High expression of G-protein signaling modulator 2 in hepatocellular carcinoma facilitates tumor growth and metastasis by activating the PI3K/AKT signaling pathway

Decrease in GPSM2 mediated by the natural product luteolin contributes to colon adenocarcinoma treatment and increases the sensitivity to fluorouracil

Luteolin, a monomeric substance, is a natural product of the Brucea javanica (BJ) plant. Brucea javanica oil emulsion injection (BJOEI) is a proprietary Chinese medicine purified from BJ that is widely used clinically as an anti-tumor treatment. Although a growing body of research suggests that luteolin and BJOEI have anti-tumor effects, the molecular mechanism of action has not been fully elucidated. In this study, through molecular docking technology, we found that luteolin can interact directly with GPSM2 and regulate the FoxO signaling pathway through GPSM2. In addition, the inhibitory effect of luteolin on colon adenocarcinoma (COAD) cells was found to be offset by knockdown of GPSM2. In contrast, the anti-proliferative effects of luteolin could be notably reversed by overexpression of GPSM2. The results reveal that GPSM2 is crucial in luteolin-mediated anti-proliferative effects. The mediation of anti-proliferative effects by GPSM2 has also been indirectly demonstrated in RKO and SW480 xenograft mice models. In addition, we verified that BJOEI inhibits the progression of COAD by mediating GPSM2 and regulating the FoxO signaling pathway. We also found that BJOEI achieved a better anti-tumor effect when combined with fluorouracil injection. Collectively, our data show that the anti-tumor effects of BJOEI and luteolin on COAD are GPSM2-dependent and downregulating the expression of GPSM2 to regulate the FoxO signaling pathway may be an effective way to treat COAD.

Ferns G, Batra J, Lam AKY, Giovannetti E, Avan A. G-Protein Signaling Modulator 2 as a Potential Biomarker in Colorectal Cancer: Integrative Analysis Using Genetic Profiling and Pan-Cancer Studies

Colorectal cancer (CRC) imposes a significant healthcare burden globally, prompting the quest for innovative biomarkers to enhance diagnostic and therapeutic strategies. This study investigates the G-protein signaling modulator (GPSM) family across several cancers and presents a comprehensive pan-cancer analysis of the GPSM2 gene across several gastrointestinal (GI) cancers. Leveraging bioinformatics methodologies, we investigated GPSM2 expression patterns, protein interactions, functional enrichments, prognostic implications, genetic alterations, and immune infiltration associations. Furthermore, the expression of the GPSM2 gene was analyzed using real-time analysis. Our findings reveal a consistent upregulation of GPSM2 expression in all GI cancer datasets analyzed, suggesting its potential as a universal biomarker in GI cancers. Functional enrichment analysis underscores the involvement of GPSM2 in vital pathways, indicating its role in tumor progression. The prognostic assessment indicates that elevated GPSM2 expression correlates with adverse overall and disease-free survival outcomes across multiple GI cancer types. Genetic alteration analysis highlights the prevalence of mutations, particularly missense mutations, in GPSM2. Furthermore, significant correlations between GPSM2 expression and immune cell infiltration are observed, suggesting its involvement in tumor immune evasion mechanisms. Collectively, our study underscores the multifaceted role of GPSM2 in GI cancers, particularly in CRC, emphasizing its potential as a promising biomarker for prognosis and therapeutic targeting. Further functional investigations are warranted to elucidate its clinical utility and therapeutic implications in CRC management.

A comprehensive analysis of G-protein-signaling modulator 2 as a prognostic and diagnostic marker for pan-cancer

Background: G-protein signaling modulator 2 (GPSM2) maintains cell polarization and regulates the cell cycle. Recent studies have shown that it is highly expressed in various tumors, but its pan-cancer analysis has not been reported.

Methods: First, we analyzed the differential GPSM2 expression in normal and cancer tissues by the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and Human Protein Atlas databases and investigated its expression effect on the survival of cancer patients by gene expression profiling interactive analysis 2 (GEPIA2). Second, we analyzed the GPSM2 phosphorylation level using the clinical proteomic tumor analysis consortium dataset. In addition, we investigated GPSM2 gene mutations in human tumor specimens and the impact of gene mutations on patient survival. Finally, we analyzed the relationship between GPSM2 expression and cellular immune infiltration through the TIMER 2.0 database. Meanwhile, the possible signaling pathway of the gene was analyzed by the Gene Ontology (GO)| Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway to explore its potential mechanism.

