Complex roles of the actin-binding protein Girdin/GIV in DNA damage-induced apoptosis of cancer cells

GIV/Girdin Modulation of Microglial Activation in Ischemic Stroke: Impact of FTO-Mediated m6A Modification

Ischemic stroke (IS) is one of the most common causes of death in the world. The lack of effective pharmacological treatments for IS was primarily due to a lack of understanding of its pathogenesis. Gα-Interacting vesicle-associated protein (GIV/Girdin) is a multi-modular signal transducer and guanine nucleotide exchange factor that controls important signaling downstream of multiple receptors. The purpose of this study was to investigate the role of GIV in IS. In the present study, we found that GIV is highly expressed in the central nervous system (CNS). GIV protein level was decreased, while GIV transcript level was increased in the middle cerebral artery occlusion reperfusion (MCAO/R) mice model. Additionally, GIV was insensitive lipopolysaccharide (LPS) exposure. Interestingly, we found that GIV overexpression dramatically restrained microglial activation, inflammatory response, and M1 polarization in BV-2 microglia induced by oxygen-glucose deprivation and reoxygenation (OGD/R). On the contrary, GIV knockdown had the opposite impact. Mechanistically, we found that GIV activated the Wnt/β-catenin signaling pathway by interacting with DVL2 (disheveled segment polarity protein 2). Notably, m6A demethylase fat mass and obesity-associated protein (FTO) decreased the N6-methyladenosine (m6A) modification-mediated increase of GIV expression and attenuated the inflammatory response in BV-2 stimulated by OGD/R. Taken together, our results demonstrate that GIV inhibited the inflammatory response via activating the Wnt/β-catenin signaling pathway which expression regulated in an FTO-mediated m6A modification in IS. These results broaden our understanding of the role of the FTO-GIV axis in IS development.

An orchestra of machine learning methods reveals landmarks in single-cell data exemplified with aging fibroblasts

In this work, a Python framework for characteristic feature extraction is developed and applied to gene expression data of human fibroblasts. Unlabeled feature selection objectively determines groups and minimal gene sets separating groups. ML explainability methods transform the features correlating with phenotypic differences into causal reasoning, supported by further pipeline and visualization tools, allowing user knowledge to boost causal reasoning. The purpose of the framework is to identify characteristic features that are causally related to phenotypic differences of single cells. The pipeline consists of several data science methods enriched with purposeful visualization of the intermediate results in order to check them systematically and infuse the domain knowledge about the investigated process. A specific focus is to extract a small but meaningful set of genes to facilitate causal reasoning for the phenotypic differences. One application could be drug target identification. For this purpose, the framework follows different steps: feature reduction (PFA), low dimensional embedding (UMAP), clustering ((H)DBSCAN), feature correlation (chi-square, mutual information), ML validation and explainability (SHAP, tree explainer). The pipeline is validated by identifying and correctly separating signature genes associated with aging in fibroblasts from single-cell gene expression measurements: PLK3, polo-like protein kinase 3; CCDC88A, Coiled-Coil Domain Containing 88A; STAT3, signal transducer and activator of transcription-3; ZNF7, Zinc Finger Protein 7; SLC24A2, solute carrier family 24 member 2 and lncRNA RP11-372K14.2. The code for the preprocessing step can be found in the GitHub repository https://github.com/AC-PHD/NoLabelPFA, along with the characteristic feature extraction https://github.com/LauritzR/characteristic-feature-extraction.

An unusual signal transducer GIV/Girdin engages in the roles of adipocyte-derived hormone leptin in liver fibrosis

