Genes In Genome Research Articles

Interaction between plant-specific transcription factors TCP and YABBY expressed in the tendrils of the melon Cucumis melo

Plant tendrils are specialized organs that can twine around other structures to facilitate climbing. They occur in a variety of plant families and have diverse ontogenic origins. In cucurbits, tendrils originate from lateral shoots. Fine mapping verified that the tendril-less ctl mutation of the melon Cucumis melo corresponds to a frameshift mutation in the CmTCP1 gene, which encodes a TCP transcription factor. A yeast two-hybrid screen for CmTCP1/CTL-interacting proteins identified a member of the plant-specific YABBY transcription factor family, which was named CmYAB1. Each of the N- and C-terminal regions of CmTCP1 interacted with CmYAB1. The ctl mutation impaired the interaction between CmTCP1 and CmYAB1. Both proteins interacted in vitro and were localized to the nucleus in plant cells. In situ expression analysis revealed the coexistence of the CmTCP1 and CmYAB1 mRNAs in the abaxial domains of developing tendrils. An RNA-seq analysis of the seven YABBY genes in the melon genome revealed relatively high expression ratios of CmYAB1 in tendrils compared with those in leaves. These results suggest a novel function of the YABBY protein through its interaction with a TCP protein in the development of cucurbit tendrils.

ERBB2 is a potential diagnostic and prognostic biomarker in renal clear cell carcinoma

Renal clear cell carcinoma (ccRCC) is a common parenchymal tumor of the kidney, and the discovery of biomarkers for early and effective diagnosis of ccRCC can improve the early diagnosis of patients and thus improve long-term survival. Erb-b2 receptor tyrosine kinase 2 (ERBB2) mediates the processes of cell proliferation, differentiation, and apoptosis inhibition. The purpose of this study was to investigate the diagnostic and prognostic role of ERBB2 in ccRCC. We analyzed the expression levels of ERBB2 in various cancers from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RNA-seq data were analyzed using R packages to identify differentially expressed genes between the high and low ERBB2 expression groups in the TCGA-KIRC dataset. Spearman correlation analysis was performed to determine the correlation between ERBB2 expression and immune cell infiltration, immune checkpoint expression, and PTEN expression. DNA methylation changes and genetic alterations in ERBB2 were assessed using the MethSurv and cBioPortal databases. Logistic regression analysis was performed to determine the correlation between ERBB2 expression and the clinicopathological characteristics of ccRCC patients. The diagnostic and prognostic value of ERBB2 was assessed using Kaplan‒Meier (K‒M) survival curves, diagnostic ROC curves, time-dependent ROC curves, nomogram models, and Cox regression models. The expression level of ERBB2 is lower in tumor tissues of ccRCC patients than in the corresponding control tissues. Differentially expressed genes associated with ERBB2 were significantly enriched in the pathways “BMP2WNT4FOXO1 pathway in primary endometrial stromal cell differentiation” and “AMAN pathway”. In ccRCC tissues, ERBB2 expression levels were associated with immune cell infiltration, immune checkpoints, and PTEN. The DNA methylation status of 10 CpG islands in the ERBB2 gene was associated with the prognosis of ccRCC. ERBB2 expression levels in ccRCC tissues were associated with race, sex, T stage, M stage, histological grade, and pathological stage. Cox regression analysis showed that ERBB2 was a potential independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in ccRCC patients. ROC curve analysis showed that the expression level of ERBB2 could accurately distinguish between ccRCC tissue and adjacent normal renal tissue. Our study showed that ERBB2 expression in ccRCC tissues can be of clinical importance as a potential diagnostic and prognostic biomarker.

A unified-field theory of genome organization and gene regulation

A unified-field theory of genome organization and gene regulation

Construction and experimental verification of a novel nine-glycosylation-related gene prognostic risk model for clear cell renal carcinoma

