Genetic variations in the regulator of G-protein signaling genes are associated with survival in late-stage non-small cell lung cancer

Regulator of G protein signaling 1 is a potential target in gastric cancer and impacts tumor-associated macrophages

Regulator of G protein signaling 1 (RGS1) is closely associated with the tumor immune microenvironment and is highly expressed in various tumors and immune cells. The specific effects of RGS1 in the dynamic progression from chronic gastritis to gastric cancer have not been reported, and the role of tumor-associated macrophages (TAMs) is also unclear. In the present study, RGS1 was identified as an upregulated gene in different pathological stages ranging from chronic gastritis to gastric cancer by using Gene Expression Omnibus (GEO) screening together with pancancer analysis of The Cancer Genome Atlas and clinical prognostic analysis. The results indicated that RGS1 is highly expressed in gastric cancer and has potential prognostic value. We confirmed through in vivo experiments that RGS1 inhibited the proliferation of gastric cancer cells and promoted apoptosis, which was further corroborated by in vitro experiments. Additionally, RGS1 influenced cell migration and invasion. In our subsequent investigation of RGS1, we discovered its role in the immune response. Through analyses of single-cell and GEO database data, we confirmed its involvement in immune cell regulation, specifically TAM activation. Subsequently, we conducted in vivo and in vitro experiments to confirm the involvement of RGS1 in polarizing M1 macrophages while indirectly regulating M2 macrophages through tumor cells. In conclusion, RGS1 could be a potential target for the transformation of chronic gastritis into gastric cancer and has a measurable impact on TAMs, which warrants further in-depth research.

Blood regulator of G protein signalling 1 as a potential prognostic biomarker in surgical nonsmall cell lung cancer patients: Correlation with clinical features and survival

INTRODUCTION

Regulator of G protein signalling 1 (RGS1) closely regulates malignant phenotypes and tumour immunity in several cancers, while its clinical value in nonsmall cell lung cancer (NSCLC) is by far rarely reported. Consequently, this study aimed to explore the linkage of blood RGS1 with clinical features and prognosis in surgical NSCLC patients.

METHODS

Two-hundred and ten surgical NSCLC patients were consecutively enrolled in this study, whose RGS1 in peripheral blood mononuclear cells was determined before treatment via reverse transcriptional-quantitative polymerase chain reaction. Additionally, the blood RGS1 was also collected from 30 healthy controls (HCs).

RESULTS

Blood RGS1 was increased in NSCLC patients compared with HCs (P < 0.001). Elevated blood RGS1 was related to lymph node (LYN) metastasis (P = 0.001), higher tumour-nodes-metastasis (TNM) stage (P = 0.004), neoadjuvant chemotherapy administration (P = 0.044), shortened accumulative disease-free survival (DFS) (P = 0.008) and overall survival (OS) (P = 0.013) in NSCLC patients. A multivariate Cox's regression analysis showed that blood RGS1 high expression could independently reflect shortened DFS (hazard ratio = 1.499, P = 0.023), whereas it could not independently predict OS (P > 0.050). Furthermore, blood RGS1 high expression was associated with shortened OS (P = 0.020) in patients with neoadjuvant therapy and with worse DFS (P = 0.028) and OS (P = 0.026) in patients with adjuvant therapy, while blood RGS1 was not linked with DFS or OS in patients without neoadjuvant or adjuvant therapy (all P > 0.050).

CONCLUSION

Elevated blood RGS1 correlates with LYN metastasis, neoadjuvant chemotherapy administration, worse DFS and OS, which might serve as a useful prognostic biomarker for surgical NSCLC patients.

Tumor-intrinsic RGS1 potentiates checkpoint blockade response via ATF3-IFNGR1 axis

Background

Non-responsiveness is a major barrier in current cancer immune checkpoint blockade therapies, and the mechanism has not been elucidated yet. Therefore, it is necessary to discover the mechanism and biomarkers of tumor immunotherapeutic resistance.