Results:GPSM2 is overexpressed in most cancers, which leads to reduced overall survival (OS) and disease-free survival in patients. The results of phosphorylation analysis suggest that tumor development involves a complex GPSM2 phosphorylation process. We identified GPSM2 mutation loci with the highest frequency of mutations in uterine corpus endometrial carcinoma (UCEC), and this mutation increased progression-free survival and overall survival in uterine corpus endometrial carcinoma patients. Finally, we found that the role of GPSM2 in tumors may be associated with cellular immune infiltration. Gene Ontology|KEGG pathway analysis showed that the enrichment pathways were mainly “mitotic nuclear division,” “chromosome segregation,” and “spindle.”

Conclusions: Our pan-cancer analysis provides a comprehensive overview of the oncogenic roles and potential mechanisms of GPSM2 in multiple human cancers.

Transforming growth factor-β induced protein regulates pulmonary fibrosis via the G-protein signaling modulator 2 /Snail axis

Pulmonary fibrosis, a severe condition that can progress to respiratory failure and death, is characterized by aberrant activation/proliferation of fibroblasts and excessive extracellular matrix (ECM) deposition and has limited therapeutic options. Identifying novel mediators of pulmonary fibrosis is currently needed to facilitate the development of more effective therapeutic strategies targeting pulmonary fibrosis. The present study was designed to investigate whether transforming growth factor-β (TGF-β) induced protein (TGFBI), an extracellular matrix protein, regulates pulmonary fibrosis in vitro and in vivo and the possible mechanism of actions. It was found that protein expressions of TGFBI were significantly upregulated and G-protein signaling modulator 2 (GPSM2) expression downregulated in fibrotic lung tissues from bleomycin (BLM)-induced rats and TGF-β1-stimulated human lung IMR-90 fibroblasts. Either silencing TGFBI with specific siRNA or treatment with the TGF-β signaling inhibitor SB431542 significantly inhibited TGF-β1-induced fibrotic effects and dysregulation of GPSM2 and Snail expressions in IMR-90 fibroblasts. Moreover, GPSM2 overexpression also inhibited TGF-β1-induced fibrotic effects and Snail upregulation in IMR-90 fibroblasts. Silencing Snail with specific siRNA attenuated TGF-β1-induced fibrotic effects. Therefore, our findings suggest that the extracellular matrix protein TGFBI mediates pulmonary fibrosis through regulation of the GPSM2/Snail axis, which identifies TGFBI as a novel mediator of pulmonary fibrosis and may be a potential therapeutic target for the treatment of pulmonary fibrosis.

A p53 transcriptional signature in primary and metastatic cancers derived using machine learning

The tumor suppressor gene, TP53, has the highest rate of mutation among all genes in human cancer. This transcription factor plays an essential role in the regulation of many cellular processes. Mutations in TP53 result in loss of wild-type p53 function in a dominant negative manner. Although TP53 is a well-studied gene, the transcriptome modifications caused by the mutations in this gene have not yet been explored in a pan-cancer study using both primary and metastatic samples. In this work, we used a random forest model to stratify tumor samples based on TP53 mutational status and detected a p53 transcriptional signature. We hypothesize that the existence of this transcriptional signature is due to the loss of wild-type p53 function and is universal across primary and metastatic tumors as well as different tumor types. Additionally, we showed that the algorithm successfully detected this signature in samples with apparent silent mutations that affect correct mRNA splicing. Furthermore, we observed that most of the highly ranked genes contributing to the classification extracted from the random forest have known associations with p53 within the literature. We suggest that other genes found in this list including GPSM2, OR4N2, CTSL2, SPERT, and RPE65 protein coding genes have yet undiscovered linkages to p53 function. Our analysis of time on different therapies also revealed that this signature is more effective than the recorded TP53 status in detecting patients who can benefit from platinum therapies and taxanes. Our findings delineate a p53 transcriptional signature, expand the knowledge of p53 biology and further identify genes important in p53 related pathways.