ObjectivePatients with clear cell renal carcinoma (ccRCC) typically have poor prognosis. Glycosylation modification plays an important role in ccRCC. This study aimed to develop a novel signature for predicting ccRCC prognosis based on glycosylation-related genes (GRGs). MethodsDifferentially expressed GRGs (DE_GRGs) were identified using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus and used for constructing the risk model. The function of key genes was validated. ResultsTwenty-two DE_GRGs were intersected between GSE53757 and TCGA. Patients with ccRCC were divided into two clusters based on the expression profile of these DE_GRGs. Significant differences in the infiltration of 10 immune cell types were observed between two subclusters. Subsequently, the prognostic signatures of nine DE_GRGs (CHST9, COLGALT1, FUT3, FUT6, HS3ST2, POMGNT2, ST8SIA4, UGT3A1, and UGT8) were established. Patients in the high-risk group showed a poorer prognosis relative to the low-risk group. According to univariate and multivariate Cox regression analyses, the risk score, stage, and grade could be independent prognostic factors. A nomogram incorporating information on gender, age, risk group, TNM stage, and clinical stage showed accurate prediction in the survival probability. Except for CHST9, HS3ST2, and ST8SIA4, expression patterns of the remaining 6 DE_GRGs in Caki-1and 786-O cells were confirmed by quantitative real-time PCR. FUT6 overexpression resulted in the inhibition of proliferation, migration, and invasion of ccRCC cells. ConclusionThis study established a nine-DE_GRG-based prognostic signature, which independently predicted ccRCC prognosis. This finding emphasizes that GRGs are stratification factors for the precise prognosis of ccRCC.

A Risk Model Developed based on Homologous Recombination Deficiency Genes for Evaluating the Drug Sensitivity and Prognostic Prediction of Lung Adenocarcinoma.

This study was designed to construct a risk model based on homologous recombination deficiency (HRD) to evaluate the prognosis and drug sensitivity for patients with lung adenocarcinoma (LUAD). LUAD is a subtype of lung cancer with unfavorable overall survival (OS) and prognosis. HRD has been widely studied in various tumors, but its role in LUAD has not been fully understood. We aimed to construct an HRD-related risk model for predicting the prognosis and drug sensitivity of patients with LUAD. Gene expression data of the LUAD samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We extracted HRD genes from previous literature and performed univariate COX analysis to select those closely associated with LUAD prognosis. ConsensusClusterPlus was employed to stratify the samples in the TCGA-LUAD cohort into different subtypes. A RiskScore model was established applying random forest method. Furthermore, immunotherapy response and drug sensitivity were predicted using Tumor Immune Dysfunction and Exclusion (TIDE) software and pRRophytic R package, respectively. Finally, the clinical features between High- and Low- RiskScore groups were compared. A total of 16 HRD genes relevant to LUAD prognosis were selected and used to classify 3 LUAD clusters (C1, C2, and C3). Specifically, C1, with a lower TIDE score displayed higher immune infiltration and immunotherapy benefit and the optimal OS, while C2 was closely correlated with tumor-relevant pathways and had the worst OS. Finally, 4 HRD genes (RAD51AP1, BRCA1, H2AFX, and FANCL) were determined to develop a RiskScore signature. It was found that a higher RiskScore was related to more advanced stages, worse OS, and tumor development pathways. Additionally, the High-RiskScore group with a higher TIDE score was sensitive to 44 traditional chemotherapy drugs. A nomogram combined with RiskScore exhibited an accurate survival prediction ability. The HRD-based RiskScore played a crucial role in LUAD development, showing a strong potential to serve as a prognostic indicator for LUAD. Our findings contributed to the diagnosis of LUAD and its treatment.

The role of SEC14L4 in esophageal squamous cell cancer: insights into clinical relevance and molecular pathways.

Esophageal squamous cell cancer (ESCC) is the most common type of esophageal cancer. This study aimed to elucidate the role of Saccharomyces cerevisiae-like 4 (SEC14L4) in ESCC. To elucidate the role of SEC14L4 in ESCC, this study analyzed the clinical data, gene sequencing data, and other relevant data retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) of the National Center for Biotechnology Information. The methodology involved several analytical approaches, including nomogram model analysis, co-expression analysis, gene set enrichment and variation analysis, weighted correlation network analysis, drug susceptibility analysis, and single-cell analysis. These methods were employed to evaluate the significance of SEC14L4 in ESCC. The expression of SEC14L4 was evaluated via quantitative real-time polymerase chain reaction (qRT-PCR). SEC14L4 expression (P<0.001) was significantly elevated in those with ESCC, especially in patients with locally advanced disease (P=0.005), and indicated a poor prognosis (P=0.045). Findings from the nomogram model analysis identified the contribution of clinical indicators to survival prediction with good efficacy. Subsequently, the single-nucleotide polymorphisms and co-expressed genes of SEC14L4 were identified. Furthermore, pathways associated with SEC14L4, including DNA metabolic process, transcription factor binding, apoptosis, and others, were examined. Notably, SEC14L4 expression was predominantly observed in monocytes. Drug sensitivity analysis indicated the association of SEC14L4 expression with sensitivity of ESCC to the common chemotherapy drugs AICAR, BMS.708163, GNF.2, Nutlin.3a, PD.0325901, and RDEA119. Verification of the high expression of SEC14L4 in KYSE520 and KYSE150 was conducted, thereby confirming the study's findings. High expression of SEC14L4 is associated with poorer clinical outcomes, highlighting its potential as a therapeutic target and suggesting its involvement in the molecular mechanisms underlying ESCC.

