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Neofusicoccum laricinum is the causal agent of larch shoot blight, a fungal disease affecting several species of larch. It causes severe damage, including stunting and mortality. This study aims to address the severe impact of larch shoot blight by evaluating the effect of farrerol on the inhibition of Neofusicoccum laricinum in Larix olgensis. We used LC-MS/MS and weighted gene co-expression network analysis to investigate farrerol's effects on Neofusicoccum laricinum and identify associated genes in resistant and susceptible larch. Our study identified significant differences in metabolite profiles between resistant and susceptible cultivars, with higher concentrations of farrerol showing complete inhibition of N. laricinum. Additionally, specific genes associated with farrerol content were up-regulated in resistant larch. Farrerol at higher concentrations completely inhibited N. laricinum, showing a strong correlation with increased disease resistance. This research suggests that farrerol enhances disease resistance in larch and provides a foundation for developing disease-resistant larch varieties based on antifungal metabolite traits. [ABSTRACT FROM AUTHOR]

Mechanisms regulating the gene expression program at different hypoxia severity levels in patient tumors are not understood. We aimed to determine microRNA (miRNA) regulation of this program at defined hypoxia levels from moderate to severe in prostate cancer. Biopsies from 95 patients were used, where 83 patients received the hypoxia marker pimonidazole before prostatectomy. Forty hypoxia levels were extracted from pimonidazole‐stained histological sections and correlated with miRNA and gene expression profiles determined by RNA sequencing and Illumina bead arrays. This identified miRNAs associated with moderate (n = 7) and severe (n = 28) hypoxia and predicted their target genes. The scores of miRNAs or target genes showed prognostic significance, as validated in an external cohort of 417 patients. The target genes showed enrichment of gene sets for cell proliferation and MYC activation at all hypoxia levels and PTEN inactivation at severe hypoxia. This was confirmed by RT‐qPCR for MYC and PTEN, by Ki67 immunohistochemistry, and by gene set analysis in an external cohort. To assess whether miRNA regulation occurred within the predicted hypoxic regions, a method to quantify co‐localization of multiple histopathology parameters at defined hypoxia levels was applied. A high Ki67 proliferation index co‐localized significantly with hypoxia at all levels. The co‐localization index was strongly associated with poor prognosis. Absence of PTEN staining co‐localized significantly with severe hypoxia. The scores for miRNAs correlated with the co‐localization index for Ki67 staining and hypoxia, consistent with miRNA regulation within the overlapping regions. This was confirmed by showing miR‐210‐3p expression within severe hypoxia by in situ hybridization. Cell line experiments (22Rv1, PC3) were conducted to determine whether miRNAs and target genes were regulated directly by hypoxia. Most of them were hypoxia‐unresponsive, and probably regulated by other mechanisms such as MYC activation. In conclusion, in aggressive, hypoxic prostate tumors, cancer cells exhibit different proliferative gene expression programs that is regulated by miRNAs and depend on whether the cells reside in moderate or severe hypoxic regions. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) are two common and aggressive subtypes of soft tissue sarcoma. The aim of this study was to assess potential transcriptomic differences between MFS and UPS tumours and to evaluate the extent to which differences in gene expression profiles were associated with genomic and clinical features. The study included 162 patients with tumours diagnosed as MFS (N = 62) or UPS (N = 100). The patients had been diagnosed and treated at two Swedish sarcoma centres during a 30‐year period. For gene expression profiling and gene fusion detection all tumours were analysed using RNA‐sequencing and could be compared with data on clinical outcome (N = 155), global copy number profiles (N = 145), and gene mutations (N = 128). Gene expression profiling revealed three transcriptomic clusters (TCs) without any clear separation of MFS and UPS. One TC was associated with longer metastasis‐free survival. These tumours had lower tumour mutation burden (TMB), were enriched for a copy number signature representative of focal LOH and chromosomal instability on a diploid background, and were relatively immune‐depleted. MFS and UPS showed extensive genomic overlap, with whole genome doubling occurring more frequently among the latter. The results support the idea that MFS and UPS tumours have largely overlapping genomic and transcriptomic features, with UPS tumours showing more aggressive behaviour and more complex genomes. Independently of the tumour type, clinically relevant subgroups were revealed by gene expression analysis, and the finding of multiple genomic subgroups strongly suggest the existence of subgroups of relevance to treatment stratification. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Yttrium (Y), an important rare earth element (REE), is increasingly prevalent in the environment due to industrial activities, raising concerns about its toxicity. Understanding the effects of Y on microorganisms is essential for bioremediation and biorecovery processes. This study investigates how Mesorhizobium qingshengii J19, a strain with notable resistance to Y, manages iron homeostasis as a detoxifying mechanism under Y stress. Using comparative genomic and transcriptomic analyses, we explored the gene expression profile of strain J19 to identify the mechanisms underlying its high Y resistance and effective Y removal from the medium. Genome-wide transcriptional profiling revealed 127 significantly differentially expressed genes out of 6,343 under Y stress, with 36.2 % up-regulated and 63.8 % down-regulated. Notably, Y exposure significantly affects cellular iron homeostasis and activates arsenic detoxifying mechanisms. A key finding was the 7.6-fold up-regulation of a TonB transporter gene, indicating its crucial role in Y detoxification. Real-time PCR (RT-PCR) analysis of the selected gene confirmed the accuracy of RNA sequencing results. Further validation showed that iron supplementation mitigates Y-induced growth inhibition, leading to reduced ROS production in strain J19. This study elucidates the molecular mechanisms by which strain M. qingshengii J19 adapts to Y stress, emphasizing the importance of iron in controlling ROS and protecting against Y toxicity. It also highlights critical pathways and adaptive responses involved in the strain’s resilience to metal stress. [ABSTRACT FROM AUTHOR]

Carboxylesterases (CXE, EC 3.1.1.1), a class of hydrolases with an a/b folding domain, play important roles in plant growth and development and stress response. Here, we identified 32, 63, 41, and 45 CXE genes in Oryza sativa Japonica (Nipponbare), Oryza sativa Indica (93-11), Oryza sativa Indica (Xian-1B1 var.IR64), and Oryza sativa Japonica (Geng-sbtrp var.ChaoMeo), respectively. Then, we analyzed the chromosomal location, physical and chemical properties, subcellular localization, collinearity, and selection pressure of CXE genes in four rice varieties. We also analyzed the functional interaction network, cis-regulatory elements, evolutionary relationship, and protein tertiary structure, and performed gene expression profiling and qPCR verification under abiotic stress, as well as diversity analysis of 3010 gene-CDS-haplotype (gcHap) rice samples, aiming to understand the potential function of the 32 OsCXE genes. Our results indicated that fragment replication is the main reason for amplification of the CXE gene family in rice, and the gene family has undergone strong purification selection. OsCXE3.1, OsCXE3.2, OsCXE3.3, OsCXE5.1, and OsCXE7.3 may be used to improve the tolerance of rice to abiotic stress. OsCXE play important roles in rice population differentiation and improvement, and the major gcHaps at most OsCXE locus are significantly associated with yield traits. Therefore, natural variations of most OsCXE locus have great potential value for improvement of rice productivity. [ABSTRACT FROM AUTHOR]

Background: Hypoxic conditions in glioma are linked to tumor aggressiveness, poor prognosis, and treatment resistance. Long non-coding RNAs (lncRNAs) play key roles in the hypoxic and immune microenvironment of cancers, but their link to hypoxia-induced immunosuppression in high-grade glioma (HGG) is not well-studied. Methods: Gene expression profiles from TCGA and CGGA, along with clinical and genomic data, were analyzed. Bioinformatics methods including Consensus Clustering, Pearson correlation, and Cox regression analyses were used. Cell proliferation was assessed using cell counting kit-8 and colony formation assays. Glioma-macrophage interactions were evaluated using a co-culture model. Results: Hypoxia subtype clustering showed hypoxic stress correlates with worse HGG prognosis. Eight hypoxia-related lncRNAs (AP000695.4, OSMR-AS1, AC078883.3, RP11-545E17.3, LINC01057, LINC01503, TP73-AS1, and LINC00672) with prognostic value were identified, forming a risk signature that separated patients into distinct prognostic groups. Multivariate Cox regression confirmed the signature as an independent prognostic factor. High-risk patients had greater hypoxia, leading to an immunosuppressive environment and immunotherapy resistance via tumor-associated macrophages (TAMs). TP73-AS1 significantly influenced hypoxia-induced TAM infiltration and M2 polarization. Conclusions: We profiled hypoxic stress in HGG and developed an 8-lncRNA hypoxia-related signature predicting patient survival and immunotherapy response, emphasizing its role in hypoxia-induced immunosuppression. [ABSTRACT FROM AUTHOR]