Migration and homeostasis of regulatory T cells in rheumatoid arthritis

Regulatory T (T_reg) cells are garnering increased attention in research related to autoimmune diseases, including rheumatoid arthritis (RA). They play an essential role in the maintenance of immune homeostasis by restricting effector T cell activity. Reduced functions and frequencies of T_reg cells contribute to the pathogenesis of RA, a common autoimmune disease which leads to systemic inflammation and erosive joint destruction. T_reg cells from patients with RA are characterized by impaired functions and by an altered phenotype. They show increased plasticity towards Th17 cells and a reduced suppressive capacity. Besides the suppressive function of T_reg cells, their effectiveness is determined by their ability to migrate into inflamed tissues. In the past years, new mechanisms involved in T_reg cell migration have been identified. One example of such a mechanism is the phosphorylation of vasodilator-stimulated phosphoprotein (VASP). Efficient migration of T_reg cells requires the presence of VASP. IL-6, a cytokine which is abundantly present in the peripheral blood and in the synovial tissue of RA patients, induces posttranslational modifications of VASP. Recently, it has been shown in mice with collagen-induced arthritis (CIA) that this IL-6 mediated posttranslational modification leads to reduced T_reg cell trafficking. Another protein which facilitates T_reg cell migration is G-protein-signaling modulator 2 (GPSM2). It modulates G-protein coupled receptor functioning, thereby altering the cellular activity initiated by cell surface receptors in response to extracellular signals. The almost complete lack of GPSM2 in T_reg cells from RA patients contributes to their reduced ability to migrate towards inflammatory sites. In this review article, we highlight the newly identified mechanisms of T_reg cell migration and review the current knowledge about impaired T_reg cell homeostasis in RA.

Molecular and Clinical Characterization of a Novel Prognostic and Immunologic Biomarker GPSM3 in Low-Grade Gliomas

Background: as the most common malignancy of the central nervous system, low-grade glioma (LGG) patients suffered a poor prognosis. Tumor microenvironment, especially immune components, plays an important role in the progression of tumors. Thus, it is critical to explore the key immune-related genes, a comprehensive understanding of the TME in LGG helps us find novel cancer biomarkers and therapeutic targets. Methods: the GPSM3 expression level and the correlations between clinical characteristics and GPSM3 levels were analyzed with the data from CGGA and TCGA dataset. Univariate and multivariate cox regression model were built to predict the prognosis of LGG patients with multiple factors. Then the correlation between GPSM3 with immune cell infiltration was explored by ESTIMATE, CIBERSORT and TIMER2.0. At last, the correlation analyzed between GPSM3 expression and immune checkpoint related genes were also analyzed. Results: GPSM3 expression was overexpressed in LGG and negatively correlated to the GPSM3 DNA methylation. Univariate and multivariate Cox analysis demonstrated that GPSM3 expression was an independent prognostic factor in LGG patients. Functional characterization of GPSM3 revealed that it was associated with many immune processes to tumor cells. GPSM3 expression was positive related to the immune score, Stromal scores and ESTIMATE scores, but negative related to the Tumor purity. Immune features in the TME of GPSM3-high LGG group is characterized by a higher infiltrating of regulatory T cells, neutrophils, macrophages M2, and a lower proportion of monocytes than to the GPSM3-low group. Furthermore, GPSM3 expression exhibited significant correlations with the immune checkpoint-related genes, especially PD-1, PD-L1, PD-L2, CTLA4 and TIM3. Conclusions: these findings proved that GPSM3 could serve as a prognostic biomarker and potential immunotherapy target for LGG.

Kinase activity profiling reveals contribution of G-protein signaling modulator 2 deficiency to impaired regulatory T cell migration in rheumatoid arthritis

The ability of regulatory T (T_reg) cells to migrate into inflammatory sites is reduced in autoimmune diseases, including rheumatoid arthritis (RA). The reasons for impaired T_reg cell migration remain largely unknown. We performed multiplex human kinase activity arrays to explore possible differences in the post-translational phosphorylation status of kinase related proteins that could account for altered T_reg cell migration in RA. Results were verified by migration assays and Western blot analysis of CD4⁺ T cells from RA patients and from mice with collagen type II induced arthritis. Kinome profiling of CD4⁺ T cells from RA patients revealed significantly altered post-translational phosphorylation of kinase related proteins, including G-protein-signaling modulator 2 (GPSM2), protein tyrosine kinase 6 (PTK6) and vitronectin precursor (VTNC). These proteins have not been associated with RA until now. We found that GPSM2 expression is reduced in CD4⁺ T cells from RA patients and is significantly downregulated in experimental autoimmune arthritis following immunization of mice with collagen type II. Interestingly, GPSM2 acts as a promoter of T_reg cell migration in healthy individuals. Treatment of RA patients with interleukin-6 receptor (IL-6R) blocking antibodies restores GPSM2 expression, thereby improving T_reg cell migration. Our study highlights the potential of multiplex kinase activity arrays as a tool for the identification of RA-related proteins which could serve as targets for novel treatments.

