CD2AP inhibits metastasis in gastric cancer by promoting cellular adhesion and cytoskeleton assembly

DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation rates

Messenger RNA splicing and degradation are critical for gene expression regulation, the abnormality of which leads to diseases. Previous methods for estimating kinetic rates have limitations, assuming uniform rates across cells. DeepKINET is a deep generative model that estimates splicing and degradation rates at single-cell resolution from scRNA-seq data. DeepKINET outperforms existing methods on simulated and metabolic labeling datasets. Applied to forebrain and breast cancer data, it identifies RNA-binding proteins responsible for kinetic rate diversity. DeepKINET also analyzes the effects of splicing factor mutations on target genes in erythroid lineage cells. DeepKINET effectively reveals cellular heterogeneity in post-transcriptional regulation.

Predictive value analysis of the interaction network of Tks4 scaffold protein in colon cancer

Background

Colorectal carcinoma (CRC) has emerged as one of the most widespread cancers and was the third leading cause of cancer-related mortality in 2020. The role of the podosomal protein Tks4 in tumor formation and progression is well established, including its involvement in gastric carcinoma and hepatocellular carcinoma; however, exploration of Tks4 and its associated EMT-regulating interactome in the context of colon cancer remains largely unexplored.

Methods

We conducted a comprehensive bioinformatic analysis to investigate the mRNA and protein expression levels of Tks4 and its associated partner molecules (CD2AP, GRB2, WASL, SRC, CTTN, and CAPZA1) across different tumor types. We quantified the expression levels of Tks4 and its partner molecules using qPCR, utilizing a TissueScan colon cancer array. We then validated the usefulness of Tks4 and its associated molecules as biomarkers via careful statistical analyses, including Pearson's correlation analysis, principal component analysis (PCA), multiple logistic regression, confusion matrix analysis, and ROC analysis.

Results

Our findings indicate that the co-expression patterns of the seven examined biomarker candidates better differentiate between tumor and normal samples compared with the expression levels of the individual genes. Moreover, variable importance analysis of these seven genes revealed four core genes that yield consistent results similar to the seven genes. Thus, these four core genes from the Tks4 interactome hold promise as potential combined biomarkers for colon adenocarcinoma diagnosis and prognosis.

Conclusion

Our proposed biomarker set from the Tks4 interactome shows promising sensitivity and specificity, aiding in colon cancer prevention and diagnosis.

Unveiling epithelial plasticity regulation in lung cancer: Exploring the cross-talk among Tks4 scaffold protein partners

The epithelial-to-mesenchymal transition (EMT) represents a hallmark event in the evolution of lung cancer. This work aims to study a recently described EMT-regulating protein, Tks4, and to explore its potential as a prognostic biomarker in non-small cell lung cancer. In this study, we used CRISPR/Cas9 method to knockout (KO) Tks4 to study its functional roles in invadopodia formation, migration, and regulation of EMT marker expressions and we identified Tks4-interacting proteins. Tks4-KO A549 cells exhibited an EMT-like phenotype characterized by elongated morphology and increased expression of EMT markers. Furthermore, analyses of a large-scale lung cancer database and a patient-derived tissue array data revealed that the Tks4 mRNA level was decreased in more aggressive lung cancer stages. To understand the regulatory role of Tks4 in lung cancer, we performed a Tks4-interactome analysis via Tks4 immunoprecipitation-mass spectrometry on five different cell lines and identified CAPZA1 as a novel Tks4 partner protein. Thus, we propose that the absence of Tks4 leads to disruption of a connectome of multiple proteins and that the resulting undocking and likely mislocalization of signaling molecules impairs actin cytoskeleton rearrangement and activates EMT-like cell fate switches, both of which likely influence disease severity.

Unraveling pathogenesis, biomarkers and potential therapeutic agents for endometriosis associated with disulfidptosis based on bioinformatics analysis, machine learning and experiment validation

BACKGROUND

Endometriosis (EMs) is an enigmatic disease of yet-unknown pathogenesis. Disulfidptosis, a novel identified form of programmed cell death resulting from disulfide stress, stands a chance of treating diverse ailments. However, the potential roles of disulfidptosis-related genes (DRGs) in EMs remain elusive. This study aims to thoroughly explore the key disulfidptosis genes involved in EMs, and probe novel diagnostic markers and candidate therapeutic compounds from the aspect of disulfidptosis based on bioinformatics analysis, machine learning, and animal experiments.