Methods

Bioinformatics analysis was performed based on CD8+ T cell infiltration in multiple tumor databases to screen out genes related to anti-tumor immunity. Associations between Regulator of G-protein signaling 1 (RGS1) and IFNγ-STAT1 signaling, and MHCI antigen presentation pathway were examined by RT-qPCR, western blotting, and flow cytometry. The modulatory mechanisms of RGS1 were investigated via CHIP-qPCR and dual-luciferase assay. The clinical and therapeutic implications of RGS1 were comprehensively investigated using tumor cell lines, mouse models, and clinical samples receiving immunotherapy.

Results

RGS1 was identified as the highest gene positively correlated with immunogenicity among RGS family. Inhibition of RGS1 in neoplastic cells dampened anti-tumor immune response and elicited resistance to immunotherapy in both renal and lung murine subcutaneous tumors. Mechanistically, RGS1 enhanced the binding of activating transcription factor 3 (ATF3) to the promoter of interferon gamma receptor 1 (IFNGR1), activated STAT1 and the subsequent expression of IFNγ-inducible genes, especially CXCL9 and MHC class I (MHCI), thereby influenced CD8+ T cell infiltration and antigen presentation and processing. Clinically, lower expression level of RGS1 was associated with resistance of PD1 inhibition therapy and shortened progression-free survival among 21 NSCLC patients receiving immunotherapy.

Conclusions

Together, these findings uncover a novel mechanism that elicits immunotherapy resistance and highlight the function of tumor-intrinsic RGS1, which brings new insights for future strategies to sensitize anti-PD1 immunotherapy.

Thrombogenesis-associated genetic determinants as predictors of thromboembolism and prognosis in cervical cancer

Venous thromboembolism (VTE) is a leading cause of death among cancer patients. Khorana score (KS) is the most studied tool to predict cancer-related VTE, however, it exerts poor sensitivity. Several single-nucleotide polymorphisms (SNPs) have been associated with VTE risk in the general population, but whether they are predictors of cancer-related VTE is a matter of discussion. Compared to other solid tumours, little is known about VTE in the setting of cervical cancer (CC) and whether thrombogenesis-related polymorphisms could be valuable biomarkers in patients with this neoplasia. This study aims to analyse the effect of VTE occurrence on the prognosis of CC patients, explore the predictive capability of KS and the impact of thrombogenesis-related polymorphisms on CC-related VTE incidence and patients' prognosis regardless of VTE. A profile of eight SNPs was evaluated. A retrospective hospital-based cohort study was conducted with 400 CC patients under chemoradiotherapy. SNP genotyping was carried on by using TaqMan® Allelic Discrimination methodology. Time to VTE occurrence and overall survival were the two measures of clinical outcome evaluated. The results indicated that VTE occurrence (8.5%) had a significant impact on the patient's survival (log-rank test, P < 0.001). KS showed poor performance (KS ≥ 3, χ², P = 0.191). PROCR rs10747514 and RGS7 rs2502448 were significantly associated with the risk of CC-related VTE development (P = 0.021 and P = 0.006, respectively) and represented valuable prognostic biomarkers regardless of VTE (P = 0.004 and P = 0.010, respectively). Thus, thrombogenesis-related genetic polymorphisms may constitute valuable biomarkers among CC patients allowing a more personalized clinical intervention.

A RGS7-CaMKII complex drives myocyte-intrinsic and myocyte-extrinsic mechanisms of chemotherapy-induced cardiotoxicity