Identifying GPSM Family Members as Potential Biomarkers in Breast Cancer: A Comprehensive Bioinformatics Analysis

G-protein signaling modulators (GPSMs) are a class of proteins involved in the regulation of G protein-coupled receptors, the most abundant family of cell-surface receptors that are crucial in the development of various tumors, including breast cancer. This study aims to identify the potential therapeutic and prognostic roles of GPSMs in breast cancer. Oncomine and UALCAN databases were queried to determine GPSM expression levels in breast cancer tissues compared to normal samples. Survival analysis was conducted to reveal the prognostic significance of GPSMs in individuals with breast cancer. Functional enrichment analysis was performed using cBioPortal and MetaCore platforms. Finally, the association between GPSMs and immune infiltration cells in breast cancer was identified using the TIMER server. The experimental results then showed that all GPSM family members were significantly differentially expressed in breast cancer according to Oncomine and UALCAN data. Their expression levels were also associated with advanced tumor stages, and GPSM2 was found to be related to worse distant metastasis-free survival in patients with breast cancer. Functional enrichment analysis indicated that GPSMs were largely involved in cell division and cell cycle pathways. Finally, GPSM3 expression was correlated with the infiltration of several immune cells. Members of the GPSM class were differentially expressed in breast cancer. In conclusion, expression of GPSM2 was linked with worse distant metastasis-free outcomes, and hence could potentially serve as a prognostic biomarker. Furthermore, GPSM3 has potential to be a possible target for immunotherapy for breast cancer.

Identification of G-protein signaling modulator 2 as a diagnostic and prognostic biomarker of pancreatic adenocarcinoma: an exploration of its regulatory mechanisms

Background

Pancreatic adenocarcinoma (PAAD) has a high rate of mortality. Unfortunately, it is difficult to diagnosis. This study aimed to develop a more in-depth understanding of the disease.

Methods

A total of 177 patients with PAAD were recruited from The Cancer Genome Atlas (TCGA) database. Microarray analysis was performed to identify differentially expressed genes (DEGs) in PAAD. The microarray data were adapted to the ingenuity pathway analysis (IPA) for annotation and visualization, followed by protein-protein interaction (PPI) network analysis. In vitro transwell migration assays were conducted to explore the molecular and functional characteristics of pancreatic adenocarcinoma cells (PANC-1) with stable low expression of G-protein signaling modulator 2 (GPSM2). Expression of GPSM2 and the associated hub genes were detected by reverse transcription-quantitative polymerase chain reaction (qPCR).

Results

The overexpression of GPSM2 was proved in PAAD, as compared with the healthy tissues, as well as its correlation with history of chronic pancreatitis, T stage, TNM stage and tumor grade. We described it as an independent prognostic factor and found that it could influence the infiltration of immune cells in the tumor microenvironment. Silencing of GPSM2 restrained the and migration of the cells. Microarray analysis identified 1,631 DEGs in PAAD cells. The PPI network analysis identified hub genes including CD44, ITGB1, ITGB5, ITGA2, ITGA5, AKT1, EGFR, NRAS and MAP2K1, and their relationship with GPSM2 was confirmed by qPCR.

Conclusions

GPSM2 is a novel prognostic factor and therapeutic target for PAAD. GPSM2 promoted the migration of pancreatic adenocarcinoma cells .Targeting GPSM2 and its downstream genes may prolong the survival time of patients with PAAD.

Integrated Genomic and Transcriptomic Analysis reveals key genes for predicting dual-phenotype Hepatocellular Carcinoma Prognosis

Dual-phenotype hepatocellular carcinoma (DPHCC) expresses both hepatocyte and cholangiocyte markers, and is characterized by high recurrence and low survival rates. The underlying molecular mechanisms of DPHCC pathogenesis are unclear.

We performed whole exome sequencing and RNA sequencing of three subtypes of HCC (10 DPHCC, 10 CK19-positive HCC, and 14 CK19-negative HCC), followed by integrated bioinformatics analysis, including somatic mutation analysis, mutation signal analysis, differential gene expression analysis, and pathway enrichment analysis. Cox proportional hazard regression analyses were applied for exploring survival related characteristics.

