Expression patterns of kinin-dependent genes in endometrial cancer

Kinin Receptors and Kinin-Related Gene Expression in Astrocytic Brain Tumors

Kinins are a set of peptides present in tissues that are involved in the inflammatory response and cancer progression. However, studies showing the expression of kinin receptors in human glioma samples are still incomplete and contradictory. The aim of the present study was to ascertain the expression of BDKRB1 and BDKRB2 genes, as well as the level of B1R and B2R proteins in human gliomas, depending on the degree of malignancy. Additionally, representative kinin-dependent genes with altered expression were indicated. The expression profile of kinin-dependent genes was determined using oligonucleotide microarray technique. In addition, RT-qPCR was used to assess the expression level of selected differentiating genes. The location of kinin receptors in brain gliomas was assessed using immunohistochemical methods. The oligonucleotide microarray method was used to identify 12 mRNA IDs of kinin-related genes whose expression was upregulated or downregulated in gliomas of different grades. In immunohistochemically stained samples, the concentrations of BR1 and BR2 proteins, measured by optical density, were statistically significantly higher in grade G3 vs. G2 and G4 vs. G3. Increased expression of kinin receptors BDKRB1 and BDKRB2 in brain gliomas, depending on the degree of malignancy, suggests the involvement of kinins and their receptors in the disease's pathogenesis. Quantitative assessment of mRNA BDKRB1, PRKAR1A, MAP2K, and EGFR in patients with brain tumors may hold diagnostic and therapeutic significance.

Inferring cancer common and specific gene networks via multi-layer joint graphical model

Cancer is a complex disease caused primarily by genetic variants. Reconstructing gene networks within tumors is essential for understanding the functional regulatory mechanisms of carcinogenesis. Advances in high-throughput sequencing technologies have provided tremendous opportunities for inferring gene networks via computational approaches. However, due to the heterogeneity of the same cancer type and the similarities between different cancer types, it remains a challenge to systematically investigate the commonalities and specificities between gene networks of different cancer types, which is a crucial step towards precision cancer diagnosis and treatment. In this study, we propose a new sparse regularized multi-layer decomposition graphical model to jointly estimate the gene networks of multiple cancer types. Our model can handle various types of gene expression data and decomposes each cancer-type-specific network into three components, i.e., globally shared, partially shared and cancer-type-unique components. By identifying the globally and partially shared gene network components, our model can explore the heterogeneous similarities between different cancer types, and our identified cancer-type-unique components can help to reveal the regulatory mechanisms unique to each cancer type. Extensive experiments on synthetic data illustrate the effectiveness of our model in joint estimation of multiple gene networks. We also apply our model to two real data sets to infer the gene networks of multiple cancer subtypes or cell lines. By analyzing our estimated globally shared, partially shared, and cancer-type-unique components, we identified a number of important genes associated with common and specific regulatory mechanisms across different cancer types.

Circular RNA hsa_circ_0000285 regulates the microRNA‐599/G‐protein subunit gamma 12 (miR‐599/GNG12) axis to promote glioma progression

Objective

Glioma is the most common, rapidly progressing, lethal brain tumor. However, underlying mechanisms behind its abnormal progression remain largely unknown. This study aimed to investigate mechanism of action and effects of the hsa_circ_0000285 on glioma progression.

Methods

RT‐qPCR was utilized to study RNA expression in glioma tissues and cell lines. The effects of hsa_circ_0000285 on glioma progression were studied by measuring cell proliferation and migration, apoptosis, tumor volume and weight in both glioma cells and xenograft glioma mice. The features of hsa_circ_0000285 were identified using chromatin fractionation and RNase digestion. Its mechanism of action was analyzed using bioinformatics, RNA‐binding protein immunoprecipitation, and luciferase reporter assay.

Results

We found glioma tissues and cell lines were overexpressing hsa_circ_0000285. While hsa_circ_0000285 promoted cell proliferation and migration, it inhibited apoptosis in vitro. It also increased tumor volume and weight in vivo. Using bioinformatic analysis and verification experiments for studying its mechanisms, we confirmed that hsa_circ_0000285 sponged miR‐599, which negatively regulated GNG12 by binding to its mRNA.

Conclusion

Hsa_circ_0000285 is overexpressed in the glioma and promotes its progression by directly regulating the miR‐599/GNG12 axis. This novel mechanism, therefore, shows that the hsa_circ_0000285/miR‐599/GNG12 axis may be a promising therapeutic target for glioma treatment.

