BACKGROUND: B chromosomes are extra non-essential elements present in several eukaryotes. Unlike A chromosomes which are essential and present in all individuals of a species, B chromosomes are not necessary for normal functioning of an organism. Formerly regarded as genetically inactive, B chromosomes have been discovered to not only express their own genes, but also to exert influence on gene expression in A chromosomes. Recent studies have shown that, in some Psalidodon (Characiformes, Characidae) species, B chromosomes might be associated with phenotypic effects, such as changes in the reproductive cycle and gene expression.
RESULTS: In this study, we aimed to establish stable reference genes for RT-qPCR experiments conducted on gonads of three fish species within Psalidodon genus, both in the presence and absence of B chromosomes. The stability of five selected reference genes was assessed using NormFinder, geNorm, BestKeeper, and RefFinder algorithms. We determined ppiaa and pgk1 as the most stable genes in P. fasciatus, whereas ppiaa and hmbsa showed the highest stability in P. bockmanni. For P. paranae, tbp and hprt1 were the most stable genes in females, and ppiaa and hprt1 were the most stable in males.
CONCLUSIONS: We determined the most stable reference genes in gonads of three Psalidodon species considering the presence of B chromosomes. This is the first report of reference gene stability in the genus and provides valuable tools to better understand the effects of B chromosomes at gene expression level.

CONCLUSIONS: Lysine plays an essential role in the growth differences between male and female S. linearistipularis plants under salt stress. Furthermore, SlDHDPS is identified as a vital gene contributing to the differences in saline-alkali tolerance between male and female plants of S. linearistipularis. Soil salinization is a significant problem that severely restricts agricultural production worldwide. High salinity and low nutrient concentrations consequently prevent the growth of most plant species. Salix linearistipularis is the only woody plant (shrub) naturally distributed in the saline-alkali lands of the Songnen Plain in Northeast China, and it is one of the few plants capable of thriving in soils with extremely high salt and alkaline pH (>9.0) levels. However, insufficient attention has been given to the interplay between salt and nitrogen in the growth and development of S. linearistipularis. Here, the male and female plants of S. linearistipularis were subjected to salt stress with nitrogen-starvation or nitrogen-supplement treatments, and it was found that nitrogen significantly affects the difference in salt tolerance between male and female plants, with nitrogen-starvation significantly enhancing the salt stress tolerance of female plants compared to male plants. Transcriptional analyses showed 66 differentially expressed nitrogen-responsive genes in female and male roots, with most of them showing sexual differences in expression patterns under salinity stress. RNA-seq and RT-qPCR analysis demonstrated that six genes had an opposite salt-induced expression pattern in female and male roots. The expression of the 4-hydroxy-tetrahydrodipicolinate synthase encoding gene (SlDHDPS) in female roots was higher than that in male roots. Further treatment with exogenous lysine could significantly alleviate the inhibitory effect of salt stress on the growth of female and male plants. These results indicate that the SlDHDPS in the nitrogen metabolism pathway is involved in the resistance of S. linearistipularis to salt stress, which lays a foundation for further exploring the mechanism of nitrogen on salt tolerance of S. linearistipularis, and has a significant reference value for saline-alkali land management and sustainable agricultural development.

Patients with severe COVID-19 and those with sepsis have similar clinical manifestations. We used bioinformatics methods to identify the common hub genes in these 2 diseases. Two RNA-seq datasets from the Gene Expression Omnibus were used to identify common differentially expressed genes (DEGs) in COVID-19 and sepsis. These common genes were used for analysis of functional enrichment; pathway analysis; identification of associated transcription factors, metabolites, and miRNAs; and mapping of protein-protein interaction networks. The major hub genes of COVID-19 and sepsis were identified, and validation datasets were used to assess the value of these hub genes using receiver operating characteristic (ROC) curves. Analysis of the 800 common DEGs for COVID-19 and sepsis, as well as common transcription factors, miRNAs, and metabolites, demonstrated that the immune response had a key role in both diseases. DLGAP5, BUB1, CDK1, CCNB1, and BUB1B were the most important common hub genes. Analysis of a validation cohort indicated these 5 genes had significantly higher expression in COVID-19 patients and sepsis patients than in corresponding controls, and the area under the ROC curves ranged from 0.832 to 0.981 for COVID-19 and 0.840 to 0.930 for sepsis. We used bioinformatics tools to identify common DEGs, miRNAs, and transcription factors for COVID-19 and sepsis. The 5 identified hub genes had higher expression in validation cohorts of COVID-19 and sepsis. These genes had good or excellent diagnostic performance based on ROC analysis, and therefore have potential use as novel markers or therapeutic targets.

