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Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. The aim of this study is to identify the diagnostic and poor prognostic signatures in TNBC by exploring the aberrant DNA methylation and gene expression. Differential expression and methylation analysis of the TNBC and paracancer samples from The Cancer Genome Atlas were performed. Gene set enrichment and protein-protein interaction (PPI) network analysis was used to explore the mechanisms of TNBC. Methylation-gene expression correlation analysis was performed, and multivariate Cox analysis and receiver operating characteristics analysis were used to further screen the hub genes for TNBC. We identified 1,525 differentially expressed genes and 150 differentially methylated genes between TNBC and paracancer samples. About 96.64% of the methylation sites were located on the CpG island. A total of 17 Gene Ontology biological process terms and 18 signal pathways were significantly enriched. GNG4, GNG11, PENK, MAOA, and AOX1 were identified as the core genes of the PPI network. Methylation-expression correlations revealed that ABCC9 (cg06951626), NKAPL (cg18675097, cg01031101, and cg17384889), and TMEM132C (cg03530754) showed promise as diagnostic and prognostic markers in TNBC. ABCC9 (cg06951626), NKAPL (cg18675097, cg01031101, and cg17384889), and TMEM132C (cg03530754) were potential diagnostic and prognostic markers in TNBC.

Cervical cancer (CC) is one kind of female cancer. With the development of bioinformatics, targeted specific biomarkers therapy has become much more valuable. GSE26511 was obtained from gene expression omnibus (GEO). We utilized a package called "WGCNA" to build co-expression network and choose the hub module. Search Tool for the Retrieval of Interacting Genes Database (STRING) was used to analyze protein-protein interaction (PPI) information of those genes in the hub module. A Plug-in called MCODE was utilized to choose hub clusters of PPI network, which was visualized in Cytoscape. Clusterprofiler was used to do functional analysis. Univariate and multivariate cox proportional hazards regression analysis were both conducted to predict the risk score of CC patients. Kaplan-Meier curve analysis was done to show the overall survival. Receiver operating characteristic (ROC) curve analysis was utilized to evaluate the predictive value of the patient outcome. Validation of the hub gene in databases, Gene set enrichment analysis (GSEA) and GEPIA were completed. We built co-expression network based on GSE26511 and one CC-related module was identified. Functional analysis of this module showed that extracellular space and Signaling pathways regulating pluripotency of stem cells were most related pathways. PPI network screened GNG11 as the most valuable protein. Cox analysis showed that ACKR1 was negatively correlated with CC progression, which was validated in Gene Expression Profiling Interactive Analysis (GEPIA) and datasets. Survival analysis was performed and showed the consistent result. GSEA set enrichment analysis was also completed. This study showed hub functional terms and gene participated in CC and then speculated that ACKR1 might be tumor suppressor for CC.

PurposeThe molecular mechanism underlying the carcinogenesis and development of lung squamous cell carcinoma (LUSC) has not been sufficiently elucidated. This analysis was performed to find pivotal genes and explore their prognostic roles in LUSC.MethodsA microarray dataset from GEO (GSE19188) and a TCGA-LUSC dataset were used to identify differentially co-expressed genes through Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. We conducted functional enrichment analyses of differentially co-expressed genes and established a protein-protein interaction (PPI) network. Then, we identified the top 10 hub genes using the Maximal Clique Centrality (MCC) algorithm. We performed overall survival (OS) analysis of these hub genes among LUSC cases. GSEA analyses of survival-related hub genes were conducted. Ultimately, the GEO and The Human Protein Atlas (THPA) databases and immunohistochemistry (IHC) results from the real world were used to verify our findings.ResultsA list of 576 differentially co-expressed genes were selected. Functional enrichment analysis indicated that regulation of vasculature development, cell−cell junctions, actin binding and PPAR signaling pathways were mainly enriched. The top 10 hub genes were selected according to the ranking of MCC scores, and 5 genes were closely correlated with OS of LUSC. Additionally, GSEA analysis showed that spliceosome and cell adhesion molecules were associated with the expression of GNG11 and ADCY4, respectively. The GSE30219 and THPA databases and IHC results from the real world indicated that although GNG11 was not detected, ADCY4 was obviously downregulated in LUSC tissues at the mRNA and protein levels.ConclusionsThis analysis showed that survival-related hub genes are highly correlated to the tumorigenesis and development of LUSC. Additionally, ADCY4 is a candidate therapeutic and prognostic biomarker of LUSC.