Identifying and optimizing human endometrial gene expression signatures for endometrial dating

STUDY QUESTION

What are the key considerations for developing an enhanced transcriptomic method for secretory endometrial tissue dating?

SUMMARY ANSWER

Multiple gene expression signature combinations can serve as biomarkers for endometrial dating, but their predictive performance is variable and depends on the number and identity of the genes included in the prediction model, the dataset characteristics and the technology employed for measuring gene expression.

WHAT IS KNOWN ALREADY

Among the new generation of transcriptomic endometrial dating (TED) tools developed in the last decade, there exists variation in the technology used for measuring gene expression, the gene makeup and the prediction model design. A detailed study, comparing prediction performance across signatures for understanding signature behaviour and discrepancies in gene content between them, is lacking.

STUDY DESIGN, SIZE, DURATION

A multicentre prospective study was performed between July 2018 and October 2020 at five different centres from the same group of clinics (Spain). This study recruited 281 patients and finally included in the gene expression analysis 225 Caucasian patients who underwent IVF treatment. After preprocessing and batch effect filtering, gene expression measurements from 217 patients were combined with artificial intelligence algorithms (support vector machine, random forest and k-nearest neighbours) allowing evaluation of different prediction models. In addition, secretory-phase endometrial transcriptomes from gene expression omnibus (GEO) datasets were analysed for 137 women, to study the endometrial dating capacity of genes independently and grouped by signatures. This provided data on the consistency of prediction across different gene expression technologies and datasets.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Endometrial biopsies were analysed using a targeted TruSeq (Illumina) custom RNA expression panel called the endometrial dating panel (ED panel). This panel included 301 genes previously considered relevant for endometrial dating as well as new genes selected for their anticipated value in detecting the secretory phase. Final samples (n = 217) were divided into a training set for signature discovery and an independent testing set for evaluation of predictive performance of the new signature. In addition, secretory-phase endometrial transcriptomes from GEO were analysed for 137 women to study endometrial dating capacity of genes independently and grouped by signatures. Predictive performance among these signatures was compared according to signature gene set size.

MAIN RESULTS AND THE ROLE OF CHANCE

Testing of the ED panel allowed development of a model based on a new signature of 73 genes, which we termed 'TED' and delivers an enhanced tool for the consistent dating of the secretory phase progression, especially during the mid-secretory endometrium (3-8 days after progesterone (P) administration (P + 3-P + 8) in a hormone replacement therapy cycle). This new model showed the best predictive capacity in an independent test set for staging the endometrial tissue in the secretory phase, especially in the expected window of implantation (average of 114.5 ± 7.2 h of progesterone administered; range in our patient population of 82-172 h). Published sets of genes, in current use for endometrial dating and the new TED genes, were evaluated in parallel in whole-transcriptome datasets and in the ED panel dataset. TED signature performance was consistently excellent for all datasets assessed, frequently outperforming previously published sets of genes with a smaller number of genes for dating the endometrium in the secretory phase. Thus, this optimized set exhibited prediction consistency across datasets.

LARGE SCALE DATA

The data used in this study is partially available at GEO database. GEO identifiers GSE4888, GSE29981, GSE58144, GSE98386.

LIMITATIONS, REASONS FOR CAUTION

Although dating the endometrial biopsy is crucial for investigating endometrial progression and the receptivity process, further studies are needed to confirm whether or not endometrial dating methods in general are clinically useful and to guide the specific use of TED in the clinical setting.

WIDER IMPLICATIONS OF THE FINDINGS

Multiple gene signature combinations provide adequate endometrial dating, but their predictive performance depends on the identity of the genes included, the gene expression platform, the algorithms used and dataset characteristics. TED is a next-generation endometrial assessment tool based on gene expression for accurate endometrial progression dating especially during the mid-secretory.

STUDY FUNDING/COMPETING INTEREST(S)

Research funded by IVI Foundation (1810-FIVI-066-PD). P.D.-G. visiting scientist fellowship at Oxford University (BEFPI/2010/032) and Josefa Maria Sanchez-Reyes' predoctoral fellowship (ACIF/2018/072) were supported by a program from the Generalitat Valenciana funded by the Spanish government. A.D.-P. is supported by the FPU/15/01398 predoctoral fellowship from the Ministry of Science, Innovation and Universities (Spanish Government). D.W. received support from the NIHR Oxford Biomedical Research Centre. The authors do not have any competing interests to declare.

