GPCR Modulation in Breast Cancer

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.

Thiazolyl-isatin derivatives: Synthesis, in silico studies, in vitro biological profile against breast cancer cells, mRNA expression, P-gp modulation, and interactions of Akt2 and VIM proteins

The literature reports that thiazole and isatin nuclei present a range of biological activities, with an emphasis on anticancer activity. Therefore, our proposal was to make a series of compounds using the molecular hybridization strategy, which has been used by our research group, producing hybrid molecules containing the thiazole and isatin nuclei. After structural planning and synthesis, the compounds were characterized and evaluated in vitro against breast cancer cell lines (T-47D, MCF-7 and MDA-MB-231) and against normal cells (PBMC). The activity profile on membrane proteins involved in chemoresistance and tumorigenic signaling proteins was also evaluated. Among the compounds tested, the compounds 4c and 4a stood out with IC50 values of 1.23 and 1.39 μM, respectively, against the MDA-MB-231 cell line. Both compounds exhibited IC50 values of 0.45 μM for the MCF-7 cell line. Compounds 4a and 4c significantly decreased P-gp mRNA expression levels in MCF-7, 4 and 2 folds respectively. Regarding the impact on tumorigenic signaling proteins, compound 4a inhibited Akt2 in MDA-MB-231 and compound 4c inhibited the mRNA expression of VIM in MCF-7.

Bayesian Multi-View Clustering given complex inter-view structure

Multi-view datasets are becoming increasingly prevalent. These datasets consist of different modalities that provide complementary characterizations of the same underlying system. They can include heterogeneous types of information with complex relationships, varying degrees of missingness, and assorted sample sizes, as is often the case in multi-omic biological studies. Clustering multi-view data allows us to leverage different modalities to infer underlying systematic structure, but most existing approaches are limited to contexts in which entities are the same across views or have clear one-to-one relationships across data types with a common sample size. Many methods also make strong assumptions about the similarities of clusterings across views. We propose a Bayesian multi-view clustering approach (BMVC) which can handle the realities of multi-view datasets that often have complex relationships and diverse structure. BMVC incorporates known and complex many-to-many relationships between entities via a probabilistic graphical model that enables the joint inference of clusterings specific to each view, but where each view informs the others. Additionally, BMVC estimates the strength of the relationships between each pair of views, thus moderating the degree to which it imposes dependence constraints. We benchmarked BMVC on simulated data to show that it accurately estimates varying degrees of inter-view dependence when inter-view relationships are not limited to one-to-one correspondence. Next, we demonstrated its ability to capture visually interpretable inter-view structure in a public health survey of individuals and households in Puerto Rico following Hurricane Maria. Finally, we showed that BMVC clusters integrate the complex relationships between multi-omic profiles of breast cancer patient data, improving the biological homogeneity of clusters and elucidating hypotheses for functional biological mechanisms. We found that BMVC leverages complex inter-view structure to produce higher quality clusters than those generated by standard approaches. We also showed that BMVC is a valuable tool for real-world discovery and hypothesis generation.

Activation of PI3K/Akt pathway by G protein-coupled receptor 37 promotes resistance to cisplatin-induced apoptosis in non-small cell lung cancer

OBJECTIVES

Lung cancer is a major public health concern and represents the most common cause of cancer-related death worldwide. Among eukaryotes, the G protein-coupled receptor (GPCR) family stands as the largest group of membrane proteins. Alterations in GPCR gene expression and dysregulation of signal transduction have been recognized as the markers of malignancy. As a member of the GPCR family, G protein-coupled receptor 37 (GPR37) exhibits unknown functions in tumors, particularly in non-small-cell lung cancer (NSCLC) METHODS: We explored the expression and prognosis of GPR37 in NSCLC through TCGA, GTEx, GEO, and GEPIA2. We detected the expression of GPR37 in NSCLC tissues and cell lines. The study explored the influence of GPR37 on tumor cell proliferation. Furthermore, we examined the effects of GPR37 on tumor cell apoptosis and invasion. Most importantly, we investigated whether GPR37 affects cisplatin-induced drug resistance in NSCLC. Furthermore, by conducting animal experiments, we assessed the impact of GPR37 on NSCLC and delved into underlying mechanisms.

RESULTS

(1) In NSCLC, the expression of GPR37 is markedly higher than that in corresponding normal tissues. We found that elevated GPR37 expression predicts an unfavorable prognosis. (2) It was demonstrated that GPR37 positively regulates NSCLC cell invasion, migration, and proliferation, suppresses cell apoptosis, heightens resistance to cisplatin, and promotes tumor formation and growth. Conversely, we observed that GPR37 knockdown suppresses NSCLC cell invasion, migration, and proliferation, promotes cell apoptosis, increases sensitivity to cisplatin, and affects tumor formation and growth. (3) GPR37 activates PI3K/Akt/mTOR signal transduction pathways to mediate epithelial-mesenchymal transition (EMT), thereby promoting the progression of NSCLC.