HDAC1: a promising target for cancer treatment: insights from a thorough analysis of tumor functions.

Many significant findings from recent studies have revealed the significance of histone deacetylase 1 (HDAC1) in the development of tumors and its strong association with tumor prognosis; these studies have mainly focused on one single cancer such as in lung cancer, breast cancer, and hepatocellular carcinoma (HCC). To date, there has been no comprehensive analysis and pan-analysis conducted from the overall perspective of cancer across all types. Hence, we analyzed public databases, conducted tube formation assay, and immunohistochemistry (IHC) staining of HDAC1 on six kinds of clinical samples to explore the prognostic and oncogenic effects of HDAC1 on 33 tumors for the first time. There currently remains a lack of efficient testing methods, therapies, and diagnostic and prognostic markers of tumor formation and development in different tumors. Our initial objective was to investigate the possible cancer-causing functions of HDAC1 in 33 different types of tumors by utilizing The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and many different online websites, such as Tumor IMmune Estimation Resource 2 (TIMER2), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Genotype Tissue Expression (GTEx) database, Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset, and University of ALabama at Brimingham CANcer data analysis portal (UALCAN) tool, and so on. We even used small interfering RNA (siRNA) to knock down HDAC2 in HCC cell lines. IHC of HDAC1 was performed. HDAC1 exhibited high expression in numerous tumors, and strong correlations were observed between the messenger RNA (mRNA) levels of HDAC1 and the prognosis of individuals diagnosed with tumors. Human umbilical vein endothelial cells (HUVECs) tube formation and migration were significantly inhibited by conditioned media from HCC cells treated with siRNA of HDAC1. Several types of cancer have been found to exhibit elevated levels of phosphorylation at S421. Furthermore, as in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), and kidney renal papillary cell carcinoma (KIRP), HDAC1 expression was found to be correlated with inflammatory cell infiltration. The levels of HDAC1 are expected to adapt to clinical adjuvant targeted therapy in most types of solid cancer.

Two-step consensus clustering approach to immune cell infiltration: An integrated exploration and validation of prognostic and immune implications in sarcomas

To conduct a comprehensive investigation of the sarcoma immune cell infiltration (ImmCI) patterns and tumoral microenvironment (TME). We utilized transcriptomic, clinical, and mutation data of sarcoma patients (training cohort) obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) server. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithms were applied to decipher the immune cell infiltration landscape and TME profiles of sarcomas. An unsupervised clustering method was utilized for classifying ImmCI clusters (initial clustering) and ImmCI-based differentially expressed gene-driven clusters (secondary clustering). Mortality rates and immune checkpoint gene levels was analyzed among the identified clusters. We calculated the ImmCI score through principal component analysis. The tumor immune dysfunction evaluation (TIDE) score was also employed to quantify immunotherapy efficacy between two ImmCI score groups. We further validated the biomarkers for ImmCI and gene-driven clusters via experimental verification and the accuracy of the ImmCI score in predicting survival outcomes and immunotherapy efficacy by external validation cohorts (testing cohort). We demonstrated that ImmCI cluster A and gene-driven cluster A, were beneficial prognostic biomarkers and indicators of immune checkpoint blockade response in sarcomas via in-silico and laboratory experiments. Additionally, the ImmCI score exhibited independent prognostic significance and was predictive of immunotherapy response. Our research underscores the clinical significance of ImmCI scores in identifying sarcoma patients likely to respond to immunotherapy.