Obese patients usually have hyperleptinemia and are prone to develop liver fibrosis. Leptin is intimately linked to liver fibrogenesis, a multi-receptor-driven disease. Gα-Interacting Vesicle-associated protein (GIV) functions as a multimodular signal transducer and a guanine nucleotide exchange factor for Gi controling key signalings downstream of diverse receptors. This study aimed to examine the roles of GIV in leptin-caused liver fibrosis and employed the culture-activated hepatic stellate cells (HSCs) and leptin-deficient mice, respectively. Results indicated that leptin upregulated GIV expression in HSCs. GIV was involved in leptin-induced HSC activation and liver fibrosis. GIV mediated leptin regulation of TIMP1, MMP9, PDGFβ receptor and TGFβ receptor and was required for leptin stimulating the pathways of Erk1/2, Akt1, and Smad3. GIV was also a mediator for leptin-regulation of Cyclin D1 and Caspase-3 activity but GIV reduced Caspase-3 level independently of leptin in vivo. Erk1/2 signaling, Egr1 and c-Jun were associated with the effect of leptin on GIV expression in HSCs. Leptin-induced Erk1/2 signaling increased Egr1 and p-c-Jun levels and promoted their binding to GIV promoter at the sites between -190 bp and -180 bp and between -382 bp and - 376 bp, respectively. Egr1 knockdown lessened leptin-upregulation of GIV in vitro and in vivo. In human cirrhotic livers, the increase in GIV protein level parallelled with the elevated p-Erk1/2 and Egr1 levels in HSCs. In summary, the unusual signal transducer GIV was identified as an important mediator in leptin-induced liver fibrosis. GIV may have significant implications in liver fibrosis progression of obese patients with hyperleptinaemia.

The sialyl-Tn antigen synthase genes regulates migration-proliferation dichotomy in prostate cancer cells under hypoxia

A low-oxygen (hypoxia) tumor microenvironment can facilitate chemotherapy and radiation therapy resistance in tumors and is associated with a poor prognosis. Hypoxia also affects PCa (prostate cancer) phenotype transformation and causes therapeutic resistance. Although O-glycans are known to be involved in the malignancy of various cancers under hypoxia, the expression and function of O-glycans in PCa are not well understood. In this study, the saccharide primer method was employed to analyze O-glycan expression in PCa cells. Results showed that the expression of sTn antigens was increased in PCa cells under hypoxia. Furthermore, it was found that ST6GalNAc1, the sTn antigen synthase gene, was involved in the migration-proliferation dichotomy and drug resistance in PCa cells under hypoxia. The results of this study will contribute to the development of novel diagnostic markers and drug targets for PCa under hypoxia.

Girdin acts as an oncogene in gastric cancer by regulating AKT/GSK3β/β-catenin signaling

ThE present work focused on exploring Girdin expression within gastric cancer (GC), examining the effect of Girdin on the cell phenotype of GC, and clarifying the underlying mechanisms. Girdin expression in GC samples was identified by immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR) assays. Girdin-targeting siRNAs were transfected into GC cells; later, we examined GC cell proliferation, migration, invasion, and apoptosis, respectively. Additionally, the protein expression was examined through Western blotting assay. Moreover, the tumor implantation experiment was conducted for examining Girdin knockdown in vivo. The results showed that Girdin expression elevated within GC samples, which was associated with the dismal prognostic outcome. Girdin knockdown suppressed GC cell proliferation, migration, and invasion, and enhanced apoptosis and cell cycle arrest. Girdin promoted the phosphorylation of AKT, GSK3β, and β-catenin. Moreover, Girdin inhibited the phosphorylation of β-catenin. Girdin suppressed cell apoptosis and stimulated cell migration and invasion, while AKT inhibitor (MK2206) treatment reversed the effect of Girdin overexpression, and GSK3β inhibitor (CHIR99021) treatment enhanced the effect of Girdin overexpression on GC cells. Besides, Girdin delayed tumor growth in vivo. In conclusion, Girdin was abnormally expressed in GC samples, which promoted the development of GC by regulating AKT/GSK3β/β-catenin signaling.