CONCLUSIONS

It was suggested that GPR37 acts a crucial role in promoting the occurrence and development of NSCLC. Knockdown of GPR37 significantly inhibits the occurrence and development of NSCLC. Therefore, our findings demonstrated that GPR37 may represent a viable therapeutic target for NSCLC.

Inhibition of FNDC1 suppresses gastric cancer progression by interfering with Gβγ-VEGFR2 complex formation

Gastric cancer (GC) is a prevalent digestive tract malignant tumor characterized by an insidious onset, ease of metastasis, rapid growth, and poor prognosis. Here, we report that fibronectin type III domain containing 1 (FNDC1) has high expression in GC and indicates poor outcomes in patients with GC. FNDC1 over-expression or knockdown promotes or inhibits tumorigenesis and metastasis, respectively. The expression of FNDC1 is upregulated by TWIST1, strengthening its interaction with Gβγ and VEGFR2. The formation of the trimers, TWIST1 plus Gβγ and VEGFR2, increases VEGFR2 phosphorylation and Gβγ trafficking, which activates RAS-MAPK and PI3K-AKT signaling, benefiting GC progression. In this study, we demonstrated that arsenite can efficiently suppress FNDC1 expression, attenuating the formation of the trimers and downstream pathways. Altogether, our results indicate that FNDC1 might be a promising target for clinical treatment and prognostic judgment, while FNDC1 inhibition by arsenite provides a new opportunity for overcoming this fatal disease.

An insight into the potential role of LINC00968 in luminal breast cancer: Case-control study and bioinformatics analysis

Background

Luminal A and B subtypes of breast cancer (BC) comprises up to 70% of all BC patients. LncRNAs can affect many biological and pathological processes, and dysregulation of them is related to human cancers. The potential role of lncRNA LINC00968 in luminal BC is still unclear.

Materials and methods

We analyzed the LINC00968 expression across 44 paired luminal BC tissues from the TCGA-BRCA RNA sequencing dataset. Besides, we used the GEPIA2 web server and GENEVESTIGATOR software, as well. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) assay was performed to confirm the LINC00968 expression in 71 paired luminal BC tissues and two luminal A cell lines (MCF7 and T47D). Moreover, to better understanding the potential role of LINC00968 in luminal BC, computational data analyses including co-expression analysis, functional annotation analysis, and genetic alteration analysis have been done.

Results

The results of data analyses retrieved from BRCA dataset and databases revealed the significant downregulation of LINC00968 in luminal A and B BC. Also, the results of qRT-PCR in luminal BC tissues and cell lines confirmed the earlier data. LINC00968 expression was negatively associated with tumor stage and lymph node metastasis. Additionally, functional annotation analyses revealed that LINC00968 might be involved in vascular development and angiogenesis, extracellular matrix organization, and cell motility and migration. LINC00968 might play role in some cancer-related signaling pathways.

Conclusion

Our study found that downregulation of LINC00968 might promote tumorigenesis, invasion, and metastasis of luminal BC.

Molecular characterization of breast cancer cell pools with normal or reduced ability to respond to progesterone: a study based on RNA-seq

BACKGROUND

About one-third of patients with estrogen receptor alpha (ERα)-positive breast cancer have tumors which are progesterone receptor (PR) negative. PR is an important prognostic factor in breast cancer. Patients with ERα-positive/PR-negative tumors have shorter disease-free and overall survival than patients with ERα-positive/PR-positive tumors. New evidence has shown that progesterone (P4) has an anti-proliferative effect in ERα-positive breast cancer cells. However, the role of PR in breast cancer is only poorly understood.

METHODS

We disrupted the PR gene (PGR) in ERα-positive/PR-positive T-47D cells using the CRISPR/Cas9 system. This resulted in cell pools we termed PR-low as P4 mediated effects were inhibited or blocked compared to control T-47D cells. We analyzed the gene expression profiles of PR-low and control T-47D cells in the absence of hormone and upon treatment with P4 alone or P4 together with estradiol (E2). Differentially expressed (DE) genes between experimental groups were characterized based on RNA-seq and Gene Ontology (GO) enrichment analyses.

