X-Linked Epilepsies: A Narrative Review

X-linked epilepsies are a heterogeneous group of epileptic conditions, which often overlap with X-linked intellectual disability. To date, various X-linked genes responsible for epilepsy syndromes and/or developmental and epileptic encephalopathies have been recognized. The electro-clinical phenotype is well described for some genes in which epilepsy represents the core symptom, while less phenotypic details have been reported for other recently identified genes. In this review, we comprehensively describe the main features of both X-linked epileptic syndromes thoroughly characterized to date (PCDH19-related DEE, CDKL5-related DEE, MECP2-related disorders), forms of epilepsy related to X-linked neuronal migration disorders (e.g., ARX, DCX, FLNA) and DEEs associated with recently recognized genes (e.g., SLC9A6, SLC35A2, SYN1, ARHGEF9, ATP6AP2, IQSEC2, NEXMIF, PIGA, ALG13, FGF13, GRIA3, SMC1A). It is often difficult to suspect an X-linked mode of transmission in an epilepsy syndrome. Indeed, different models of X-linked inheritance and modifying factors, including epigenetic regulation and X-chromosome inactivation in females, may further complicate genotype-phenotype correlations. The purpose of this work is to provide an extensive and updated narrative review of X-linked epilepsies. This review could support clinicians in the genetic diagnosis and treatment of patients with epilepsy featuring X-linked inheritance.

Cambium Reactivation Is Closely Related to the Cell-Cycle Gene Configuration in Larix kaempferi

Dormancy release and reactivation in temperate trees are mainly controlled by temperature and are affected by age, but the underlying molecular mechanisms are still unclear. In this study, we explored the effects of low temperatures in winter and warm temperatures in spring on dormancy release and reactivation in Larix kaempferi. Further, we established the relationships between cell-cycle genes and cambium cell division. The results showed that chilling accelerated L. kaempferi bud break overall, and the longer the duration of chilling is, the shorter the bud break time is. After dormancy release, warm temperatures induced cell-cycle gene expression; when the configuration value of the cell-cycle genes reached 4.97, the cambium cells divided and L. kaempferi reactivated. This study helps to predict the impact of climate change on wood production and provides technical support for seedling cultivation in greenhouses.

Identification of genes and key pathways underlying the pathophysiological association between sarcopenia and chronic obstructive pulmonary disease

PURPOSE

Chronic obstructive pulmonary disease (COPD) patients are likely to develop sarcopenia, while the exact mechanism underlying the association between sarcopenia and COPD is still not clear. This cohort study aims to explore the genes, signaling pathways, and transcription factors (TFs) that are related to the molecular pathogenesis of sarcopenia and COPD.

METHODS

According to the strict inclusion criteria, two gene sets (GSE8479 for sarcopenia and GSE76925 for COPD) were obtained from the Gene Expression Omnibus (GEO) platform. Overlapping differentially expressed genes (DEGs) in sarcopenia and COPD were detected, and comprehensive bioinformatics analysis was conducted, including functional annotation, enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), construction of a protein-protein interaction (PPI) network, co-expression analysis, identification and validation of hub genes, and TFs prediction and verification.

RESULTS

In total, 118 downregulated and 92 upregulated common DEGs were detected. Functional analysis revealed that potential pathogenesis involves oxidoreductase activity and ferroptosis. Thirty hub genes were detected, and ATP metabolic process and oxidative phosphorylation were identified to be closely related to the hub genes. Validation analysis revealed that SAA1, C3, and ACSS2 were significantly upregulated, whereas ATF4, PPARGC1A, and MCTS1 were markedly downregulated in both sarcopenia and COPD. In addition, six TFs (NFKB1, RELA, IRF7, SP1, MYC, and JUN) were identified to regulate the expression of these genes, and SAA1 was found to be coregulated by NFKB1 and RELA.

CONCLUSION

This study uncovers potential common mechanisms of COPD complicated by sarcopenia. The hub gene SAA1 and the NF-κB signaling pathway could be involved, and oxidative phosphorylation and ferroptosis might be important contributors to this comorbidity.

Characterization of Common Minke Whale (Balaenoptera Acutorostrata) Cell Lines Immortalized with the Expression of Cell Cycle Regulators

Primary cultured cells cannot proliferate infinite. The overcoming of this limit can be classified as immortalization. Bypass of p16 senescence protein induces efficient immortalization various types of mammalians is previously reported. However, the Cetacea species is not known. Here, that common minke whale-derived cells can be immortalized with a combination of human genes, mutant cyclin-dependent kinase 4 (CDK4R24C ), cyclin D1, and Telomerase Reverse Transcriptase (TERT) is reported. These results indicate that the function of cell cycle regulators in premature senescence is evolutionarily conserved. This study describes the conserved roles of cell cycle regulators in the immortalization of cells from humans to Cetacea species. Furthermore, using RNA-seq based on next-generation sequencing, the gene expression profiles of immortalized cells are compared with parental cells as well as those immortalized with SV40 large T antigen, which is once a popular method for cellular immortalization. The profiling results show that newly established common minke-whale-derived immortaliozed cells have completely different profiles from SV40 cells. This result indicates that the expression of mutant CDK4, cyclin D1, and TERT enables to establish immortalized cell lines with different biological nature from SV40 expressing cells.

Integrative analysis identifies oxidative stress biomarkers in non-alcoholic fatty liver disease via machine learning and weighted gene co-expression network analysis

Background

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease globally, with the potential to progress to non-alcoholic steatohepatitis (NASH), cirrhosis, and even hepatocellular carcinoma. Given the absence of effective treatments to halt its progression, novel molecular approaches to the NAFLD diagnosis and treatment are of paramount importance.

Methods

Firstly, we downloaded oxidative stress-related genes from the GeneCards database and retrieved NAFLD-related datasets from the GEO database. Using the Limma R package and WGCNA, we identified differentially expressed genes closely associated with NAFLD. In our study, we identified 31 intersection genes by analyzing the intersection among oxidative stress-related genes, NAFLD-related genes, and genes closely associated with NAFLD as identified through Weighted Gene Co-expression Network Analysis (WGCNA). In a study of 31 intersection genes between NAFLD and Oxidative Stress (OS), we identified three hub genes using three machine learning algorithms: Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine - Recursive Feature Elimination (SVM-RFE), and RandomForest. Subsequently, a nomogram was utilized to predict the incidence of NAFLD. The CIBERSORT algorithm was employed for immune infiltration analysis, single sample Gene Set Enrichment Analysis (ssGSEA) for functional enrichment analysis, and Protein-Protein Interaction (PPI) networks to explore the relationships between the three hub genes and other intersecting genes of NAFLD and OS. The distribution of these three hub genes across six cell clusters was determined using single-cell RNA sequencing. Finally, utilizing relevant data from the Attie Lab Diabetes Database, and liver tissues from NASH mouse model, Western Blot (WB) and Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) assays were conducted, this further validated the significant roles of CDKN1B and TFAM in NAFLD.

Results

In the course of this research, we identified 31 genes with a strong association with oxidative stress in NAFLD. Subsequent machine learning analysis and external validation pinpointed two genes: CDKN1B and TFAM, as demonstrating the closest correlation to oxidative stress in NAFLD.

Conclusion

This investigation found two hub genes that hold potential as novel targets for the diagnosis and treatment of NAFLD, thereby offering innovative perspectives for its clinical management.

Single-cell combined with bulk-RNA data reveal a pattern related to angiogenesis in breast cancer patients: Individualized medicine

Angiogenesis contributes to tumor progression, aggressive behavior, and metastasis. Although several endothelial dysfunction genes (angiogenesis-related genes [ARGs]) have been identified as diagnostic biomarkers of breast cancer in a few studies, the mixed effects of ARGs have not been thoroughly investigated. The RNA sequencing data and patient survival datasets of breast cancer were obtained for further analysis. MSigDB website includes angiogenesis-related mechanisms. The consensus clustering analysis identifies 1082 breast cancer patients as three clusters. differential expression genes (DEGs) were identified by limma package. GO combined with gene set enrichment analysis (GSEA) to identify cytogenetic functions between two predefined clusters. Then Serpin Family F Member 1 (SERPINF1), angiomotin (AMOT), promyelocytic leukemia (PML), and BTG anti-proliferation factor 1 (BTG) were selected to construct prediction models using random forest survival analysis. External validation was performed using the GSE58812 triple-negative breast cancer cohort as the validation set. The median scoring system was used to discern the high- and low-risk groups, and there was a significant difference in their diagnostic results. Immunological infiltration scores were calculated using single sample gene set enrichment analysis (ssGSEA) and xCell algorithms, and consciousness scores were calculated using the R package "oncoPredict" for drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) database. In addition, the single-cell analysis of seven triple-negative breast cancers using scRNA-seq information from GSE118389 demonstrated the interpretation of SERPINF1, AMOT, PML, and BTG1. In conclusion, this investigation engineered ARG-centric disease paradigms that not only prognosticated prospective therapeutic compounds, but also projected their mechanistic trajectories, thereby facilitating the proposition of tailored treatments within diverse patient cohorts diagnosed with breast cancer.

Cell cycle gene alterations associate with a redistribution of mutation risk across chromosomal domains in human cancers

Mutations in human cells exhibit increased burden in heterochromatic, late DNA replication time (RT) chromosomal domains, with variation in mutation rates between tissues mirroring variation in heterochromatin and RT. We observed that regional mutation risk further varies between individual tumors in a manner independent of cell type, identifying three signatures of domain-scale mutagenesis in >4,000 tumor genomes. The major signature reflects remodeling of heterochromatin and of the RT program domains seen across tumors, tissues and cultured cells, and is robustly linked with higher expression of cell proliferation genes. Regional mutagenesis is associated with loss of activity of the tumor-suppressor genes RB1 and TP53, consistent with their roles in cell cycle control, with distinct mutational patterns generated by the two genes. Loss of regional heterogeneity in mutagenesis is associated with deficiencies in various DNA repair pathways. These mutation risk redistribution processes modify the mutation supply towards important genes, diverting the course of somatic evolution.