RESULTS

Enrichment analysis on key module genes and differentially expressed genes (DEGs) of eutopic and ectopic endometrial tissues in EMs suggested that EMs was closely related to disulfidptosis. And then, we obtained 20 and 16 disulfidptosis-related DEGs in eutopic and ectopic endometrial tissue, respectively. The protein-protein interaction (PPI) network revealed complex interactions between genes, and screened nine and ten hub genes in eutopic and ectopic endometrial tissue, respectively. Furthermore, immune infiltration analysis uncovered distinct differences in the immunocyte, human leukocyte antigen (HLA) gene set, and immune checkpoints in the eutopic and ectopic endometrial tissues when compared with health control. Besides, the hub genes mentioned above showed a close correlation with the immune microenvironment of EMs. Furthermore, four machine learning algorithms were applied to screen signature genes in eutopic and ectopic endometrial tissue, including the binary logistic regression (BLR), the least absolute shrinkage and selection operator (LASSO), the support vector machine-recursive feature elimination (SVM-RFE), and the extreme gradient boosting (XGBoost). Model training and hyperparameter tuning were implemented on 80% of the data using a ten-fold cross-validation method, and tested in the testing sets which determined the excellent diagnostic performance of these models by six indicators (Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value, Accuracy, and Area Under Curve). And seven eutopic signature genes (ACTB, GYS1, IQGAP1, MYH10, NUBPL, SLC7A11, TLN1) and five ectopic signature genes (CAPZB, CD2AP, MYH10, OXSM, PDLIM1) were finally identified based on machine learning. The independent validation dataset also showed high accuracy of the signature genes (IQGAP1, SLC7A11, CD2AP, MYH10, PDLIM1) in predicting EMs. Moreover, we screened 12 specific compounds for EMs based on ectopic signature genes and the pharmacological impact of tretinoin on signature genes was further verified in the ectopic lesion in the EMs murine model.

CONCLUSION

This study verified a close association between disulfidptosis and EMs based on bioinformatics analysis, machine learning, and animal experiments. Further investigation on the biological mechanism of disulfidptosis in EMs is anticipated to yield novel advancements for searching for potential diagnostic biomarkers and revolutionary therapeutic approaches in EMs.

Disulfidptosis-related signature elucidates the prognostic, immunologic, and therapeutic characteristics in ovarian cancer

Introduction

Ovarian cancer (OC) is the deadliest malignancy in gynecology, but the mechanism of its initiation and progression is poorly elucidated. Disulfidptosis is a novel discovered type of regulatory cell death. This study aimed to develop a novel disulfidptosis-related prognostic signature (DRPS) for OC and explore the effects and potential treatment by disulfidptosis-related risk stratification.

Methods

The disulfidptosis-related genes were first analyzed in bulk RNA-Seq and a prognostic nomogram was developed and validated by LASSO algorithm and multivariate cox regression. Then we systematically assessed the clinicopathological and mutational characteristics, pathway enrichment analysis, immune cell infiltration, single-cell-level expression, and drug sensitivity according to DRPS.

Results

The DRPS was established with 6 genes (MYL6, PDLIM1, ACTN4, FLNB, SLC7A11, and CD2AP) and the corresponding prognostic nomogram was constructed based on the DRPS, FIGO stage, grade, and residual disease. Stratified by the risk score derived from DRPS, patients in high-risk group tended to have worse prognosis, lower level of disulfidptosis, activated oncogenic pathways, inhibitory tumor immune microenvironment, and higher sensitivity to specific drugs including epirubicin, stauroporine, navitoclax, and tamoxifen. Single-cell transcriptomic analysis revealed the expression level of genes in the DRPS significantly varied in different cell types between tumor and normal tissues. The protein-level expression of genes in the DRPS was validated by the immunohistochemical staining analysis.

Conclusion

In this study, the DRPS and corresponding prognostic nomogram for OC were developed, which was important for OC prognostic assessment, tumor microenvironment modification, drug sensitivity prediction, and exploration of potential mechanisms in tumor development.