Ming-Min Jiang, Fan Zhao, Tao-Tao Lou Department of Obstetrics and Gynaecology, Zhuji Central Hospital, Shaoxing, 311800, Zhejiang, People’s Republic of ChinaCorrespondence: Ming-Min JiangDepartment of Obstetrics and Gynaecology, Zhuji Central Hospital, Shaoxing, 311800, Zhejiang, People’s Republic of ChinaTel +86-13575599091Email jiangminmin918@163.comBackground: GNG11 (G protein subunit gamma 11) is a member of guanine nucleotide-binding protein (G protein) gamma family. Few studies elucidated the role of GNG11 in human disease, especially in tumors. The present study initially analyzed the function of GNG11 in ovarian serous cystadenocarcinoma.Methods: The differential expression of GNG11 mRNA in ovarian cancer and normal tissues was evaluated through Oncomine, CCLE, Gepia, UCSC Xena and UALCAN databases. The protein expression of GNG11 was assessed via HPA database. Prognosis analysis was performed by Kaplan–Meier Plotter. Restrict survival analysis to subtypes including tumor grade, cancer stage and TP53 mutation status was then carried out. GSEA enrichment analysis was performed to explore the significant pathways associated with GNG11 in ovarian cancer. Finally, the upstream miRNAs of GNG11 were predicted by DIANA, Target Scan, miRDB and miRWalk databases, and the potential key KEGG pathways were subsequently determined by DIANA.Results: The mRNA expression of GNG11 was down-regulated in ovarian cancer patients (P< 0.05). The cancer stage of patients correlated with the expression of GNG11 (P< 0.05). Survival analysis indicated that GNG11 high expression statistically shortened the overall survival time of patients (HR=1.26, P=0.0043) compared with low expression group, especially for the patients with earlier stage (HR=2.48, P=0.035) and lower grade (HR=1.72, P=0.0016). Subsequently, the consistent upstream miRNA of GNG11, hsa-miR-22-5p, was predicted from 4 databases. The differential expression profile of hsa-miR-22-5p in blood was observed in ovarian cancer patients. According to the GSEA analysis on GNG11 and KEGG analysis on hsa-miR-22-5p, the consistent pathway of ECM-receptor interaction was observed (all P< 0.01). ECM-receptor interaction pathway and differential expression of hsa-miR-22-5p in blood suggested the migration risk of ovarian cancer.Conclusion: High expression of GNG11 indicated the poor prognosis of ovarian cancer patients. GNG11 might play a crucial role in the biological process of ovarian serous cystadenocarcinoma by ECM-receptor interaction pathway, thus affecting the prognosis of patients.Keywords: GNG11, ovarian serous cystadenocarcinoma, poor prognosis, ECM-receptor interaction

Continuous risk of recurrence scores (CRS) based on tumor gene expression are vital prognostic tools for breast cancer. Studies have shown that Black women (BW) have higher CRS than White women (WW). Although systemic injustices contribute substantially to breast cancer disparities, evidence of biological and germline contributions is emerging. In this study, we investigated germline genetic associations with CRS and CRS disparity using approaches modeled after transcriptome-wide association studies (TWAS). In the Carolina Breast Cancer Study, using race-specific predictive models of tumor expression from germline genetics, we performed race-stratified (N = 1,043 WW, 1,083 BW) linear regressions of three CRS (ROR-S: PAM50 subtype score; proliferation score; ROR-P: ROR-S plus proliferation score) on imputed tumor genetically regulated tumor expression (GReX). Bayesian multivariate regression and adaptive shrinkage tested GReX-prioritized genes for associations with tumor PAM50 expression and subtype to elucidate patterns of germline regulation underlying GReX-CRS associations. At FDR-adjusted P < 0.10, 7 and 1 GReX prioritized genes among WW and BW, respectively. Among WW, CRS were positively associated with MCM10, FAM64A, CCNB2, and MMP1 GReX and negatively associated with VAV3, PCSK6, and GNG11 GReX. Among BW, higher MMP1 GReX predicted lower proliferation score and ROR-P. GReX-prioritized gene and PAM50 tumor expression associations highlighted potential mechanisms for GReX-prioritized gene to CRS associations. Among patients with breast cancer, differential germline associations with CRS were found by race, underscoring the need for larger, diverse datasets in molecular studies of breast cancer. These findings also suggest possible germline trans-regulation of PAM50 tumor expression, with potential implications for CRS interpretation in clinical settings. Significance: This study identifies race-specific genetic associations with breast cancer risk of recurrence scores and suggests mediation of these associations by PAM50 subtype and expression, with implications for clinical interpretation of these scores.