Introduction: This study leverages bioinformatics and medical big data to integrate datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), providing a comprehensive overview of immunogenic cell death (ICD)-related gene expression in colorectal cancer (CRC). The research aims to elucidate the molecular pathways and gene networks associated with ICD in CRC, with a focus on the therapeutic potential of cell death inducers, including ferroptosis agents, and their implications for precision medicine. Methods: We conducted differential expression analysis and utilized advanced bioinformatic techniques to analyze ICD-related gene expression in CRC tissues. Unsupervised consensus clustering was applied to categorize CRC patients into distinct ICD-associated subtypes, followed by an in-depth immune microenvironment analysis and single-cell RNA sequencing to investigate immune responses and cell infiltration patterns. Experimental validation was performed to assess the impact of cell death inducers on ICD gene expression and their interaction with ferroptosis inducers in combination with other clinical drugs. Results: Distinct ICD gene expression profiles were identified in CRC tissues, revealing molecular pathways and intricate gene networks. Unsupervised consensus clustering refined the CRC cohort into unique ICD-associated subtypes, each characterized by distinct clinical and immunological features. Immune microenvironment analysis and single-cell RNA sequencing revealed significant variations in immune responses and cell infiltration patterns across these subtypes. Experimental validation confirmed that cell death inducers directly affect ICD gene expression, highlighting their therapeutic potential. Additionally, combinatorial therapies with ferroptosis inducers and clinical drugs were shown to influence drug sensitivity and resistance in CRC. Discussion: Our findings underscore the importance of ICD-related genes in CRC prognosis and therapeutic targeting. The study provides actionable insights into the efficacy of cell death-inducing therapies, particularly ferroptosis inducers, and their regulatory mechanisms in CRC. These discoveries support the development of precision medicine strategies targeting ICD genes and offer valuable guidance for translating these therapies into clinical practice, with the potential to enhance CRC treatment outcomes and patient survival. [ABSTRACT FROM AUTHOR]

Background: Cancer cells evolve under unique functional adaptations that unlock transcriptional programs embedded in adult stem and progenitor-like cells for progression, metastasis, and therapeutic resistance. However, it remains challenging to quantify the stemness-aware cell state of a tumor based on its gene expression profile. Methods: We develop a developmental-status-aware transcriptional decomposition strategy using single-cell RNA-sequencing-derived tissue-specific fetal and adult cell signatures as anchors. We apply our method to various biological contexts, including developing human organs, adult human tissues, experimentally induced differentiation cultures, and bulk human tumors, to benchmark its performance and to reveal novel biology of entangled developmental signaling in oncogenic processes. Results: Our strategy successfully captures complex dynamics in developmental tissue bulks, reveals remarkable cellular heterogeneity in adult tissues, and resolves the ambiguity of cell identities in in vitro transformations. Applying it to large patient cohorts of bulk RNA-seq, we identify clinically relevant cell-of-origin patterns and observe that decomposed fetal cell signals significantly increase in tumors versus normal tissues and metastases versus primary tumors. Across cancer types, the inferred fetal-state strength outperforms published stemness indices in predicting patient survival and confers substantially improved predictive power for therapeutic responses. Conclusions: Our study not only provides a general approach to quantifying developmental-status-aware cell states of bulk samples but also constructs an information-rich, biologically interpretable, cell-state panorama of human cancers, enabling diverse translational applications. [ABSTRACT FROM AUTHOR]

The two-component system (TCS) consists of histidine kinase (HK), histidine phosphate transfer protein (HP), and response regulatory factor (RR). It is one of the most crucial components of signal transduction in plants, playing a significant role in regulating plant growth, development, and responses to various abiotic stresses. Although TCS genes have been extensively identified in a variety of plants, the genome-wide recognition and examination of TCS in switchgrass remain unreported. Accordingly, this study identified a total of 87 TCS members in the genome of switchgrass, comprising 20 HK(L)s, 10 HPs, and 57 RRs. Detailed analyses were also conducted on their gene structures, conserved domains, and phylogenetic relationships. Moreover, this study analysed the gene expression profiles across diverse organs and investigated their response patterns to adverse environmental stresses. Results revealed that 87 TCS genes were distributed across 18 chromosomes, with uneven distribution. Expansion of these genes in switchgrass was achieved through both fragment and tandem duplication. PvTCS members are relatively conservative in the evolutionary process, but the gene structure varies significantly. Various cis-acting elements, varying in types and amounts, are present in the promoter region of PvTCSs, all related to plant growth, development, and abiotic stress, due to the TCS gene structure. Protein-protein interaction and microRNA prediction suggest complex interactions and transcriptional regulation among TCS members. Additionally, most TCS members are expressed in roots and stems, with some genes showing organ-specific expression at different stages of leaf and inflorescence development. Under conditions of abiotic stress such as drought, low temperature, high temperature, and salt stress, as well as exogenous abscisic acid (ABA), the expression of most TCS genes is either stimulated or inhibited. Our systematic analysis could offer insight into the characterization of the TCS genes, and further the growth of functional studies in switchgrass. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. This study was aimed to identify a lipid metabolism-related signature associated with the HCC microenvironment to improve the prognostic prediction of HCC patients. Clinical information and expression profile data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, including the GEO dataset GSE76427. The gene expression profile of lipid metabolism was downloaded from Molecular Signatures Database (MSigDB) database. The infiltrating immune cells were estimated by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE), MCP-counter, and TIMER algorithms. Functional analysis, including Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) were performed to elucidate the underlying mechanisms. The prognostic risk model was performed by Least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analysis. Two distinct subgroups of survival were identified. Better prognosis was associated with high immune score, high abundance of immune infiltrating cells, and high immune status. GO and KEGG analysis showed that differentially expressed genes (DEGs) between the two subgroups were mainly enriched in immune related pathways. GSEA analysis suggested that the expression of lipid metabolism related genes (LMRGs) was related to dysregulation of immune in the high-risk group. Risk models and clinical features based on LMRGs predicted HCC prognosis. This study indicated that the lipid metabolism-related signature was important for the prognosis of HCC. The expression of LMRGs was related to the immune microenvironment of HCC patients and could be used to predict the prognosis of HCC. [ABSTRACT FROM AUTHOR]

Pulmonary arterial hypertension (PAH) is a progressive and rapidly fatal disease with an intricate etiology. Identifying biomarkers for early PAH lesions based on the exploration of subtle biological processes is significant for timely diagnosis and treatment. In the present study, nine distinct cell populations identified based on gene expression profiles revealed high heterogeneity in cell composition ratio, biological function, distribution preference, and communication patterns in PAH. Notably, compared to other cells, endothelial cells (ECs) showed prominent variation in multiple perspectives. Further analysis demonstrated the endothelial-to-mesenchymal transition (EndMT) in ECs and identified a subgroup exhibiting a contrasting phenotype. Based on these findings, a machine-learning integrated program consisting of nine learners was developed to create a PAH Endothelial-to-mesenchymal transition Signature (PETS). This study identified cell populations underlying EndMT and furnished a potential tool that might be valuable for PAH diagnosis and new precise therapies. [ABSTRACT FROM AUTHOR]

In nature, germination of orchid seeds and early plant development rely on a symbiotic association with orchid mycorrhizal (ORM) fungi. These fungi provide the host with the necessary nutrients and facilitate the transition from embryos to protocorms. Despite recent advances in omics technologies, our understanding of this symbiosis remains limited, particularly during the initial stages of the interaction. To address this gap, we employed transcriptomics and metabolomics to investigate the early responses occurring in the mycorrhizal fungus Tulasnella sp. isolate SV6 when co-cultivated with orchid seeds of Serapias vomeracea. The integration of data from gene expression and metabolite profiling revealed the activation of some fungal signalling pathways before the establishment of the symbiosis. Prior to seed contact, an indole-related metabolite was produced by the fungus, and significant changes in the fungal lipid profile occurred throughout the symbiotic process. Additionally, the expression of plant cell wall-degrading enzymes (PCWDEs) was observed during the pre-symbiotic stage, as the fungus approached the seeds, along with changes in amino acid metabolism. Thus, the dual-omics approach employed in this study yielded novel insights into the symbiotic relationship between orchids and ORM fungi and suggest that the ORM fungus responds to the presence of the orchid seeds prior to contact. [ABSTRACT FROM AUTHOR]

SUMMARY Somatic embryogenesis (SE) is a powerful model system for studying embryo development and an important method for scaling up availability of elite and climate‐adapted genetic material of Norway spruce (Picea abies L. Karst). However, there are several steps during the development of the somatic embryo (Sem) that are suboptimal compared to zygotic embryo (Zem) development. These differences are poorly understood and result in substantial yield losses during plant production, which limits cost‐effective large‐scale production of SE plants. This study presents a comprehensive data resource profiling gene expression during zygotic and somatic embryo development to support studies aiming to advance understanding of gene regulatory programmes controlling embryo development. Transcriptome expression patterns were analysed during zygotic embryogenesis (ZE) in Norway spruce, including separated samples of the female gametophytes and Zem, and at multiple stages during SE. Expression data from eight developmental stages of SE, starting with pro‐embryogenic masses (PEMs) up until germination, revealed extensive modulation of the transcriptome between the early and mid‐stage maturing embryos and at the transition of desiccated embryos to germination. Comparative analysis of gene expression changes during ZE and SE identified differences in the pattern of gene expression changes and functional enrichment of these provided insight into the associated biological processes. Orthologs of transcription factors known to regulate embryo development in angiosperms were differentially regulated during Zem and Sem development and in the different zygotic embryo tissues, providing clues to the differences in development observed between Zem and Sem. This resource represents the most comprehensive dataset available for exploring embryo development in conifers. [ABSTRACT FROM AUTHOR]