Osteoarthritis (OA) is a comprehensive joint disorder. The specific genes that trigger OA and the strategies for its effective management are not fully understood. This study focuses on identifying key genes linked to iron metabolism that could influence both the diagnosis and therapeutic approaches for OA. Analysis of GEO microarray data and iron metabolism genes identified 15 ferroptosis-related DEGs, enriched in hypoxia and HIF-1 pathways. Ten key hub genes (ATM, GCLC, PSEN1, CYBB, ATG7, MAP1LC3B, PLIN2, GRN, APOC1, SIAH2) were identified. Through stepwise regression, we screened 4 out of the above 10 genes, namely, GCLC, GRN, APOC1, and SIAH2, to obtain the optimal model. AUROCs for diagnosis of OA for the four hub genes were 0.81 and 0.80 of training and validation sets, separately. According to immune infiltration results, OA was related to significantly increased memory B cells, M0 macrophages, regulatory T cells, and resting mast cells but decreased activated dendritic cells. The four hub genes showed a close relation to them. It is anticipated that this model will aid in diagnosing osteoarthritis by assessing the expression of specific genes in blood samples. Moreover, studying these hub genes may further elucidate the pathogenesis of osteoarthritis.

We aimed to find new therapeutic targets related to Cancer Stem Cell alterations in recurrent patients from two TCGA cohorts: Testicular Germ Cell Tumor (TGCT) and Uterine Corpus Endometrial Carcinoma (UCEC). Raw sequencing data were downloaded from the TCGA database. Datasets containing RNA expression and Methylation files were directly downloaded from cBioportal. Variant Call Format files (VCFs) were downloaded from the GDC portal. Gene enrichment analysis was performed using GSEA (Gene Set Enrichment Analysis) software. Transcriptome profiling, coexpression co-occurrence, networks, and survival analyses were performed using cBioportal tools, while mutational analysis of patients was processed using UNIX scripts. We found that cancer stem cell transcription factors were highly expressed in Testicular Germ Cell Tumor (TGCT) and Uterine Corpus Endometrial Carcinoma (UCEC) cohorts, compared to the other 29 cancer cohorts in TCGA. Patients presented a poorer diagnosis when the genes (POU5F1, NANOG, SOX2, SALL4, ABCB1, ABCC1, and ABCG2) were altered. In UCEC cohorts, recurrent patients showed the ABCG2 potentially phosphorylated by the PIM1 kinase. In the TGCT cohort, genes ABCB1 and ABCG2 only appeared in the phosphonetwork in recurrent patients potentially phosphorylated by the same kinase, PIM1, but also by PRKACA. Our data indicate that PRKACA and PIM1 may modulate POU5F1 phosphorylation.

UNASSIGNED: Precise staging and classification of liver fibrosis are crucial for the hierarchy management of patients. The roles of lactylation are newly found in the progression of liver fibrosis. This study is committed to investigating the signature genes with histone lactylation and their connection with immune infiltration among liver fibrosis with different phenotypes.
UNASSIGNED: Firstly, a total of 629 upregulated and 261 downregulated genes were screened out of 3 datasets of patients with liver fibrosis from the GEO database and functional analysis confirmed that these differentially expressed genes (DEGs) participated profoundly in fibrosis-related processes. After intersecting with previously reported lactylation-related genes, 12 DEGs related to histone lactylation were found and narrowed down to 6 core genes using R algorithms, namely S100A6, HMGN4, IFI16, LDHB, S100A4, and VIM. The core DEGs were incorporated into the Least absolute shrinkage and selection operator (LASSO) model to test their power to distinguish the fibrotic stage.
UNASSIGNED: Advanced fibrosis presented a pattern of immune infiltration different from mild fibrosis, and the core DEGs were significantly correlated with immunocytes. Gene set and enrichment analysis (GSEA) results revealed that core DEGs were closely linked to immune response and chemokine signaling. Samples were classified into 3 clusters using the LASSO model, followed by gene set variation analysis (GSVA), which indicated that liver fibrosis can be divided into status featuring lipid metabolism reprogramming, immunity immersing, and intermediate of both. The regulatory networks of the core genes shared several transcription factors, and certain core DEGs also presented dysregulation in other liver fibrosis and idiopathic pulmonary fibrosis (IPF) cohorts, indicating that lactylation may exert comparable functions in various fibrotic pathology. Lastly, core DEGs also exhibited upregulation in HCC.
UNASSIGNED: Lactylation extensively participates in the pathological progression and immune infiltration of fibrosis. Lactylation and related immune infiltration could be a worthy focus for the investigation of HCC developed from liver fibrosis.