Background: Lung adenocarcinoma (LADC) is the most common type of lung cancer and is a subtype of non-small-cell lung cancer (NSCLC). Approximately 40% of LADC patients experience brain metastases (BMs) during the course of the disease. In this study, integrated bioinformatics methods were applied to identify key genes related to brain metastasis in lung adenocarcinoma. Methods: We derived and characterized genes differentially expressed between the primary tumour and brain metastases using tumour cells isolated from two lung cancer Patient-derived xenografts (PDX) cases (GSE 69405). Gene ontology (GO) and KEGG pathway enrichment analyses were applied, and protein-protein interaction (PPI) networks and Cytoscape software were utilized to identify key genes. Results: Four key genes, including CKAP4 (Cytoskeleton Associated Protein 4), SERPINA1 (Serpin Family A Member 1), SDC2 (Syndecan 2) and GNG11 (G Protein Subunit Gamma 11) were identified for BM-LADC by the Venn diagram. Conclusion: We believe these key genes may be potential biomarkers for improved prognosis and treatment of lung adenocarcinoma.

Background Luminal subtype is the most common subgroup of breast cancer (BC), accounting for more than 70% of this cancer. Long non-coding RNAs (lncRNAs) are a group of RNAs which play critical roles in diverse cellular processes. It is proved that dysregulation of them can contribute to the development of various cancers, including BC. LINC00961 was reported to be downregulated in several cancers, however, its expression level in BC remains largely unknown. The purpose of the present study was to investigate the possible role of LINC00961 in luminal A and B subtypes of BC. Methods To obtain novel lncRNAs associated with different cancers and differentially expressed lncRNAs (DElncRNAs) between BC tumor and normal tissues, Lnc2Cancer and GDC databases were used, respectively. After performing literature review, the expression level of the selected lncRNA (LINC00961) was evaluated in 79 luminal A and B BC specimens and adjacent non-cancerous tissues by Quantitative Reverse Transcription PCR (qRT-PCR). LINC00961 expression was also evaluated in two luminal A BC cell lines, compared to a normal breast cell line. The comparison of the differences between tumor and adjacent non-tumor samples was performed by paired sample t-test. Moreover, correlation analysis between LINC00961 expression and clinicopathological features was performed using the chi-square, fisher exact, and independent t-test. In order to investigate the possible roles of LINC00961 in luminal A and B BC, different bioinformatics analyses such as functional annotation of the LINC00961 co-expressed genes and protein–protein interaction (PPI) networks construction were also performed. Results LINC00961 was selected as a significant DElncRNA which had not been studied in BC. According to q-RT PCR assay, LINC00961 was downregulated in luminal BC tissues and cell lines. Its expression was correlated with smoking status and the age of menarche in luminal BC patients. Also, the results of the bioinformatics analysis were consistent with the data obtained from q-RT PCR assay. The final results indicated that LINC00961 might be involved in multiple cancer-associated pathways such as chemokine, Ras and PI3K–Akt signaling pathways, GPCR ligand binding, and signal transduction in luminal subtypes of BC. CDH5, GNG11, GNG8, SELL, S1PR1, CCL19, FYN, ACAN, CD3E, ACVRL1, CAV1, and PPARGC1A were identified as the top hub genes of the PPI networks across luminal subgroup. Conclusion Our findings suggested that LINC00961 was significantly downregulated in luminal A and B subtypes of BC. Moreover, bioinformatics analysis provided a basis for better identification of the potential role of LINC00961 in luminal subtype of BC.