We found that mutated genes in DPHCC patients were associated with carcinogenesis and immunity, and the up-regulated genes were mainly enriched in transcription-related and cancer-related pathways, and the down-regulated genes were mainly enriched in immune-related pathways. CXCL9 was selected as the hub gene, which is associated with immune cells and survival prognosis. Our results showed that low CXCL9 expression was significantly associated with poor prognosis, and its expression was significantly reduced in DPHCC samples.

In conclusion, we explored the molecular mechanisms governing DPHCC development and progression and identified CXCL9, which influences the immune microenvironment and prognosis of DPHCC and might be new clinically significant biomarkers for predicting prognosis.

Identification of an extracellular vesicle-related gene signature in the prediction of pancreatic cancer clinical prognosis

Although extracellular vesicles (EVs) in body fluid have been considered to be ideal biomarkers for cancer diagnosis and prognosis, it is still difficult to distinguish EVs derived from tumor tissue and normal tissue. Therefore, the prognostic value of tumor-specific EVs was evaluated through related molecules in pancreatic tumor tissue. NA sequencing data of pancreatic adenocarcinoma (PAAD) were acquired from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). EV-related genes in pancreatic cancer were obtained from exoRBase. Protein–protein interaction (PPI) network analysis was used to identify modules related to clinical stage. CIBERSORT was used to assess the abundance of immune and non-immune cells in the tumor microenvironment. A total of 12 PPI modules were identified, and the 3-PPI-MOD was identified based on the randomForest package. The genes of this model are involved in DNA damage and repair and cell membrane-related pathways. The independent external verification cohorts showed that the 3-PPI-MOD can significantly classify patient prognosis. Moreover, compared with the model constructed by pure gene expression, the 3-PPI-MOD showed better prognostic value. The expression of genes in the 3-PPI-MOD had a significant positive correlation with immune cells. Genes related to the hypoxia pathway were significantly enriched in the high-risk tumors predicted by the 3-PPI-MOD. External databases were used to verify the gene expression in the 3-PPI-MOD. The 3-PPI-MOD had satisfactory predictive performance and could be used as a prognostic predictive biomarker for pancreatic cancer.

Umbilical Cord Mesenchymal Stem Cell-Derived Nanovesicles Potentiate the Bone-Formation Efficacy of Bone Morphogenetic Protein 2

Recombinant human bone morphogenetic protein 2 (rhBMP-2) is one of the most potent osteogenic factors used to treat bone loss. However, at higher doses, rhBMP-2 does not necessarily increase bone formation but rather increases the incidence of adverse side effects. Here, we investigated whether umbilical cord mesenchymal stem cell (UCMSC)-derived nanovesicles (NVs) further increase the in vivo bone formation at high doses of rhBMP-2. In the presence of UCMSC-derived NVs, proliferation, migration, and tube formation of human umbilical vein endothelial cells were stimulated in vitro. Furthermore, migration and osteogenesis of human bone marrow-derived mesenchymal stem cells were stimulated. To examine the efficacy of UCMSC-derived NVs on in vivo bone formation, collagen sponges soaked with rhBMP-2 and UCMSC-derived NVs were used in athymic nude mice with calvarial defects. At a high rhBMP-2 dosage (500 ng/mL), UCMSC-derived NVs significantly promoted bone formation in calvarial defects; however, the UCMSC-derived NVs alone did not induce in vivo bone formation. Our results indicate that UCMSC-derived NVs can potentiate the bone formation efficacy of rhBMP-2 at a high dosage.

GPSM2 Serves as an Independent Prognostic Biomarker for Liver Cancer Survival

Background and Objective:

Liver cancer is a malignancy with a poor prognosis. G protein signaling modulator 2 is mainly related to cell division and cell cycle regulation. In this review, the relationship between G protein signaling modulator 2 and clinical characteristics of patients with liver cancer has been explored, especially with respect to its prognostic value.