Risk model based on genes regulating the response of tumor cells to T-cell-mediated killing in esophageal squamous cell carcinoma

Immune checkpoint inhibitors (ICIs) represent a promising therapeutic approach for esophageal squamous cell carcinoma (ESCC). However, the subpopulations of ESCC patients expected to benefit from ICIs have not been clearly defined. The anti-tumor cytotoxic activity of T cells is an important pharmacological mechanism of ICIs. In this study, the prognostic value of the genes regulating tumor cells to T cell-mediated killing (referred to as GRTTKs) in ESCC was explored by using a comprehensive bioinformatics approach. Training and validation datasets were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. A prognostic risk scoring model was developed by integrating prognostic GRTTKs from TCGA and GEO datasets using a ridge regression algorithm. Patients with ESCC were divided into high- and low-risk groups based on eight GRTTKs (EIF4H, CDK2, TCEA1, SPTLC2, TMEM209, RGP1, EIF3D, and CAPZA3) to predict overall survival in the TCGA cohort. Using Kaplan-Meier curves, receiver operating characteristic curves, and C-index analysis, the high reliability of the prognostic risk-scoring model was certified. The model scores served as independent prognostic factors, and combining clinical staging with risk scoring improved the predictive value. Patients in the high-risk group exhibited abundant immune cell infiltration, including immune checkpoint expression, antigen presentation capability, immune cycle gene expression, and high tumor inflammation signature scores. The high-risk group exhibited a greater response to immunotherapy and neoadjuvant chemotherapy than the low-risk group. Drug sensitivity analysis demonstrated lower IC50 for AZD6244 and PD.0332991 in high-risk groups and lower IC50 for cisplatin, ATRA, QS11, and vinorelbine in the low-risk group. Furthermore, the differential expression of GRTTK-related signatures including CDK2, TCEA1, and TMEM209 were verified in ESCC tissues and paracancerous tissues. Overall, the novel GRTTK-based prognostic model can serve as indicators to predict the survival status and immunotherapy response of patients with ESCC, thereby providing guidance for the development of personalized treatment strategies.

TRPS1 modulates chromatin accessibility to regulate estrogen receptor alpha (ER) binding and ER target gene expression in luminal breast cancer cells

Common genetic variants in the repressive GATA-family transcription factor (TF) TRPS1 locus are associated with breast cancer risk, and luminal breast cancer cell lines are particularly sensitive to TRPS1 knockout. We introduced an inducible degron tag into the native TRPS1 locus within a luminal breast cancer cell line to identify the direct targets of TRPS1 and determine how TRPS1 mechanistically regulates gene expression. We acutely deplete over 80 percent of TRPS1 from chromatin within 30 minutes of inducing degradation. We find that TRPS1 regulates transcription of hundreds of genes, including those related to estrogen signaling. TRPS1 directly regulates chromatin structure, which causes estrogen receptor alpha (ER) to redistribute in the genome. ER redistribution leads to both repression and activation of dozens of ER target genes. Downstream from these primary effects, TRPS1 depletion represses cell cycle-related gene sets and reduces cell doubling rate. Finally, we show that high TRPS1 activity, calculated using a gene expression signature defined by primary TRPS1-regulated genes, is associated with worse breast cancer patient prognosis. Taken together, these data suggest a model in which TRPS1 modulates the genomic distribution of ER, both activating and repressing transcription of genes related to cancer cell fitness.

Coordinating single-cell and bulk RNA-seq in deciphering the intratumoral immune landscape and prognostic stratification of prostate cancer patients

INTRODUCTION

Prostate cancer is a common cancer among male population. The aberrant expression of histone modifiers has been identified as a potential driving force in numerous cancer types. However, the mechanism of histone modifiers in the development of prostate cancer remains unknown.

METHODS

Expression profiles and clinical data were obtained from GSE70769, GSE46602, and GSE67980. Seruat R package was utilized to calculate the gene set enrichment of the histone modification pathway and obtain the Histone score. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were employed to identify marker genes with prognostic value. Kaplan-Meier survival analysis was conducted to assess the efficacy of the prognostic model. In addition, microenvironment cell populations counter (MCPcounter), single-sample gene set enrichment analysis (ssGSEA), and xCell algorithms were employed for immune infiltration analysis. Drug sensitivity prediction was performed using oncoPredict R package.

RESULTS

We screened differentially expressed genes (DEGs) between Histone-high score (Histone-H) and Histone-low score (Histone-L) groups, which were enriched in RNA splicing and DNA-binding transcription factor binding pathways. We retained four prognostic marker genes, including TACC3, YWHAH, TAF1C and TTLL5. The risk model showed significant efficacy in stratification of the prognosis of prostate cancer patients in both internal and external cohorts (p < .0001 and p = .032, respectively). In addition, prognostic gene YWHAH was infiltrated in abundance of fibroblasts and highly correlated with Entinostat_1593 drug sensitivity score and the value of risk score.

CONCLUSION

We innovatively developed a histone modification-related prognostic model with high prognostic potency and identified YWHAH as possible diagnostic and therapeutic biomarkers for prostate cancer. It provides novel insights to address prostate cancer and enhance clinical outcomes, thereby opening up a new avenue for customized treatment alternatives.

An update of clinical value of circulating tumor DNA in esophageal cancer: a systematic review and meta-analysis

BACKGROUND

Esophageal cancer (EC) is a deadly disease with limited therapeutic options. Although circulating tumor DNA (ctDNA) could be a promising tool in this regard, the availiable evidence is limited. We performed a systematic review and meta-analysis to summarize the clinical applicability of the next-generation sequencing (NGS) and droplet digital polymerase chain reaction (ddPCR) technology on the ctDNA detection of the EC and listed the current challenges.

METHODS

We systematically searched MEDLINE (via PubMed), Embase (via OVID), ISI Web of Science database and Cochrane Library from January, 2000 to April, 2023. Progression-free survival (PFS) and overall survival (OS) were set as primary outcome endpoints. Pathologic response was evaluated by tumor regression grade (TRG), according to the eighth edition of the American Joint Committee on Cancer (AJCC). Major pathologic regression (MPR) was defined as TRG 1 and 2. The MPR was set as secondary endpoint. Hazard rate (HR) and associated 95% CI were used as the effect indicators the association between ctDNA and prognosis of EC. MPR rates were also calculated. Fixed-effect model (Inverse Variance) or random-effect model (Mantel-Haenszel method) was performed depending on the statistically heterogeneity.

RESULTS

Twenty-two studies, containing 1144 patients with EC, were included in this meta-analysis. The results showed that OS (HR = 3.87; 95% CI, 2.86-5.23) and PFS (HR = 4.28; 95% CI, 3.34-5.48) were shorter in ctDNA-positive patients. In the neoadjuvant therapy, the sensitivity analysis showed the clarified HR of ctDNA-positive was 1.13(95% CI, 1.01-1.28). We also found that TP53, NOTCH1, CCND1 and CNKN2A are the most frequent mutation genes.

CONCLUSIONS

Positive ctDNA is associated with poor prognosis, which demonstrated clinical value of ctDNA. Longitudinal ctDNA monitoring showed potential prognostic value in the neoadjuvant therapy. In an era of precision medicine, ctDNA could be a promising tool to individualize treatment planning and to improve outcomes in EC.

PROSPERO REGISTRATION NUMBER

CRD42023412465.

Cloning, tissue expression and imprinting status analysis of the NDN gene in Dolang sheep

BACKGROUND

Genomic imprinting refers to expressing parent-specific genes in mammalian diploid cells. The NDN gene is maternally imprinted in humans and mice and correlates with the timing of puberty. This study aimed to investigate its imprinting status and its relationship with the onset of puberty in Dolang sheep.

METHODS AND RESULTS

In this study, cloning and sequencing obtained the NDN gene cDNA sequence of 1082 bp of Dolang sheep, coding for 325 amino acids. Similarity analysis and phylogenetic tree showed that the NDN gene conformed to the law of speciation and was highly conserved among mammals. RT-qPCR results showed the highest expression of NDN mRNA was found in the hypothalamus at puberty, and the expression was significantly increased and then significantly decreased from prepuberty to postpuberty in the hypothalamus, pituitary, and ovary and oviduct. Based on expressed single nucleotide polymorphism (SNP), the NDN gene was expressed monoallelically in the tissues of adult and neonatal umbilical cords, and the expressed allele was paternally inherited. The NDN promoter region of 3400 bp was obtained by cloning and identified in monoallelic-expressing tissues (hypothalamus, ovary, spleen) as a differentially methylated region (DMR).

CONCLUSION

These findings will enrich the number of imprinted genes in sheep and suggest that the NDN gene could be a candidate gene for studying puberty initiation in Dolang sheep.

CDK16 as a potential prognostic biomarker correlated with an immunosuppressive tumor microenvironment and benefits in enhancing the effectiveness of immunotherapy in human cancers

BACKGROUND

Cyclin-Dependent Kinase 16 (CDK16) plays significant biological roles in various diseases. Nonetheless, its function in different cancer types and its relationship with the Tumor Immune Microenvironment (TIME) are still not well-understood.

METHODS

We analyzed the expression profile, genetic alterations, clinical features, and prognostic value of CDK16 in pan-cancer using data from The Cancer Genome Atlas, Genotype-Tissue Expression databases, and in vitro experiments. Additionally, the TIMER2 and ImmuCellAI databases were utilized to assess the correlation between CDK16 expression and immune cell infiltration levels. Finally, we examined the correlation between CDK16 and the response to immunotherapy using collected immunotherapy data.

RESULTS

CDK16 is notably overexpressed in pan-cancer and is a risk factor for poor prognosis in various cancers. Our findings reveal that CDK16 regulates not only cell cycle-related functions to promote cell proliferation but also the autoimmunity-related functions of the innate and adaptive immune systems, along with other immune-related signaling pathways. Moreover, CDK16 overexpression contributes to an immunosuppressive tumor microenvironment, extensively suppressing immune-related features such as the expression of immune-related genes and pathways, as well as the count of immune-infiltrating cells. Our analysis indicated that individuals with low CDK16 expression showed higher response rates to immune checkpoint inhibitors and longer overall survival compared to those with high CDK16 expression.

CONCLUSIONS

This study establishes CDK16 as a potential biomarker for predicting poor prognosis in a wide range of cancers. Its role in shaping the immunosuppressive tumor microenvironment and influencing the efficacy of immunotherapy highlights the urgent need for developing targeted therapies against CDK16, offering new avenues for cancer treatment and management.