Research Progress of Porcine Reproductive and Respiratory Syndrome Virus NSP2 Protein

Porcine reproductive and respiratory syndrome virus (PRRSV) is globally prevalent and seriously harms the economic efficiency of pig farming. Because of its immunosuppression and high incidence of mutant recombination, PRRSV poses a great challenge for disease prevention and control. Nonstructural protein 2 (NSP2) is the most variable functional protein in the PRRSV genome and can generate NSP2N and NSP2TF variants due to programmed ribosomal frameshifts. These variants are broad and complex in function and play key roles in numerous aspects of viral protein maturation, viral particle assembly, regulation of immunity, autophagy, apoptosis, cell cycle and cell morphology. In this paper, we review the structural composition, programmed ribosomal frameshift and biological properties of NSP2 to facilitate basic research on PRRSV and to provide theoretical support for disease prevention and control and therapeutic drug development.

Studying the Association of TKS4 and CD2AP Scaffold Proteins and Their Implications in the Partial Epithelial-Mesenchymal Transition (EMT) Process

Colon cancer is a leading cause of death worldwide. Identification of new molecular factors governing the invasiveness of colon cancer holds promise in developing screening and targeted therapeutic methods. The Tyrosine Kinase Substrate with four SH3 domains (TKS4) and the CD2-associated protein (CD2AP) have previously been linked to dynamic actin assembly related processes and cancer cell migration, although their co-instructive role during tumor formation remained unknown. Therefore, this study was designed to investigate the TKS4-CD2AP interaction and study the interdependent effect of TKS4/CD2AP on oncogenic events. We identified CD2AP as a novel TKS4 interacting partner via co-immunoprecipitation-mass spectrometry methods. The interaction was validated via Western blot (WB), immunocytochemistry (ICC) and proximity ligation assay (PLA). The binding motif of CD2AP was explored via peptide microarray. To uncover the possible cooperative effects of TKS4 and CD2AP in cell movement and in epithelial-mesenchymal transition (EMT), we performed gene silencing and overexpressing experiments. Our results showed that TKS4 and CD2AP form a scaffolding protein complex and that they can regulate migration and EMT-related pathways in HCT116 colon cancer cells. This is the first study demonstrating the TKS4-CD2AP protein-protein interaction in vitro, their co-localization in intact cells, and their potential interdependent effects on partial-EMT in colon cancer.

A novel extrachromosomal circular DNA related genes signature for overall survival prediction in patients with ovarian cancer

OBJECTIVE

Ovarian cancer (OV) has a high mortality rate all over the world, and extrachromosomal circular DNA (eccDNA) plays a key role in carcinogenesis. We wish to study more about the molecular structure of eccDNA in the UACC-1598-4 cell line and how its genes are associated with ovarian cancer prognosis.

METHODS

We sequenced and annotated the eccDNA by Circle_seq of the OV cell line UACC-1598-4. To acquire the amplified genes of OV on eccDNA, the annotated eccDNA genes were intersected with the overexpression genes of OV in TCGA. Univariate Cox regression was used to find the genes on eccDNA that were linked to OV prognosis. The least absolute shrinkage and selection operator (LASSO) and cox regression models were used to create the OV prognostic model, as well as the receiver operating characteristic curve (ROC) curve and nomogram of the prediction model. By applying the median value of the risk score, the samples were separated into high-risk and low-risk groups, and the differences in immune infiltration between the two groups were examined using ssGSEA.

RESULTS

EccDNA in UACC-1598-4 has a length of 0-2000 bp, and some of them include the whole genes or gene fragments. These eccDNA originated from various parts of chromosomes, especially enriched in repeatmasker, introns, and coding regions. They were annotated with 2188 genes by Circle_seq. Notably, the TCGA database revealed that a total of 198 of these eccDNA genes were overexpressed in OV (p < 0.05). They were mostly enriched in pathways associated with cell adhesion, ECM receptors, and actin cytoskeleton. Univariate Cox analysis showed 13 genes associated with OV prognosis. LASSO and Cox regression analysis were used to create a risk model based on remained 9 genes. In both the training (TCGA database) and validation (International Cancer Genome Consortium, ICGC) cohorts, a 9-gene signature could successfully discriminate high-risk individuals (all p < 0.01). Immune infiltration differed significantly between the high-risk and low-risk groups. The model's area under the ROC curve was 0.67, and a nomograph was created to assist clinician.