Dose-limiting cardiotoxicity remains a major limitation in the clinical use of cancer chemotherapeutics. Here, we describe a role for Regulator of G protein Signaling 7 (RGS7) in chemotherapy-dependent heart damage, the demonstration for a functional role of RGS7 outside of the nervous system and retina. Though expressed at low levels basally, we observed robust up-regulation of RGS7 in the human and murine myocardium following chemotherapy exposure. In ventricular cardiomyocytes (VCM), RGS7 forms a complex with Ca²⁺/calmodulin-dependent protein kinase (CaMKII) supported by key residues (K412 and P391) in the RGS domain of RGS7. In VCM treated with chemotherapeutic drugs, RGS7 facilitates CaMKII oxidation and phosphorylation and CaMKII-dependent oxidative stress, mitochondrial dysfunction, and apoptosis. Cardiac-specific RGS7 knockdown protected the heart against chemotherapy-dependent oxidative stress, fibrosis, and myocyte loss and improved left ventricular function in mice treated with doxorubicin. Conversely, RGS7 overexpression induced fibrosis, reactive oxygen species generation, and cell death in the murine myocardium that were mitigated following CaMKII inhibition. RGS7 also drives production and release of the cardiokine neuregulin-1, which facilitates paracrine communication between VCM and neighboring vascular endothelial cells (EC), a maladaptive mechanism contributing to VCM dysfunction in the failing heart. Importantly, while RGS7 was both necessary and sufficient to facilitate chemotherapy-dependent cytotoxicity in VCM, RGS7 is dispensable for the cancer-killing actions of these same drugs. These selective myocyte-intrinsic and myocyte-extrinsic actions of RGS7 in heart identify RGS7 as an attractive therapeutic target in the mitigation of chemotherapy-driven cardiotoxicity.

Functional Assessment of Cancer-Linked Mutations in Sensitive Regions of Regulators of G Protein Signaling Predicted by Three-Dimensional Missense Tolerance Ratio Analysis

Regulators of G protein signaling (RGS) proteins modulate G protein-coupled receptor (GPCR) signaling by acting as negative regulators of G proteins. Genetic variants in RGS proteins are associated with many diseases, including cancers, although the impact of these mutations on protein function is uncertain. Here we analyze the RGS domains of 15 RGS protein family members using a novel bioinformatic tool that measures the missense tolerance ratio (MTR) using a three-dimensional (3D) structure (3DMTR). Subsequent permutation analysis can define the protein regions that are most significantly intolerant (P < 0.05) in each dataset. We further focused on RGS14, RGS10, and RGS4. RGS14 exhibited seven significantly tolerant and seven significantly intolerant residues, RGS10 had six intolerant residues, and RGS4 had eight tolerant and six intolerant residues. Intolerant and tolerant-control residues that overlap with pathogenic cancer mutations reported in the COSMIC cancer database were selected to define the functional phenotype. Using complimentary cellular and biochemical approaches, proteins were tested for effects on GPCR-Gα activation, Gα binding properties, and downstream cAMP levels. Identified intolerant residues with reported cancer-linked mutations RGS14-R173C/H and RGS4-K125Q/E126K, and tolerant RGS14-S127P and RGS10-S64T resulted in a loss-of-function phenotype in GPCR-G protein signaling activity. In downstream cAMP measurement, tolerant RGS14-D137Y and RGS10-S64T and intolerant RGS10-K89M resulted in change of function phenotypes. These findings show that 3DMTR identified intolerant residues that overlap with cancer-linked mutations cause phenotypic changes that negatively impact GPCR-G protein signaling and suggests that 3DMTR is a potentially useful bioinformatics tool for predicting functionally important protein residues. SIGNIFICANCE STATEMENT: Human genetic variant/mutation information has expanded rapidly in recent years, including cancer-linked mutations in regulator of G protein signaling (RGS) proteins. However, experimental testing of the impact of this vast catalogue of mutations on protein function is not feasible. We used the novel bioinformatics tool three-dimensional missense tolerance ratio (3DMTR) to define regions of genetic intolerance in RGS proteins and prioritize which cancer-linked mutants to test. We found that 3DMTR more accurately classifies loss-of-function mutations in RGS proteins than other databases thereby offering a valuable new research tool.

Single-Cell Transcriptome Analysis Reveals RGS1 as a New Marker and Promoting Factor for T-Cell Exhaustion in Multiple Cancers