Deciphering the Immune Microenvironment at the Forefront of Tumor Aggressiveness by Constructing a Regulatory Network with Single-Cell and Spatial Transcriptomic Data

The heterogeneity and intricate cellular architecture of complex cellular ecosystems play a crucial role in the progression and therapeutic response of cancer. Understanding the regulatory relationships of malignant cells at the invasive front of the tumor microenvironment (TME) is important to explore the heterogeneity of the TME and its role in disease progression. In this study, we inferred malignant cells at the invasion front by analyzing single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data of ER-positive (ER+) breast cancer patients. In addition, we developed a software pipeline for constructing intercellular gene regulatory networks (IGRNs), which help to reduce errors generated by single-cell communication analysis and increase the confidence of selected cell communication signals. Based on the constructed IGRN between malignant cells at the invasive front of the TME and the immune cells of ER+ breast cancer patients, we found that a high expression of the transcription factors FOXA1 and EZH2 played a key role in driving tumor progression. Meanwhile, elevated levels of their downstream target genes (ESR1 and CDKN1A) were associated with poor prognosis of breast cancer patients. This study demonstrates a bioinformatics workflow of combining scRNA-seq and ST data; in addition, the study provides the software pipelines for constructing IGRNs automatically (cIGRN). This strategy will help decipher cancer progression by revealing bidirectional signaling between invasive frontline malignant tumor cells and immune cells, and the selected signaling molecules in the regulatory network may serve as biomarkers for mechanism studies or therapeutic targets.

Establishment of the Myeloid TBX-Code Reveals Aberrant Expression of T-Box Gene TBX1 in Chronic Myeloid Leukemia

T-box genes encode transcription factors, which control developmental processes and promote cancer if deregulated. Recently, we described the lymphoid TBX-code, which collates T-box gene activities in normal lymphopoiesis, enabling identification of members deregulated in lymphoid malignancies. Here, we have extended this analysis to cover myelopoiesis, compiling the myeloid TBX-code and, thus, highlighting which of these genes might be deregulated in myeloid tumor types. We analyzed public T-box gene expression datasets bioinformatically for normal and malignant cells. Candidate T-box-gene-expressing model cell lines were identified and examined by RQ-PCR, Western Blotting, genomic profiling, and siRNA-mediated knockdown combined with RNA-seq analysis and live-cell imaging. The established myeloid TBX-code comprised 10 T-box genes, including progenitor-cell-restricted TBX1. Accordingly, we detected aberrant expression of TBX1 in 10% of stem/progenitor-cell-derived chronic myeloid leukemia (CML) patients. The classic CML cell line K-562 expressed TBX1 at high levels and served as a model to identify TBX1 activators, including transcription factor GATA1 and genomic amplification of the TBX1 locus at 22q11; inhibitors, including BCR::ABL1 fusion and downregulated GNAI2, as well as BMP, FGF2, and WNT signaling; and the target genes CDKN1A, MIR17HG, NAV1, and TMEM38A. The establishment of the myeloid TBX-code permitted identification of aberrant TBX1 expression in subsets of CML patients and cell lines. TBX1 forms an integral part of an oncogenic regulatory network impacting proliferation, survival, and differentiation. Thus, the data spotlight novel diagnostic markers and potential therapeutic targets for this malignancy.

Multifactor assessment of ovarian cancer reveals immunologically interpretable molecular subtypes with distinct prognoses

Background

Ovarian cancer (OC) is a highly heterogeneous and malignant gynecological cancer, thereby leading to poor clinical outcomes. The study aims to identify and characterize clinically relevant subtypes in OC and develop a diagnostic model that can precisely stratify OC patients, providing more diagnostic clues for OC patients to access focused therapeutic and preventative strategies.

Methods

Gene expression datasets of OC were retrieved from TCGA and GEO databases. To evaluate immune cell infiltration, the ESTIMATE algorithm was applied. A univariate Cox analysis and the two-sided log-rank test were used to screen OC risk factors. We adopted the ConsensusClusterPlus algorithm to determine OC subtypes. Enrichment analysis based on KEGG and GO was performed to determine enriched pathways of signature genes for each subtype. The machine learning algorithm, support vector machine (SVM) was used to select the feature gene and develop a diagnostic model. A ROC curve was depicted to evaluate the model performance.

Results

A total of 1,273 survival-related genes (SRGs) were firstly determined and used to clarify OC samples into different subtypes based on their different molecular pattern. SRGs were successfully stratified in OC patients into three robust subtypes, designated S-I (Immunoreactive and DNA Damage repair), S-II (Mixed), and S-III (Proliferative and Invasive). S-I had more favorable OS and DFS, whereas S-III had the worst prognosis and was enriched with OC patients at advanced stages. Meanwhile, comprehensive functional analysis highlighted differences in biological pathways: genes associated with immune function and DNA damage repair including CXCL9, CXCL10, CXCL11, APEX, APEX2, and RBX1 were enriched in S-I; S-II combined multiple gene signatures including genes associated with metabolism and transcription; and the gene signature of S-III was extensively involved in pathways reflecting malignancies, including many core kinases and transcription factors involved in cancer such as CDK6, ERBB2, JAK1, DAPK1, FOXO1, and RXRA. The SVM model showed superior diagnostic performance with AUC values of 0.922 and 0.901, respectively. Furthermore, a new dataset of the independent cohort could be automatically analyzed by this innovative pipeline and yield similar results.

Conclusion

This study exploited an innovative approach to construct previously unexplored robust subtypes significantly related to different clinical and molecular features for OC and a diagnostic model using SVM to aid in clinical diagnosis and treatment. This investigation also illustrated the importance of targeting innate immune suppression together with DNA damage in OC, offering novel insights for further experimental exploration and clinical trial.

A Machine Learning Method for Predicting Biomarkers Associated with Prostate Cancer

BACKGROUND

Prostate cancer (PCa) is a prevalent form of malignant tumors affecting the prostate gland and is frequently diagnosed in males in Western countries. Identifying diagnostic and prognostic biomarkers is not only important for screening drug targets but also for understanding their pathways and reducing the cost of experimental verification of PCa. The objective of this study was to identify and validate promising diagnostic and prognostic biomarkers for PCa.

METHODS

This study implemented a machine learning technique to evaluate the diagnostic and prognostic biomarkers of PCa using protein-protein interaction (PPI) networks. In addition, multi-database validation and literature review were performed to verify the diagnostic biomarkers. To optimize the prognosis of our results, univariate Cox regression analysis was utilized to screen survival-related genes. This study employed stepwise multivariate Cox regression analysis to develop a prognostic risk model. Finally, receiver operating characteristic analysis confirmed that these predictive biomarkers demonstrated a substantial level of sensitivity and specificity when predicting the prognostic survival of patients.

RESULTS

The hub genes were UBE2C (Ubiquitin Conjugating Enzyme E2 C), CCNB1 (Cyclin B1), TOP2A (DNA Topoisomerase II Alpha), TPX2 (TPX2 Microtubule Nucleation Factor), CENPM (Centromere Protein M), F5 (Coagulation Factor V), APOE (Apolipoprotein E), NPY (Neuropeptide Y), and TRIM36 (Tripartite Motif Containing 36). All of these hub genes were validated by multiple databases. By validation in these databases, these 10 hub genes were significantly involved in significant pathways. The risk model was constructed by a four-gene-based prognostic factor that included TOP2A, UBE2C, MYL9, and FLNA.

CONCLUSIONS

The machine learning algorithm combined with PPI networks identified hub genes that can serve as diagnostic and prognostic biomarkers for PCa. This risk model will enable patients with PCa to be more accurately diagnosed and predict new drugs in clinical trials.

Single-cell and bulk RNA sequencing analysis of B cell marker genes in TNBC TME landscape and immunotherapy

Objective

This study amied to investigate the prognostic characteristics of triple negative breast cancer (TNBC) patients by analyzing B cell marker genes based on single-cell and bulk RNA sequencing.

Methods

Utilizing single-cell sequencing data from TNBC patients, we examined tumor-associated B cell marker genes. Transcriptomic data from The Cancer Genome Atlas (TCGA) database were used as the foundation for predictive modeling. Independent validation set was conducted using the GSE58812 dataset. Immune cell infiltration into the tumor was assessed through various, including XCELL, TIMER, QUANTISEQ, CIBERSORT, CIBERSORT-ABS, and ssGSEA. The TIDE score was utilized to predict immunotherapy outcomes. Additional investigations were conducted on the immune checkpoint blockade gene, tumor mutational load, and the GSEA enrichment analysis.

Results

Our analysis encompassed 22,106 cells and 20,556 genes in cancerous tissue samples from four TNBC patients, resulting in the identification of 116 B cell marker genes. A B cell marker gene score (BCMG score) involving nine B cell marker genes (ZBP1, SEL1L3, CCND2, TNFRSF13C, HSPA6, PLPP5, CXCR4, GZMB, and CCDC50) was developed using TCGA transcriptomic data, revealing statistically significant differences in survival analysis (P<0.05). Functional analysis demonstrated that marker genes were predominantly associated with immune-related pathways. Notably, substantial differences between the higher and lower- BCMG score groups were observed in terms of immune cell infiltration, immune cell activity, tumor mutational burden, TIDE score, and the expression of immune checkpoint blockade genes.

Conclusion

This study has established a robust model based on B-cell marker genes in TNBC, which holds significant potential for predicting prognosis and response to immunotherapy in TNBC patients.

Identification of a Novel CD8+ T cell exhaustion-related gene signature for predicting survival in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a major health concern, necessitating a deeper understanding of its prognosis and underlying mechanisms. This study aimed to investigate the mechanism and prognostic value of CD8+ T Cell exhaustion (CD8+ TEX)-related genes in HCC and construct a survival prognosis prediction model for patients with HCC.

METHODS

CD8+ TEX-related genes associated with HCC prognosis were analysed and identified, and a prognostic prediction model was constructed using the 'least absolute shrinkage and selection operator' Cox regression model. Immunohistochemistry was used to verify the expression of the model genes in HCC tissues. A nomogram was constructed based on risk scores and clinical features, and its predictive efficacy was verified. The expression of STAM, ANXA5, and MAD2L2 in HCC cell lines was detected by western blotting; subsequently, these genes were knocked down in HCC cell lines by small interfering RNA, and their effects on the proliferation and migration of HCC cell lines were detected by colony formation assay, cck8, wound healing, and transwell assays.