UNASSIGNED: Glioma is a highly heterogeneous malignancy of the central nervous system. This heterogeneity is driven by various molecular processes, including neoplastic transformation, cell cycle dysregulation, and angiogenesis. Among these biomolecular events, inflammation and stress pathways in the development and driving factors of glioma heterogeneity have been reported. However, the mechanisms of glioma heterogeneity under stress response remain unclear, especially from a spatial aspect.
UNASSIGNED: This study employed single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to explore the impact of oxidative stress response genes in oligodendrocyte precursor cells (OPCs). Our analysis identified distinct pathways activated by oxidative stress in two different types of gliomas: high- and low- grade (HG and LG) gliomas.
UNASSIGNED: In HG gliomas, oxidative stress induced a metabolic shift from oxidative phosphorylation to glycolysis, promoting cell survival by preventing apoptosis. This metabolic reprogramming was accompanied by epithelial-to-mesenchymal transition (EMT) and an upregulation of stress response genes. Furthermore, SCENIC (Single-Cell rEgulatory Network Inference and Clustering) analysis revealed that oxidative stress activated the AP1 transcription factor in HG gliomas, thereby enhancing tumor cell survival and proliferation.
UNASSIGNED: Our findings provide a novel perspective on the mechanisms of oxidative stress responses across various grades of gliomas. This insight enhances our comprehension of the evolutionary processes and heterogeneity within gliomas, potentially guiding future research and therapeutic strategies.

OBJECTIVE: Survival rates of breast cancer (BC) patients are particularly low in rural regions in sub-Saharan Africa (SSA) which is due to limited access to therapy. In recent years, gene expression profiling (GEP) of BC showed a strong prognostic value in patients with local tumour surgery and (neo)adjuvant treatment. The aim of this study was to evaluate the impact of intrinsic subtypes on survival of patients in rural Ethiopia without any (neo)adjuvant therapy.
METHODS: In total, 113 female patients from Aira Hospital with histologically proven BC and treated only with surgery were included in this study. All samples were analysed by immunohistochemistry (IHC) for estrogen receptor, progesterone receptor, HER2 and Ki67, as well as RNA-expression analysis for PAM50 subtyping.
RESULTS: A positive hormone receptor status was found in 69.0% of the tumours and intrinsic subtyping demonstrated Luminal B to be the most common subtype (34.5%). Follow-up data was available for 79 of 113 patients. Two-year overall survival (OS) was 57.3% and a considerably worse OS was observed in patients with Basal-like BC compared to Luminal A BC. Moreover, advanced tumours showed an increased risk of mortality.
CONCLUSIONS: The OS was very low in the patient cohort that received no (neo)adjuvant treatment. Immunohistochemistry and GEP confirmed endocrine-sensitive tumours in more than half of the patients, with a large proportion of Luminal B, HER2-enriched and Basal-like tumours so that adjuvant chemotherapy should be recommended.

Immune checkpoint blockades are actively adopted in diverse cancer types including metastatic melanoma and lung cancer. Despite of durable response in 20-30% of patients, we still lack molecular markers that could predict the patient responses reliably before treatment. Here we present a composite model for predicting anti-PD-1 response based on tumor mutation burden (TMB) and transcriptome sequencing data of 85 lung adenocarcinoma (LUAD) patients who received anti-PD-(L)1 treatment. We found that TMB was a good predictor (AUC = 0.81) for PD-L1 negative patients (n = 20). For PD-L1 positive patients (n = 65), we built an ensemble model of 100 XGBoost learning machines where gene expression, gene set activities and cell type composition were used as input features. The transcriptome-based models showed excellent accuracy (AUC > 0.9) and highlighted the contribution of T cell activities. Importantly, nonresponder patients with high prediction score turned out to have high CTLA4 expression, which suggested that neoadjuvant CTLA4 combination therapy might be effective for these patients. Our data and analysis results provide valuable insights into developing biomarkers and strategies for treating LUAD patients using immune checkpoint inhibitors.

Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increased significantly. Neutrophil Extracellular Traps (NETs) play a crucial role in the progression of this disease and are key to the pathogenesis of NAFLD. However, research into the specific roles of NETs-related genes in NAFLD is still a field requiring thorough investigation. Utilizing techniques like AddModuleScore, ssGSEA, and WGCNA, our team conducted gene screening to identify the genes linked to NETs in both single-cell and bulk transcriptomics. Using algorithms including Random Forest, Support Vector Machine, Least Absolute Shrinkage, and Selection Operator, we identified ZFP36L2 and PHLDA1 as key hub genes. The pivotal role of these genes in NAFLD diagnosis was confirmed using the training dataset GSE164760. This study identified 116 genes linked to NETs across single-cell and bulk transcriptomic analyses. These genes demonstrated enrichment in immune and metabolic pathways. Additionally, two NETs-related hub genes, PHLDA1 and ZFP36L2, were selected through machine learning for integration into a prognostic model. These hub genes play roles in inflammatory and metabolic processes. scRNA-seq results showed variations in cellular communication among cells with different expression patterns of these key genes. In conclusion, this study explored the molecular characteristics of NETs-associated genes in NAFLD. It identified two potential biomarkers and analyzed their roles in the hepatic microenvironment. These discoveries could aid in NAFLD diagnosis and management, with the ultimate goal of enhancing patient outcomes.