Irinotecan (CPT11) is one of the most effective drugs for treating colon cancer, but its severe side effects limit its application. Recently, a traditional Chinese herbal preparation, named PHY906, has been proved to be effective for improving therapeutic effect and reducing side effects of CPT11. The aim of the present study was to provide novel insight to understand the molecular mechanism underlying PHY906-CPT11 intervention of colon cancer. Based on the GSE25192 dataset, for different three treatments (PHY906, CPT11, and PHY906-CPT11), we screened out differentially expressed genes (DEGs) and constructed a co-expression network by weighted gene co-expression network analysis (WGCNA) to identify hub genes. The key genes of the three treatments were obtained by merging the DEGs and hub genes. For the PHY906-CPT11 treatment, a total of 18 key genes including Eif4e, Prr15, Anxa2, Ddx5, Tardbp, Skint5, Prss12 and Hnrnpa3, were identified. The results of functional enrichment analysis indicated that the key genes associated with PHY906-CPT11 treatment were mainly enriched in ‘superoxide anion generation’ and ‘complement and coagulation cascades’. Finally, we validated the key genes by Gene Expression Profiling Interactive Analysis (GEPIA) and RT-PCR analysis, the results indicated that EIF4E, PRR15, ANXA2, HNRNPA3, NCF1, C3AR1, PFDN2, RGS10, GNG11, and TMSB4X might play an important role in the treatment of colon cancer with PHY906-CPT11. In conclusion, a total of 18 key genes were identified in the present study. These genes showed strong correlation with PHY906-CPT11 treatment in colon cancer, which may help elucidate the underlying molecular mechanism of PHY906-CPT11 treatment in colon cancer.

Enforced expression of GNG11, G-protein subunit γ 11, induces cellular senescence in normal human diploid fibroblasts. We here examined the effect of the expression of GNG11 on the growth of immortalized human cell lines, and found that it suppressed the growth of SUSM-1 cells, but not of HeLa cells. We then compared these two cell lines to understand the molecular basis for the action of GNG11. We found that expression of GNG11 induced the generation of reactive oxygen species (ROS) and abnormal nuclear morphology in SUSM-1 cells but not in HeLa cells. Increased ROS generation by GNG11 would likely be caused by the down-regulation of the antioxidant enzymes in SUSM-1 cells. We also found that SUSM-1 cells, even under normal culture conditions, showed higher levels of ROS and higher incidence of abnormal nuclear morphology than HeLa cells, and that abnormal nuclear morphology was relevant to the increased ROS generation in SUSM-1 cells. Thus, SUSM-1 and HeLa cells showed differences in the regulation of ROS and nuclear morphology, which might account for their different responses to the expression of GNG11. Thus, SUSM-1 cells may provide a unique system to study the regulatory relationship between ROS generation, nuclear morphology, and G-protein signaling.

BACKGROUND Lung cancer is a leading cause of morbidity diseases worldwide, but the key mechanisms of lung cancer remain elusive. This study aims to integrate of GSE 118370 and GSE 32863 profile and identify the key genes and pathway involved in human lung adenocarcinoma. METHODS R software (RStudio, Version info: R 3.2.3, Forrester, USA) were utilized to find the differentially expressed genes. All the differentially expressed genes were analyzed by gene ontology, kyoto encyclopedia of genes and genomes. Protein-protein interaction networks were constructed by STRING database and analyzed by Cytohubber and Module. The cancer genome atlas database was used to verification the expression of hub genes. Quantitative reverse transcription-PCR was used to verify the bio-information results. RESULTS Sixty-four lung adenocarcinoma and 64 adjacent normal tissues were used for integration analysis. Five hundred ninety-nine co-expression genes were locked. Biological processes mainly enriched in angiogenesis. Cellular component focused on extracellular exosome and molecular function aimed on protein disulfide isomerase activity. Cytohubber analysis showed that GNG11, FPR2, P4HB, PIK3R1, CDC20, ADCY4, TIMP1, IL6, CXC chemokine ligand (CXCL)12, and GAS6 acted as the hub genes during lung adenocarcinoma. Module analysis presented Chemokine signaling pathway was a key pathway. Quantitative reverse transcription-PCR showed that the expression level of GNG11, FPR2, PIK3R1, ADCY4, IL6, CXCL12, and GAS6 were significantly decreased and P4HB, CDC20 and TIMP1 were increased in human adenocarcinoma tissues (P

Heat stress has a negative impact on dairy cow productivity. In order to reveal the mechanisms of heat-stress response, the mRNA and miRNA expression profiles of five cows under chronic heat-stress and thermoneutral conditions were assayed in blood by high-throughput sequencing technology. A total of 540 mRNAs and 9 miRNAs were expressed differently under heat-stress and thermoneutral conditions. Functional analyses revealed that MAPK signaling pathway, cellular senescence, circadian entrainment, aldosterone synthesis and secretion, and pathways in cancer were enriched for differently expressed mRNAs; meanwhile cGMP-PKG signaling pathway, thermogenesis, and protein digestion and absorption were enriched for differently expressed miRNAs. In addition, GADD45G, TGFB2, and GNG11 may play roles in the heat stress, and bta-miR-423-5p might be one of the regulators of heat-stress response in cows as potential mediators of chronic heat-stress response. In conclusion, the present study described the mRNA and miRNA expression patterns in blood extracted from cows during the transition from heat-stress to thermoneutral conditions. The results provide new data that could help in identifying mechanisms that mediate cows' response to chronic heat stress.