RESULTS

Six genes related to CD8+ TEX were included in the risk-prediction model. The prognosis of patients with HCC in the low-risk group was significantly better than that of those in the high-risk group. Cox regression analysis revealed that the risk score was an independent risk factor for the prognosis of patients with HCC. The differentially expressed genes in patients with high-risk HCC were mainly enriched in the nucleotide-binding oligomerization domain-containing protein-like receptor, hypoxia-inducible factor-1, and tumour programmed cell death protein (PD)-1/PD-L1 immune checkpoint pathways. The CD8+ TEX-related genes STAM, ANXA5, and MAD2L2 were knocked down in HCC cell lines to significantly inhibit cell proliferation and migration. The prediction results of the nomogram based on the risk score showed a good fit and application value.

CONCLUSION

The prediction model based on CD8+ TEX-related genes can predict the prognosis of HCC and provide a theoretical basis for the early identification of patients with poor HCC prognosis.

The mutational pattern of homologous recombination repair genes in urothelial carcinoma and its correlation with immunotherapeutic response

BACKGROUND

The mutational pattern of homologous recombination repair (HRR)-associated gene alterations in Chinese urothelial carcinoma (UC) necessitates comprehensive sequencing efforts, and the clinical implications of HRR gene mutations in UC remain to be elucidated.

MATERIALS AND METHODS

We delineated the mutational landscape of 343 Chinese UC patients from West China Hospital and 822 patients from The Cancer Genome Atlas (TCGA) using next-generation sequencing (NGS). Data from 182 metastatic UC patients from MSK-IMPACT cohort were used to assess the association between HRR mutations and immunotherapy efficacy. Comprehensive transcriptomic analysis was performed to explore the impact of HRR mutations on tumor immune microenvironment.

RESULTS

Among Chinese UC patients, 34% harbored HRR gene mutations, with BRCA2, ATM, BRCA1, CDK12, and RAD51C being the most prevalently mutated genes. Mutational signatures contributing to UC differed between patients with and without HRR mutations. Signature 22 for exposure to aristolochic acid was only observed in Chinese UC patients. The presence of HRR mutations was correlated with higher tumor mutational burden, neoantigen burden, and PD-L1 expression. Importantly, patients with HRR mutations exhibited significantly improved prognosis following immunotherapy compared to those without HRR mutations.

CONCLUSIONS

Our findings provide valuable insights into the genomic landscape of Chinese UC patients and underscore the molecular rationale for utilizing immunotherapy in UC patients with HRR mutations.

Herba Patriniae and its component Isovitexin show anti-colorectal cancer effects by inducing apoptosis and cell-cycle arrest via p53 activation

Colorectal cancer (CRC) is the most prevalent cancer of the digestive tract. Herba Patriniae (also known as Bai Jiang Cao, HP) have been widely used to manage diarrhea, ulcerative colitis, and several cancers, including CRC. Nonetheless, the molecular mechanisms underlying the pharmacological action of HP on CRC remain unclear. This study investigated the underlying mechanisms of HP against CRC using network pharmacology analysis and in vitro and in vivo experiments. The results revealed nine bioactive compounds of HP. Furthermore, 3460 CRC-related targets of the identified active compounds were predicted from the Gene Expression Omnibus (GEO) database. Furthermore, 65 common targets were identified through the intersection of two related targets. Moreover, ten hub genes, including CDK4, CDK2, CDK1, CCND1, CCNB1, CCNA2, MYC, E2F1, CHEK1, and CDKN1A were identified through the topological analysis. Meanwhile, the GO and KEGG pathway analysis revealed that the core target genes were majorly enriched in the p53 and HIF-1 signaling pathways. Moreover, HP promoted apoptosis and suppressed cell proliferation by activating the p53 signaling pathway in a dose-dependent manner, while a similar effect was observed for Isovitexin (the primary component of HP). Overall, this study provides valuable insights into the underlying mechanisms of HP and its component Isovitexin against CRC, providing a theoretical foundation for additional experimental verification of its clinical application.

Identification and validation of functional roles for three MYC-associated genes in hepatocellular carcinoma

BACKGROUND

Aberrations in MYC underlie a large proportion of liver hepatocellular carcinoma (LIHC) cases; however, MYC is difficult to target because of its undruggable structure. We aimed to uncover MYC-associated molecular targets to provide new strategies for LIHC treatment.

METHODS

LIHC transcriptome datasets and clinical information were obtained from The Cancer Genome Atlas. A series of bioinformatics analyses were performed for 370 patients who were stratified based on the median MYC expression level (high-MYC group and low-MYC group). Correlation analysis was performed to determine relationships between the expression of key MYC-associated genes and prognosis, DNA promotor methylation, and immune cell infiltration. Gene ontology and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analyses were performed to elucidate the functions of these genes in LIHC. Their expression and functions in LIHC were further verified using transgenic mice overexpressing c-Myc under control of the hepatocyte-specific promoter (Alb-Cre).

RESULTS

AURKB, CCNB2, and CDKN3 were overexpressed in LIHC patients with high MYC expression and were associated with poor prognosis. Upregulation of these 3 genes was significantly correlated with hypomethylated promoter status, advanced T stage, metastasis, and immune cell infiltration in LIHC patients. Functional enrichment analyses indicated that these genes participate in the "p53 signaling pathway" and "cell cycle". Furthermore, RT-PCR and IHC analysis revealed that their mRNA and protein expression levels were upregulated in an Alb-Cre;cMYClsl/- mouse model. Drugs that target these 3 MYC-related genes were identified.

CONCLUSION

Taken together, our results identify biomarkers of potential utility for managing liver cancer therapy owing to their significance in tumorigenesis, proliferation, and tumor immunity.

ETV5 regulates proliferation and cell cycle genes in the INS-1 (832/13) cell line independently of the concentration of secreted insulin

The transcription factor E-twenty-six variant 5 (ETV5) regulates acute insulin secretion. Adequate insulin secretion is dependent on pancreatic β-cell size and cell proliferation, but the effects of ETV5 on proliferation, cell number, and viability, as well as its relationship with insulin secretion, have not been established yet. Here, we partially silenced ETV5 in the INS-1 (832/13) cell line by siRNA transfection and then measured secreted insulin concentration at different time points, observing similar levels to control cells. After 72 h of ETV5 silencing, we observed decreased cell number and proliferation, without any change in viability or apoptosis. Thus, partial silencing of ETV5 modulates cell proliferation in INS-1 (832/13) independently of secreted insulin levels via upregulation of E2F1 and of inhibitors of the cyclin/CDKs complexes (p21Cdkn1a , p27Cdkn1b , and p57Cdkn1c ) and downregulation of cell cycle activators (PAK3 and FOS).

Identification of autophagy-related genes in osteoarthritis articular cartilage and their roles in immune infiltration

Background

Autophagy plays a critical role in the progression of osteoarthritis (OA), mainly by regulating inflammatory and immune responses. However, the underlying mechanisms remain unclear. This study aimed to investigate the potential relevance of autophagy-related genes (ARGs) associated with infiltrating immune cells in OA.

Methods

GSE114007, GSE169077, and ARGs were obtained from the Gene Expression Omnibus (GEO) database and the Human Autophagy database. R software was used to identify the differentially expressed autophagy-related genes (DEARGs) in OA. Functional enrichment and protein-protein interaction (PPI) analyses were performed to explore the role of DEARGs in OA cartilage, and then Cytoscape was utilized to screen hub ARGs. Single-sample gene set enrichment analysis (ssGSEA) was used to conduct immune infiltration analysis and evaluate the potential correlation of key ARGs and immune cell infiltration. Then, the expression levels of hub ARGs in OA were further verified by the GSE169077 and qRT-PCR. Finally, Western blotting and immunohistochemistry were used to validate the final hub ARGs.

Results

A total of 24 downregulated genes and five upregulated genes were identified, and these genes were enriched in autophagy, mitophagy, and inflammation-related pathways. The intersection results identified nine hub genes, namely, CDKN1A, DDIT3, FOS, VEGFA, RELA, MAP1LC3B, MYC, HSPA5, and HSPA8. GSE169077 and qRT-PCR validation results showed that only four genes, CDKN1A, DDT3, MAP1LC3B, and MYC, were consistent with the bioinformatics analysis results. Western blotting and immunohistochemical (IHC) showed that the expression of these four genes was significantly downregulated in the OA group, which is consistent with the qPCR results. Immune infiltration correlation analysis indicated that DDIT3 was negatively correlated with immature dendritic cells in OA, and FOS was positively correlated with eosinophils.

Conclusion

CDKN1A, DDIT3, MAP1LC3B, and MYC were identified as ARGs that were closely associated with immune infiltration in OA cartilage. Among them, DDIT3 showed a strong negative correlation with immature dendritic cells. This study found that the interaction between ARGs and immune cell infiltration may play a crucial role in the pathogenesis of OA; however, the specific interaction mechanism needs further research to be clarified. This study provides new insights to further understand the molecular mechanisms of immunity involved in the process of OA by autophagy.

A dual role of RBM42 in modulating splicing and translation of CDKN1A/p21 during DNA damage response

p53-mediated cell cycle arrest during DNA damage is dependent on the induction of p21 protein, encoded by the CDKN1A gene. p21 inhibits cyclin-dependent kinases required for cell cycle progression to guarantee accurate repair of DNA lesions. Hence, fine-tuning of p21 levels is crucial to preserve genomic stability. Currently, the multilayered regulation of p21 levels during DNA damage is not fully understood. Herein, we identify the human RNA binding motif protein 42 (RBM42) as a regulator of p21 levels during DNA damage. Genome-wide transcriptome and interactome analysis reveals that RBM42 alters the expression of p53-regulated genes during DNA damage. Specifically, we demonstrate that RBM42 facilitates CDKN1A splicing by counteracting the splicing inhibitory effect of RBM4 protein. Unexpectedly, we also show that RBM42, underpins translation of various splicing targets, including CDKN1A. Concordantly, transcriptome-wide mapping of RBM42-RNA interactions using eCLIP further substantiates the dual function of RBM42 in regulating splicing and translation of its target genes, including CDKN1A. Collectively, our data show that RBM42 couples splicing and translation machineries to fine-tune gene expression during DNA damage response.

Loss of p53-DREAM-mediated repression of cell cycle genes as a driver of lymph node metastasis in head and neck cancer

BACKGROUND

The prognosis for patients with head and neck cancer (HNC) is poor and has improved little in recent decades, partially due to lack of therapeutic options. To identify effective therapeutic targets, we sought to identify molecular pathways that drive metastasis and HNC progression, through large-scale systematic analyses of transcriptomic data.

