respective corresponding best predictive model. Four novel molecular subtypes were classified. Specifically, S1 exhibited a low proliferative profile; S2 exhibited the profile of high proliferation, IDH1 mutation, TP53 mutation and deletion; S3 was characterized by high immune scores, innate immunity and adaptive immune infiltration scores, with the lowest TIDE score and was most likely to benefit from immunotherapy; S4 was characterized by high proliferation, EGFR amplification, and high protein abundance, and was the most suitable subtype for bevacizumab. LASSO analysis constructed the best prediction model composed of 13 genes in S2 with an accuracy of 96.7%, and the prediction model consisting of 17 genes in S3 with an accuracy of 86.7%, and screened 14 genes as components of the best prediction model in S4 with an accuracy of 93%. To conclude, our study classified reproducible and robust molecular subtypes of GBM, and these findings might contribute to the identification of patients responding to immunotherapy, thereby improving GBM prognosis.