Guangda Yang,1 Qianya Chen,1 Jieming Xiao,2 Hailiang Zhang,1 Zhichao Wang,1 Xiangan Lin3 1Department of Cancer Chemotherapy, Zengcheng District People’s Hospital of Guangzhou (BoJi-Affiliated Hospital of Sun Yat-Sen University), Guangzhou, China; 2Department of Emergency, Zengcheng District People’s Hospital of Guangzhou (BoJi-Affiliated Hospital of Sun Yat-Sen University), Guangzhou, China; 3Department of Cancer Chemotherapy, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China Background: This study was performed to identify disease-related genes and analyze prognostic values in nonsmoking females with non-small cell lung carcinoma (NSCLC).Materials and methods: Gene expression profile GSE19804 was downloaded from the Gene Expression Omnibus (GEO) database and analyzed by using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for the functional and pathway enrichment analysis. Then, the Search Tool for the Retrieval of Interacting Genes, Cytoscape, and Molecular Complex Detection were used to construct the protein–protein interaction (PPI) network and identify hub genes. Finally, the Kaplan–Meier plotter online tool was used for the overall survival analysis of hub genes.Results: A cohort of 699 differentially expressed genes was screened, and they were mainly enriched in the terms of ECM–receptor interaction, focal adhesion, and cell adhesion molecules. A PPI network was constructed, and 15 hub genes were identified base on the subset of PPI network. Then, two significant modules were detected and several genes were found to be associated with the cell cycle pathway. Finally, nine hub genes’ (UBE2C, DLGAP5, TPX2, CCNB2, BIRC5, KIF20A, TOP2A, GNG11, and ANXA1) expressions were found to be associated with the prognosis of the patients.Conclusion: Overall, we propose that the cell cycle pathway may play an important role in nonsmoking females with NSCLC and the nine hub genes may be further explored as potential targets for NSCLC diagnosis and treatment. Keywords: non-small cell lung carcinoma, NSCLC, nonsmoking females, GEO2R, prognostic biomarkers, Kaplan–Meier plotter

Inflammatory bowel diseases (IBDs), including ulcerative colitis (UC) and Crohn's disease (CD), are chronic inflammatory disorders caused by genetic influences, the immune system and environmental factors. However, the underlying pathogenesis of IBDs and the pivotal molecular interactions remain to be fully elucidated. The aim of the present study was to identify genetic signatures in patients with IBDs and elucidate the potential molecular mechanisms underlying IBD subtypes. The gene expression profiles of the GSE75214 datasets were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in UC and CD patients compared with controls using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs were performed using DAVID. Furthermore, protein-protein interaction (PPI) networks of the DEGs were constructed using Cytoscape software. Subsequently, significant modules were selected and the hub genes were identified. In the GO and KEGG pathway analysis, the top enriched pathways in UC and CD included Staphylococcus aureus infection, rheumatoid arthritis, complement and coagulation cascades, PI3K/Akt signaling pathway and osteoclast differentiation. In addition, the GO terms in the category biological process significantly enriched by these genes were inflammatory response, immune response, leukocyte migration, cell adhesion, response to molecules of bacterial origin and extracellular matrix (ECM) organization. However, several other biological processes (GO terms) and pathways (e.g., ‘chemotaxis’, ‘collagen catabolic process’ and ‘ECM-receptor interaction’) exhibited significant differences between the two subtypes of IBD. The top 10 hub genes were identified from the PPI network using respective DEGs. Of note, the hub genes G protein subunit gamma 11 (GNG11), G protein subunit beta 4 (GNB4), Angiotensinogen (AGT), Phosphoinositide-3-kinase regulatory subunit 3 (PIK3R3) and C-C motif chemokine receptor 7 (CCR7) are disease-specific and may be used as biomarkers for differentiating UC from CD. Furthermore, module analysis further confirmed that common significant pathways involved in the pathogenesis of IBD subtypes were associated with chemokine-induced inflammation, innate immunity, adapted immunity and infectious microbes. In conclusion, the present study identified DEGs, key target genes, functional pathways and enrichment analysis of IBDs, enhancing the understanding of the pathogenesis of IBDs and also advancing the clarification of the underlying molecular mechanisms of UC and CD. Furthermore, these results may provide potential molecular targets and diagnostic biomarkers for UC and CD.