METHODS

We performed meta-analysis across 29 gene expression studies including 2074 primary HNC biopsies to identify genes and transcriptional pathways associated with survival and lymph node metastasis (LNM). To understand the biological roles of these genes in HNC, we identified their associated cancer pathways, as well as the cell types that express them within HNC tumor microenvironments, by integrating single-cell RNA-seq and bulk RNA-seq from sorted cell populations.

RESULTS

Patient survival-associated genes were heterogenous and included drivers of diverse tumor biological processes: these included tumor-intrinsic processes such as epithelial dedifferentiation and epithelial to mesenchymal transition, as well as tumor microenvironmental factors such as T cell-mediated immunity and cancer-associated fibroblast activity. Unexpectedly, LNM-associated genes were almost universally associated with epithelial dedifferentiation within malignant cells. Genes negatively associated with LNM consisted of regulators of squamous epithelial differentiation that are expressed within well-differentiated malignant cells, while those positively associated with LNM represented cell cycle regulators that are normally repressed by the p53-DREAM pathway. These pro-LNM genes are overexpressed in proliferating malignant cells of TP53 mutated and HPV + ve HNCs and are strongly associated with stemness, suggesting that they represent markers of pre-metastatic cancer stem-like cells. LNM-associated genes are deregulated in high-grade oral precancerous lesions, and deregulated further in primary HNCs with advancing tumor grade and deregulated further still in lymph node metastases.

CONCLUSIONS

In HNC, patient survival is affected by multiple biological processes and is strongly influenced by the tumor immune and stromal microenvironments. In contrast, LNM appears to be driven primarily by malignant cell plasticity, characterized by epithelial dedifferentiation coupled with EMT-independent proliferation and stemness. Our findings postulate that LNM is initially caused by loss of p53-DREAM-mediated repression of cell cycle genes during early tumorigenesis.

Identification of novel potential homologous repair deficiency-associated genes in pancreatic adenocarcinoma via WGCNA coexpression network analysis and machine learning

Homologous repair deficiency (HRD) impedes double-strand break repair, which is a common driver of carcinogenesis. Positive HRD status can be used as theranostic markers of response to platinum- and PARP inhibitor-based chemotherapies. Here, we aimed to fully investigate the therapeutic and prognostic potential of HRD in pancreatic adenocarcinoma (PAAD) and identify effective biomarkers related to HRD using comprehensive bioinformatics analysis. The HRD score was defined as the unweighted sum of the LOH, TAI, and LST scores, and it was obtained based on the previous literature. To characterize PAAD immune infiltration subtypes, the "ConsensusClusterPlus" package in R was used to conduct unsupervised clustering. A WGCNA was conducted to elucidate the gene coexpression modules and hub genes in the HRD-related gene module of PAAD. The functional enrichment study was performed using Metascape. LASSO analysis was performed using the "glmnet" package in R, while the random forest algorithm was realized using the "randomForest" package in R. The prognostic variables were evaluated using univariate Cox analysis. The prognostic risk model was built using the LASSO approach. ROC curve and KM survival analyses were performed to assess the prognostic potential of the risk model. The half-maximal inhibitory concentration (IC50) of the PARP inhibitors was estimated using the "pRRophetic" package in R and the Genomics of Drug Sensitivity in Cancer database. The "rms" package in R was used to create the nomogram. A high HRD score indicated a poor prognosis and an advanced clinical process in PAAD patients. PAAD tumors with high HRD levels revealed significant T helper lymphocyte depletion, upregulated levels of cancer stem cells, and increased sensitivity to rucaparib, Olaparib, and veliparib. Using WGCNA, 11 coexpression modules were obtained. The red module and 122 hub genes were identified as the most correlated with HRD in PAAD. Functional enrichment analysis revealed that the 122 hub genes were mainly concentrated in cell cycle pathways. One novel HRD-related gene signature consisting of CKS1B, HJURP, and TPX2 were screened via LASSO analysis and a random forest algorithm, and they were validated using independent validation sets. No direct association between HRD and CKS1B, HJURP, or TPX2 has not been reported in the literature so far. Thus, these findings indicated that CKS1B, HJURP, and TPX2 have potential as diagnostic and prognostic biomarkers for PAAD. We constructed a novel HRD-related prognostic model that provides new insights into PAAD prognosis and immunotherapy. Based on bioinformatics analysis, we comprehensively explored the therapeutic and prognostic potential of HRD in PAAD. One novel HRD-related gene signature consisting of CKS1B, HJURP, and TPX2 were identified through the combination of WGCNA, LASSO analysis and a random forest algorithm. A novel HRD-related risk model that can predict clinical prognosis and immunotherapeutic response in PAAD patients was constructed.

The Cyclin-dependent kinase 1: more than a cell cycle regulator

The Cyclin-dependent kinase 1, as a serine/threonine protein kinase, is more than a cell cycle regulator as it was originally identified. During the last decade, it has been shown to carry out versatile functions during the last decade. From cell cycle control to gene expression regulation and apoptosis, CDK1 is intimately involved in many cellular events that are vital for cell survival. Here, we provide a comprehensive catalogue of the CDK1 upstream regulators and substrates, describing how this kinase is implicated in the control of key 'cell cycle-unrelated' biological processes. Finally, we describe how deregulation of CDK1 expression and activation has been closely associated with cancer progression and drug resistance.

Estrogen-related genes for thyroid cancer prognosis, immune infiltration, staging, and drug sensitivity

BACKGROUND

Thyroid cancer (THCA) has become increasingly common in recent decades, and women are three to four times more likely to develop it than men. Evidence shows that estrogen has a significant impact on THCA proliferation and growth. Nevertheless, the effects of estrogen-related genes (ERGs) on THCA stages, immunological infiltration, and treatment susceptibility have not been well explored.

METHODS

Clinicopathological and transcriptome data of patients with THCA from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were cleaned before consensus clustering. Differential expression analysis was performed on the genes expressed between THCA and paraneoplastic tissues in TCGA, and Wayne analysis was performed on the ERGs obtained from the Gene Set Enrichment Analysis MsigDB and differentially expressed genes (DEGs). Univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were used to identify the set of estrogen-related differentially expressed genes (ERDEGs) associated with progression-free intervals (PFI) and to establish a prediction model. Receiver operating characteristic curves were plotted to calculate the risk scores and PFI status to validate the predictive effect of the model. Enrichment analyses and immune infiltration analyses were performed to analyze DEGs between the high- and low-risk groups, and a nomogram plot was used in the risk model to predict the PFI of THCA.

RESULTS

The expression of 120 ERDEGs differed significantly between the two groups (P < 0.05). Five (CD24, CAV1, TACC1, TIPARP, and HSD17B10) of the eight ERDEGs identified using univariate Cox and LASSO regression were validated via RT-qPCR and immunohistochemistry analysis of clinical tissue samples and were used for clinical staging and drug sensitivity analysis. Risk-DEGs were shown to be associated with immune modulation and tumor immune evasion, as well as defense systems, signal transduction, the tumor microenvironment, and immunoregulation. In 19 of the 28 immune cells, infiltration levels differed between the high- and low-risk groups. High-risk patients in the immunotherapy dataset had considerably shorter survival times than low-risk patients.

CONCLUSION

We identified and confirmed eight ERDEGs using a systematic analysis and screened sensitive drugs for ERDEGs. These results provide molecular evidence for the involvement of ERGs in controlling the immunological microenvironment and treatment response in THCA.

FGF12 regulates cell cycle gene expression and promotes follicular granulosa cell proliferation through ERK phosphorylation in geese

The granulosa cells play an important role in the fate of follicular development or atresia in poultry. Fibroblast growth factor 12 (FGF12) is downregulated in atretic follicles and may be involved in regulating granulosa cell survival in previous studies, but its molecular mechanism remains unclear. In this study, FGF12 overexpression and knockdown models of goose granulosa cells were constructed to investigate its function. The downstream expression of the cell cycle pathway was analyzed by qPCR. Granulosa cell proliferative activity and apoptosis were detected by CCK8 and TUNEL. Protein phosphorylation levels of ERK and AKT were measured using Western blotting to analyze the key pathway of FGF12 regulation of granulosa cell proliferation. ERK protein phosphorylation inhibitor was added for further verification. After overexpression of FGF12, cell proliferation activity was increased, the expressions of cell cycle pathway genes CCND1, CCNA2, MAD2, and CHK1 were upregulated, the apoptosis of granulosa cell was decreased, and Caspase 3 gene and protein expression were downregulated. After the knockdown of FGF12, cell proliferation activity decreased, the expression of downstream genes in the cell cycle pathway was downregulated, the apoptosis of granulosa cells was increased, and the Bcl-2 gene and protein were downregulated. Overexpression of FGF12 promoted the synthesis of P4 and upregulates the expression of the STAR gene. Overexpression of FGF12 promoted ERK protein phosphorylation but did not affect AKT phosphorylation. The addition of ERK phosphorylation inhibitors resulted in the elimination of the increase in cell proliferative activity caused by FGF12 overexpression. In conclusion, FGF12 could promote proliferation and inhibit apoptosis of goose granulosa cells by increasing ERK phosphorylation.

Genome Doubling Shapes High-Grade Transformation and Novel EWSR1::LARP4 Fusion Shows SOX10 Immunostaining in Hyalinizing Clear Cell Carcinoma of Salivary Gland

Hyalinizing clear cell carcinoma (HCCC) is a rare indolent malignant tumor of minor salivary gland origin with EWSR1::ATF1 rearrangement. Pathologically, the tumor cells possess a clear cytoplasm in a background of hyalinized stroma. Generally, the tumor cells are positive for p63 and p40 and negative for s100 and α-smooth muscle actin, suggesting that they differentiate into squamous epithelium and not into myoepithelium. In this study, we performed a detailed histopathological and genomic analysis of 6 cases of HCCC, including 2 atypical subtypes-a case of "high-grade transformation" and 1 "possessing a novel partner gene for EWSR1." We performed a sequential analysis of the primary and recurrent tumor by whole-exome sequencing, RNA sequencing, Sanger sequencing, and fluorescence in situ hybridization to investigate the effect of genomic changes on histopathology and clinical prognosis. A fusion gene involving the EWSR1 gene was detected in all cases. Five cases, including the "high-grade transformation," harbored a known EWSR1::ATF1 fusion gene; however, 1 case harbored a novel EWSR1::LARP4 fusion gene. This novel EWSR1::LARP4-fused HCCC has a SOX10-positive staining, which is different from the EWSR1::ATF1-fused HCCC. According to whole-exome sequencing and fluorescence in situ hybridization analysis, the "whole-genome doubling" and focal deletion involving CDKN2A, CDKN2B, and PTEN were detected in HCCC with "high-grade transformation." Conclusively, we identified a novel partner gene for EWSR1, LARP4, in indolent HCCC. Importantly, "high-grade transformation" and poor prognosis were caused by whole-genome doubling and subsequent genomic aberrations.