RESULTS

The overall gene expression pattern was very similar between untreated PR-low and untreated control T-47D cells. More than 6000 genes were DE in control T-47D cells upon stimulation with P4 or P4 plus E2. When PR-low pools were subjected to the same hormonal treatment, up- or downregulation was either blocked/absent or consistently lower. We identified more than 3000 genes that were DE between hormone-treated PR-low and control T-47D cells. GO analysis revealed seven significantly enriched biological processes affected by PR and associated with G protein-coupled receptor (GPCR) pathways which have been described to support growth, invasiveness, and metastasis in breast cancer cells.

CONCLUSIONS

The present study provides new insights into the complex role of PR in ERα-positive/PR-positive breast cancer cells. Many of the genes affected by PR are part of central biological processes of tumorigenesis.

MOBILE pipeline enables identification of context-specific networks and regulatory mechanisms

Robust identification of context-specific network features that control cellular phenotypes remains a challenge. We here introduce MOBILE (Multi-Omics Binary Integration via Lasso Ensembles) to nominate molecular features associated with cellular phenotypes and pathways. First, we use MOBILE to nominate mechanisms of interferon-γ (IFNγ) regulated PD-L1 expression. Our analyses suggest that IFNγ-controlled PD-L1 expression involves BST2, CLIC2, FAM83D, ACSL5, and HIST2H2AA3 genes, which were supported by prior literature. We also compare networks activated by related family members transforming growth factor-beta 1 (TGFβ1) and bone morphogenetic protein 2 (BMP2) and find that differences in ligand-induced changes in cell size and clustering properties are related to differences in laminin/collagen pathway activity. Finally, we demonstrate the broad applicability and adaptability of MOBILE by analyzing publicly available molecular datasets to investigate breast cancer subtype specific networks. Given the ever-growing availability of multi-omics datasets, we envision that MOBILE will be broadly useful for identification of context-specific molecular features and pathways.

Bioinformatics and network biology approach to identifying type 2 diabetes genes and pathways that influence the progression of breast cancer

Breast cancer is the second most prevalent malignancy affecting women. Postmenopausal women breast tumor is one of the top causes of death in women, accounting for 23% of cancer cases. Type 2 diabetes, a worldwide pandemic, has been connected to a heightened risk of several malignancies, although its association with breast cancer is still uncertain. In comparison to non-diabetic women, women with T2DM had a 23% elevated likelihood of developing breast cancer. It is difficult to determine causative or genetic susceptibility that connect T2DM and breast cancer. We created a large-scale network-based quantitative approach employing unbiased methods to discover abnormally amplified genes in both T2DM and breast cancer, to solve these issues. We performed transcriptome analysis to uncover identical genetic biomarkers and pathways to clarify the connection between T2DM and breast cancer patients. In this study, two RNA-seq datasets (GSE103001 and GSE86468) from the Gene Expression Omnibus (GEO) are used to identify mutually differentially expressed genes (DEGs) for breast cancer and T2DM, as well as common pathways and prospective medicines. Firstly, 45 shared genes (30 upregulated and 15 downregulated) between T2D and breast cancer were detected. We employed gene ontology and pathway enrichment to characterize prevalent DEGs' molecular processes and signal transduction pathways and observed that T2DM has certain connections to the progression of breast cancer. Using several computational and statistical approaches, we created a protein-protein interactions (PPI) network and revealed hub genes. These hub genes can be potential biomarkers, which may also lead to new therapeutic strategies for investigated diseases. We conducted TF-gene interactions, gene-microRNA interactions, protein-drug interactions, and gene-disease associations to find potential connections between T2DM and breast cancer pathologies. We assume that the potential drugs that emerged from this study could be useful therapeutic values. Researchers, doctors, biotechnologists, and many others may benefit from this research.

Promising Perspectives of the Antiproliferative GPER Inverse Agonist ERα17p in Breast Cancer

The estrogen receptor α (ERα) corresponds to a large platform in charge of the recruitment of a panel of molecules, including steroids and related heterocyclic derivatives, oligonucleotides, peptides and proteins. Its 295-311 region is particularly targeted by post-translational modifications, suggesting that it could be crucial for the control of transcription. In addition to anionic phospholipids, the ERα 295-311 fragment interacts with Ca²⁺-calmodulin, the heat shock protein 70 (Hsp70), ERα and possibly importins. More recently, we have demonstrated that it is prone to interacting with the G-protein-coupled estrogen receptor (GPER). In light of these observations, the pharmacological profile of the corresponding peptide, namely ERα17p, has been explored in breast cancer cells. Remarkably, it exerts apoptosis through GPER and induces a significant decrease (more than 50%) of the size of triple-negative breast tumor xenografts in mice. Herein, we highlight not only the promising therapeutic perspectives in the use of the first peptidic GPER modulator ERα17p, but also the opportunity to modulate GPER for clinical purposes.