T-cell exhaustion is one of the main reasons of tumor immune escape. Using single-cell transcriptome data of CD8+ T cells in multiple cancers, we identified different cell types, in which Pre_exhaust and exhausted T cells participated in negative regulation of immune system process. By analyzing the coexpression network patterns and differentially expressed genes of Pre_exhaust, exhausted, and effector T cells, we identified 35 genes related to T-cell exhaustion, whose high GSVA scores were associated with significantly poor prognosis in various cancers. In the differentially expressed genes, RGS1 showed the greatest fold change in Pre_exhaust and exhausted cells of three cancers compared with effector T cells, and high expression of RGS1 was also associated with poor prognosis in various cancers. Additionally, RGS1 protein was upregulated significantly in tumor tissues in the immunohistochemistry verification. Furthermore, RGS1 displayed positive correlation with the 35 genes, especially highly correlated with PDCD1, CTLA4, HAVCR2, and TNFRSF9 in CD8+ T cells and cancer tissues, indicating the important roles of RGS1 in CD8+ T-cell exhaustion. Considering the GTP-hydrolysis activity of RGS1 and significantly high mRNA and protein expression in cancer tissues, we speculated that RGS1 potentially mediate the T-cell retention to lead to the persistent antigen stimulation, resulting in T-cell exhaustion. In conclusion, our findings suggest that RGS1 is a new marker and promoting factor for CD8+ T-cell exhaustion and provide theoretical basis for research and immunotherapy of exhausted cells.

Regulator of G protein signaling 10: Structure, expression and functions in cellular physiology and diseases

Regulator of G protein signaling 10 (RGS10) belongs to the superfamily of RGS proteins, defined by the presence of a conserved RGS domain that canonically binds and deactivates heterotrimeric G-proteins. RGS proteins act as GTPase activating proteins (GAPs), which accelerate GTP hydrolysis on the G-protein α subunits and result in termination of signaling pathways downstream of G protein-coupled receptors. RGS10 is the smallest protein of the D/R12 subfamily and selectively interacts with Gαi proteins. It is widely expressed in many cells and tissues, with the highest expression found in the brain and immune cells. RGS10 expression is transcriptionally regulated via epigenetic mechanisms. Although RGS10 lacks multiple of the defined regulatory domains found in other RGS proteins, RGS10 contains post-translational modification sites regulating its expression, localization, and function. Additionally, RGS10 is a critical protein in the regulation of physiological processes in multiple cells, where dysregulation of its expression has been implicated in various diseases including Parkinson's disease, multiple sclerosis, osteopetrosis, chemoresistant ovarian cancer and cardiac hypertrophy. This review summarizes RGS10 features and its regulatory mechanisms, and discusses the known functions of RGS10 in cellular physiology and pathogenesis of several diseases.

Genetic Analysis of Rare Human Variants of Regulators of G Protein Signaling Proteins and Their Role in Human Physiology and Disease

Regulators of G protein signaling (RGS) proteins modulate the physiologic actions of many neurotransmitters, hormones, and other signaling molecules. Human RGS proteins comprise a family of 20 canonical proteins that bind directly to G protein-coupled receptors/G protein complexes to limit the lifetime of their signaling events, which regulate all aspects of cell and organ physiology. Genetic variations account for diverse human traits and individual predispositions to disease. RGS proteins contribute to many complex polygenic human traits and pathologies such as hypertension, atherosclerosis, schizophrenia, depression, addiction, cancers, and many others. Recent analysis indicates that most human diseases are due to extremely rare genetic variants. In this study, we summarize physiologic roles for RGS proteins and links to human diseases/traits and report rare variants found within each human RGS protein exome sequence derived from global population studies. Each RGS sequence is analyzed using recently described bioinformatics and proteomic tools for measures of missense tolerance ratio paired with combined annotation-dependent depletion scores, and protein post-translational modification (PTM) alignment cluster analysis. We highlight selected variants within the well-studied RGS domain that likely disrupt RGS protein functions and provide comprehensive variant and PTM data for each RGS protein for future study. We propose that rare variants in functionally sensitive regions of RGS proteins confer profound change-of-function phenotypes that may contribute, in newly appreciated ways, to complex human diseases and/or traits. This information provides investigators with a valuable database to explore variation in RGS protein function, and for targeting RGS proteins as future therapeutic targets.