Myelodysplastic syndromes/neoplasms (MDS) and acute myeloid leukaemia (AML) are neoplastic haematopoietic cell proliferations that are diagnosed and classified based on a combination of morphological, clinical and genetic features. Specifically, the percentage of myeloblasts in the blood and bone marrow is a key feature that has historically separated MDS from AML and, together with several other morphological parameters, defines distinct disease entities within MDS. Both MDS and AML have recurrent genetic abnormalities that are increasingly influencing their definitions and subclassification. For example, in 2022, two new MDS entities were recognised based on the presence of SF3B1 mutation or bi‐allelic TP53 abnormalities. Genomic information is more objective and reproducible than morphological analyses, which are subject to interobserver variability and arbitrary numeric cut‐offs. Nevertheless, the integration of genomic data with traditional morphological features in myeloid neoplasm classification has proved challenging by virtue of its sheer complexity; gene expression and methylation profiling also can provide information regarding disease pathogenesis, adding to the complexity. New machine‐learning technologies have the potential to effectively integrate multiple diagnostic modalities and improve on historical classification systems. Going forward, the application of machine learning and advanced statistical methods to large patient cohorts can refine future classifications by advancing unbiased and robust previously unrecognised disease subgroups. Future classifications will probably incorporate these newer technologies and higher‐level analyses that emphasise genomic disease entities over traditional morphologically defined entities, thus promoting more accurate diagnosis and patient risk stratification. [ABSTRACT FROM AUTHOR]

Autoimmune diseases result from autoantigen-mediated activation of adaptive immunity; intriguingly, autoantigen-specific T cells are also present in healthy donors. An assessment of dynamic changes of this autoreactive repertoire in both health and disease is thus warranted. Here we investigate the physiological versus pathogenic autoreactive processes in the context of Type 1 diabetes (T1D) and one of its landmark autoantigens, glutamic acid decarboxylase 65 (GAD65). Using single cell gene expression profiling and tandem T cell receptor (TCR) sequencing, we find that GAD65-specific true naïve cells are present in both health and disease, with GAD65-specific effector and memory responses showing similar ratios in healthy donors and patients. Deeper assessment of phenotype and TCR repertoire uncover differential features in GAD65-specific TCRs, including lower clonal sizes of healthy donor-derived clonotypes in patients. We thus propose a model whereby physiological autoimmunity against GAD65 is needed during early life, and that alterations of these physiological autoimmune processes in predisposed individuals trigger overt Type 1 diabetes. Autoreactive T cells contribute to the onset of autoimmune diseases but are also detectable in healthy individuals. Here, by examining the dynamics of autoreactive T cell responses to a diabetogenic antigen, the authors show that specific phenotype and T cell receptor repertoire changes are associated with health or disease, with additional cues implicated for this transition. [ABSTRACT FROM AUTHOR]

Background: Associated with high-dimensional omics data there are often "meta-features" such as biological pathways and functional annotations, summary statistics from similar studies that can be informative for predicting an outcome of interest. We introduce a regularized hierarchical framework for integrating meta-features, with the goal of improving prediction and feature selection performance with time-to-event outcomes. Methods: A hierarchical framework is deployed to incorporate meta-features. Regularization is applied to the omic features as well as the meta-features so that high-dimensional data can be handled at both levels. The proposed hierarchical Cox model can be efficiently fitted by a combination of iterative reweighted least squares and cyclic coordinate descent. Results: In a simulation study we show that when the external meta-features are informative, the regularized hierarchical model can substantially improve prediction performance over standard regularized Cox regression. We illustrate the proposed model with applications to breast cancer and melanoma survival based on gene expression profiles, which show the improvement in prediction performance by applying meta-features, as well as the discovery of important omic feature sets with sparse regularization at meta-feature level. Conclusions: The proposed hierarchical regularized regression model enables integration of external meta-feature information directly into the modeling process for time-to-event outcomes, improves prediction performance when the external meta-feature data is informative. Importantly, when the external meta-features are uninformative, the prediction performance based on the regularized hierarchical model is on par with standard regularized Cox regression, indicating robustness of the framework. In addition to developing predictive signatures, the model can also be deployed in discovery applications where the main goal is to identify important features associated with the outcome rather than developing a predictive model. [ABSTRACT FROM AUTHOR]

Undifferentiated pleomorphic sarcomas (UPS) represent a prevalent and aggressive subtype of soft tissue sarcomas (STS) in adults. Despite advancements in loco regional treatments, many patients with high grade STS, including UPS, develop metastatic disease. Neoadjuvant chemotherapy is a standard approach to mitigate this risk, but response variability necessitates refined patient selection strategies. This study investigated the correlation between UPS microenvironment and neoadjuvant chemotherapy response in resectable UPS. The NEOSARCOMICS study (NCT02789384) enrolled patients with resectable STS from six sarcoma centers in France. Patients received anthracycline based chemotherapy, followed by surgery. Histological response, gene expression profiling, and multiplex immunohistofluorescence were performed on baseline and post treatment tumor samples. Plasma proteomics was analyzed to identify biomarkers. Good responders to neoadjuvant chemotherapy showed enrichment in genes related to stemness and cell cycle regulation, while poor responders exhibited immune related gene enrichment. Proteomic profiling revealed immune pathway activation and downregulation of cell cycle pathways in non responders. Despite being associated with a good prognosis, high immune infiltration, particularly of CD8 + T cells and CD20 + B cells, predicts a poor response to neoadjuvant chemotherapy in UPS, suggesting the need for alternative therapeutic strategies for patients with inflamed UPS.Ongoing clinical trials are exploring the efficacy of combining chemotherapy with immune checkpoint inhibitors to improve outcomes. [ABSTRACT FROM AUTHOR]

Background: Osteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood. Method: We analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform. Result: After quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified. Conclusion: This research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets. [ABSTRACT FROM AUTHOR]

Sepsis-induced myopathy is one of the serious complications of sepsis, which severely affects the respiratory and peripheral motor systems of patients, reduces their quality of life, and jeopardizes their lives, as evidenced by muscle atrophy, loss of strength, and impaired regeneration after injury. The pathogenesis of sepsis-induced myopathy is complex, mainly including cytokine action, enhances free radical production in muscle, increases muscle protein hydrolysis, and decreases skeletal muscle protein synthesis, etc. The above mechanisms have been demonstrated in existing studies. However, it is still unclear how the overall pattern of gene co-expression affects the pathological process of sepsis-induced myopathy. Therefore, we intend to identify hub genes and signaling pathways. Weighted gene co-expression network analysis was our main approach to study gene expression profiles: skeletal muscle transcriptome in ICU patients with sepsis-induced multi-organ failure (GSE13205). After data pre-processing, about 15,181 genes were used to identify 13 co-expression modules. Then, 16 genes (FEM1B, KLHDC3, GPX3, NIFK, GNL2, EBNA1BP2, PES1, FBP2, PFKP, BYSL, HEATR1, WDR75, TBL3, and WDR43) were selected as the hub genes including 3 up-regulated genes and 13 down-regulated genes. Then, Gene Set Enrichment Analysis was performed to show that the hub genes were closely associated with skeletal muscle dysfunction, necrotic and apoptotic skeletal myoblasts, and apoptosis in sepsis-induced myopathy. Overall, 16 candidate biomarkers were certified as reliable features for more in-depth exploration of sepsis-induced myopathy in basic and clinical studies. [ABSTRACT FROM AUTHOR]

The therapeutic efficacy of lung adenocarcinoma (LUAD), the most prevalent histological subtype of primary lung cancer, remains inadequate, with accurate prognostic assessment posing significant challenges. This study sought to elucidate the prognostic significance of mitochondrial-related genes in LUAD through an integrative multi-omics approach, aimed at developing personalized therapeutic strategies. Utilizing transcriptomic and single-cell RNA sequencing (scRNA-seq) data, alongside clinical information from publicly available databases, we first applied dimensionality reduction and clustering techniques to the LUAD single-cell dataset, focusing on the subclassification of fibroblasts, epithelial cells, and T cells. Mitochondrial-related prognostic genes were subsequently identified using TCGA-LUAD data, and LUAD cases were stratified into distinct molecular subtypes through consensus clustering, allowing for the exploration of gene expression profiles and clinical feature distributions across subtypes. By leveraging an ensemble of machine learning algorithms, we developed an Artificial Intelligence-Derived Prognostic Signature (AIDPS) model based on mitochondrial-related genes and validated its prognostic accuracy across multiple independent datasets. The AIDPS model demonstrated robust predictive power for LUAD patient outcomes, revealing significant differences in responses to immunotherapy and chemotherapy, as well as survival outcomes between risk groups. Furthermore, we conducted comprehensive analyses of tumor mutation burden (TMB), immune microenvironment characteristics, and genome-wide association study (GWAS) data, providing additional insights into the mechanistic roles of mitochondrial-related genes in LUAD pathogenesis. This study not only offers a novel approach to improving prognostic assessments in LUAD but also establishes a strong foundation for the development of personalized therapeutic interventions. [ABSTRACT FROM AUTHOR]