Smoking is considered the major risk factor for lung cancer, but only a small portion of female lung adenocarcinoma patients are associated with smoking. Thus, identifying crucial genes and pathways related to nonsmoking female lung cancer patients is of great importance. Gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. The R software packages were applied to screen the differentially expressed genes (DEGs). GO term enrichment and KEGG pathway analyses were carried out using DAVID tools. The protein-protein interaction (PPI) network was constructed by Cytoscape software. In total, 487 downregulated and 199 upregulated DEGs were identified. The down-regulated DEGs were mainly enriched for behavior and response to wounding, and the upregulated DEGs were significantly enriched for multicellular organismal metabolic process and cell division. The KEGG pathway analysis revealed that the downregulated DEGs were significantly enriched for cell adhesion molecules and neuroactive ligand-receptor interaction, while the upregulated DEGs were mainly enriched for cell cycle and the p53 signaling pathway. The top 10 hub genes and top 3 gene interaction modules were selected from the PPI network. Of the ten hub genes, a high expression of five genes was related to a poor OS in female lung cancer patients who never smoked, including IL6, CXCR2, FPR2, PPBP and HBA1. However, a low expression of GNG11, LRRK2, CDH5, CAV1 and SELE was associated with a worse OS for the female lung cancer patients who never smoked. In conclusion, our study provides novel insight for a better understanding of the pathogenesis of nonsmoking female lung cancer, and these identified DEGs may serve as biomarkers for diagnostics and treatment.

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.

Malignant melanoma is one of the most aggressive human cancers. Invasion of cells is the first step in metastasis, resulting in cell migration through tissue compartments. We aimed to evaluate genomic alterations specifically associated with the invasive characteristics of melanoma cells. Matrigel invasion assays were used to determine the invasive properties of cell lines that originated from primary melanomas. Array comparative genomic hybridization analyses were carried out to define the chromosome copy number alterations (CNAs). Several recurrent CNAs were identified by array comparative genomic hybridization that affected melanoma-related genes. Invasive primary cell lines showed high frequencies of CNAs, including the loss of 7q and gain of 12q chromosomal regions targeting PTPN12, ADAM22, FZD1, TFPI2, GNG11, COL1A2, SMURF1, VGF, RELN and GLIPR1 genes. Gain of the GDNF (5p13.1), GPAA1, PLEC and SHARPIN (8q24.3) genes was significantly more frequent in invasive cell lines compared with the noninvasive ones. Importantly, copy number gains of these genes were also found in cell lines that originated from metastases, suggesting their role in melanoma metastasis formation. The present study describes genomic differences between invasive and noninvasive melanoma cell lines that may contribute toward the aggressive phenotype of human melanoma cells.

The heterogeneity of acute myeloid leukemia (AML) with respect to biology and clinical course resides in the fact that patients belonging to the same group show marked differences in their response to chemotherapy, necessitating a refinement of AML classification.In order to define molecular markers for AML, we performed microarray analysis on peripheral blood cells from two M5 AML patients, and selected four differentially expressed genes to validate their expression by real-time quantitative PCR (RT-PCR).We have shown that two downregulated genes in AML, those encoding guanine nucleotide-binding protein gamma11 (GNG11) and amphiregulin (AREG), are also downregulated in B-lineage acute lymphoblastic leukemia (B-ALL) and T-lineage acute lymphoblastic leukemia (T-ALL) patients. A second gene, that encoding ceruloplasmin (CP), is upregulated in AML but not in B-ALL and T-ALL. The level of expression of these genes varies from one patient to another.Since the number of patients studied is limited, further studies are needed with a larger series of patients to evaluate the potential utility of GNG11, AREG and CP as molecular markers for AML subtype classification. Our study is the first to analyze these genes in AML, B-ALL, T-ALL and chronic leukemia (myeloid and lymphoid) patients by RT-PCR. This rapid and sensitive method could be used to screen these genes in different types of leukemia.