Overexpression of regulator of G protein signaling 11 promotes cell migration and associates with advanced stages and aggressiveness of lung adenocarcinoma

Regulator of G protein signaling 11 (RGS11), a member of the R7 subfamily of RGS proteins, is a well-characterized GTPase-accelerating protein that is involved in the heterotrimeric G protein regulation of the amplitude and kinetics of receptor-promoted signaling in retinal bipolar and nerve cells. However, the role of RGS11 in cancer is completely unclear. Using subtractive hybridization analysis, we found that RGS11 was highly expressed in the lymph-node metastatic tissues and bone-metastatic tumors obtained from patients with lung adenocarcinoma. Characterization of the clinicopathological features of 91 patients showed that around 57.1% of the tumor samples displayed RGS11 overexpression that was associated with primary tumor status, nodal metastasis and increased disease stages. Its high expression was an independent predictive factor for poor prognosis of these patients. Cotransfection of guanine nucleotide-binding protein beta-5 (GNB5) markedly increased RGS11 expression. Enhancement or attenuation of RGS11 expression pinpointed its specific role in cell migration, but not in cell invasion and proliferation. Signaling events initiated by the RGS11–GNB5 coexpression activated the c-Raf/ERK/FAK-mediated pathway through upregulation of the Rac1 activity. Consistently, increasing the cell invasiveness of the transfectants by additional cotransfection of the exogenous urokinase–plasminogen activator gene caused a significant promotion in cell invasion in vitro and in vivo, confirming that RGS11 functions in cell migration, but requires additional proteolytic activity for cell and tissue invasion. Collectively, overexpression of RGS11 promotes cell migration, participates in tumor metastasis, and correlates the clinicopathological conditions of patients with lung adenocarcinoma.

Non-small-cell lung cancer pathological subtype-related gene selection and bioinformatics analysis based on gene expression profiles

Lung cancer is one of the most common malignant diseases and a major threat to public health on a global scale. Non-small-cell lung cancer (NSCLC) has a higher degree of malignancy and a lower 5-year survival rate compared with that of small-cell lung cancer. NSCLC may be mainly divided into two pathological subtypes, adenocarcinoma and squamous cell carcinoma. The aim of the present study was to identify disease genes based on the gene expression profile and the shortest path analysis of weighted functional protein association networks with the existing protein-protein interaction data from the Search Tool for the Retrieval of Interacting Genes. The gene expression profile (GSE10245) was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database, including 40 lung adenocarcinoma and 18 lung squamous cell carcinoma tissues. A total of 8 disease genes were identified using Naïve Bayesian Classifier based on the Maximum Relevance Minimum Redundancy feature selection method following preprocessing. An additional 21 candidate genes were selected using the shortest path analysis with Dijkstra's algorithm. The AURKA and SLC7A2 genes were selected three and two times in the shortest path analysis, respectively. All those genes participate in a number of important pathways, such as oocyte meiosis, cell cycle and cancer pathways with Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. The present findings may provide novel insights into the pathogenesis of NSCLC and enable the development of novel therapeutic strategies. However, further investigation is required to confirm these findings.

NanoString-based breast cancer risk prediction for women with sclerosing adenosis

Purpose

Sclerosing adenosis (SA), found in ¼ of benign breast disease (BBD) biopsies, is a histological feature characterized by lobulocentric proliferation of acini and stromal fibrosis and confers a two-fold increase in breast cancer risk compared to women in the general population. We evaluated a NanoString-based gene expression assay to model breast cancer risk using RNA derived from formalin-fixed, paraffin-embedded (FFPE) biopsies with SA.

Methods

The study group consisted of 151 women diagnosed with SA between 1967 and 2001 within the Mayo BBD cohort, of which 37 subsequently developed cancer within 10 years (cases) and 114 did not (controls). RNA was isolated from benign breast biopsies, and NanoString-based methods were used to assess expression levels of 61 genes, including 35 identified by previous array-based profiling experiments and 26 from biological insight. Diagonal linear discriminant analysis of these data was used to predict cancer within 10 years. Predictive performance was assessed with receiver operating characteristic area under the curve (ROC-AUC) values estimated from 5-fold cross-validation.

Results

Gene expression prediction models achieved cross-validated ROC-AUC estimates ranging from 0.66 to 0.70. Performing univariate associations within each of the five folds consistently identified genes DLK2, EXOC6, KIT, RGS12, and SORBS2 as significant; a model with only these five genes showed cross-validated ROC-AUC of 0.75, which compared favorably to risk prediction using established clinical models (Gail/BCRAT: 0.57; BBD-BC: 0.67).