Role of collagen regulators in cancer treatment: A comprehensive review

Abstract:

Collagen is the most important structural protein and also a main component of extra-cellular matrix (ECM). It plays a role in tumor progression. Collagen can be regulated by altering it’s biosynthesis pathway through various signaling pathways, receptors and genes. Activity of cancer cells can also be regulated by other ECM components like metalloproteinases, hyaluronic acid, fibronectin and so on. Hypoxia is also one of the condition which leads to cancer progression by stimulating the expression of procollagen lysine as a collagen crosslinker, which increases the size of collagen fibres promoting cancer spread. The collagen content in cancerous cells leads to resistance in chemotherapy. So, to reduce this resistance, some of the collagen regulating therapies are introduced, which include inhibiting its biosynthesis, disturbing cancer cell signaling pathway, mediating ECM components and directly utilizing collagenase. This study is an effort to compile the strategies reported to control the collagen level and different collagen inhibitors reported so far. More research is needed in this area, growing understandings of collagen’s structural features and its role in cancer progression will aid in the advancement of newer chemotherapies.

Investigation of the effects of overexpression of jumping translocation breakpoint (JTB) protein in MCF7 cells for potential use as a biomarker in breast cancer

Jumping translocation breakpoint (JTB) gene acts as a tumor suppressor or an oncogene in different malignancies, including breast cancer (BC), where it was reported as overexpressed. However, the molecular functions, biological processes and underlying mechanisms through which JTB protein causes increased cell growth, proliferation and invasion is still not fully deciphered. Our goal is to identify the functions of JTB protein by cellular proteomics approaches. MCF7 breast cancer cells were transfected with sense orientation of hJTB cDNA in HA, His and FLAG tagged CMV expression vector to overexpress hJTB and the expression levels were confirmed by Western blotting (WB). Proteins extracted from transfected cells were separated by SDS-PAGE and the in-gel digested peptides were analyzed by nano-liquid chromatography tandem mass spectrometry (nanoLC-MS/MS). By comparing the proteome of cells with upregulated conditions of JTB vs control and identifying the protein dysregulation patterns, we aim to understand the function of this protein and its contribution to tumorigenesis. Gene Set Enrichment Analysis (GSEA) algorithm was performed to investigate the biological processes and pathways that are associated with the JTB protein upregulation. The results demonstrated four significantly enriched gene sets from the following significantly upregulated pathways: mitotic spindle assembly, estrogen response late, epithelial-to-mesenchymal transition (EMT) and estrogen response early. JTB protein itself is involved in mitotic spindle pathway by its role in cell division/cytokinesis, and within estrogen response early and late pathways, contributing to discrimination between luminal and mesenchymal breast cancer. Thus, the overexpressed JTB condition was significantly associated with an increased expression of ACTNs, FLNA, FLNB, EZR, MYOF, COL3A1, COL11A1, HSPA1A, HSP90A, WDR, EPPK1, FASN and FOXA1 proteins related to deregulation of cytoskeletal organization and biogenesis, mitotic spindle organization, ECM remodeling, cellular response to estrogen, proliferation, migration, metastasis, increased lipid biogenesis, endocrine therapy resistance, antiapoptosis and discrimination between different breast cancer subtypes. Other upregulated proteins for overexpressed JTB condition are involved in multiple cellular functions and pathways that become dysregulated, such as tumor microenvironment (TME) acidification, the transmembrane transport pathways, glycolytic flux, iron metabolism and oxidative stress, metabolic reprogramming, nucleocytosolic mRNA transport, transcriptional activation, chromatin remodeling, modulation of cell death pathways, stress responsive pathways, and cancer drug resistance. The downregulated proteins for overexpressed JTB condition are involved in adaptive communication between external and internal environment of cells and maintenance between pro-apoptotic and anti-apoptotic signaling pathways, vesicle trafficking and secretion, DNA lesions repair and suppression of genes involved in tumor progression, proteostasis, redox state regulation, biosynthesis of macromolecules, lipolytic pathway, carbohydrate metabolism, dysregulation of ubiquitin-mediated degradation system, cancer cell immune escape, cell-to-cell and cell-to-ECM interactions, and cytoskeletal behaviour. There were no significantly enriched downregulated pathways.