Plants monitor multiple environmental cues, such as light and temperature, to ensure they germinate at the right time and place. Some specialist plants, like ephemeral fire-following weeds and root parasitic plants, germinate primarily in response to small molecules found in specific environments. Although these species come from distinct clades, they use the same HYPOSENSITIVE TO LIGHT/KARRIKIN INSENSITIVE 2 (HTL/KAI2) signalling pathway, to perceive different small molecules suggesting convergent evolution on this pathway. Here, we show that HTL/KAI2 signalling in Arabidopsis thaliana bypasses the light requirement for germination. The HTL/KAI2 downstream component, SUPPRESSOR OF MAX2 1 (SMAX1) accumulates in the dark and is necessary for PHYTOCHROME INTERACTING FACTOR 1/PHYTOCHROME INTERACTING FACTOR 3-LIKE 5 (PIF1/PIL5) to regulate hormone response pathways conducive to germination. The interaction of HTL/KAI2 and light signalling may help to explain how specialist plants like ephemeral and parasitic weeds evolved their germination behaviour in response to specific environments. Author summary: Specialist plants have convergently evolved to use the same family of receptors to perceive different small molecules in lieu of necessary germination cues, like light. Although light is necessary for the germination of many generalist plants such as the model organism Arabidopsis thaliana, we show that activating the conserved receptor in Arabidopsis promotes germination in the absence of light. We show that the downstream component of the AtKAI2 signalling pathway is stable in the dark which explains its ability to negatively regulate germination. Additionally, we show that activating the receptor in the dark can modulate the gene expression profile by regulating key components of the light signalling pathway. Our study highlights how specialist plants may recycle components of conserved signaling pathways to thrive in new environments. [ABSTRACT FROM AUTHOR]

Introduction: Early-onset Alzheimer's disease (EOAD) is sporadic, highly heterogeneous, and its underlying pathogenic mechanisms remain largely elusive. Proteomics research aims to uncover the biological processes and key proteins involved in disease progression. However, no proteomic studies to date have specifically focused on EOAD brain tissue. Method: We integrated proteomic data from brain tissues of two Alzheimer's disease (AD) cohorts and constructed a protein co-expression network using weighted gene co-expression network analysis (WGCNA). We identified modules associated with EOAD, conducted functional enrichment analysis to understand the biological processes involved in EOAD, and pinpointed potential key proteins within the core modules most closely linked to AD pathology. Results: In this study, we identified a total of 2,749 proteins associated with EOAD. Through protein co-expression network analysis, we discovered 41 distinct co-expression modules. Notably, the proteins within the core module most closely linked to AD pathology were significantly enriched in neutrophil degranulation. Additionally, we identified two potential key proteins within this core module that have not been previously reported in AD and validated their expression levels in 5xFAD mice. Conclusion: In summary, through a protein co-expression network analysis, we identified EOAD-related biological processes and molecular pathways, and screened and validated two key proteins, ERBB2IP and LSP1. These proteins may play an important role in the progression of EOAD, suggesting they could serve as potential therapeutic targets for the disease. [ABSTRACT FROM AUTHOR]

Leopard coral grouper (Plectropomus leopardus) is one of the most important cultured fish in the Pacific and Indian oceans. Vibrio harveyi is a serious pathogen causing serious skin ulceration and high mortality in P. leopardus. To gain more insight into the tissue-specific and dynamic immune regulation process of P. leopardus in response to V. harveyi infection, RNA sequencing (RNA-seq) was used to examine the transcriptome profiles in the spleen and liver at 0, 6, 12, 24, 48, and 72 h post-infection. The upregulated differentially expressed genes (DEGs) were predominantly involved in the immune response in the spleen and liver at the early infection stage (6-12 h), and downregulated DEGs were mainly involved in metabolic processes in the liver at the early and middle infection stage (6-48 h). Moreover, an overview of the immune response of P. leopardus against V. harveyi was exhibited including innate and adaptive immune-related pathways. Afterwards, the results of WGCNA analysis in the spleen indicated that TAP2, IRF1, SOCS1, and CFLAR were the hub genes closely involved in immune regulation in the gene co-expression network. This study provides a global picture of V. harveyi-induced gene expression profiles of P. leopardus at the transcriptome level and uncovers a set of key immune pathways and genes closely linked to V. harveyi infection, which will lay a foundation for further study the immune regulation of bacterial diseases in P. leopardus. [ABSTRACT FROM AUTHOR]

Introduction: Recently, a novel type of metabolic-regulated cell demise titled disulfidptosis has been discovered. Studies have demonstrated its importance in immune responses against cancer and its impact on the proliferation of cancer cells. Nonetheless, the precise mechanism and roles of disulfidptosis are not fully understood, particularly regarding the prognosis for individuals with uterine corpus endometrial carcinoma (UCEC). Methods: In this research, a distinctive disulfidptosis pattern was developed in UCEC, and by utilizing Non-negative Matrix Factorization (NMF) on 23 disulfidptosis related genes within the TCGA database, 3 distinct subgroups were distinguished. To collect data, we acquired gene expression profiles, somatic mutation information, copy number variation data, and corresponding clinical data from the TCGA and GEO database, specifically from UCEC patients. Cell line experiments and immunohistochemical (IHC) staining were conducted to validate the role of the LRPPRC in proliferation, migration and invasion. Results: The genetic features and immune microenvironment of these subgroups were examined. It is worth mentioning that these subgroups offer important insights into comprehending the tumor microenvironment (TME) and the response of patients to immunotherapy and chemotherapy. Moreover, a disulfidptosis model was developed and validated, demonstrating a high level of accuracy in predicting the prognosis and outcomes of immunotherapy in UCEC patients. Additionally, a novel biomarker, LRPPRC, was identified, which can server as a promising predictor for forecasting prognosis in UCEC patients, with validation through tissue microarray staining and cell line experiments. Discussion: This study has designed a classification system and a disulfidptosis model for UCEC, in addition to identifying a new biomarker, LRPPRC, for UCEC. These advancements serve as reliable and positive indicators for predicting outcomes and the efficacy of immunotherapy for each UCEC patient. [ABSTRACT FROM AUTHOR]

Background: DNA polymerase theta (POLQ) is a translesion synthesis polymerase essential for the repair of double strand breaks by the error-prone TMEJ (Theta Mediated End Joining) pathway. Although POLQ participates in maintaining genome stability, several studies have shown that its overexpression correlates with cancer progression and poor prognosis. Due to the fact that its role as a biomarker in pancreatic cancer remains unexplored, we aimed to study the usefulness of POLQ H-score as a prognostic factor in a pancreatic cancer patient cohort. Methods: We evaluated POLQ gene expression using a web-based tool to deliver gene expression profiling and interactive analyses based on TCGA and GTEx (GEPIA) and we examined the POLQ immunostaining in 152 biliopancreatic cancer surgical specimens using tissue microarrays. Association with survival was evaluated by Kaplan Meier curves and uni-multivariate Cox regression. Results: GEPIA analysis showed statistical differences according to POLQ mRNA levels in Disease Free Survival (DFS) (log rank 0.023, HR 2.8, p=0.029) and Overall Survival (OS) (log rank 0.011, HR 3.1, p=0.016). For immunohistochemistry (IHC) evaluation, POLQ H-score was calculated, and showed statistical differences for OS in Kaplan Meier curves (log rank 0.001) and uni-multivariate analysis (HR 2.27; 95% CI 1.24-4.15, p=0.008). Conclusions: Our results indicate that POLQ is an independent prognostic factor in pancreatic cancer when analyzed by immunostaining, which is in agreement with the results shown by the POLQ gene expression analysis (GEPIA). [ABSTRACT FROM AUTHOR]