Identification and verification of microtubule associated genes in lung adenocarcinoma

Associated with high morbidity and mortality, lung adenocarcinoma (LUAD) is lacking in effective prognostic prediction and treatment. As chemotherapy drugs commonly used in clinics, microtubule-targeting agents (MTAs) are limited by high toxicity and drug resistance. This research aimed to analyze the expression profile of microtubule-associated genes (MAGs) in LUAD and explore their therapy efficiency and impact on prognosis. Key MAGs were identified as novel molecular targets for targeting microtubules. The LUAD project in The Cancer Genome Atlas (TCGA) database was used to identify differently expressed MAGs. On the one hand, a microtubule-related prognostic signature was constructed and validated, and its links with clinical characteristics and the immune microenvironment were analyzed. On the other hand, hub MAGs were obtained by a protein-protein interaction (PPI) network. Following the expression of hub MAGs, patients with LUAD were classified into two molecular subtypes. A comparison was made of the differences in half-maximal drug inhibitory concentration (IC50) and tumor mutational burden (TMB) between groups. In addition, the influence of MAGs on the anticancer efficacy of different therapies was explored. MAGs, which were included in both the prognosis signature and hub genes, were considered to have great value in prognosis and targeted therapy. They were identified by quantitative real-time polymerase chain reaction (qRT-PCR). A total of 154 differently expressed MAGs were discovered. For one thing, a microtubule-related prognostic signature based on 14 MAGs was created and identified in an external validation cohort. The prognostic signature was used as an independent prognostic factor. For another, 45 hub MAGs were obtained. In accordance with the expression profile of 45 MAGs, patients with LUAD were divided into two subtypes. Distinct differences were observed in TMB and IC50 values of popular chemotherapy and targeted drugs between subtypes. Finally, five genes were included in both the prognosis signature and hub genes, and identified by qRT-PCR. A microtubule-related prognosis signature that can serve as an independent prognostic factor was constructed. Microtubule subtype influenced the efficacy of different treatments and could be used to guide therapy selection. In this research, five key MAGs, including MYB proto-oncogene like 2 (MYBL2), nucleolar and spindle-associated protein 1 (NUSAP1), kinesin family member 4A (KIF4A), KIF15 and KIF20A, were verified and identified. They are promising biomarkers and therapeutic targets in LUAD.

FLII Modulates the Myogenic Differentiation of Progenitor Cells via Actin Remodeling-Mediated YAP1 Regulation

The dynamic rearrangement of the actin cytoskeleton plays an essential role in myogenesis, which is regulated by diverse mechanisms, such as mechanotransduction, modulation of the Hippo signaling pathway, control of cell proliferation, and the influence of morphological changes. Despite the recognized importance of actin-binding protein Flightless-1 (FLII) during actin remodeling, the role played by FLII in the differentiation of myogenic progenitor cells has not been explored. Here, we investigated the roles of FLII in the proliferation and differentiation of myoblasts. FLII was found to be enriched in C2C12 myoblasts, and its expression was stable during the early stages of differentiation but down-regulated in fully differentiated myotubes. Knockdown of FLII in C2C12 myoblasts resulted in filamentous actin (F-actin) accumulation and inhibited Yes-associated protein 1 (YAP1) phosphorylation, which triggers its nuclear translocation from the cytoplasm. Consequently, the expressions of YAP1 target genes, including PCNA, CCNB1, and CCND1, were induced, and the cell cycle and proliferation of myoblasts were promoted. Moreover, FLII knockdown significantly inhibited the expression of myogenic regulatory factors, i.e., MyoD and MyoG, thereby impairing myoblast differentiation, fusion, and myotube formation. Thus, our findings demonstrate that FLII is crucial for the differentiation of myoblasts via modulation of the F-actin/YAP1 axis and suggest that FLII is a putative novel therapeutic target for muscle wasting.

Identification, characterization and expression profiles of E2 and E3 gene superfamilies during the development of tetrasporophytes in Gracilariopsis lemaneiformis (Rhodophyta)

E2 ubiquitin conjugating enzymes and E3 ubiquitin ligases play important roles in the growth and development of plants and animals. To date, the systematic analysis of E2 and E3 genes in Rhodophyta is limited. In this study, 14 E2 genes and 51 E3 genes were identified in Gracilariopsis lemaneiformis, an economically important red alga. E2 genes were classified into four classes according to the structure of the conserved domain, UBC. E3 genes were classified into 12 subfamilies according to individual conserved domains. A phylogenetic tree of seven algae species showed that functional differentiation of RING-type E3s was the highest, and the similarity between orthologous genes was high except in Chlamydomonas reinhardtii and Chara braunii. RNA-seq data analysis showed significant differential expression levels of E2 and E3 genes under the life stages of tetraspore formation and release, especially GlUBCN and GlAPC3. According to GO and KEGG analysis of two transcriptomes, GlUBCN and GlAPC3 were involved in ubiquitin-mediated proteolysis, and other subunits of the anaphase promoting complex or cyclosome (APC/C) and its activators GlCDC20 and GlCDH1 were also enriched into this process. The CDH1 and CDC20 in 981 were down-regulated during tetraspores formation and release, with the down-regulation of CDH1 being particularly significant; CDH1 and CDC20 in WLP-1, ZC, and WT were up-regulated during tetraspores formation and release, with CDC20 being more significantly up-regulated. Therefore, GlCDH1, rather than GlCDC20, in '981' might play the leading role in the activation of the APC/C, and GlCDC20 might play the leading role rather than GlCDH1 in strains WLP-1, ZC and wild type. The low fertility of cultivar 981 might be highly correlated with the inactivity of activators CDH1 and CDC20. This study provided a basic and comprehensive understanding of characteristic of E2 and E3 genes in Gp. lemaneiformis and set a foundation for further understanding of E2 ubiquitin conjugating enzymes and E3 ubiquitin ligase in regulating tetrasporophytes development of Gp. lemaneiformis.

Identification of co-diagnostic effect genes for aortic dissection and metabolic syndrome by multiple machine learning algorithms

Aortic dissection (AD) is a life-threatening condition in which the inner layer of the aorta tears. It has been reported that metabolic syndrome (MS) has a close linkage with aortic dissection. However, the inter-relational mechanisms between them were still unclear. This article explored the hub gene signatures and potential molecular mechanisms in AD and MS. We obtained five bulk RNA-seq datasets of AD, one single cell RNA-seq (scRNA-seq) dataset of ascending thoracic aortic aneurysm (ATAA), and one bulk RNA-seq dataset of MS from the gene expression omnibus (GEO) database. Identification of differentially expressed genes (DEGs) and key modules via weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, and machine learning algorithms (Random Forest and LASSO regression) were used to identify hub genes for diagnosing AD with MS. XGBoost further improved the diagnostic performance of the model. The receiver operating characteristic (ROC) and precision-recall (PR) curves were developed to assess the diagnostic value. Then, immune cell infiltration and metabolism-associated pathways analyses were created to investigate immune cell and metabolism-associated pathway dysregulation in AD and MS. Finally, the scRNA-seq dataset was performed to confirm the expression levels of identified hub genes. 406 common DEGs were identified between the merged AD and MS datasets. Functional enrichment analysis revealed these DEGs were enriched for applicable terms of metabolism, cellular processes, organismal systems, and human diseases. Besides, the positively related key modules of AD and MS were mainly enriched in transcription factor binding and inflammatory response. In contrast, the negatively related modules were significantly associated with adaptive immune response and regulation of nuclease activity. Through machine learning, nine genes with common diagnostic effects were found in AD and MS, including MAD2L2, IMP4, PRPF4, CHSY1, SLC20A1, SLC9A1, TIPRL, DPYD, and MAPKAPK2. In the training set, the AUC of the hub gene on RP and RR curves was 1. In the AD verification set, the AUC of the Hub gene on RP and RR curves were 0.946 and 0.955, respectively. In the MS set, the AUC of the Hub gene on RP and RR curves were 0.978 and 0.98, respectively. scRNA-seq analysis revealed that the SLC20A1 was found to be relevant in fatty acid metabolic pathways and expressed in endothelial cells. Our study revealed the common pathogenesis of AD and MS. These common pathways and hub genes might provide new ideas for further mechanism research.

Differing responses of osteogenic cell lines to β-glycerophosphate

Ascorbic acid (Asc), dexamethasone (Dex) and β-glycerophosphate (β-Gly) are commonly used to promote osteogenic behaviour by osteoblasts in vitro. According to the literature, several osteosarcoma cells lines appear to respond differently to the latter with regards to proliferation kinetics and osteogenic gene transcription. Unsurprisingly, these differences lead to contrasting data between publications that necessitate preliminary studies to confirm the phenotype of the chosen osteosarcoma cell line in the presence of Asc, Dex and β-Gly. The present study exposed Saos-2 cells to different combinations of Asc, Dex and β-Gly for 14 days and compared the response with immortalised human mesenchymal stromal/stem cells (MSCs). Cell numbers, cytotoxicity, mineralised matrix deposition and cell proliferation were analysed to assess osteoblast-like behaviour in the presence of Asc, Dex and β-Gly. Additionally, gene expression of runt-related transcription factor 2 (RUNX2); osteocalcin (OCN); alkaline phosphatase (ALP); phosphate regulating endopeptidase homolog X-linked (PHEX); marker of proliferation MKI67 and proliferating cell nuclear antigen (PCNA) was performed every two days during the 14-day cultures. It was found that proliferation of Saos-2 cells was significantly decreased by the presence of β-Gly which contrasted with hMSCs where no change was observed. Furthermore, unlike hMSCs, Saos-2 cells demonstrated an upregulated expression of late osteoblastic markers, OCN and PHEX that suggested β-Gly could affect later stages of osteogenic differentiation. In summary, it is important to consider that β-Gly significantly affects key cell processes of Saos-2 when using it as an osteoblast-like cell model.