CRISPR/Cas9 as precision and high-throughput genetic engineering tools in gastrointestinal cancer research and therapy

Gastrointestinal cancer (GI) is one of the most serious and health-threatening diseases worldwide. Many countries have encountered an escalating prevalence of shock. Therefore, there is a pressing need to clarify the molecular pathogenesis of these cancers. The use of high-throughput technologies that allow the precise and simultaneous investigation of thousands of genes, proteins, and metabolites is a critical step in disease diagnosis and cure. Recent innovations have provided easy and reliable methods for genome investigation, including TALENs, ZFNs, and the CRISPR/Cas9 (clustered regularly interspaced palindromic repeats system). Among these, CRISPR/Cas9 has been revolutionary tool in genetic research. Recent years were prosperous years for CRISPR by the discovery of novel Cas enzymes, the Nobel Prize, and the development of critical clinical trials. This technology utilizes comprehensive information on genes associated with tumor development, provides high-throughput libraries for tumor therapy by developing screening platforms, and generates rapid tools for cancer therapy. This review discusses the various applications of CRISPR/Cas9 in genome editing, with a particular focus on genome manipulation, including infection-related genes, RNAi targets, pooled library screening for identification of unknown driver mutations, and molecular targets for gastrointestinal cancer modeling. Finally, it provides an overview of CRISPR/Cas9 clinical trials, as well as the challenges associated with its use.

In Silico Identification and Validation of Cuproptosis-Related LncRNA Signature as a Novel Prognostic Model and Immune Function Analysis in Colon Adenocarcinoma

Background: Colon adenocarcinoma (COAD) is the most common subtype of colon cancer, and cuproptosis is a recently newly defined form of cell death that plays an important role in the development of several malignant cancers. However, studies of cuproptosis-related lncRNAs (CRLs) involved in regulating colon adenocarcinoma are limited. The purpose of this study is to develop a new prognostic CRLs signature of colon adenocarcinoma and explore its underlying biological mechanism. Methods: In this study, we downloaded RNA-seq profiles, clinical data and tumor mutational burden (TMB) data from the TCGA database, identified cuproptosis-associated lncRNAs using univariate Cox, lasso regression analysis and multivariate Cox analysis, and constructed a prognostic model with risk score based on these lncRNAs. COAD patients were divided into high- and low-risk subgroups based on the risk score. Cox regression was also used to test whether they were independent prognostic factors. The accuracy of this prognostic model was further validated by receiver operating characteristic curve (ROC), C-index and Nomogram. In addition, the lncRNA/miRNA/mRNA competing endogenous RNA (ceRNA) network and protein−protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). Results: We constructed a prognostic model based on 15 cuproptosis-associated lncRNAs. The validation results showed that the risk score of the model (HR = 1.003, 95% CI = 1.001−1.004; p < 0.001) could serve as an independent prognostic factor with accurate and credible predictive power. The risk score had the highest AUC (0.793) among various factors such as risk score, stage, gender and age, also indicating that the model we constructed to predict patient survival was better than other clinical characteristics. Meanwhile, the possible biological mechanisms of colon adenocarcinoma were explored based on the lncRNA/miRNA/mRNA ceRNA network and PPI network constructed by WGCNA. Conclusion: The prognostic model based on 15 cuproptosis-related lncRNAs has accurate and reliable predictive power to effectively predict clinical outcomes in colon adenocarcinoma patients.

Complex roles of the actin-binding protein Girdin/GIV in DNA damage-induced apoptosis of cancer cells

The actin‐binding protein Girdin is a hub protein that interacts with multiple proteins to regulate motility and Akt and trimeric G protein signaling in cancer cells. Girdin expression correlates with poor outcomes in multiple human cancers. However, those findings are not universal, as they depend on study conditions. Those data suggest that multiple aspects of Girdin function and its role in tumor cell responses to anticancer therapeutics must be reconsidered. In the present study, we found that Girdin is involved in DNA damage‐induced cancer cell apoptosis. An esophageal cancer cell line that exhibited high Girdin expression showed a marked sensitivity to UV‐mediated DNA damage compared to a line with low Girdin expression. When transcriptional activation of endogenous Girdin was mediated by an engineered CRISPR/Cas9 activation system, sensitivity to DNA damage increased in both stationary and migrating HeLa cancer cells. High Girdin expression was associated with dysregulated cell cycle progression and prolonged G₁ and M phases. These features were accompanied by p53 activation, which conceivably increases cancer cell vulnerability to UV exposure. These data highlight the importance of understanding complex Girdin functions that influence cancer cell sensitivity to therapeutics.