Conclusions

Our results demonstrate that biomarkers of breast cancer risk can be detected in benign breast tissue years prior to cancer development in women with SA. These markers can be assessed using assay methods optimized for RNA derived from FFPE biopsy tissues which are commonly available.

Electronic supplementary material

The online version of this article (doi:10.1007/s10549-017-4441-z) contains supplementary material, which is available to authorized users.

RGS12 Is a Novel Tumor-Suppressor Gene in African American Prostate Cancer That Represses AKT and MNX1 Expression

African American (AA) men exhibit a relatively high incidence and mortality due to prostate cancer even after adjustment for socioeconomic factors, but the biological basis for this disparity is unclear. Here, we identify a novel region on chromosome 4p16.3 that is lost selectively in AA prostate cancer. The negative regulator of G-protein signaling RGS12 was defined as the target of 4p16.3 deletions, although it has not been implicated previously as a tumor-suppressor gene. RGS12 transcript levels were relatively reduced in AA prostate cancer, and prostate cancer cell lines showed decreased RGS12 expression relative to benign prostate epithelial cells. Notably, RGS12 exhibited potent tumor-suppressor activity in prostate cancer and prostate epithelial cell lines in vitro and in vivo We found that RGS12 expression correlated negatively with the oncogene MNX1 and regulated its expression in vitro and in vivo Further, MNX1 was regulated by AKT activity, and RGS12 expression decreased total and activated AKT levels. Our findings identify RGS12 as a candidate tumor-suppressor gene in AA prostate cancer, which acts by decreasing expression of AKT and MNX1, establishing a novel oncogenic axis in this disparate disease setting. Cancer Res; 77(16); 4247-57. ©2017 AACR.

RGS6 as a Novel Therapeutic Target in CNS Diseases and Cancer

Regulator of G protein signaling (RGS) proteins are gatekeepers regulating the cellular responses induced by G protein-coupled receptor (GPCR)-mediated activation of heterotrimeric G proteins. Specifically, RGS proteins determine the magnitude and duration of GPCR signaling by acting as a GTPase-activating protein for Gα subunits, an activity facilitated by their semiconserved RGS domain. The R7 subfamily of RGS proteins is distinguished by two unique domains, DEP/DHEX and GGL, which mediate membrane targeting and stability of these proteins. RGS6, a member of the R7 subfamily, has been shown to specifically modulate Gαi/o protein activity which is critically important in the central nervous system (CNS) for neuronal responses to a wide array of neurotransmitters. As such, RGS6 has been implicated in several CNS pathologies associated with altered neurotransmission, including the following: alcoholism, anxiety/depression, and Parkinson's disease. In addition, unlike other members of the R7 subfamily, RGS6 has been shown to regulate G protein-independent signaling mechanisms which appear to promote both apoptotic and growth-suppressive pathways that are important in its tumor suppressor function in breast and possibly other tissues. Further highlighting the importance of RGS6 as a target in cancer, RGS6 mediates the chemotherapeutic actions of doxorubicin and blocks reticular activating system (Ras)-induced cellular transformation by promoting degradation of DNA (cytosine-5)-methyltransferase 1 (DNMT1) to prevent its silencing of pro-apoptotic and tumor suppressor genes. Together, these findings demonstrate the critical role of RGS6 in regulating both G protein-dependent CNS pathology and G protein-independent cancer pathology implicating RGS6 as a novel therapeutic target.

Regulated genes in mesenchymal stem cells and gastric cancer

AIM: To investigate the genes regulated in mesenchymal stem cells (MSCs) and diffuse-type gastric cancer (GC), gene expression was analyzed.

METHODS: Gene expression of MSCs and diffuse-type GC cells were analyzed by microarray. Genes related to stem cells, cancer and the epithelial-mesenchymal transition (EMT) were extracted from human gene lists using Gene Ontology and reference information. Gene panels were generated, and messenger RNA gene expression in MSCs and diffuse-type GC cells was analyzed. Cluster analysis was performed using the NCSS software.