Background: Metabolic reprogramming is one of the hallmarks of cancer, and in breast cancer (BC), several metabolic enzymes are overexpressed and overactivated. One of these, Enolase 1 (ENO1), catalyses glycolysis and is involved in the regulation of multiple signalling pathways. Objectives: This study aimed to evaluate in silico the prognostic and predictive effects of ENO1 expression in BC. Design: This is a bioinformatic in silico analysis. Methods: Using available online platforms (Kaplan–Meier [KM] plotter, receiver operating characteristic curve [ROC] plotter, cBioPortal, Genotype-2-Outcome [G-2-O], MethSurv, and Tumour–Immune System Interaction Database [TISIDB]), we performed a bioinformatic in silico analysis to establish the prognostic and predictive effects related to ENO1 expression in BC. A network analysis was performed using the Oncomine platform, and signalling, epigenetic, and immune regulation pathways were explored. Results: ENO1 was overexpressed in all the analysed Oncomine, epigenetic, and immune pathways in triple-negative, but not in hormone receptor–positive BCs. In human epidermal growth factor receptor 2 (HER2)-positive BCs, ENO1 expression showed a mixed profile. Analysis on disease progression and histological types showed ENO1 overexpression in ductal in situ and invasive carcinoma, in high-grade tumours followed by advanced or metastasis and was linked to worse survival. High ENO1 expression was also associated with relapse-free, distant metastasis-free and overall survival, irrespectively of treatment and was mainly related to basal subtype. Conclusion: ENO1 overexpression recruits a range of signalling pathways during disease progression conferring a worse prognosis and can be potentially used as a biomarker of disease progression and therapeutic target, particularly in triple-negative and in ductal invasive carcinoma. [ABSTRACT FROM AUTHOR]

Background: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory condition. Given patients with COPD continue to experience exacerbations despite the availability of effective therapies, anti-inflammatory treatments targeting novel pathways are needed. Kinases, notably the phosphoinositide 3-kinases (PI3K), are thought to be involved in chronic airway inflammation, with this pathway proposed as a critical regulator of inflammation and oxidative stress response in COPD. CHF6523 is an inhaled PI3Kδ inhibitor that has shown positive preclinical results. This manuscript reports the results of a study of CHF6523 in patients with stable COPD (chronic bronchitis phenotype), and who had evidence of type-2 inflammation. Methods: This randomised, double-blind, placebo-controlled, two-way crossover study comprised two 28-day treatment periods separated by a 28-day washout. Patients (N = 44) inhaled CHF6523 in one period, and placebo in the other, both twice daily. The primary objective was to assess the safety and tolerability of CHF6523; the secondary objective was to assess CHF6523 pharmacokinetics. Exploratory endpoints included target engagement (the relative reduction in phosphatidylinositol (3,4,5)-trisphosphate [PIP3]), pharmacodynamic evaluations such as airflow obstruction, and hyperinflation, and to identify biomarker(s) of drug response using proteomics and transcriptomics. Results: CHF6523 plasma pharmacokinetics were characterised by an early maximum concentration (Cmax), reached 15 and 10 min after dosing on Days 1 and 28, respectively, followed by a rapid decline. Systemic exposure on Day 28 showed limited accumulation, with ratios < 1.6 for Cmax and area under the curve from 0 to 12 h post-dose, and with steady state achieved on Day 20. Target engagement was confirmed by a significant 29.7% reduction from baseline in induced sputum PIP3 (29.5% reduction vs. placebo; adjusted ratio 0.705 [0.580, 0.856]; p = 0.001), but this did not translate into an anti-inflammatory pharmacodynamic effect, as assessed through measures including biomarkers and multi-omics. Additionally, although CHF6523 was generally well-tolerated, 95.2% of patients reported cough as an adverse event, most mild to moderate and resolving within one-hour post-dose. Conclusions: These data, together with those from other PI3K inhibitors, suggest that PI3Kδ is not a suitable pathway for the management of COPD, as the achieved target engagement did not translate into any pharmacodynamic anti-inflammatory effect. Trial registration: ClinicalTrials.gov (NCT04032535); posted 23rd July 2019. [ABSTRACT FROM AUTHOR]

Calcium phosphate-based materials (CaP) are introduced as potential dental pulp capping materials for deciduous teeth. The present study investigated the influence of inorganic phosphate (Pi) on regulating stem cells isolated from human exfoliated deciduous teeth (SHED). SHEDs were treated with Pi. Cell cycle progression and apoptosis were examined using flow cytometry analysis. Osteo/odontogenic and adipogenic differentiation were analyzed using alizarin red S and oil red O staining, respectively. The mRNA expression profile was investigated using a high-throughput RNA sequencing technique. Pi increased the late apoptotic cell population while cell cycle progression was not altered. Pi upregulated osteo/odontoblastic gene expression and enhanced calcium deposition. Pi-induced mineralization was reversed by pretreatment of cells with Foscarnet, or p38 inhibitor. Pi treatment inhibited adipogenic differentiation as determined by decreased PPARγ expression and reduced intracellular lipid accumulation. Bioinformatic analysis of gene expression profiles demonstrated several involved pathways, including PI3K/AKT, MAPK, EGFR, and VEGF signaling. In conclusion, Pi enhanced osteo/odontogenic but inhibited adipogenic differentiation in SHED. [ABSTRACT FROM AUTHOR]

Older age (≥ 65 years) is associated with impaired responses to influenza vaccination, leading to the preferential recommendation of MF59-adjuvanted (MF59Flu) or high-dose (HDFlu) influenza vaccines for this age group in the United States. Herein, we characterized transcriptomic profiles of CD4+ T cells isolated from 234 recipients (≥ 65 years) of either MF59Flu or HDFlu vaccine, prior to vaccination and 28 days thereafter. We identified 412 and 645 differentially expressed genes (DEGs) in CD4+ T cells of older adults after receiving MF59Flu and HDFlu, respectively. DEGs in CD4+ T cells of MF59Flu recipients were enriched in 14 KEGG pathways, all of which were downregulated. DEGs in CD4+ T cells of HDFlu recipients were enriched in 11 upregulated pathways and 20 downregulated pathways. CD4+ T cells in both vaccine groups shared 50 upregulated genes and 75 downregulated genes, all of which were enriched in 7 KEGG pathways. The remaining 287 and 520 DEGs were specifically associated with MF59Flu and HDFlu, respectively. Unexpectedly, none of these DEGs was significantly correlated with influenza A/H3N2-specific HAI titers, suggesting these DEGs at the individual level may have a limited role in protection against influenza. Our findings emphasize the need for further investigation into other factors influencing immunity against influenza in older adults. [ABSTRACT FROM AUTHOR]

Wireworms, the larva of click beetle (Agriotes species), are one of the most destructive pests of horticultural crops in North America, responsible for considerable economic losses in Canada. Agriotes sputator (A. sputator) species is a predominant wireworm pest attacking potato fields in Eastern Canada. However, no information about its genome-wide gene expression profile, specifically for the genes involved with development is available to date. Therefore, we generated the transcriptome profile of A. sputator during five developmental stages, including the three larval stages and adult male and female click beetle. Out of 714.7 million raw reads, de novo assembly generated 564,561 transcripts. The data were subjected to differential expression analysis using DESeq2, gene ontology, annotation, and pathway analyses. A total of 34,709 differentially expressed genes (DEGs) were significant (log2 fold change > 2, padj < 0.05) across the developmental stages. Functional analysis of DEGs identified development signaling, metabolism, transport, cellular mechanisms, and drug metabolism (cytochrome p450) pathways. This study provides comprehensive sequence resources and potential gene differences at different developmental stages of A. sputator. These findings will represent a major step towards developing sustainable methods to control this widely distributed pest in agricultural fields. [ABSTRACT FROM AUTHOR]

Neural crest cells (NCCs) are central to vertebrate embryonic development, giving rise to diverse cell types with unique migratory and differentiation capacities. This study examines the molecular characteristics of cranial neural crest cell (CNCC)-derived mesenchymal cells, specifically those from teeth which in deer show continuous but limited growth, and antlers, which exhibit remarkable regenerative capabilities. Here, through single-cell RNA sequencing analysis, we uncover shared gene expression profiles between adult antlerogenic and dental mesenchymal cells, indicating common developmental pathways. We identify a striking resemblance in transcriptomic features between antlerogenic progenitor cells and dental pulp mesenchymal cells. Comparative analysis of CNCC-derived and non-CNCC-derived mesenchymal cell pools across species reveals core signature genes associated with CNCCs and their derivatives, delineating essential connections between CNCCs and CNCC-derived adult mesenchymal pools. Furthermore, whole-genome DNA methylation analysis unveils hypomethylation of CNCC derivate signature genes in regenerative antlerogenic periosteum, implying a role in maintaining multipotency. These findings offer crucial insights into the developmental biology and regenerative potential of CNCC-derived mesenchymal cells, laying a foundation for innovative therapeutic strategies in tissue regeneration. Single-cell RNA sequencing reveals key molecular characteristics of cranial neural crest cell-derived mesenchymal cells in teeth and antlers, laying foundation innovative therapeutic strategies for tissue regeneration [ABSTRACT FROM AUTHOR]