Methods:

G protein signaling modulator 2 messenger RNA expression and clinicopathological characteristics of patients with liver cancer were obtained from The Cancer Genome Atlas. The expression level of G protein signaling modulator 2 RNA-Seq was validated by using Gene Expression Omnibus. Chi-square test was performed to evaluate the relationship between G protein signaling modulator 2 expression and clinical characteristics. The threshold value of G protein signaling modulator 2 in the diagnosis of liver cancer was evaluated by a receiver–operating characteristic curve. Cox regression analysis and Kaplan-Meier curves were performed to evaluate the relationship between G protein signaling modulator 2 and liver cancer prognosis, which included overall and residual-free survival, and explored the prognostic value of G protein signaling modulator 2. Liver cancer survival analyses were validated by using the data of G protein signaling modulator 2 RNA-Seq from the International Cancer Genome Consortium.

Results:

The expression level of G protein signaling modulator 2 messenger RNA was remarkably higher in liver cancer than that in healthy tissues (P < 2.2 × e⁻¹⁶), which was also validated by data from the GSE14520 database. In addition, high G protein signaling modulator 2 expression significantly correlated with histological grade (P = .020), vital status (P < .001), clinical (P = .001), and T stage (P = .001). The receiver–operating characteristic curves showed G protein signaling modulator 2 to be an advantageous diagnostic molecule for liver cancer (area under curve = 0.893). Furthermore, the results of Cox analysis and Kaplan-Meier curves suggested that the upregulation of G protein signaling modulator 2 expression is linked to poor prognosis and G protein signaling modulator 2 messenger RNA could be an independent predictor for liver cancer, which was validated by data from the International Cancer Genome Consortium database.

Conclusions:

G protein signaling modulator 2 messenger RNA was overexpressed in liver cancer, and G protein signaling modulator 2 is an independent prognostic factor. G protein signaling modulator 2 is expected to be a treatment target for cancer.

Knockdown of G-protein-signaling modulator 2 promotes metastasis of non-small-cell lung cancer by inducing the expression of Snail

Non‐small‐cell lung cancer (NSCLC) is the leading global cause of cancer‐related death. Due to the lack of reliable diagnostic or prognostic biomarkers, the prognosis of NSCLC remains poor. Consequently, there is an urgent need to explore the mechanisms underlying this condition in order to identify effective biomarkers. G‐protein‐signaling modulator 2 (GPSM2) is widely recognized as a determinant of mitotic spindle orientation. However, its role in cancer, especially NSCLC, remains uncertain. In this study, we found that GPSM2 was downregulated in NSCLC tissues and was correlated with a poor prognosis. Furthermore, the knockdown of GPSM2 promoted NSCLC cell metastasis in vitro and in vivo and accelerated the process of epithelial‐mesenchymal transition (EMT). Mechanistically, we showed that silencing GPSM2 induced cell metastasis and EMT through the ERK/glycogen synthase kinase‐3β/Snail pathway. These results confirm that GPSM2 plays an important role in NSCLC. Moreover, GPSM2, as an independent prognostic factor, could be a potential prognostic biomarker and drug target for NSCLC.

Comparison of Transcriptomics Changes Induced by TCS and MTCS Exposure in Human Hepatoma HepG2 Cells

Triclosan (TCS) has been a widely used antibacterial agent in medical and personal care products in the last few decades. Methyl TCS (MTCS) is the major biotransformation product of TCS through replacement of the hydroxyl group with methoxy. Previous studies revealed that MTCS showed reduced toxicity but enhanced environmental persistence, when compared with TCS. Till date, the toxicological molecular mechanisms of TCS and MTCS remain to be clarified. This study aimed to investigate the transcriptomic changes in HepG2 cells induced by TCS and MTCS using microarray chips and to identify key target genes and related signal pathways. The microarray data showed that there were 1664 and 7144 differentially expressed genes (DEGs) in TCS- and MTCS-treated groups, respectively. Gene ontology (GO) enrichment and Kyoto Encyclopedia of genes and genomes (KEGG) analysis revealed that TCS and MTCS induced overlapping as well as distinct transcriptome signatures in HepG2 cells. Both TCS and MTCS could result in various biological responses in HepG2 cells mainly responding to biosynthetic and metabolic processes but probably through different regulatory pathways. Among the selected 50 GO terms, 9 GO terms belonging to the cellular component category were only enriched in the MTCS group, which are mainly participating in the regulation of cellular organelle's function. KEGG analysis showed that 19 and 59 pathway terms were separately enriched in TCS and MTCS groups, with only seven identical pathways. The selected 10 TCS-specific signal pathways are mainly involved in cell proliferation and apoptosis, while the selected 10 MTCS-specific pathways mainly take part in the regulation of protein synthesis and modification. The overall data suggested that MTCS induced more enriched DEGs, GO terms, and pathway terms than TCS. In conclusion, compared with TCS, MTCS presents lower polarity and stronger lipophilicity, enabling MTCS to cause more extensive transcriptomic changes in HepG2 cells, activate differentiated signal pathways, and finally lead to differences in biological responses.