Compiling molecular evidence from a tetraploid rose genome into a near-saturated map for the identification of pigment-related genes

With their high economic value and cultural significance, modern roses are one of the most important ornamental plants. Because of their complicated genetic background and tetraploid nature, the creation of high-density genetic maps of roses has been a challenge that has slowed the pace of molecular breeding for modern roses. The current construction of tetraploid genetic maps based on existing diploid rose genomes could lead to inaccurate marker information and genotyping results. Therefore, we generated the first high-quality tetraploid genome of Rosa chinensis ‘Yunzheng Xiawei.’ Utilizing Illumina, PacBio, and Hi-C sequencing technologies, we assembled a genome of 858.59 Mb with 14 pseudo-chromosomes. Mode of inheritance analysis using PolyOrigin indicated that modern roses show both quadrivalent and bivalent pairing. Based on this reference genome, high-density genetic maps were constructed using MSTmap with nearly saturated markers. Quantitative trait locus (QTL) analysis was conducted using WinQTLCart and R/qtl for flavonoids and carotenoids, and 11 QTL clusters were identified. By combining the genome annotation, phylogenetic analyses, and gene expression analyses, we were able to identify several key genes related to flavonoid and carotenoid biosynthesis. This study provides the basis for further genetic analyses of highly heterozygous tetraploid roses and could facilitate the progress of marker-assisted selection in modern roses.

A consequential one-night stand: Episodic historical hybridization leads to mitochondrial takeover in sympatric desert ant-eating spiders

Disentangling the genomic intricacies underlying speciation and the causes of discordance between sources of evidence can offer remarkable insights into evolutionary dynamics. The ant-eating spider Zodarion nitidum, found across the Middle East and Egypt, displays yellowish and blackish morphs that co-occur sympatrically. These morphs additionally differ in behavioral and physiological features and show complete pre-mating reproductive isolation. In contrast, they possess similar sexual features and lack distinct differences in their mitochondrial DNA. We analyzed both Z. nitidum morphs and outgroups using genome-wide and additional mitochondrial DNA data. The genomic evidence indicated that Yellow and Black are reciprocally independent lineages without signs of recent admixture. Interestingly, the sister group of Yellow is not Black but Z. luctuosum, a morphologically distinct species. Genomic gene flow analyses pinpointed an asymmetric nuclear introgression event, with Yellow contributing nearly 5 % of its genome to Black roughly 320,000 years ago, intriguingly aligning with the independently estimated origin of the mitochondrial DNA of Black. We conclude that the blackish and yellowish morphs of Z. nitidum are long-diverged distinct species, and that the ancient and modest genomic introgression event registered resulted in a complete mitochondrial takeover of Black by Yellow. This investigation underscores the profound long-term effects that even modest hybridization events can have on the genome of organisms. It also exemplifies the utility of phylogenetic networks for estimating historical events and how integrating independent lines of evidence can increase the reliability of such estimations.

Pangenomes of human gut microbiota uncover links between genetic diversity and stress response

The genetic diversity of the gut microbiota has a central role in host health. Here, we created pangenomes for 728 human gut prokaryotic species, quadrupling the genes of strain-specific genomes. Each of these species has a core set of a thousand genes, differing even between closely related species, and an accessory set of genes unique to the different strains. Functional analysis shows high strain variability associates with sporulation, whereas low variability is linked with antibiotic resistance. We further map the antibiotic resistome across the human gut population and find 237 cases of extreme resistance even to last-resort antibiotics, with a predominance among Enterobacteriaceae. Lastly, the presence of specific genes in the microbiota relates to host age and sex. Our study underscores the genetic complexity of the human gut microbiota, emphasizing its significant implications for host health. The pangenomes and antibiotic resistance map constitute a valuable resource for further research.

Transcription factor condensates, 3D clustering, and gene expression enhancement of the MET regulon.

Some transcription factors (TFs) can form liquid-liquid phase separated (LLPS) condensates. However, the functions of these TF condensates in 3-Dimentional (3D) genome organization and gene regulation remain elusive. In response to methionine (met) starvation, budding yeast TF Met4 and a few co-activators, including Met32, induce a set of genes involved in met biosynthesis. Here, we show that the endogenous Met4 and Met32 form co-localized puncta-like structures in yeast nuclei upon met depletion. Recombinant Met4 and Met32 form mixed droplets with LLPS properties in vitro. In relation to chromatin, Met4 puncta co-localize with target genes, and at least a subset of these target genes is clustered in 3D in a Met4-dependent manner. A MET3pr-GFP reporter inserted near several native Met4-binding sites becomes co-localized with Met4 puncta and displays enhanced transcriptional activity. A Met4 variant with a partial truncation of an intrinsically disordered region (IDR) shows less puncta formation, and this mutant selectively reduces the reporter activity near Met4-binding sites to the basal level. Overall, these results support a model where Met4 and co-activators form condensates to bring multiple target genes into a vicinity with higher local TF concentrations, which facilitates a strong response to methionine depletion.