Tissue-Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach

Tissue-specific gene methylation events are key to the pathogenesis of several diseases and can be utilized for diagnosis and monitoring. Here, we established an in silico pipeline to analyze high-throughput methylome datasets to identify specific methylation fingerprints in three pathological entities of major burden, i.e., breast cancer (BrCa), osteoarthritis (OA) and diabetes mellitus (DM). Differential methylation analysis was conducted to compare tissues/cells related to the pathology and different types of healthy tissues, revealing Differentially Methylated Genes (DMGs). Highly performing and low feature number biosignatures were built with automated machine learning, including: (1) a five-gene biosignature discriminating BrCa tissue from healthy tissues (AUC 0.987 and precision 0.987), (2) three equivalent OA cartilage-specific biosignatures containing four genes each (AUC 0.978 and precision 0.986) and (3) a four-gene pancreatic β-cell-specific biosignature (AUC 0.984 and precision 0.995). Next, the BrCa biosignature was validated using an independent ccfDNA dataset showing an AUC and precision of 1.000, verifying the biosignature’s applicability in liquid biopsy. Functional and protein interaction prediction analysis revealed that most DMGs identified are involved in pathways known to be related to the studied diseases or pointed to new ones. Overall, our data-driven approach contributes to the maximum exploitation of high-throughput methylome readings, helping to establish specific disease profiles to be applied in clinical practice and to understand human pathology.

MALT1 is a Targetable Driver of Epithelial-to-Mesenchymal Transition in Claudin-low, Triple-Negative Breast Cancer

MALT1 is the effector protein of the CARMA/Bcl10/MALT1 (CBM) signalosome, a multi-protein complex that drives pro-inflammatory signaling pathways downstream of a diverse set of receptors. While CBM activity is best known for its role in immune cells, emerging evidence suggests that it plays a key role in the pathogenesis of solid tumors, where it can be activated by selected G protein-coupled receptors (GPCRs). Here, we demonstrated that overexpression of GPCRs implicated in breast cancer pathogenesis, specifically the receptors for Angiotensin II and thrombin (AT1R and PAR1), drove a strong epithelial-to-mesenchymal transition (EMT) program in breast cancer cells that is characteristic of claudin-low, triple-negative breast cancer (TNBC). In concert, MALT1 was activated in these cells and contributed to the dramatic EMT phenotypic changes through regulation of master EMT transcription factors including Snail and ZEB1. Importantly, blocking MALT1 signaling, through either siRNA-mediated depletion of MALT1 protein or pharmacologic inhibition of its activity, was effective at partially reversing the molecular and phenotypic indicators of EMT. Treatment of mice with mepazine, a pharmacologic MALT1 inhibitor, reduced growth of PAR1+, MDA-MB-231 xenografts and had an even more dramatic effect in reducing the burden of metastatic disease. These findings highlight MALT1 as an attractive therapeutic target for claudin-low TNBCs harboring overexpression of one or more selected GPCRs. Implications: This study nominates a GPCR/MALT1 signaling axis as a pathway that can be pharmaceutically targeted to abrogate EMT and metastatic progression in TNBC, an aggressive form of breast cancer that currently lacks targeted therapies.

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.

Targeting Gi/o protein-coupled receptor signaling blocks HER2-induced breast cancer development and enhances HER2-targeted therapy

GPCRs are highly desirable drug targets for human disease. Although GPCR dysfunction drives development and progression of many tumors, including breast cancer (BC), targeting individual GPCRs has limited efficacy as a cancer therapy because numerous GPCRs are activated. Here, we sought a new way of blocking GPCR activation in HER2⁺ BC by targeting a subgroup of GPCRs that couple to G_i/o proteins (G_i/o-GPCRs). In mammary epithelial cells of transgenic mouse models, and BC cell lines, HER2 hyperactivation altered GPCR expression, particularly, G_i/o-GPCR expression. G_i/o-GPCR stimulation transactivated EGFR and HER2 and activated the PI3K/AKT and Src pathways. If we uncoupled G_i/o-GPCRs from their cognate G_i/o proteins by pertussis toxin (PTx), then BC cell proliferation and migration was inhibited in vitro and HER2-driven tumor formation and metastasis were suppressed in vivo. Moreover, targeting G_i/o-GPCR signaling via PTx, PI3K, or Src inhibitors enhanced HER2-targeted therapy. These results indicate that, in BC cells, HER2 hyperactivation drives aberrant G_i/o-GPCR signaling and G_i/o-GPCR signals converge on the PI3K/AKT and Src signaling pathways to promote cancer progression and resistance to HER2-targeted therapy. Our findings point to a way to pharmacologically deactivate GPCR signaling to block tumor growth and enhance therapeutic efficacy.