Spatial transcriptomics is an emerging technology that enables the profiling of gene expression in tissues while preserving spatial location information. This innovative approach is anticipated to provide a comprehensive understanding of the spatial distribution of different cells within tissues and facilitate in-depth analysis of tissue structure. To accurately recognize spatial domains from spatial transcriptomics, we have introduced a generalized deep learning method called GAAEST (Graph Attention-based Autoencoder for Spatial Transcriptomics). Our proposed approach effectively integrates both spatial location information and gene expression data from spatial transcriptomics. Specifically, it leverages spatial location details to construct a neighborhood graph and employs a graph attention network-based encoder to embed gene expression information into a spatially informed space. At the same time, to further optimize the learned potential embedding, self-supervised contrastive learning is introduced to capture spatial information at three levels: local, global and contextual feature of spots. Finally, the decoder reconstructs gene expressions, which are then clustered to identify spatial domains with similar expression patterns and spatial proximity. Based on our experiments conducted on multiple datasets, GAAEST consistently outperforms existing state-of-the-art methods. The proposed GAAEST demonstrates excellent capabilities in spatial domain recognition, positioning it as an ideal tool for advancing spatial transcriptomics research. The graph attention based automatic encoder utilizing contrastive learning effectively combines spatial location information and gene expression data from spatial transcriptomics for enhanced domain recognition capacity. [ABSTRACT FROM AUTHOR]

Control of the electrochemical environment in living cells is typically attributed to ion channels. Here, we show that the formation of biomolecular condensates can modulate the electrochemical environment in bacterial cells, which affects cellular processes globally. Condensate formation generates an electric potential gradient, which directly affects the electrochemical properties of a cell, including cytoplasmic pH and membrane potential. Condensate formation also amplifies cell-cell variability of their electrochemical properties due to passive environmental effect. The modulation of the electrochemical equilibria further controls cell-environment interactions, thus directly influencing bacterial survival under antibiotic stress. The condensate-mediated shift in intracellular electrochemical equilibria drives a change of the global gene expression profile. Our work reveals the biochemical functions of condensates, which extend beyond the functions of biomolecules driving and participating in condensate formation, and uncovers a role of condensates in regulating global cellular physiology. [Display omitted] • Condensate formation regulates cytoplasmic ion distribution • Condensate formation modulates membrane potential • Condensate-dependent electrochemical effects affect cellular physiology Biomolecular condensation modulates the electrochemical equilibria of a cell, affecting cytoplasmic ion distribution and membrane potential. These electrochemical environmental features, mediated by condensate formation, modulate bacterial cellular physiology. [ABSTRACT FROM AUTHOR]

The accurate diagnosis of haematolymphoid malignancies is crucial for effective cancer care, but major obstacles to diagnosis exist in low‐ and middle‐income countries (LMICs). This article explores the global applicability of current haematolymphoid classification systems, which are predominantly derived from data generated in high‐income countries (HICs). Although disproportionately burdened with poor cancer outcomes, LMICs are generally faced with limited diagnostic resources, suboptimal access to therapeutics, and inadequate healthcare infrastructure. The article highlights the challenges faced by LMICs, including inconsistent access to high‐quality pathology services, limited availability of advanced diagnostic techniques, and a lack of population‐based cancer registry data. It also discusses the progress made in narrowing the gap between LMICs and HICs, such as the introduction of resource‐adapted classifications, improved guidance on essential diagnostic tools, and strengthening of in‐country professional pathology networks. Innovative diagnostic approaches, including gene expression profiling and machine learning, represent potential solutions for improving the diagnostic accuracy in LMICs, but addressable gaps remain. Recommendations are suggested for sustainable investments in diagnostic infrastructure, capacity‐building, and population‐based cancer registries to enhance the global applicability of haematolymphoid classification systems and improve outcomes for patients in LMICs. [ABSTRACT FROM AUTHOR]

The spatial organization of gene expression dictates tissue functions in multicellular parasites. Here, we present the spatial transcriptome of a parasitic flatworm, the common liver fluke Fasciola hepatica. We identify gene expression profiles and marker genes for eight distinct tissues and validate the latter by in situ hybridization. To demonstrate the power of our spatial atlas, we focus on genes with substantial medical importance, including vaccine candidates (Ly6 proteins) and drug resistance genes (glutathione S-transferases, ABC transporters). Several of these genes exhibit unique expression patterns, indicating tissue-specific biological functions. Notably, the prioritization of tegumental protein kinases identifies a PKCβ, for which small-molecule targeting causes parasite death. Our comprehensive gene expression map provides unprecedented molecular insights into the organ systems of this complex parasitic organism, serving as a valuable tool for both basic and applied research. Fasciola hepatica is a complex multicellular pathogen and the causative agent of fascioliasis, a zoonotic disease that compromises liver function. Using spatial transcriptomics, the authors uncover the tissue-specific gene expression of F. hepatica and identify genes with expression in the surface layer for drug-target discovery. [ABSTRACT FROM AUTHOR]

BACKGROUND: Integrative multiomics can elucidate pulmonary arterial hypertension (PAH) pathobiology, but procuring human PAH lung samples is rare. METHODS: We leveraged transcriptomic profiling and deep phenotyping of the largest multicenter PAH lung biobank to date (96 disease and 52 control) by integration with clinicopathologic data, genome-wide association studies, Bayesian regulatory networks, single-cell transcriptomics, and pharmacotranscriptomics. RESULTS: We identified 2 potentially protective gene network modules associated with vascular cells, and we validated ASPN, coding for asporin, as a key hub gene that is upregulated as a compensatory response to counteract PAH. We found that asporin is upregulated in lungs and plasma of multiple independent PAH cohorts and correlates with reduced PAH severity. We show that asporin inhibits proliferation and transforming growth factor-ß/phosphorylated SMAD2/3 signaling in pulmonary artery smooth muscle cells from PAH lungs. We demonstrate in Sugen-hypoxia rats that ASPN knockdown exacerbated PAH and recombinant asporin attenuated PAH. CONCLUSIONS: Our integrative systems biology approach to dissect the PAH lung transcriptome uncovered asporin as a novel protective target with therapeutic potential in PAH. [ABSTRACT FROM AUTHOR]

Simple Summary: Therapeutic response and survival outcomes in hepatocellular carcinoma (HCC) patients remain unsatisfactory, with a 5-year survival rate of less than 25%. The lack of molecular analysis of HCC tissue hinders the identification of precise predictors of disease progression and treatment outcomes. Analyzing the hepatic neoangiogenic transcriptomic signature can predict the biological aggressiveness of HCC and its resistance to therapies, offering a valuable diagnostic and prognostic tool that can significantly enhance the management of HCC. Background/Objectives: We evaluated the relationship between the neoangiogenic transcriptomic signature (nTS) and clinical symptoms, treatment outcomes, and survival in hepatocellular carcinoma (HCC) patients. Methods: This study prospectively followed 328 patients in the derivation and 256 in the validation cohort (with a median follow-up of 31 and 22 months, respectively). The nTS was associated with disease presentation, treatments administered, and overall survival rates. Additionally, this study investigated how multiple treatments influenced changes in nTS status and alterations in microRNA expression. Results: The nTS was identified in 27.4% of patients, linked to aggressive features like multifocality and elevated alpha-fetoprotein (AFP), a pattern consistent with that of the validation cohort. Most patients in both cohorts received treatment for HCC. nTS+ patients had limited access to, and benefited less from, liver transplantation or radiofrequency ablation (RFA) compared to nTS− patients. By the end, 78.9% had died, with nTS− patients showing better median survival and response to treatments than their nTS+ counterparts, who had lower survival across all treatment types. Among those who received transarterial chemoembolization (TACE), 31.2% (21/80 patients after the initial treatment and another four following a second TACE) transitioned from an nTS− to an nTS+ status. This shift was associated with lower survival and alterations in microRNA expressions related to oncogenic pathways. Conclusions: The nTS markedly influences treatment eligibility and survival in patients with HCC. Notably, the nTS can develop after repeated TACE procedures, significantly impacting patient survival and altering oncogenic microRNA expression patterns. These findings highlight the critical role of the nTS in guiding treatment decisions and prognostication in HCC management. [ABSTRACT FROM AUTHOR]