Low GNG12 Expression Predicts Adverse Outcomes: A Potential Therapeutic Target for Osteosarcoma

Background

G protein subunit gamma 12 (GNG12) is observed in some types of cancer, but its role in osteosarcoma is unknown. This study hypothesized that GNG12 may be a potential biomarker and therapeutic target. We aimed to identify an association between GNG12 and osteosarcoma based on the Gene Expression Omnibus and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) databases.

Methods

Osteosarcoma samples in GSE42352 and TARGET database were selected as the test cohorts. As the external validation cohort, 78 osteosarcoma specimens from The Second Affiliated Hospital of Nanchang University were collected. Patients with osteosarcoma were divided into high and low GNG12 mRNA-expression groups; differentially expressed genes were identified as GNG12-related genes. The biological function of GNG12 was annotated using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and immune infiltration analysis. Gene expression correlation analysis and competing endogenous RNA regulatory network construction were used to determine potential biological regulatory relationships of GNG12. Overall survival, Kaplan–Meier analysis, and log-rank tests were calculated to determine GNG12 reliability in predicting survival prognosis.

Results

GNG12 expression decreased in osteosarcoma samples. GNG12 was a highly effective biomarker for osteosarcoma [area under the receiver operating characteristic (ROC) curve (AUC) = 0.920], and the results of our Kaplan–Meier analysis indicated that overall survival and progression-free survival differed significantly between low and high GNG-expression group (p < 0.05). Functional analyses indicated that GNG12 may promote osteosarcoma through regulating the endoplasmic reticulum. Expression correlation analysis and competing endogenous RNA network construction showed that HOTTIP/miR-27a-3p may regulate GNG12 expression. Furthermore, the subunit suppresses adaptive immunity via inhibiting M1 and M2 macrophage infiltration. GNG12 was inhibited in metastatic osteosarcoma compared with non-metastatic osteosarcoma, and its expression predicted survival of patients (1, 3, and 5-year AUCs were 0.961, 0.826, and 0.808, respectively).

Conclusion

This study identified GNG12 as a potential biomarker for osteosarcoma prognosis, highlighting its potential as an immunotherapy target.

GNG5 is a novel oncogene associated with cell migration, proliferation, and poor prognosis in glioma

Background

Although many biomarkers have been reported for detecting glioma, the prognosis for the disease remains poor, and therefore, new biomarkers need to be identified. GNG5, which is part of the G-protein family, has been associated with different malignant tumors, though the role of GNG5 in glioma has not been studied. Therefore, we aimed to identify the relationship between GNG5 and glioma prognosis and identify a new biomarker for the diagnosis and treatment of gliomas.

Methods

We used data on more than a thousand gliomas from multiple databases and clinical data to determine the expression of GNG5 in glioma. Based on clinical data and CGGA database, we identified the correlation between GNG5 and multiple molecular and clinical features and prognosis using various analytical methods. Co-expression analysis and GSEA were performed to detect GNG5-related genes in glioma and possible signaling pathways involved. ESTIMATE, ssGSEA, and TIMER were used to detect the relationship between GNG5 and the immune microenvironment. Functional experiments were performed to explore the function of GNG5 in glioma cells.

Results

GNG5 is highly expressed in gliomas, and its expression level is positively correlated with pathological grade, histological type, age, and tumor recurrence and negatively correlated with isocitrate dehydrogenase mutation, 1p/19 co-deletion, and chemotherapy. Moreover, GNG5 as an independent risk factor was negatively correlated with the overall survival time. GSEA revealed the potential signaling pathways involved in GNG5 function in gliomas, including cell adhesion molecules signaling pathway. The ssGSEA, ESTIMATE, and TIMER based analysis indicated a correlation between GNG5 expression and various immune cells in glioma. In vivo and in vitro experiments showed that GNG5 could participate in glioma cell proliferation and migration.

Conclusions

Based on the large data platform and the use of different databases to corroborate results obtained using various datasets, as well as in vitro and in vivo experiments, our study reveals for the first time that GNG5, as an oncogene, is overexpressed in gliomas and can inhibit the proliferation and migration of glioma cells and lead to poor prognosis of patients. Thus, GNG5 is a potential novel biomarker for the clinical diagnosis and treatment of gliomas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01935-7.