Overexpression of β-Arrestins inhibits proliferation and motility in triple negative breast cancer cells

β-Arrestins (βArrs) are intracellular signal regulating proteins. Their expression level varies in some cancers and they have a significant impact on cancer cell function. In general, the significance of βArrs in cancer research comes from studies examining GPCR signalling. Given the diversity of different GPCR signals in cancer cell regulation, contradictory results are inevitable regarding the role of βArrs. Our approach examines the direct influence of βArrs on cellular function and gene expression profiles by changing their expression levels in breast cancer cells, MDA-MB-231 and MDA-MB-468. Reducing expression of βArr1 or βArr2 tended to increase cell proliferation and invasion whereas increasing their expression levels inhibited them. The overexpression of βArrs caused cell cycle S-phase arrest and differential expression of cell cycle genes, CDC45, BUB1, CCNB1, CCNB2, CDKN2C and reduced HER3, IGF-1R, and Snail. Regarding to the clinical relevance of our results, low expression levels of βArr1 were inversely correlated with CDC45, BUB1, CCNB1, and CCNB2 genes compared to normal tissue samples while positively correlated with poorer prognosis in breast tumours. These results indicate that βArr1 and βArr2 are significantly involved in cell cycle and anticancer signalling pathways through their influence on cell cycle genes and HER3, IGF-1R, and Snail in TNBC cells.

In silico molecular docking and physicochemical property studies on effective phytochemicals targeting GPR116 for breast cancer treatment

G protein-coupled receptor 116 (GPR116), an orphan adhesion receptor, found an important role in cell adhesion and migration in eukaryotes. Abnormal expression of GPCR identified in various cancers turns focus of research community towards GPCR to identify the targeting drug against GPCR. Though GPR116 role was studied in progression of metastasis in triple-negative breast cancer (TNBC), unfortunately, still no drugs targeting GPR116 were identified. TNBC is a hormone-negative aggressive breast cancer found even in young women. Since TNBC has no target receptor for therapy, it would be desirable to target GPR116. Currently, chemotherapy is the only promising option for TNBC; however, these drugs cause chemoresistance. Hence this current study concentrated on finding drugable natural phytochemical ligands targeting GPR116 using in silico approach. Best docked ligand with target and active binding site amino acids were identified in molecular docking study. Pharmacokinetic properties (ADME) were assessed by Qikprop. Result showed that pharmacokinetics properties of natural phytochemicals were as good as existing chemotherapeutic cancer drugs. This study indicates that phytochemicals could be a promising target for GPR116. This in silico analysis facilitates further research to design the drug targeting GPR116 for treatment of TNBC.

In silico structure prediction, molecular docking and dynamic simulation studies on G Protein-Coupled Receptor 116: a novel insight into breast cancer therapy

G Protein-Coupled Receptor gains more importance in cancer research; because of their key role in several physiologic functions of cells. However, most of the GPCR's are orphan receptors, this hampers the finding of drugs against GPCR. G Protein-Coupled Receptor 116 is an adhesion orphan receptor that intensifies the invasion of cells in Triple-Negative Breast Cancer. In this study, existing FDA approved anticancer drugs were chosen as ligands and molecular docking was performed using in silico protein model of GPR116. Molecular interaction was analyzed carefully to identify the crucial amino acids present in binding pocket. Molecular dynamics simulations study executed to verify the structural and dynamic properties of Doxorubicin-GPR116 protein complex. The results have shown that Doxorubicin, Neratinib maleate, Epirubicin, and Lapatinib Ditosylate have good interaction with GPR116 binding site. Tyrosine 195 (Y195), Cysteine 196 (C196), Argenine 197 (R197), and Tryptophan 100 (W100) are commonly found in the majority of ligand-target interaction, hence based on the computational studies selective amino acids might be crucial for functional properties. Further to confirm crucial amino acids, computational mutation studies were executed. Molecular docking analysis with mutated GPR116 disclosed that significant variation in G score compared withligand-native protein interaction. Hence, the theoretical confirmatory structural properties changes support to prove selective crucial amino acids play the significant role in ligand binding. Molecular dynamic simulation results reveal that the interaction was stable throughout the MD simulation. To the best of our prognosis, GPR116 could be the best molecular target for breast cancer drug discovery.Communicated by Ramaswamy H. Sarma.

Heterotrimeric Gq proteins as therapeutic targets?

Heterotrimeric G proteins are the core upstream elements that transduce and amplify the cellular signals from G protein-coupled receptors (GPCRs) to intracellular effectors. GPCRs are the largest family of membrane proteins encoded in the human genome and are the targets of about one-third of prescription medicines. However, to date, no single therapeutic agent exerts its effects via perturbing heterotrimeric G protein function, despite a plethora of evidence linking G protein malfunction to human disease. Several recent studies have brought to light that the Gq family-specific inhibitor FR900359 (FR) is unexpectedly efficacious in silencing the signaling of Gq oncoproteins, mutant Gq variants that mostly exist in the active state. These data not only raise the hope that researchers working in drug discovery may be able to potentially strike Gq oncoproteins from the list of undruggable targets, but also raise questions as to how FR achieves its therapeutic effect. Here, we place emphasis on these recent studies and explain why they expand our pharmacological armamentarium for targeting Gq protein oncogenes as well as broaden our mechanistic understanding of Gq protein oncogene function. We also highlight how this novel insight impacts the significance and utility of using G(q) proteins as targets in drug discovery efforts.