Clinical and Genomic Characteristics of Patients with Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Metastatic Breast Cancer Following Progression on Cyclin-Dependent Kinase 4 and 6 Inhibitors

PURPOSE

We explored the clinical and genomic characteristics of hormone receptor-positive (HR+), HER2-negative (HER2-) metastatic breast cancer (MBC) after progression on cyclin-dependent kinase 4 and 6 inhibitors (CDK4 and 6i) ± endocrine therapy (ET) to understand potential resistance mechanisms that may aid in identifying treatment options.

EXPERIMENTAL DESIGN

Patients in the United States with HR+, HER2- MBC had tumor biopsies collected from a metastatic site during routine care following progression on a CDK4 and 6i ± ET (CohortPost) or prior to initiating CDK4 and 6i treatment (CohortPre) and analyzed using a targeted mutation panel and RNA-sequencing. Clinical and genomic characteristics were described.

RESULTS

The mean age at MBC diagnosis was 59 years in CohortPre (n = 133) and 56 years in CohortPost (n = 223); 14% and 45% of patients had prior chemotherapy/ET, and 35% and 26% had de novo stage IV MBC, respectively. The most common biopsy site was liver (CohortPre, 23%; CohortPost, 56%). CohortPost had significantly higher tumor mutational burden (TMB; median 3.16 vs. 1.67 Mut/Mb, P < 0.0001), ESR1 alteration frequency (mutations: 37% vs. 10%, FDR < 0.0001; fusions: 9% vs. 2%, P = 0.0176), and higher copy-number amplification of genes on chr12q15, including MDM2, FRS2, and YEATS4 versus patients in the CohortPre group. In addition, CDK4 copy-number gain on chr12q13 was significantly higher in CohortPost versus CohortPre (27% vs. 11%, P = 0.0005).

CONCLUSIONS

Distinct mechanisms potentially associated with resistance to CDK4 and 6i ± ET, including alterations in ESR1 and amplification of chr12q15 and CDK4 copy-number gain, were identified.

The Influence of Race/Ethnicity on the Transcriptomic Landscape of Uterine Fibroids

The objective of this study was to determine if the aberrant expression of select genes could form the basis for the racial disparity in fibroid characteristics. The next-generation RNA sequencing results were analyzed as fold change [leiomyomas/paired myometrium, also known as differential expression (DF)], comparing specimens from White (n = 7) and Black (n = 12) patients. The analysis indicated that 95 genes were minimally changed in tumors from White (DF ≈ 1) but were significantly altered by more than 1.5-fold (up or down) in Black patients. Twenty-one novel genes were selected for confirmation in 69 paired fibroids by qRT-PCR. Among these 21, coding of transcripts for the differential expression of FRAT2, SOX4, TNFRSF19, ACP7, GRIP1, IRS4, PLEKHG4B, PGR, COL24A1, KRT17, MMP17, SLN, CCDC177, FUT2, MYO5B, MYOG, ZNF703, CDC25A, and CDCA7 was significantly higher, while the expression of DAB2 and CAV2 was significantly lower in tumors from Black or Hispanic patients compared with tumors from White patients. Western blot analysis revealed a greater differential expression of PGR-A and total progesterone (PGR-A and PGR-B) in tumors from Black compared with tumors from White patients. Collectively, we identified a set of genes uniquely expressed in a race/ethnicity-dependent manner, which could form the underlying mechanisms for the racial disparity in fibroids and their associated symptoms.

POGZ suppresses 2C transcriptional program and retrotransposable elements

The POGZ gene has been found frequently mutated in neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) and intellectual disability (ID). We have recently shown that POGZ maintains mouse embryonic stem cells (ESCs). However, the exact mechanisms remain unclear. Here, we show that POGZ plays an important role in the maintenance of ESCs by silencing Dux and endogenous retroviruses (ERVs). POGZ maintains a silent chromatin state at Dux and ERVs by associating with and recruiting TRIM28 and SETDB1, and its loss leads to decreased levels of H3K9me3/H4K20me3, resulting in up-regulation of 2C transcripts and ESC transition to a 2C-like state. POGZ suppresses different classes of ERVs through direct (IAPEy, the intracisternal A-type particle elements) and indirect regulation (MERVL). Activation of POGZ-bound ERVs is associated with up-regulation of nearby neural disease genes such as Serpina3m. Our findings provide important insights into understanding the disease mechanism caused by POGZ dysfunction.

The anoikis-related gene signature predicts survival accurately in colon adenocarcinoma

Colon adenocarcinoma (COAD) is a serious public health problem, the third most common cancer and the second most deadly cancer in the world. About 9.4% of cancer-related deaths in 2020 were due to COAD. Anoikis is a specialized form of programmed cell death that plays an important role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance. Various bioinformatic methods, such as differential expression analysis, and functional annotation analysis, machine learning, were used in this study. RNA-sequencing and clinical data from COAD patients were obtained from the Gene expression omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Construction of a prognostic nomogram for predicting overall survival (OS) using multivariate analysis and Lasso-Cox regression. Immunohistochemistry (IHC) was our method of validating the expression of seven genes that are linked to anoikis in COAD. We identified seven anoikis-related genes as predictors of COAD survival and prognosis, and confirmed their accuracy in predicting colon adenocarcinoma prognosis by KM survival curves and ROC curves. A seven-gene risk score consisting of NAT1, CDC25C, ATP2A3, MMP3, EEF1A2, PBK, and TIMP1 showed strong prognostic value. Meanwhile, we made a nomogram to predict the survival rate of COAD patients. The immune infiltration assay showed T cells. CD4 memory. Rest and macrophages. M0 has a higher proportion in COAD, and 11 genes related to tumor immunity are important. GDSC2-based drug susceptibility analysis showed that 6 out of 198 drugs were significant in COAD. Anoikis-related genes have potential value in predicting the prognosis of COAD and provide clues for developing new therapeutic strategies for COAD. Immune infiltration and drug susceptibility results provide important clues for finding new personalized treatment options for COAD. These findings also suggest possible mechanisms that may affect prognosis. These results are the starting point for planning individualized treatment and managing patient outcomes.

BRD4 as a Therapeutic Target in Pulmonary Diseases

Bromodomain and extra-terminal domain (BET) proteins are epigenetic modulators that regulate gene transcription through interacting with acetylated lysine residues of histone proteins. BET proteins have multiple roles in regulating key cellular functions such as cell proliferation, differentiation, inflammation, oxidative and redox balance, and immune responses. As a result, BET proteins have been found to be actively involved in a broad range of human lung diseases including acute lung inflammation, asthma, pulmonary arterial hypertension, pulmonary fibrosis, and chronic obstructive pulmonary disease (COPD). Due to the identification of specific small molecular inhibitors of BET proteins, targeting BET in these lung diseases has become an area of increasing interest. Emerging evidence has demonstrated the beneficial effects of BET inhibitors in preclinical models of various human lung diseases. This is, in general, largely related to the ability of BET proteins to bind to promoters of genes that are critical for inflammation, differentiation, and beyond. By modulating these critical genes, BET proteins are integrated into the pathogenesis of disease progression. The intrinsic histone acetyltransferase activity of bromodomain-containing protein 4 (BRD4) is of particular interest, seems to act independently of its bromodomain binding activity, and has implication in some contexts. In this review, we provide a brief overview of the research on BET proteins with a focus on BRD4 in several major human lung diseases, the underlying molecular mechanisms, as well as findings of targeting BET proteins using pharmaceutical inhibitors in different lung diseases preclinically.

Identification and subsequent validation of transcriptomic signature associated with metabolic status in endometrial cancer

Aberrant metabolism has been identified as a main driver of cancer. Profiling of metabolism-related pathways in cancer furthers the understanding of tumor plasticity and identification of potential metabolic vulnerabilities. In this prospective controlled study, we established transcriptomic profiles of metabolism-related pathways in endometrial cancer (EC) using a novel method, NanoString nCounter Technology. Fifty-seven ECs and 30 normal endometrial specimens were studied using the NanoString Metabolic Panel, further validated by qRT-PCR with a very high similarity. Statistical analyses were by GraphPad PRISM and Weka software. The analysis identified 11 deregulated genes (FDR ≤ 0.05; |FC|≥ 1.5) in EC: SLC7A11; SLC7A5; RUNX1; LAMA4; COL6A3; PDK1; CCNA1; ENO1; PKM; NR2F1; and NAALAD2. Gene ontology showed direct association of these genes with 'central carbon metabolism (CCM) in cancer'. Thus, 'CCM in cancer' appears to create one of the main metabolic axes in EC. Further, transcriptomic data were functionally validated with drug repurposing on three EC cell lines, with several drug candidates suggested. These results lay the foundation for personalized therapeutic strategies in this cancer. Metabolic plasticity represents a promising diagnostic and therapeutic option in EC.

Genome-wide association study on abdomen depth, head width, hip width, and withers height in native cattle of Guilan (Bos indicus)

Native breeds in any country are a national capital, and their preservation is of great importance. Native Cattle of Guilan (NCG) is one of the few pure native breeds in Iran and the West Asia region. During the last decade, NCG population has decreased by more than 40%. This study aimed to identify significant single nucleotide polymorphisms (SNPs) and candidate genes associated with meat production traits in NCG using a genome-wide association study (GWAS). The blood and hair samples were collected from 72 NCG individuals and genotyped using the Illumina Bovine SNP50 chip. The results of the genomic scan showed that several SNPs were associated with abdominal depth, head width, hip width, and withers height in NCG. Several candidate genes were identified, including multiple epidermal growth factor-like domains 11 (MEGF11), Methionine Sulfoxide Reductase A (MSRA), chondroitin sulfate synthase 3 (CHSY3), Cyclin-Dependent Kinase 7 (CDK7), and Parkin (PRKN) genes, which are involved in muscle growth, meat tenderness, differentiation of fat cells, fat metabolism, and adipogenesis. These genes can contribute to meat quantity and quality in NCG. This study provided valuable insights into the genetics of NCG and the identification of effective genes associated with meat production traits. The results of this study could be used for the preservation and sustainable use of this breed of native cattle, as an important genetic resource in Iran.

Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers

BACKGROUND

In breast cancer, as in all cancers, genetic and epigenetic deregulations can result in out-of-context expressions of a set of normally silent tissue-specific genes. The activation of some of these genes in various cancers empowers tumours cells with new properties and drives enhanced proliferation and metastatic activity, leading to a poor survival prognosis.