GNG11 is a member of the γ subunit family of heteromeric G-protein, but its function is entirely unknown. Here, we successfully characterized its specific role in cellular senescence. We have found that overexpression of GNG11 immediately induces cellular senescence in normal human fibroblasts, and its down-regulation by antisense cDNA extends their lifespan. Surprisingly, this gene is very rapidly induced by senescence-inducing agents such as H 2 O 2 . Furthermore, overexpression of GNG11 activated ERK1/2 of the MAP kinase family, but did not Ras. Collectively, these results suggest a novel senescence pathway mediated by GNG11 in response to environmental cues.

The aim of the present study was to search for the differential gene expression and measure the serum level of a number of biochemical parameters in the cold Zheng (CZ) and non-cold Zheng (NCZ) in patients receiving hemodialysis. Hemodialysis (HD) patients were randomly selected from the CZ and NCZ groups. The between-group differences in gene expression were assessed using complementary DNA (cDNA) microarray. Differential gene expression was further validated by real-time reverse transcriptase polymerase chain reaction (RT-PCR). Our results demonstrated that the up-regulation of the inflammation-associated genes, ALOX5AP, S100A8 and S100A12, down-regulation of the genes related to immunity (DEFA4), metabolism (GNG11, PYGB, PRKAR2B), and growth/proliferation (HSF2, DDR2, TK1) were found in the CZ group. Furthermore, the CZ HD patients had significantly lower serum albumin levels compared with their NCZ counterparts (3.31 ± 0.08 g/dL versus 4.18 ± 0.12 g/dL ). It appears reasonable to conclude that up-regulated inflammatory-gene expression (ALOX5AP, S100A8 and S100A12) may play an important role in CZ HD patients.

181 Background: A component of the epithelial to mesenchymal transition (EMT) is degradation of extracellular matrix and acquisition of migration, both of which support invasiveness. The expression of CXCL7 is associated with the invasive phenotype through interaction with the CXCL7/CXCR2 axis and heparan sulfate. The purpose of this study is to quantify the expression of genes associated with EMT by CXCL7-expressing cells with the migration/invasive phenotype. Methods: Total RNA from CXCL7-transfected breast cells (MCF10AT) was tested for relative gene expression using RT2 Profiler PCR array for EMT (SABiosciences). Vector transfected cells were compared. Each result was verified by real time PCR assay. In parallel, migration assays were performed quantitatively using transwell membranes and qualitatively with the scratch test and photodocumented. Results: The expression of GNG11 and TCF4 was upregulated and SPP1 downregulated as expected for the EMT profile. Specifically, GNG11 (Guanine nucleotide binding protein (G protein), gamma 11) expression was increased 2.94 fold and TCF4 (Transcription factor 4) increased 1.89 fold. The expression of SPP1 (Secreted phosphoprotein 1) was decreased by 6.8 fold. The expression of ZEB2 (Zinc finger E-box binding homeobox 2) was decreased by 1.96 as a transcription factor. Migration of CXCL7-transfectants was significantly increased over vector controls and comparable to invasive isogenic breast cancer cells. Conclusions: The CXCL7-transfected cells with invasive phenotype express genes associated with the EMT expression profile including G-protein signaling pathway.

Introduction: The expression of CXCL7 is associated with the invasive phenotype through interaction with the CXCL7/CXCR2 axis and heparan sulfate. A component of the epithelial to mesenchymal transition (EMT) is degradation of extracellular matrix and acquisition of migration, both of which support invasiveness. The purpose of this study is to quantify the expression of genes associated with EMT by CXCL7-expressing cells with the invasive phenotype. Methods: Total RNA from CXCL7-transfected breast cells (MCF10AT) was tested for relative gene expression using RT2 ProfilerTM PCR array for EMT (SABiosciences). Vector transfected cells were compared. Each result was verified by real time PCR assay. Results: The expression of GNG11 and TCF4 was upregulated and SPP1 downregulated as expected for the EMT profile. Specifically, GNG11 (Guanine nucleotide binding protein (G protein), gamma 11) expression was increased 2.94 fold and TCF4 (Transcription factor 4) increased 1.89 fold. The expression of SPP1 (Secreted phosphoprotein 1) was decreased by 6.8 fold. The expression of ZEB2 (Zinc finger E-box binding homeobox 2) was decreased by 1.96 as a transcription factor. Summary: The CXCL7-transfected cells with invasive phenotype express genes associated with the EMT expression profile including G-protein signaling pathway. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 307. doi:1538-7445.AM2012-307