A Key mRNA-miRNA-lncRNA Competing Endogenous RNA Triple Sub-network Linked to Diagnosis and Prognosis of Hepatocellular Carcinoma

Growing evidence has illustrated critical roles of competing endogenous RNA (ceRNA) regulatory network in human cancers including hepatocellular carcinoma. In this study, we aimed to find promising diagnostic and prognostic biomarkers for patients with hepatocellular carcinoma. Three novel unfavorable prognosis-associated genes (CELSR3, GPSM2, and CHEK1) was first identified. We also demonstrated that these genes were significantly upregulated in hepatocellular carcinoma cell lines and tissues. Next, 154 potential miRNAs of CELSR3, GPSM2, and CHEK1 were predicted. CHEK1-hsa-mir-195-5p/hsa-mir-497-5p and GPSM2-hsa-mir-122-5p axes were defined as two key pathways in carcinogenesis of hepatocellular carcinoma by combination of in silico analysis and experimental validation. Subsequently, lncRNAs binding to hsa-mir-195-5p, hsa-mir-497-5p, and hsa-mir-122-5p were predicted via starBase and miRNet databases. After performing expression analysis and survival analysis for these predicted lncRNAs, we showed that nine lncRNAs (SNHG1, SNHG12, LINC00511, HCG18, FGD5-AS1, CERS6-AS1, NUTM2A-AS1, SNHG16, and ASB16-AS1) were markedly increased in hepatocellular carcinoma and their upregulation indicated poor prognosis. Moreover, a similar mRNA-miRNA-lncRNA analysis for six “known” genes (CLEC3B, DNASE1L3, PTTG1, KIF2C, XPO5, and UBE2S) was performed. Subsequently, a comprehensive mRNA-miRNA-lncRNA triple ceRNA network linked to prognosis of patients with hepatocellular carcinoma was established. Moreover, all RNAs in this network exhibited significantly diagnostic values for patients with hepatocellular carcinoma. In summary, the current study constructed a mRNA-miRNA-lncRNA ceRNA network associated with diagnosis and prognosis of hepatocellular carcinoma.

Localization of GPSM2 in the Nucleus of Invasive Breast Cancer Cells Indicates a Poor Prognosis

Purpose: GPSM2 (G protein signaling modulator 2) was reported to be involved in the cell division of breast cancer cells. Additionally, cytoplasmic dynein may mediate the transport process of GPSM2. DYNC1I1 (Cytoplasmic dynein 1 intermediate chain 1) is the most common cargo-binding subunit of dynein. However, the relationship between GPSM2 and DYNC1I1 and its clinical value is unclear.

Methods: Immunohistochemical staining was performed for assessment of GPSM2 and DYNC1I1 expression. Immunoprecipitation analysis was used to assess the interaction between GPSM2 and DYNC1I1.

Results: GPSM2 was correlated with clinical characteristics of breast cancer patients and is an unfavorable independent prognostic factor. In addition, nuclear expression of GPSM2 is an unfavorable independent prognostic factor (HR = 2.658, 95% CI = 1.490–4.741, p = 0.001). GPSM2 and DYNC1I1 are known to form a complex in breast cancer cells. Patients who were positive for expression of both DYNC1I1 and GPSM2 presented with shorter recurrence-free survival than other patients. Importantly, patients with GPSM2 nuclear expression showed higher DYNC1I1 expression.

Conclusion: GPSM2 was an independent prognostic factor in breast cancer and nuclear expression of GPSM2 was significantly associated with poor prognosis, which was related to the positive expression of DYNC1I1. Examination of both GPSM2 and DYNC1I1 is necessary to establish a prognosis in breast cancer patients.