RESULTS: The gene expression of regulator of G-protein signaling 1 (RGS1) was up-regulated in diffuse-type GC cells compared with MSCs. A panel of stem-cell related genes and genes involved in cancer or the EMT were examined. Stem-cell related genes, such as growth arrest-specific 6, musashi RNA-binding protein 2 and hairy and enhancer of split 1 (Drosophila), NOTCH family genes and Notch ligands, such as delta-like 1 (Drosophila) and Jagged 2, were regulated.

CONCLUSION: Expression of RGS1 is up-regulated, and genes related to stem cells and NOTCH signaling are altered in diffuse-type GC compared with MSCs.

TINAGL1 and B3GALNT1 are potential therapy target genes to suppress metastasis in non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC) remains lethal despite the development of numerous drug therapy technologies. About 85% to 90% of lung cancers are NSCLC and the 5-year survival rate is at best still below 50%. Thus, it is important to find drugable target genes for NSCLC to develop an effective therapy for NSCLC.

Results

Integrated analysis of publically available gene expression and promoter methylation patterns of two highly aggressive NSCLC cell lines generated by in vivo selection was performed. We selected eleven critical genes that may mediate metastasis using recently proposed principal component analysis based unsupervised feature extraction. The eleven selected genes were significantly related to cancer diagnosis. The tertiary protein structure of the selected genes was inferred by Full Automatic Modeling System, a profile-based protein structure inference software, to determine protein functions and to specify genes that could be potential drug targets.

Conclusions

We identified eleven potentially critical genes that may mediate NSCLC metastasis using bioinformatic analysis of publically available data sets. These genes are potential target genes for the therapy of NSCLC. Among the eleven genes, TINAGL1 and B3GALNT1 are possible candidates for drug compounds that inhibit their gene expression.

S-score: a scoring system for the identification and prioritization of predicted cancer genes

A new method, which allows for the identification and prioritization of predicted cancer genes for future analysis, is presented. This method generates a gene-specific score called the “S-Score” by incorporating data from different types of analysis including mutation screening, methylation status, copy-number variation and expression profiling. The method was applied to the data from The Cancer Genome Atlas and allowed the identification of known and potentially new oncogenes and tumor suppressors associated with different clinical features including shortest term of survival in ovarian cancer patients and hormonal subtypes in breast cancer patients. Furthermore, for the first time a genome-wide search for genes that behave as oncogenes and tumor suppressors in different tumor types was performed. We envisage that the S-score can be used as a standard method for the identification and prioritization of cancer genes for follow-up studies.

Methylation profiling and evaluation of demethylating therapy in renal cell carcinoma

BACKGROUND

Despite therapeutic advances in targeted therapy, metastatic renal cell carcinoma (RCC) remains incurable for the vast majority of patients. Key molecular events in the pathogenesis of RCC include inactivation of the VHL tumour suppressor gene (TSG), inactivation of chromosome 3p TSGs implicated in chromatin modification and remodelling and de novo tumour-specific promoter methylation of renal TSGs. In the light of these observations it can be proposed that, as in some haematological malignancies, demethylating agents such as azacitidine might be beneficial for the treatment of advanced RCC.

RESULTS

Here we report that the treatment of RCC cell lines with azacitidine suppressed cell proliferation in all 15 lines tested. A marked response to azacitidine therapy (>50% reduction in colony formation assay) was detected in the three cell lines with VHL promoter methylation but some RCC cell lines without VHL TSG methylation also demonstrated a similar response suggesting that multiple methylated TSGs might determine the response to demethylating therapies. To identify novel candidate methylated TSGs implicated in RCC we undertook a combined analysis of copy number and CpG methylation array data. Candidate novel epigenetically inactivated TSGs were further prioritised by expression analysis of RCC cell lines pre and post-azacitidine therapy and comparative expression analysis of tumour/normal pairs. Thus, with subsequent investigation two candidate genes were found to be methylated in more than 25% of our series and in the TCGA methylation dataset for 199 RCC samples: RGS7 (25.6% and 35.2% of tumours respectively) and NEFM in (25.6% and 30.2%). In addition three candidate genes were methylated in >10% of both datasets (TMEM74 (15.4% and 14.6%), GCM2 (41.0% and 14.6%) and AEBP1 (30.8% and 13.1%)). Methylation of GCM2 (P = 0.0324), NEFM (P = 0.0024) and RGS7 (P = 0.0067) was associated with prognosis.