Transcription factor condensates, 3D clustering, and gene expression enhancement of the MET regulon

Some transcription factors (TFs) can form liquid–liquid phase separated (LLPS) condensates. However, the functions of these TF condensates in 3-Dimentional (3D) genome organization and gene regulation remain elusive. In response to methionine (met) starvation, budding yeast TF Met4 and a few co-activators, including Met32, induce a set of genes involved in met biosynthesis. Here, we show that the endogenous Met4 and Met32 form co-localized puncta-like structures in yeast nuclei upon met depletion. Recombinant Met4 and Met32 form mixed droplets with LLPS properties in vitro. In relation to chromatin, Met4 puncta co-localize with target genes, and at least a subset of these target genes is clustered in 3D in a Met4-dependent manner. A MET3pr-GFP reporter inserted near several native Met4-binding sites becomes co-localized with Met4 puncta and displays enhanced transcriptional activity. A Met4 variant with a partial truncation of an intrinsically disordered region (IDR) shows less puncta formation, and this mutant selectively reduces the reporter activity near Met4-binding sites to the basal level. Overall, these results support a model where Met4 and co-activators form condensates to bring multiple target genes into a vicinity with higher local TF concentrations, which facilitates a strong response to methionine depletion.

Investigating the shared genetic links between hypothyroidism and psychiatric disorders: a large-scale genomewide cross-trait analysis

BackgroundAssociations between thyroid diseases and psychiatric disorders have been mainly described before. However, the genetic mechanism behind hypothyroidism and psychiatric disorders remains unexplained. MethodsWe examined the genetic architecture of hypothyroidism and 8 psychiatric disorders. Firstly, the global and local genetic relationship between the paired traits was explored. Secondly, cross-trait analysis was performed to investigate the genomic loci and genes between psychiatric disorders and hypothyroidism. Thirdly, the significant expression of these genes and the causal relationships were investigated. Lastly, enrichment analysis was conducted on these genes to explore their biological mechanisms. ResultsWe observed significant positive genetic correlations between psychiatric disorders and hypothyroidism. The cross-trait meta-analysis identified 62 shared genetic loci between hypothyroidism and psychiatric disorders. The colocalization analysis additionally revealed 15 potential pleiotropic loci with a posterior probabilities.H4 (PP·H4) value >0.7. We also found 2308 genes shared between both traits, which were highly enriched in biological pathways such as immune cell differentiation and autoimmune diseases, as well as in tissue structures like the frontal cortex and cerebral cortex. Especially, many pleiotropic genes were significantly expressed for multiple pairwise traits, such as BCL11B, RERE, and SUOX. Lastly, the Latent causal variable model (LCV) analysis did not find any causal components in the genetic structure between them. LimitationsThe limitations of this study include that the conclusions were drawn from a European population. ConclusionsThese findings not only deepens our understanding of their biological mechanisms but also has significant implications for the intervention and treatment of these diseases.

Loss-of-function of RNA-binding protein PRRC2B causes translational defects and congenital cardiovascular malformation.

Alternative splicing generates variant forms of proteins for a given gene and accounts for functional redundancy or diversification. A novel RNA-binding protein, Pro-rich Coiled-coil Containing Protein 2B (PRRC2B), has been reported by multiple laboratories to mediate uORF-dependent and independent regulation of translation initiation required for cell cycle progression and proliferation. We identified two alternative spliced isoforms in human and mouse hearts and HEK293T cells, full-length (FL) and exon 16-excluded isoform ΔE16. A congenital heart disease-associated human mutation-mimicry knock-in of the equivalent variant in the mouse genome leads to the depletion of the full-length Prrc2b mRNA but not the alternative spliced truncated form ΔE16, does not cause any apparent structural or functional disorders. In contrast, global genetic inactivation of the PRRC2B gene in the mouse genome, nullifying both mRNA isoforms, caused patent ductus arteriosus (PDA) and neonatal lethality in mice. Bulk and single nucleus transcriptome profiling analyses of embryonic mouse hearts demonstrated a significant overall downregulation of multiple smooth muscle-specific genes in Prrc2b mutant mice resulting from reduced smooth muscle cell number. Integrated analysis of proteomic changes in Prrc2b null mouse embryonic hearts and polysome-seq and RNA-seq multi-omics analysis in human HEK293T cells uncover conserved PRRC2B-regulated target mRNAs that encode essential factors required for cardiac and vascular development. Our findings reveal the connection between alternative splicing regulation of PRRC2B, PRRC2B-mediated translational control, and congenital cardiovascular development and disorder. This study may shed light on the significance of PRRC2B in human cardiovascular disease diagnosis and treatment.