Simple Summary: Pancreatic ductal adenocarcinoma (PDAC) has a rising incidence and poor prognosis due to late diagnosis and limited treatments. Currently, treatment is based solely on TNM staging, without considering molecular tumor characterization. In the present study, we validated a combined amplification refractory mutation system (ARMS) and high-resolution melting analysis (HRMA) technique for detecting mutations in codon 12 of KRAS in PDAC tumor and plasma samples and assessed its prognostic value. We included 88 newly diagnosed PDAC patients, treated with either surgery, chemotherapy, or best supportive treatment only. Both tumor and plasma samples were analyzed, and the most frequent mutations were G12D (36%) and G12V (25%). KRAS mutations G12D and/or G12C in tumors and plasma were associated with lower progression-free survival (PFS) and overall survival (OS) independently of disease stage or treatment performed. ARMS–HRMA offers a rapid, cost-effective method for detecting KRAS mutations and can aid in prognosis and treatment decisions. Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) incidence is rising, and prognosis remains poor due to late diagnosis and limited effective therapies. Currently, patients are treated based on TNM staging, without molecular tumor characterization. This study aimed to validate a technique that combines the amplification refractory mutation system (ARMS) with high-resolution melting analysis (HRMA) for detecting mutations in codon 12 of KRAS in tumor and plasma, and to assess its prognostic value. Methods: Prospective study including patients with newly diagnosed PDAC with tumor and plasma samples collected before treatment. Mutations in codon 12 of KRAS (G12D, G12V, G12C, and G12R) were detected using ARMS–HRMA and compared to Sanger sequencing (SS). Univariate and multivariate analyses were used to evaluate the prognostic significance of these mutations. Results: A total of 88 patients, 93% with ECOG-PS 0–1, 57% with resectable disease. ARMS–HRMA technique showed a higher sensitivity than SS, both in tumor and plasma (77% vs. 51%; 25 vs. 0%, respectively). The most frequent mutation was G12D (n = 32, 36%), followed by G12V (n = 22, 25%). On multivariate analysis, patients with G12D and/or G12C mutations, either in tumor or plasma, had lower PFS (HR 1.792, 95% CI 1.061–3.028, p = 0.029; HR 2.081, 95% CI 1.014–4.272, p = 0.046, respectively) and lower OS (HR 1.757, 95% CI 1.013–3.049, p = 0.045; HR 2.229, 95% CI 1.082–4.594, p = 0.030, respectively). Conclusions: ARMS–HRMA is a rapid and cost-effective method for detecting KRAS mutations in PDAC patients, offering the potential for stratifying prognosis and guiding treatment decisions. The presence of G12D and G12C mutations in both tumor and plasma is associated with a poorer prognosis. [ABSTRACT FROM AUTHOR]

Simple Summary: Intracranial Epidermoid Cysts (IECs) are rare tumors. Despite their benign course, IECs can adhere to critical brain structures resulting in impairment and morbidity. The primary treatment is surgery; however, cyst adherence often complicates complete removal, resulting in notably high progression rates after subtotal resection. Due to the rarity of IECs, there has been limited research focused on understanding the mechanisms of the disease and advancing therapeutic options. As a result, there are currently no effective drug therapies available for treating patients with IECs. Targeted therapy is an effective form of treatment for tumors. It focuses on mutations that turn healthy cells into tumor cells. The mutation profile of IECs has not been investigated. We aimed to investigate the somatic landscape of IECs to gain insights into tumor biology and identify mutations that could potentially serve as targets for additional therapies. Surgery is still the most effective treatment for these patients. Background/Objectives: Intracranial Epidermoid Cysts (IECs) are rare intracranial tumors primarily treated through surgery. Cyst adherence complicates complete removal, leading to high rates of tumor progression after subtotal resection. The molecular drivers of IEC remain unknown. Consequently, advances in treatment have fallen short. Tumor genetic profiling has revealed potential targets for drug development, including FDA-approved options and reshaping treatment. The genetic landscape of IECs has not been explored. We applied Whole Exome Sequencing (WES) to IECs to gain insights into the mechanisms of oncogenesis and identify potential therapeutic targets. Methods: We performed WES on tumor tissue and matched blood samples, when available. Following GATK best practices, we conducted read processing, quality control, somatic variant calling, and copy-number inference. Data analyses and visualization were conducted in R. Results: Top altered genes are associated with the immune system and tumor microenvironment, suggesting a mechanism of immune evasion. Gene and pathway enrichment revealed a high mutation burden in genes associated with Extracellular Matrix (ECM) and PI3K-AKT-mTOR cascades. Recurrent and deleterious alterations in NOTCH2 and USP8 were identified in 50% and 30% of the cohort, respectively. Frequent amplifications in deubiquitinases and beta-defensins strengthened the involvement of immune mechanisms for oncogenic transformation. Conclusions: Top altered genes and recurrent mutations may play a role in shaping the microenvironment and modulating immune evasion in IECs. USP8 and NOTCH2 may serve as clinically relevant target for IECs. Finally, we present evidence that the crosstalk between the PI3K-Akt-mTOR and ECM signaling pathways may play a role in modulating the immune escape mechanism in IECs. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer continues to represent a leading cause of death among women globally. Recent studies have shown a growing link between breast cancer and the living microorganisms from the tumoral breast tissue, known as microbiota. This review looks at how the microbiota is found in healthy breast tissue and the changes observed during cancer development and progression. The microbiota has been shown to affect cancer growth, spread, and resistance to treatments by interacting with the tumor's environment. Moreover, this review explores how different breast cancer types have distinct microbial profiles. Future studies could improve breast cancer care by endowing the microbiota as a diagnostic, prediction and treatment marker. Breast cancer remains one of the leading causes of death among women worldwide, and recent research highlights its growing connection to alterations in the microbiota. This review delves into the intricate relationship between microbiotas and breast cancer, exploring its presence in healthy breast tissue, its changes during cancer progression, and its considerable impact on both the tumor microenvironment (TME) and the tumor immune microenvironment (TIME). We extensively analyze how the microbiota influences cancer growth, invasion, metastasis, resistance to drugs, and the evasion of the immune system, with a special focus on its effects on the TIME. Furthermore, we investigate distinct microbial profiles associated with the four primary molecular subtypes of breast cancer, examining how the microbiota in tumor tissues compares with that in adjacent normal tissues. Emerging studies suggest that microbiotas could serve as valuable diagnostic and prognostic biomarkers, as well as targets for therapy. This review emphasizes the urgent need for further research to improve strategies for breast cancer prevention, diagnosis, and treatment. By offering a detailed examination of the microbiota's critical role in breast cancer, this review aims to foster the development of novel microbiota-based approaches for managing the disease. [ABSTRACT FROM AUTHOR]

Macroscale functional gradient techniques provide a continuous coordinate system that extends from unimodal regions to transmodal higher‐order networks. However, the alterations of these functional gradients in AD and their correlations with cognitive terms and gene expression profiles remain to be established. In the present study, we directly studied the functional gradients with functional MRI data from seven scanners. We adopted data‐driven meta‐analytic techniques to unveil AD‐associated changes in the functional gradients. The principal primary‐to‐transmodal gradient was suppressed in AD. Compared to NCs, AD patients exhibited global connectome gradient alterations, including reduced gradient range and gradient variation, increased gradient scores in the somatomotor, ventral attention, and frontoparietal regions, and decreased in the default mode network. More importantly, the Gene Ontology terms of biological processes were significantly enriched in the potassium ion transport and protein‐containing complex remodeling. Our compelling evidence provides a new perspective in understanding the connectome alterations in AD. [ABSTRACT FROM AUTHOR]

Skeletal muscle contusion (SMC) is common in daily life and clinical practice, but the molecular mechanisms underlying SMC healing are unclear. Ferroptosis, a regulated cell death type, has gained attention recently. We observed iron overload in skeletal muscle following contusion through HE and Perls staining. Abnormal iron levels are highly likely to induce ferroptosis. Therefore, we aimed to explore whether iron overload after contusion leads to ferroptosis in skeletal muscle and the underlying mechanisms, which will help us understand the effects of iron abnormalities on skeletal muscle repair. Initially, we searched SMC gene expression profiles from the GEO database and used bioinformatics analysis to reveal ferroptosis occurrence. Then, we identified the gene sat1 plays an important role in this process. We further established a rat SMC model and treated rats with ferroptosis inhibitors (Ferrostatin-1, Deferoxamine). Our findings confirmed iron overload from SMC can lead to ferroptosis in rats. We also demonstrated that SAT1 can regulate ferroptosis by affecting ALOX15. Moreover, we constructed a ferroptosis L6 cell model and found that SAT1 knockdown significantly inhibited ALOX15 expression and reduced cellular lipid peroxidation. In conclusion, these results indicated ferroptosis can occur following SMC, and SAT1, as a key regulator, affects skeletal muscle injury healing by mediating high ALOX15 expression, which in turn regulates lipid peroxidation. [ABSTRACT FROM AUTHOR]

Diabetic retinopathy (DR) is the leading cause of visual impairment, particularly in the proliferative form (proliferative DR [PDR]). The impact of the PDR microenvironment on microglia, which are the resident immune cells in the central nervous system, and the specific pathological changes it may induce remain unclear. This study aimed to investigate the role of microglia in the progression of PDR under hypoxic and inflammatory conditions. We performed a comprehensive gene expression analysis using human-induced pluripotent stem cell-derived microglia under different stimuli (dimethyloxalylglycine (DMOG), lipopolysaccharide (LPS), and DMOG + LPS) to mimic the hypoxic inflammatory environment characteristic of PDR. Principal component analysis revealed distinct gene expression profiles, with 76 genes synergistically upregulated under combined stimulation. Notably, prostaglandin-endoperoxide synthase 2 (encoding cyclooxygenase (COX)-2) exhibited the most pronounced increase, leading to elevated prostaglandin E2 (PGE2) levels and driving pathological angiogenesis and inflammation via the COX-2/PGE2/PGE receptor 2 signaling axis. Additionally, the upregulation of the fibrogenic genes snail family transcriptional repressor 1 and collagen type I alpha 1 chain suggested a role for microglia in fibrosis. These findings underscore the critical involvement of microglia in PDR and suggest that targeting both the angiogenic and fibrotic pathways may present new therapeutic strategies for managing this condition. [ABSTRACT FROM AUTHOR]