CONCLUSIONS

These findings provide preclinical evidence that treatment with demethylating agents such as azacitidine might be useful for the treatment of advanced RCC and further insights into the role of epigenetic changes in the pathogenesis of RCC.

A large scale gene-centric association study of lung function in newly-hired female cotton textile workers with endotoxin exposure

Background

Occupational exposure to endotoxin is associated with decrements in pulmonary function, but how much variation in this association is explained by genetic variants is not well understood.

Objective

We aimed to identify single nucleotide polymorphisms (SNPs) that are associated with the rate of forced expiratory volume in one second (FEV₁) decline by a large scale genetic association study in newly-hired healthy young female cotton textile workers.

Methods

DNA samples were genotyped using the Illumina Human CVD BeadChip. Change rate in FEV₁ was modeled as a function of each SNP genotype in linear regression model with covariate adjustment. We controlled the type 1 error in study-wide level by permutation method. The false discovery rate (FDR) and the family-wise error rate (FWER) were set to be 0.10 and 0.15 respectively.

Results

Two SNPs were found to be significant (P<6.29×10⁻⁵), including rs1910047 (P = 3.07×10⁻⁵, FDR = 0.0778) and rs9469089 (P = 6.19×10⁻⁵, FDR = 0.0967), as well as other eight suggestive (P<5×10⁻⁴) associated SNPs. Gene-gene and gene-environment interactions were also observed, such as rs1910047 and rs1049970 (P = 0.0418, FDR = 0.0895); rs9469089 and age (P = 0.0161, FDR = 0.0264). Genetic risk score analysis showed that the more risk loci the subjects carried, the larger the rate of FEV₁ decline occurred (P_trend = 3.01×10⁻¹⁸). However, the association was different among age subgroups (P = 7.11×10⁻⁶) and endotoxin subgroups (P = 1.08×10⁻²). Functional network analysis illustrates potential biological connections of all interacted genes.

Conclusions

Genetic variants together with environmental factors interact to affect the rate of FEV₁ decline in cotton textile workers.

Common genetic variants in cell cycle pathway are associated with survival in stage III-IV non-small-cell lung cancer

Cell cycle progression contributes to the cellular response to DNA-damaging factors, such as chemotherapy and radiation. We hypothesized that the genetic variations in cell cycle pathway genes may modulate treatment responses and affect survival in patients with advanced non-small-cell lung cancer (NSCLC). We genotyped 374 single-nucleotide polymorphisms (SNPs) from 49 cell cycle-related genes in 598 patients with stages III-IV NSCLC treated with first-line platinum-based chemotherapy with/without radiation. We analyzed the individual and combined associations of these SNPs with survival and evaluated their gene-gene interactions using survival tree analysis. In the analysis of survival in all the patients, 39 SNPs reached nominal significance (P < 0.05) and 4 SNPs were significant at P <0.01. However, none of these SNPs remained significant after correction for multiple comparisons at a false discovery rate of 10%. In stratified analysis by treatment modality, after adjusting for multiple comparisons, nine SNPs in chemotherapy alone and one SNP in chemoradiation remained significant. The most significant SNP in chemotherapy group was CCNB2:rs1486878 [hazard ratio (HR) = 1.69, 95% confidence interval (CI), 1.25-2.30, P = 0.001]. TP73: rs3765701 was the only significant SNP in chemoradiation group (HR = 1.87; 95% CI = 1.35-2.59, P = 1.8 × 10(-4)). In cumulative analysis, we found a significant gene-dosage effect in patients receiving chemotherapy alone. Survival tree analysis demonstrated potential higher order gene-gene and gene-treatment interactions, which could be used to predict survival status based on distinct genetic signatures. These results suggest that genetic variations in cell cycle pathway genes may affect the survival of patients with stages III-IV NSCLC individually and jointly.