Targeting Opsin4/Melanopsin with a Novel Small Molecule Suppresses PKC/RAF/MEK/ERK Signaling and Inhibits Lung Adenocarcinoma Progression

The identification of oncogenic biomolecules as drug targets is an unmet need for the development of clinically effective novel anticancer therapies. In this study, we report for the first time that opsin 4/melanopsin (OPN4) plays a critical role in the pathogenesis of non-small cell lung cancer (NSCLC) and is a potential drug target. Our study has revealed that OPN4 is overexpressed in human lung cancer tissues and cells, and is inversely correlated with patient survival probability. Knocking down expression of OPN4 suppressed cells growth and induced apoptosis in lung cancer cells. We have also found that OPN4, a G protein-coupled receptor, interacted with Gα11 and triggered the PKC/BRAF/MEK/ERKs signaling pathway in lung adenocarcinoma cells. Genetic ablation of OPN4 attenuated the multiplicity and the volume of urethane-induced lung tumors in mice. Importantly, our study provides the first report of AE 51310 (1-[(2,5-dichloro-4-methoxyphenyl)sulfonyl]-3-methylpiperidine) as a small-molecule inhibitor of OPN4, suppressed the anchorage-independent growth of lung cancer cells and the growth of patient-derived xenograft tumors in mice. IMPLICATIONS: Overall, this study unveils the role of OPN4 in NSCLC and suggests that targeting OPN4 with small molecules, such as AE 51310 would be interesting to develop novel anticancer therapies for lung adenocarcinoma.

Identification of Genes with Prognostic Value in the Breast Cancer Microenvironment Using Bioinformatics Analysis

BACKGROUND Stromal and immune cells play essential roles in the development of breast cancer (BC). This study was conducted to identify prognosis-related genes from the tumor microenvironment. MATERIAL AND METHODS The gene expression profiles of 622 BC samples were downloaded from TCGA (The Cancer Genome Atlas) database. Stromal and immune scores were calculated by using the ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumours using Expression data) algorithm. Then, differentially expressed genes (DEGs) between the high score group and the low score group were screened. The intersecting DEGs were selected through Venn diagrams, and survival analysis was conducted. Functional and pathway enrichment analyses were performed using the DAVID (Database for Annotation, Visualization and Integrated Discovery), and a protein-protein interaction (PPI) network was constructed with the STRING database and Cytoscape. These genes were validated for prognostic value by use of the KM (Kaplan-Meier) plotter tool. RESULTS The low immune score group was associated with a poor prognosis. However, there was no difference in the prognosis between the high and low stromal score groups. A total of 248 intersecting DEGs were found in BC, and 61 genes were significantly associated with the prognosis of BC patients in the TCGA database. These genes were enriched in the immune response, components of the plasma membrane, and receptor activity. Furthermore, in the validation group, 31 of 61 genes were significantly associated with prognosis. CONCLUSIONS Our bioinformatics analysis identified 31 tumor microenvironment-related genes as potential prognostic predictors for breast cancer patients. Some of these genes that have not been widely investigated previously, such as CXCL9, GPR18, S1PR4, SASH3, and PYH1N1, might be additional predictive factors for BC patients.

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.

Targeting G protein-coupled receptors in cancer therapy

As basic research into GPCR signaling and its association with disease has come into fruition, greater clarity has emerged with regards to how these receptors may be amenable to therapeutic intervention. As a diverse group of receptor proteins, which regulate a variety of intracellular signaling pathways, research in this area has been slow to yield tangible therapeutic agents for the treatment of a number of diseases including cancer. However, recently such research has gained momentum based on a series of studies that have sought to define GPCR proteins dynamics through the elucidation of their crystal structures. In this chapter, we define the approaches that have been adopted in developing better therapeutics directed against the specific parts of the receptor proteins, such as the extracellular and the intracellular domains, including the ligands and auxiliary proteins that bind them. Finally, we also briefly outline how GPCR-derived signaling transduction pathways hold great potential as additional targets.