Examining the influence of tumor-infiltrating macrophages on breast cancer outcomes and identifying relevant genes for diagnostic purposes

ObjectiveThe purpose of this research was to investigate how different types of immune cells impact the outlook of individuals with breast cancer, as well as identify the essential genes associated with immune cell subtype enrichment.MethodsThe Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database were used to obtain global transcriptome sequencing data sets of breast tissue. The study utilized the CIBERSORT algorithm to determine the presence of 22 different types of immune cells in both breast cancer tissue and normal breast tissue.Immune cell infiltration content was utilized to conduct univariate COX analysis in order to identify risk factors linked to breast cancer prognosis.ResultsUnivariate COX analysis indicates that Macrophages M1 and B cells naive are beneficial factors for the outlook of individuals with breast cancer (P < 0.05), while Macrophages M2 and Monocytes are detrimental factors for the prognosis of breast cancer patients (P < 0.05). The high infiltration group of macrophage M2 had a poorer prognosis compared to the low infiltration group (P < 0.001); Conversely, the high infiltration group of macrophage M1 had a better prognosis than the low infiltration group (P = 0.002).ConclusionThe study provided an overview of immune cell infiltration in breast cancer tissues, identifying macrophage M1 and macrophage M2 as potential factors in breast cancer development and progression. Additionally, genes associated with macrophage phenotype were analyzed, offering insights into macrophage polarization mechanisms.

Identification of key ferroptosis genes and subtypes in kidney renal clear cell carcinoma

Tumour immunity is highly important for the occurrence and development of tumours, and many cancers are resistant to ferroptosis. This study aims to explore the relationship between ferroptosis-related genes (FRGs) and the immunological characteristics of kidney renal clear cell carcinoma (KIRC). We obtained RNA-seq profiles and clinical data of KIRC patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and identified CD44 and GLRX5 as the key FRGs involved in KIRC immune infiltration through Spearman’s correlation analysis. Based on the expression of CD44 and GLRX5, the consensus clustering algorithm was used to classify the TCGA-KIRC samples into two clusters. A nomogram was constructed to evaluate the prognosis of KIRC patients. ESTIMATE, CIBERSORT, and single-sample gene set enrichment analysis (ssGSEA) were performed to evaluate immune infiltration between the two clusters. A weighted gene co-expression network analysis (WGCNA) was used to identify the most relevant genes to the clusters and immunity. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The external dataset GSE53757 was used to validate the immunological features between the two clusters. Cluster 2 patients had more active immune infiltration and might be more sensitive to immunotherapy; Cluster 2 patients also had a worse prognosis and might be at a more advanced stage of KIRC. We identified key ferroptosis-related genes and subgroups involved in the immune infiltration of KIRC, which is highly important for exploring the molecular mechanisms and treatments of KIRC.

Delineation of global, absolutely essential and conditionally essential pangenomes of Porphyromonas gingivalis

Porphyromonas gingivalis is a Gram-negative, anaerobic oral pathobiont, an etiological agent of periodontitis and the most commonly studied periodontal bacterium. Multiple low passage clinical isolates were sequenced, and their genomes compared to several laboratory strains. Phylogenetic distances were mapped, a gene absence-presence matrix generated, and core (present in all genomes) and accessory (absent in one or more genomes) genes delineated. Subsequently, a second pangenome delineating the prevalence of inherently essential genes was generated. The prevalence of genes conditionally essential for surviving tobacco exposure, abscess formation and epithelial invasion was also determined, in addition to genes encoding key proteolytic enzymes containing putative signal peptides. While the absolutely essential pangenome was highly conserved, significant differences in the complete and conditionally essential pangenomes were apparent. Thus, genetic plasticity appears to lie primarily in gene sets facilitating adaptation to variant disease-related environments. Those genes that are highly pervasive in the P. gingivalis absolutely essential pangenome or are highly prevalent and essential for fitness in disease-relevant models, may represent particularly attractive therapeutic targets worthy of further investigation. As mutations in absolutely essential genes are expected to be lethal, the data provided herein should also facilitate improved planning for P. gingivalis gene mutation strategies.