Loss of G-protein-signaling modulator 2 accelerates proliferation of lung adenocarcinoma via EGFR signaling pathway

G-protein-signaling modulator 2 (GPSM2) belongs to a protein family that regulates activation of G proteins and plays an important role in mitotic spindle orientation. However, the role of GPSM2 in lung adenocarcinoma (LUAD) is still unclear. In this study, it was found that GPSM2 correlates with clinicopathological features and patient's prognosis in LUAD. Knocking down GPSM2 promoted LUAD cell proliferation in vitro and in vivo. Mechanistically, it was demonstrated that GPSM2 knockdown accelerates cell proliferation via the EGFR pathway. These results confirmed that GPSM2 played an important role in LUAD. Moreover, GPSM2, as an independent prognostic factor, may serve as a potential drug target and prognostic biomarker in LUAD.

Downregulation of GPSM2 is associated with primary resistance to paclitaxel in breast cancer

Paclitaxel is one of the most effective chemotherapy drugs for breast cancer worldwide but 20–30% patients show primary resistance to the drug. Screening and identification of markers that facilitate effective and rapid prediction of sensitivity to paclitaxel is therefore an urgent medical requirement. In the present study, G protein signaling modulator 2 (GPSM2) mRNA levels were significantly associated with taxane sensitivity in experiments based on the Gene Expression Omnibus (GEO) online database. Immunohistochemical analysis consistently revealed a significant association of GPSM2 protein levels with paclitaxel sensitivity in breast cancer patients. Knockdown of GPSM2 reduced the sensitivity of breast cancer cells to paclitaxel via regulation of the cell cycle. Animal experiments further corroborated our in vitro findings. These results suggest that GPSM2 plays an important role in breast cancer resistance, supporting its utility as a potential target for improving drug susceptibility in patients as well as a marker of paclitaxel sensitivity.

Emerging role of ubiquitin-specific protease 14 in oncogenesis and development of tumor: Therapeutic implication

Ubiquitin (Ub) is a small protein that can be attached to substrate proteins to direct their degradation via the proteasome. Deubiquitinating enzymes (DUBs) reverse this process by removing ubiquitin from its substrate protein. Over the past few decades, ubiquitin-specific protease 14 (USP14), a member of the DUBs, has emerged as an important player in various types of cancers. In this article, we review and summarize biological function of USP14 in tumorigenesis and multiple signaling pathways. To determine its role in cancer, we analyzed USP14 gene expression across a panel of tumors, and discussed that it could serve as a novel bio-marker in several types of cancer. And recent contributions indicated that USP14 has been shown to act as a tumor-promoting gene via the AKT, NF-κB, MAPK pathways etc. Besides, drugs targeting USP14 have shown potential anti-tumor effect and clinical significance. We focus on recent studies that explore the link between USP14 and cancer, and further discuss USP14 as a novel target for cancer therapy.

G-protein-signaling modulator 2 expression and role in a CD133+ pancreatic cancer stem cell subset

Background

To investigate the expression and role of G-protein-signaling modulator 2 (GPSM2) in a CD133⁺ pancreatic stem cell subset.

Materials and methods

Pancreatic cancer stem cells (PCSCs) from the cell line PANC-1 were sorted into CD133⁺ and CD133^- subsets by flow cytometry. The tumorigenic potential of the subsets was assessed by subcutaneous tumor formation experiments in nude mice. Differential expression of GPSM2 was examined by real-time quantitative-PCR (qPCR) and Western blotting. To silence GPSM2 expression, a shRNA lentiviral vector targeting GPSM2 was constructed and stably transfected into CD133⁺ PCSCs. The inhibitory efficiency of the GPSM2 gene was verified by qPCR and Western blotting. The proliferation, colony formation, and migration abilities of the transfected CD133⁺ pancreatic cancer cells were assessed by MTT, soft agar colony formation, and Transwell assays.

Results

CD133⁺ and CD133^- cell subsets were successfully isolated from PANC-1 cells. The CD133⁺ subset subcutaneously formed tumors in nude mice that were significantly bigger (343.05±57.59 mm³ vs 176.86±32.58 mm³, P<0.01) and denser (4.13±0.37 g vs 1.07±0.21 g, P<0.01) than those of the CD133^- group. The GPSM2 mRNA and protein expression was significantly higher in CD133⁺ cells than in CD133^- cells. Stable downregulation of GPSM2 expression reduced the proliferation, colony formation, and migration abilities of CD133⁺ PANC-1 cells (P<0.05).

Conclusion

The CD133⁺PANC-1 cells have obvious stem cell characteristics and increased GPSM2 expression. Downregulation of GPSM2 significantly reduces the proliferation and migration ability of the cells. Therefore, GPSM2 may provide an important target for regulating PCSCs.