The Olfactory Receptor Family 2, Subfamily T, Member 6 (OR2T6) Is Involved in Breast Cancer Progression via Initiating Epithelial-Mesenchymal Transition and MAPK/ERK Pathway

Breast cancer is the most common female malignancy worldwide, however its molecular pathogenesis still needs in-depth investigation. Here we first revealed that the olfactory receptor family 2, subfamily T, member 6 (OR2T6) was significantly over-expressed in breast cancer tissues compared with normal breast tissues. OR2T6 expression was tightly correlated with higher TNM staging, positive lymph node metastasis, and associated with poorer patients' overall and disease-free survival. And OR2T6 enhanced the proliferation, invasion, and migration ability of breast cancer cell lines in vitro (MCF-7 and MDA-MD-231). Mechanically, it promoted the expression of mesenchymal markers (Vimentin, N-cadherin, and β-catenin) while inhibited E-cadherin expression, suggesting that OR2T6 played a key role in the regulation of epithelial-mesenchymal transition (EMT) process. Moreover, the human gene expression microarray clarified that MAPK/ERK pathway could be initiated by OR2T6 at mRNA level, which was further confirmed at protein level by western blot analysis. Thus, we concluded that OR2T6, as a novel oncogene, contributed to the progression of breast carcinoma by the initiation of EMT and MAPK/ERK pathway.

Regulator of G-protein signaling (RGS) proteins as drug targets: Progress and future potentials

G protein-coupled receptors (GPCRs) play critical roles in regulating processes such as cellular homeostasis, responses to stimuli, and cell signaling. Accordingly, GPCRs have long served as extraordinarily successful drug targets. It is therefore not surprising that the discovery in the mid-1990s of a family of proteins that regulate processes downstream of GPCRs generated great excitement in the field. This finding enhanced the understanding of these critical signaling pathways and provided potentially new targets for pharmacological intervention. These regulators of G-protein signaling (RGS) proteins were viewed by many as nodes downstream of GPCRs that could be targeted with small molecules to tune signaling processes. In this review, we provide a brief overview of the discovery of RGS proteins and of the gradual and continuing discovery of their roles in disease states, focusing particularly on cancer and neurological disorders. We also discuss high-throughput screening efforts that have led to the discovery first of peptide-based and then of small-molecule inhibitors targeting a subset of the RGS proteins. We explore the unique mechanisms of RGS inhibition these chemical tools have revealed and highlight the most up-to-date studies using these tools in animal experiments. Finally, we discuss the future opportunities in the field, as there are clearly more avenues left to be explored and potentials to be realized.

The Peptide ERα17p Is a GPER Inverse Agonist that Exerts Antiproliferative Effects in Breast Cancer Cells

The inhibition of the G protein-coupled estrogen receptor (GPER) offers promising perspectives for the treatment of breast tumors. A peptide corresponding to part of the hinge region/AF2 domain of the human estrogen receptor α (ERα17p, residues 295–311) exerts anti-proliferative effects in various breast cancer cells including those used as triple negative breast cancer (TNBC) models. As preliminary investigations have evoked a role for the GPER in the mechanism of action of this peptide, we focused our studies on this protein using SkBr3 breast cancer cells, which are ideal for GPER evaluation. ERα17p inhibits cell growth by targeting membrane signaling. Identified as a GPER inverse agonist, it co-localizes with GPER and induces the proteasome-dependent downregulation of GPER. It also decreases the level of pEGFR (phosphorylation of epidermal growth factor receptor), pERK1/2 (phosphorylation of extracellular signal-regulated kinase), and c-fos. ERα17p is rapidly distributed in mice after intra-peritoneal injection and is found primarily in the mammary glands. The N-terminal PLMI motif, which presents analogies with the GPER antagonist PBX1, reproduces the effect of the whole ERα17p. Thus, this motif seems to direct the action of the entire peptide, as highlighted by docking and molecular dynamics studies. Consequently, the tetrapeptide PLMI, which can be claimed as the first peptidic GPER disruptor, could open new avenues for specific GPER modulators.

Applications of machine learning in GPCR bioactive ligand discovery

GPCRs constitute the largest druggable family having targets for 475 Food and Drug Administration (FDA) approved drugs. As GPCRs are of great interest to pharmaceutical industry, enormous efforts are being expended to find relevant and potent GPCR ligands as lead compounds. There are tens of millions of compounds present in different chemical databases. In order to scan this immense chemical space, computational methods, especially machine learning (ML) methods, are essential components of GPCR drug discovery pipelines. ML approaches have applications in both ligand-based and structure-based virtual screening. We present here a cheminformatics overview of ML applications to different stages of GPCR drug discovery. Focusing on olfactory receptors, which are the largest family of GPCRs, a case study for predicting agonists for an ectopic olfactory receptor, OR1G1, compares four classical ML methods.