Identification of potential diagnostic and prognostic biomarkers for LUAD based on TCGA and GEO databases

Accumulating evidence has demonstrated that gene alterations play a crucial role in LUAD development, progression, and prognosis. The present study aimed to identify the hub genes associated with LUAD. In the present study, we used TCGA database to screen the hub genes. Then, we validated the results by GEO datasets. Finally, we used cBioPortal, UALCAN, qRT-PCR, HPA database, TCGA database, and Kaplan–Meier plotter database to estimate the gene mutation, gene transcription, protein expression, clinical features of hub genes in patients with LUAD. A total of 5930 DEGs were screened out in TCGA database. Enrichment analysis revealed that DEGs were involved in the transcriptional misregulation in cancer, viral carcinogenesis, cAMP signaling pathway, calcium signaling pathway, and ECM–receptor interaction. The combining results of MCODE and CytoHubba showed that ADCY8, ADRB2, CALCA, GCG, GNGT1, and NPSR1 were hub genes. Then, we verified the above results by GSE118370, GSE136043, and GSE140797 datasets. Compared with normal lung tissues, the expression levels of ADCY8 and ADRB2 were lower in LUAD tissues, but the expression levels of CALCA, GCG, GNGT1, and NPSR1 were higher. In the prognosis analyses, the low expression of ADCY8 and ADRB2 and the high expression of CALCA, GCG, GNGT1, and NPSR1 were correlated with poor OS and poor PFS. The significant differences in the relationship of the expression of 6 hub genes and clinical features were observed. In conclusion, 6 hub genes will not only contribute to elucidating the pathogenesis of LUAD and may be potential therapeutic targets for LUAD.

Transcriptome Based Estrogen Related Genes Biomarkers for Diagnosis and Prognosis in Non-small Cell Lung Cancer

Background

Lung cancer is the tumor with the highest morbidity and mortality, and has become a global public health problem. The incidence of lung cancer in men has declined in some countries and regions, while the incidence of lung cancer in women has been slowly increasing. Therefore, the aim is to explore whether estrogen-related genes are associated with the incidence and prognosis of lung cancer.

Methods

We obtained all estrogen receptor genes and estrogen signaling pathway genes in The Cancer Genome Atlas (TCGA), and then compared the expression of each gene in tumor tissues and adjacent normal tissues for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) separately. Survival analysis was performed of the differentially expressed genes in LUAD and LUSC patients separately. The diagnostic and prognostic values of the candidate genes were validated in the Gene Expression Omnibus (GEO) datasets.

Results

We found 5 estrogen receptor genes and 66 estrogen pathway genes in TCGA. A total of 50 genes were differently expressed between tumor tissues and adjacent normal tissues and 6 of the 50 genes were related to the prognosis of LUAD in TCGA. 56 genes were differently expressed between tumor tissues and adjacent normal tissues and none of the 56 genes was related to the prognosis of LUSC in TCGA. GEO datasets validated that the 6 genes (SHC1, FKBP4, NRAS, PRKCD, KRAS, ADCY9) had different expression between tumor tissues and adjacent normal tissues in LUAD, and 3 genes (FKBP4, KRAS, ADCY9) were related to the prognosis of LUAD.

Conclusions

The expressions of FKBP4 and ADCY9 are related to the pathogenesis and prognosis of LUAD. FKBP4 and ADCY9 may serve as biomarkers in LUAD screening and prognosis prediction in clinical settings.

Uterine disorders affecting female fertility: what are the molecular functions altered in endometrium?

OBJECTIVE

To determine the molecular functions of genes exhibiting altered expression in the endometrium of women with uterine disorders affecting fertility.

DESIGN

Retrospective analysis integrating case and control data from multiple cohorts with endometrium gene expression in women with uterine disorders.

SETTING

Infertility research department affiliated with a university hospital.

PATIENT(S)

Two hundred and forty women, 121 of whom were controls, 119 of whom had endometrial adenocarcinoma (ADC), recurrent implantation failure (RIF), recurrent pregnancy loss (RPL), or stage II-IV endometriosis.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Genomewide gene expression and altered molecular functions in the endometrium of each uterine disorder.

RESULT(S)

Using robust analysis methods, we identified statistically significantly altered endometrial functions in all the uterine disorders. Cell cycle alterations were shared among all the pathologies investigated. Endometriosis was characterized by the down-regulation of ciliary processes. Among the endometriosis, ADC, and RIF samples, mitochondrial dysfunction and protein degradation were shared dysregulated processes. In addition, RPL had the most distinct functional profile, and 95% of affected functions were down-regulated.