CONCLUSION

EccDNA is found in UACC-1598-4, and part of its genes linked to OV prognosis. Patients with OV may be efficiently evaluated using a prognostic model based on eccDNA genes, including SLC7A1, NTN1, ADORA1, PADI2, SULT2B1, LINC00665, CILP2, EFNA5, TOMM.

Identification and validation of a signature based on macrophage cell marker genes to predict recurrent miscarriage by integrated analysis of single-cell and bulk RNA-sequencing

Recurrent miscarriage (RM) is a chronic, heterogeneous autoimmune disease that has serious social and personal consequences. No valid and reliable diagnostic markers or therapeutic targets for RM have been identified. Macrophages impact the innate immune system and can be used as diagnostic and prognostic markers for many diseases. We first collected 16 decidua and villi tissue samples from 5 normal patients and 3 RM patients for single-cell RNA sequencing data analysis and identified 1293 macrophage marker genes. We then screened a recurrent miscarriage cohort (GSE165004) for 186 macrophage-associated marker genes that were significantly differentially expressed between RM patients and the normal pregnancy endometrial tissues, and performed a functional enrichment analysis of differentially expressed genes. We then identified seven core genes (ACTR2, CD2AP, MBNL2, NCSTN, PUM1, RPN2, and TBC1D12) from the above differentially expressed gene group that are closely related to RM using the LASSO, Random Forest and SVM-RFE algorithms. We also used GSE26787 and our own collection of clinical specimens to further evaluate the diagnostic value of the target genes. A nomogram was constructed of the expression levels of these seven target genes to predict RM, and the ROC and calibration curves showed that our nomogram had a high diagnostic value for RM. These results suggest that ACTR2 and NCSTN may be potential targets for preventative RM treatments.

Pan-cancer analysis reveals the relationship between RCSD1 immune infiltration and clinical prognosis in human tumors

Background

RCSD1 is a cytoskeletal regulator that has been confirmed to undergo genetic mutations in hematological tumors, but the mechanisms of RCSD1 in pan-cancer and its impact on patient prognosis have not been studied.

Methods

Using TCGA, GEPIA, UALCAN, Kaplan-Meier plotters, Linkedomics, String, cBioPortal, TISIDB, TCIA and TIMER database methods, we investigated the expression of RCSD1 in human tumors and its relationship to clinical prognosis, functional analysis of co-expression networks, mutation status, and immune infiltration in cancers, especially lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC).

Results

The expression of RCSD1 is low in most tumors compared with normal tissues, and its high expression is associated with good patient survival. The RCSD1 co-expression network is mainly involved in the regulation of immune response. In human cancer, RCSD1 plays an important role in the tumor microenvironment (TME) and is significantly associated with the expression of immune infiltrating cells (TIL) in lung cancer.

Conclusions

As a prognostic biomarker of generalized cancer, RCSD1 is associated with immune infiltration.

Circular RNA VMA21 ameliorates lung injury in septic rat via targeting microRNA-497-5p/CD2-associated protein axis

Sepsis was characterized via an acute inflammatory response to infection, often accompanying by multiple organ failure, particularly lung damage. Circular RNA (circRNA) played an important role in the pathology of a variety of diseases. However, the role of circRNA in sepsis-induced lung injury (LI) remained unknown. This study was to explore the expression and role of circVMA21 in sepsis LI and the possible molecular mechanism. The results manifested circVMA21 and CD2-associated protein (CD2AP) were down-regulated in lung tissue and lipopolysaccharide (LPS)-treated BEAS-2B, while microRNA (miR)-497-5p was up-regulated. A large number of deaths in rats after surgery of 72 h were caused via cecal ligation-perforation surgery, W/D value and Bax positive cells were increased, LI was caused, cell apoptosis, tumor necrosis factor-α, Interleukin (IL)-1β and IL-6 expression were promoted and Bcl-2 positive cells were decreased. Overexpression of circVMA21 ameliorated these phenomena. In addition, LPS-induced apoptosis and inflammation of BEAS-2B cells was improved via overexpression of circVMA21, while overexpression of miR-497-5P was opposite. Apoptosis, inflammation, and oxidative damage of BEAS-2B cells were aggravated via knockdown of circVMA21, but it was reversed by knockdown of miR-497-5p or overexpression of CD2AP. Mechanistically, CircVMA21 mediated CD2AP expression through competitive adsorption of miR-497-5p. In conclusion, this work showed circVMA21 improved LI in sepsis rats by targeting miR-497-5p/CD2AP axis, suggesting that circVMA21 may be a novel therapeutic target for sepsis-induced LI.