The glyoxalase pathway, consisting of glyoxalase I (GLYI) and glyoxalase II (GLYII), is an enzymatic system that converts cytotoxic methylglyoxal to non-toxic S-D-lactoylglutathione. Although the GLY gene family has been analyzed in Arabidopsis, rice, grape, cabbage, and soybean, cucumber studies are lacking. Here, we analyzed the cucumber GLY gene family, identifying 13 CsGLYI and 2 CsGLYII genes. Furthermore, we investigated the physicochemical properties, phylogenetic relationships, chromosomal localization and colinearity, gene structure, conserved motifs, cis-regulatory elements, and protein–protein interaction networks of the CsGLY family. They were primarily localized in the cytoplasm, chloroplasts, and mitochondria, with a minor presence in the nucleus. The classification of CsGLYI and CsGLYII genes into five classes closely resembled the homologous genes in Arabidopsis and soybean. Additionally, hormone-responsive elements dominated the promoter region of GLY genes, alongside light- and stress-responsive elements. The predicted interaction proteins of CsGLYIs and CsGLYIIs exerted a significant role in cellular respiration, amino acid synthesis, and metabolism, as well as methylglyoxal catabolism. In addition, the expression profiles of GLY genes were distinct in different tissues of cucumber as well as under diverse abiotic stresses. This study is conducive to the further exploration of the functional diversity among glyoxalase genes and the mechanisms of stress responses in cucumber. [ABSTRACT FROM AUTHOR]

The Domain of Unknown Function 506 (DUF506) belongs to the PD-(D/E) XK nuclease superfamily and has been reported to play critical roles in growth and development as well as responses to abiotic stresses. However, the function of DUF506 genes in Brassica rapa (B. rapa) remains unclear. In this study, a total of 18 BrDUF506 genes were identified and randomly distributed across eight chromosomes, categorized into four subfamilies. Analyzing their promoter sequences has uncovered various stress-responsive elements, such as those for drought, methyl jasmonate (MeJA), and abscisic acid (ABA). Bra000098 and Bra017099 exhibit significantly enhanced expression in response to heat and drought stress. Protein interaction predictions indicate that Bra000098 homolog, At2g38820, is interacting with ERF012 and PUB48 and is involved in abiotic stress regulation. Furthermore, gene expression profiling has identified Bra026262 with a high expression level in flowers and significantly decreased in female sterile mutants. Protein interaction prediction further revealed that its homolog, At4g32480, interacts with MYB and AGL proteins, suggesting the potential roles in female gametophyte development. The current study enhances our understanding of the functional roles of BrDUF506s, providing significant insights that are valuable in investigating sexual reproduction and abiotic stress responses in B. rapa. [ABSTRACT FROM AUTHOR]

Sepsis remains a huge unmet medical need for which no approved drugs, besides antibiotics, are on the market. Despite the clinical impact of sepsis, its molecular mechanism remains inadequately understood. Recent insights have shown that profound hepatic transcriptional reprogramming, leading to fatal metabolic abnormalities, might open a new avenue to treat sepsis. Translation of experimental results from rodents to larger animal models of higher relevance for human physiology, such as pigs, is critical and needs exploration. We performed a comparative analysis of the transcriptome profiles in murine and porcine livers using the following sepsis models: cecal ligation and puncture (CLP) in mice and fecal instillation (FI) in pigs, both of which induce polymicrobial septic peritonitis, and lipopolysaccharide (LPS)-induced endotoxemia in pigs, inducing sterile inflammation. Using bulk RNA sequencing, Metascape pathway analysis, and HOMER transcription factor motif analysis, we were able to identify key genes and pathways affected in septic livers. Conserved upregulated pathways in murine CLP and porcine LPS and FI generally comprise typical inflammatory pathways, except for ER stress, which was only found in the murine CLP model. Conserved pathways downregulated in sepsis comprise almost exclusively metabolic pathways such as monocarboxylic acid, steroid, biological oxidation, and small-molecule catabolism. Even though the upregulated inflammatory pathways were equally induced in the two porcine models, the porcine FI model more closely resembles the metabolic dysfunction observed in the CLP liver compared to the porcine LPS model. This comprehensive comparison focusing on the hepatic responses in mouse CLP versus LPS or FI in pigs shows that the two porcine sepsis models generally resemble quite well the mouse CLP model, with a typical inflammatory signature amongst the upregulated genes and metabolic dysfunction amongst the downregulated genes. The hepatic ER stress observed in the murine model could not be replicated in the porcine models. When studying metabolic dysfunction in the liver upon sepsis, the porcine FI model more closely resembles the mouse CLP model compared to the porcine LPS model. [ABSTRACT FROM AUTHOR]

The brown planthopper (Nilaparvata lugens, BPH) is a serious insect pest responsible for causing immense economic losses to rice growers around the globe. The development of high-throughput sequencing technologies has significantly improved the research on this pest, and its genome structure, gene expression profiles, and host–plant interactions are being unveiled. The integration of genomic sequencing, transcriptomics, proteomics, and metabolomics has greatly increased our understanding of the biological characteristics of planthoppers, which will benefit the identification of resistant rice varieties and strategies for their control. Strategies like more optimal genome assembly and single-cell RNA-seq help to update our knowledge of gene control structure and cell type-specific usage, shedding light on how planthoppers adjust as well. However, to date, a comprehensive genome-wide investigation of the genetic interactions and population dynamics of BPHs has yet to be exhaustively performed using these next-generation omics technologies. This review summarizes the recent advances and new perspectives regarding the use of omics data for the BPH, with specific emphasis on the integration of both fields to help develop more sustainable pest management strategies. These findings, in combination with those of post-transcriptional and translational modifications involving non-coding RNAs as well as epigenetic variations, further detail intricate host–brown planthopper interaction dynamics, especially regarding resistant rice varieties. Finally, the symbiogenesis of the symbiotic microbial community in a planthopper can be characterized through metagenomic approaches, and its importance in enhancing virulence traits would offer novel opportunities for plant protection by manipulating host–microbe interactions. The concerted diverse omics approaches collectively identified the holistic and complex mechanisms of virulence variation in BPHs, which enables efficient deployment into rice resistance breeding as well as sustainable pest management. [ABSTRACT FROM AUTHOR]

Microglia signatures refer to distinct gene expression profiles or patterns of gene activity that are characteristic of microglia. Advances in gene expression profiling techniques, such as single-cell RNA sequencing, have allowed us to study microglia at a more detailed level and identify unique gene expression patterns that are associated, but not always, with different functional states of these cells. Microglial signatures depend on the developmental stage, brain region, and specific pathological conditions. By studying these signatures, it has been possible to gain insights into the underlying mechanisms of microglial activation and begin to develop targeted therapies to modulate microglia-mediated immune responses in the CNS. Historically, the first two signatures coincide with M1 pro-inflammatory and M2 anti-inflammatory phenotypes. The first one includes upregulation of genes such as CD86, TNF-α, IL-1β, and iNOS, while the second one may involve genes like CD206, Arg1, Chil3, and TGF-β. However, it has long been known that many and more specific phenotypes exist between M1 and M2, likely with corresponding signatures. Here, we discuss specific microglial signatures and their association, if any, with neurodegenerative pathologies and other brain disorders. [ABSTRACT FROM AUTHOR]

Summary: Nicotiana benthamiana is predominantly distributed in arid habitats across northern Australia. However, none of six geographically isolated accessions shows obvious xerophytic morphological features.To investigate how these tender‐looking plants withstand drought, we examined their responses to water deprivation, assessed phenotypic, physiological, and cellular responses, and analysed cuticular wax composition and wax biosynthesis gene expression profiles.Results showed that the Central Australia (CA) accession, globally known as a research tool, has evolved a drought escape strategy with early vigour, short life cycle, and weak, water loss‐limiting responses. By contrast, a northern Queensland (NQ) accession responded to drought by slowing growth, inhibiting flowering, increasing leaf cuticle thickness, and altering cuticular wax composition. Under water stress, NQ increased the heat stability and water impermeability of its cuticle by extending the carbon backbone of cuticular long‐chain alkanes from c. 25 to 33. This correlated with rapid upregulation of at least five wax biosynthesis genes. In CA, the alkane chain lengths (c. 25) and gene expression profiles remained largely unaltered.This study highlights complex genetic and environmental control over cuticle composition and provides evidence for divergence into at least two fundamentally different drought response strategies within the N. benthamiana species in < 1 million years. [ABSTRACT FROM AUTHOR]