Assessing Prospective Molecular Biomarkers and Functional Pathways in Severe Asthma based on a Machine Learning method and Bioinformatics Analyses

Background Severe asthma, which differs significantly from typical asthma, involves specific molecular biomarkers that enhance our understanding and diagnostic capabilities. The objective of this study is to assess the biological processes underlying severe asthma and to detect key molecular biomarkers. Methods We used Weighted Gene Co-Expression Network Analysis (WGCNA) to detect hub genes in the GSE143303 dataset and indicated their functions and regulatory mechanisms using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) annotations. In the GSE147878 dataset, we used Gene Set Enrichment Analysis (GSEA) to determine the regulatory directions of gene sets. We detected differentially expressed genes in the GSE143303 and GSE64913 datasets, constructed a Least Absolute Shrinkage and Selection Operator (LASSO) regression model, and validated the model using the GSE147878 dataset and real-time quantitative PCR (RT-qPCR) to confirm the molecular biomarkers. Results Using WGCNA, we discovered modules that were strongly correlated with clinical features, specifically the purple module (r = 0.53) and the midnight blue module (r = -0.65). The hub genes within these modules were enriched in pathways related to mitochondrial function and oxidative phosphorylation. GSEA in the GSE147878 dataset revealed significant enrichment of upregulated gene sets associated with oxidative phosphorylation and downregulated gene sets related to asthma. We discovered 12 commonly regulated genes in the GSE143303 and GSE64913 datasets and developed a LASSO regression model. The model corresponding to lambda.min selected nine genes, including TFCP2L1, KRT6A, FCER1A, and CCL5, which demonstrated predictive value. These genes were significantly upregulated or under expressed in severe asthma, as validated by RT-qPCR. Conclusion Mitochondrial abnormalities affecting oxidative phosphorylation play a critical role in severe asthma. Key molecular biomarkers like TFCP2L1, KRT6A, FCER1A, and CCL5, are essential for detecting severe asthma. This research significantly enhances the understanding and diagnosis of severe asthma.

Recurrent CLTC::SYK fusions and CSF1R mutations in juvenile xanthogranuloma of soft tissue

AbstractJuvenile xanthogranuloma (JXG) is a histiocytic neoplasm that usually presents in the skin. Rarely, extracutaneous localizations occur; the genetic drivers of this clinical variant of JXG remain incompletely characterized. We present detailed clinicopathologic and molecular data of 16 children with extracutaneous JXG and 5 adults with xanthogranulomas confined to the central nervous system (CNS) or soft tissue. Tissue samples were obtained through the Dutch Nationwide Pathology Databank and analyzed with an innovative sequencing technique capable of detecting both small genomic variants and gene rearrangements. Targetable kinase alterations were detected in 16 of 16 children and 1 of 5 adults. Alterations included CLTC::SYK fusions in 6 children and CSF1R mutations in 7 others; all aged <2 years with soft tissue tumors. One child had a CSF1R mutation and MRC1::PDGFRB fusion. Most were treated surgically, although spontaneous regression occurred in 1 of 6 with CLTC::SYK and 2 of 7 with CSF1R mutations, underscoring that treatment is not always necessary. Tumors with CLTC::SYK fusions generally lacked Touton giant cells but exhibited many other histologic features of JXG and concordant methylation profiles. Using multispectral immunofluorescence, phosphorylated–spleen tyrosine kinase expression was localized to CD163+ histiocytes; tumors with CLTC::SYK fusions also demonstrated mTOR activation, cyclin D1 expression, and variable phosphorylated–extracellular signal-regulated kinase expression. BRAFV600E was detected in 1 child and 1 adult with CNS xanthogranulomas; both responded to BRAF inhibition. Finally, a TPM3::NTRK1 fusion or MAP2K1 deletion was detected in 2 children with systemic JXG who experienced spontaneous disease regression. This study advances the molecular understanding of histiocytic neoplasms and may guide diagnostics and clinical management.