RESULTS

In this work, we undertook an unprecedented systematic and unbiased analysis of out-of-context activations of a specific set of tissue-specific genes from testis, placenta and embryonic stem cells, not expressed in normal breast tissue as a source of novel prognostic biomarkers. To this end, we combined a strict machine learning framework of transcriptomic data analysis, and successfully created a new robust tool, validated in several independent datasets, which is able to identify patients with a high risk of relapse. This unbiased approach allowed us to identify a panel of five biomarkers, DNMT3B, EXO1, MCM10, CENPF and CENPE, that are robustly and significantly associated with disease-free survival prognosis in breast cancer. Based on these findings, we created a new Gene Expression Classifier (GEC) that stratifies patients. Additionally, thanks to the identified GEC, we were able to paint the specific molecular portraits of the particularly aggressive tumours, which show characteristics of male germ cells, with a particular metabolic gene signature, associated with an enrichment in pro-metastatic and pro-proliferation gene expression.

CONCLUSIONS

The GEC classifier is able to reliably identify patients with a high risk of relapse at early stages of the disease. We especially recommend to use the GEC tool for patients with the luminal-A molecular subtype of breast cancer, generally considered of a favourable disease-free survival prognosis, to detect the fraction of patients undergoing a high risk of relapse.

CEACAM1 as a molecular target in oral cancer

OBJECTIVE

The majority of oral cancer is caused by malignant transformation of squamous cells in surface of the oral mucosa. However, the relationship between CEACAM1 and oral cancer is unclear.

METHODS

GSE23558 and GSE25099 profiles were downloaded from gene expression omnibus (GEO). Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. Construction and analysis of protein-protein interaction (PPI) Network. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG), gene set enrichment analysis (GSEA), gene expression heatmap, immune infiltration analysis, comparative toxicogenomics database (CTD) were performed. TargetScan screened miRNAs that regulated central DEGs. Western blotting (WB) experiment was performed.

RESULTS

1269 DEGs were identified. According to GO analysis, they were mainly enriched in same protein binding, signal receptor binding, cell surface, epithelial cell development. KEGG analysis showed that they were mainly enriched in cancer pathways, PI3K Akt signaling pathway, TNF signaling pathway, NF kappa B signaling pathway, TGF beta signaling pathway. PPI network showed that 11 genes (CDCA8, CCNA2, MELK, KIF2C, CDC45, HMMR, TPX2, CENPF, CDK1, CEP55, CEACAM1) were obtained. Gene expression heatmap showed that CEP55 and MELK were highly expressed in oral cancer samples. CEACAM1 was lowly expressed in oral cancer samples. CEACAM1, CEP55 and MELK were involved in tumor, inflammation, necrosis, and proliferation. Western blotting (WB) showed that CEACAM1 in oral cancer samples was lower than that in normal samples, after CEACAM1 knockdown, it was lower than that in oral cancer samples.

CONCLUSION

CEACAM1 is lowly expressed in oral cancer, the lower CEACAM1, the worse prognosis.

Bta-miR-484 Targets SFRP1 and Affects Preadipocytes Proliferation, Differentiation, and Apoptosis

MicroRNAs (miRNAs) are essential regulators of numerous biological processes in animals, including adipogenesis. Despite the abundance of miRNAs associated with adipogenesis, their exact mechanisms of action remain largely unknown. Our study highlights the role of bta-miR-484 as a major regulator of adipocyte proliferation, apoptosis, and differentiation. Here, we demonstrated that the expression of bta-miR-484 initially increased during adipogenesis before decreasing. Overexpression of bta-miR-484 in adipocytes ultimately inhibited cell proliferation and differentiation, reduced the number of EdU fluorescence-stained cells, increased the number of G1 phase cells, reduced the number of G2 and S phase cells, and downregulated the expression of proliferation markers (CDK2 and PCNA) and differentiation markers (CEBPA, FABP4, and LPL). Additionally, overexpression of bta-miR-484 promoted the expression of apoptosis-related genes (Caspase 3, Caspase 9, and BAX), and increased the number of apoptotic cells observed via flow cytometry. In contrast, bta-miR-484 inhibition in adipocytes yielded opposite effects to those observed during bta-miR-484 overexpression. Moreover, luciferase reporter assays confirmed SFRP1 as a target gene of bta-miR-484, and revealed that bta-miR-484 downregulates SFRP1 mRNA expression. These findings offer compelling evidence that bta-miR-484 targets SFRP1, inhibits proliferation and differentiation, and promotes apoptosis. Therefore, these results offer novel insights into the bta-miR-484 regulation of adipocyte growth and development.

Deciphering the crosstalk of immune dysregulation between COVID-19 and idiopathic inflammatory myopathy

Background

The coronavirus disease (COVID-19) pandemic is a serious threat to public health worldwide. Growing evidence reveals that there are certain links between COVID-19 and autoimmune diseases; in particular, COVID-19 and idiopathic inflammatory myopathies (IIM) have been observed to be clinically comorbid. Hence, this study aimed to elucidate the molecular mechanisms of COVID-19 and IIM from a genomic perspective.

Methods

We obtained transcriptome data of patients with COVID-19 and IIM separately from the GEO database and identified common differentially expressed genes (DEGs) by intersection. We then performed functional enrichment, PPI, machine learning, gene expression regulatory network, and immune infiltration analyses of co-expressed genes.

Results

A total of 91 common genes were identified between COVID-19 and IIM. Functional enrichment analysis revealed that these genes were mainly involved in immune dysregulation, response to external stimuli, and MAPK signaling pathways. The MCODE algorithm recognized two densely linked clusters in the common genes, which were related to inflammatory factors and interferon signaling. Subsequently, three key genes (CDKN1A, IFI27, and STAB1) were screened using machine learning to predict the occurrence of COVID-19 related IIM. These key genes exhibited excellent diagnostic performance in both training and validation cohorts. Moreover, we created TF-gene and miRNA-gene networks to reveal the regulation of key genes. Finally, we estimated the relationship between key genes and immune cell infiltration, of which IFI27 was positively associated with M1 macrophages.

Conclusion

Our work revealed common molecular mechanisms, core genes, potential targets, and therapeutic approaches for COVID-19 and IIM from a genomic perspective. This provides new ideas for the diagnosis and treatment of COVID-19 related IIM in the future.

Potential diagnostic biomarkers: 6 cuproptosis- and ferroptosis-related genes linking immune infiltration in acute myocardial infarction

The current diagnostic biomarkers of acute myocardial infarction (AMI), troponins, lack specificity and exist as false positives in other non-cardiac diseases. Previous studies revealed that cuproptosis, ferroptosis, and immune infiltration are all involved in the development of AMI. We hypothesize that combining the analysis of cuproptosis, ferroptosis, and immune infiltration in AMI will help identify more precise diagnostic biomarkers. The results showed that a total of 19 cuproptosis- and ferroptosis-related genes (CFRGs) were differentially expressed between the healthy and AMI groups. Functional enrichment analysis showed that the differential CFRGs were mostly enriched in biological processes related to oxidative stress and the inflammatory response. The immune infiltration status analyzed by ssGSEA found elevated levels of macrophages, neutrophils, and CCR in AMI. Then, we screened 6 immune-related CFRGs (CXCL2, DDIT3, DUSP1, CDKN1A, TLR4, STAT3) to construct a nomogram for predicting AMI and validated it in the GSE109048 dataset. Moreover, we also identified 5 pivotal miRNAs and 10 candidate drugs that target the 6 feature genes. Finally, RT-qPCR analysis verified that all 6 feature genes were upregulated in both animals and patients. In conclusion, our study reveals the significance of immune-related CFRGs in AMI and provides new insights for AMI diagnosis and treatment.

High Expression of CDCA7 in the Prognosis of Glioma and Its Relationship with Ferroptosis and Immunity

CDCA7 is a copy number amplification gene that promotes tumorigenesis. However, the clinical relevance and potential mechanisms of CDCA7 in glioma are unclear. CDCA7 expression level data were obtained from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases, and the enriched genes and related signaling pathways were explored. Data on genes in CDCA7-related signaling pathways and nine marker genes of ferroptosis were retrieved and a protein-protein interaction (PPI) network analysis was performed. The correlation of CDCA7 to ferroptosis and tumor infiltration of 22 kinds of human immune cells and the association between CDCA7 and immune checkpoint molecules were analyzed. CDCA7 was significantly increased in gliomas in comparison to healthy tissues. Gene Ontology (GO) and gene set enrichment analysis (GSEA) revealed the impact of CDCA7 expression on multiple biological processes and signaling pathways. CDCA7 may affect ferroptosis by interacting with genes in the cell cycle pathway and P53 pathway. The increase in CDCA7 was positively correlated with multiple ferroptosis suppressor genes and genes involved in tumor-infiltrating immune cells and immune checkpoint molecules in glioma. CDCA7 can be a new prognostic factor for glioma, which is closely related to ferroptosis, tumor immune cell infiltration, and immune checkpoint.

Epigenetic reprogramming of cell cycle genes by ACK1 promotes breast cancer resistance to CDK4/6 inhibitor

Hormone receptor-positive, HER2-negative advanced breast cancers exhibit high sensitivity to CDK4/6 inhibitors such as palbociclib. However, most patients inevitably develop resistance, thus identification of new actionable therapeutic targets to overcome the recurrent disease is an urgent need. Immunohistochemical studies of tissue microarray revealed increased activation of non-receptor tyrosine kinase, ACK1 (also known as TNK2) in most of the breast cancer subtypes, independent of their hormone receptor status. Chromatin immunoprecipitation studies demonstrated that the nuclear target of activated ACK1, pY88-H4 epigenetic marks, were deposited at cell cycle genes, CCNB1, CCNB2 and CDC20, which in turn initiated their efficient transcription. Pharmacological inhibition of ACK1 using its inhibitor, (R)-9b dampened CCNB1, CCNB2 and CDC20 expression, caused G2/M arrest, culminating in regression of palbociclib-resistant breast tumor growth. Further, (R)-9b suppressed expression of CXCR4 receptor, which resulted in significant impairment of metastasis of breast cancer cells to lung. Overall, our pre-clinical data identifies activated ACK1 as an oncogene that epigenetically controls the cell cycle genes governing the G2/M transition in breast cancer cells. ACK1 inhibitor, (R)-9b could be a novel therapeutic option for the breast cancer patients that have developed resistance to CDK4/6 inhibitors.