Betulonic Acid, as One of the Active Components of the Celastrus orbiculatus Extract, Inhibits the Invasion and Metastasis of Gastric Cancer Cells by Mediating Cytoskeleton Rearrangement In Vitro

Gastric cancer is a type of malignant tumor that seriously threatens human life and health. Invasion and metastasis present difficulties in the treatment of gastric cancer, and the remodeling of the tumor cytoskeleton plays an important role in mediating the ability of tumor cells to achieve invasion and metastasis. Previous experimental results suggest that Celastrus orbiculatus extract can regulate cytoskeletal remodeling in gastric cancer, but the active component has not been determined. Betulonic acid, as an effective component of COE, inhibits the invasion and metastasis of gastric cancer cells by regulating cytoskeletal remodeling in vitro; its specific mechanisms have been studied here. After betulonic acid was dissolved, it was diluted to various working concentrations in RPMI-1640 medium and added to AGS, HGC-27 and GES-1 cell lines. Cell viability was assessed by CCK-8 and colony formation assays. Cytoskeleton staining was used to detect changes in cytoskeleton morphology. Functional assays including wound healing assays and transwell assays were used to detect the invasion and migration of cells. The effect of betulonic acid on cell invasion and migration was clearly and precisely observed by high-content imaging technology. Western blotting was used to detect the regulation of matrix metalloproteinase-related proteins and epithelial–mesenchymal transformation-related proteins. We found that betulonic acid inhibited the migration and invasion of gastric cancer cells. Therefore, betulonic acid inhibits the invasion and metastasis of gastric cancer cells by mediating cytoskeletal remodeling and regulating epithelial mesenchymal transformation.

The landscape of alternative splicing reveals novel events associated with tumorigenesis and the immune microenvironment in gastric cancer

Alternative splicing (AS), contributing to vast protein diversity from a rather limited number of genes in eukaryotic transcripts, has emerged as an important signature for tumor initiation and progression. However, a systematic understanding of its functional impact and relevance to gastric cancer (GC) tumorigenesis is lacking. Differentially expressed AS (DEAS) was verified among GC-associated AS events based on RNA-seq profiles from the TCGA database. Functional enrichment analysis, unsupervised clustering analysis and prognostic models were used to infer the potential roles of DEAS events and their molecular, clinical and immune features. In total, 12,225 AS events were detected from 5,199 genes, among which 314 AS events were identified as DEAS events in GC. The parental genes of the DEAS events were significantly enriched in the regulation of GC-related processes. The splicing correlation network suggested a significant relationship between DEAS events and splicing factors (SFs). Three clusters of DEAS events were identified to be different in prognosis, cancer-specific signatures and immune features between distinct clusters. Univariate and multivariate analyses regarded 3 DEAS events as independent prognostic indicators. Profiling of the AS landscape in GC elucidated the functional roles of the splicing network in GC and might serve as a novel prognostic indicator and therapeutic target.

CD2AP inhibits metastasis in gastric cancer by promoting cellular adhesion and cytoskeleton assembly

Diffuse gastric cancer (DGC) is a lethal malignancy lacking effective systemic therapy. Among the most provocative recent results in DGC has been that the alter of the cellular cytoskeleton and intercellular adhesion. CD2‐associated protein (CD2AP) is one of the critical proteins regulating cytoskeleton assembly and intercellular adhesion. However, no study has investigated the expression and biological significance of CD2AP in gastric cancer (GC) to date. Therefore, the aim of our study was to explore if the expression of CD2AP is associated with any clinical features of GC and to elucidate the underlying mechanism. Immunohistochemistry of 620 patient tissue samples indicated that the expression of CD2AP is downregulated in DGC. Moreover, a low CD2AP level was indicative of poor patient prognosis. In vitro, forced expression of CD2AP caused a significant decrease in the migration and invasion of GC cells, whereas depletion of CD2AP had the opposite effect. Immunofluorescence analysis indicated that CD2AP promoted cellular adhesion and influenced cell cytoskeleton assembly via interaction with the F‐actin capping protein CAPZA1. Overall, the upregulation of CD2AP could attenuate GC metastasis, suggesting CD2AP as a novel biomarker for the prognosis and treatment of patients with GC.