CONCLUSION(S)

The most robust functions dysregulated in the endometrium of patients with uterine disorders across sample cohorts implicated an endometrial factor at the gene expression level. This shared endometrial factor affects endometrial receptivity processes.

A Case-Control Study of ADCY9 Gene Polymorphisms and the Risk of Hepatocellular Carcinoma in the Chinese Han Population

Background: Adenylyl cyclase type 9 (ADCY9) modulates signal transduction by producing the second messenger cyclic AMP. It has been reported that ADCY9 gene polymorphisms were associated with cancer development. The aim of this study was to investigate whether ADCY9 gene polymorphisms could contribute to the susceptibility of hepatocellular carcinoma (HCC) in the Chinese Han population.

Methods: In the present study, five single-nucleotide polymorphisms (SNPs) in ADCY9 were genotyped using Agena MassARRAY platform in 876 subjects from China. Logistic regression was used to assess the effects of SNPs on HCC risk. Associations were also evaluated for HCC risk stratified by age and gender. False discovery rate (FDR) was used to correct multiple testing.

Results: After adjusting for age and gender, we found a significant relationship between heterozygous genotypes of rs2531995 and HCC risk (OR = 1.34, 95% CI = 1.01–1.77, p = 0.045). ADCY9 rs2230742 had a strong relationship with lower risk of HCC in allele (p = 0.006), co-dominant (p = 0.023), dominant (p = 0.010), and additive (p = 0.006) models. Stratified analysis showed that rs879620 increased HCC risk and rs2230742 was associated with lower risk of HCC in the individuals aged 55 or younger, rs2531992 significantly decreased HCC risk in the elder group (age > 55). For women, rs2230742 and rs2230741 were significantly associated with HCC risk in multiple models (p < 0.05). FDR analysis showed that rs2230742 could protect individuals from HCC risk in the allele model (FDR-p = 0.030). In addition, haplotype analysis indicated that C_rs879620A_rs2230742A_rs2230741 haplotype was a protective factor for HCC (OR = 0.67, 95% CI = 0.50–0.89, p = 0.007, FDR-p = 0.028).

Conclusion: Our findings suggest that ADCY9 gene polymorphisms are associated with HCC risk in the Chinese Han population.

Prognostic Value of a Stemness Index-Associated Signature in Primary Lower-Grade Glioma

Objective

As a prevalent and infiltrative cancer type of the central nervous system, the prognosis of lower-grade glioma (LGG) in adults is highly heterogeneous. Recent evidence has demonstrated the prognostic value of the mRNA expression-based stemness index (mRNAsi) in LGG. Our aim was to develop a stemness index-based signature (SI-signature) for risk stratification and survival prediction.

Methods

Differentially expressed genes (DEGs) between LGG in the Cancer Genome Atlas (TCGA) and normal brain tissue samples from the Genotype-Tissue Expression (GTEx) project were screened out, and the weighted gene correlation network analysis (WGCNA) was employed to identify the mRNAsi-related gene sets. Meanwhile, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed for the functional annotation of the key genes. ESTIMATE was used to calculate tumor purity for acquiring the correct mRNAsi. Differences in overall survival (OS) between the high and low mRNAsi (corrected mRNAsi) groups were compared using the Kaplan Meier analysis. By combining the Lasso regression with univariate and multivariate Cox regression, the SI-signature was constructed and validated using the Chinese Glioma Genome Atlas (CGGA).

Results

There was a significant difference in OS between the high and low mRNAsi groups, which was also observed in the two corrected mRNAsi groups. Based on threshold limits, 86 DEGs were most significantly associated with mRNAsi via WGCNA. Seven genes (ADAP2, ALOX5AP, APOBEC3C, FCGRT, GNG5, LRRC25, and SP100) were selected to establish a risk signature for primary LGG. The ROC curves showed a fair performance in survival prediction in both the TCGA and the CGGA validation cohorts. Univariate and multivariate Cox regression revealed that the risk group was an independent prognostic factor in primary LGG. The nomogram was developed based on clinical parameters integrated with the risk signature, and its accuracy for predicting 3- and 5-years survival was assessed by the concordance index, the area under the curve of the time-dependent receiver operating characteristics curve, and calibration curves.

Conclusion

The SI-signature with seven genes could serve as an independent predictor, and suggests the importance of stemness features in risk stratification and survival prediction in primary LGG.

MicroRNA-384 Inhibits the Progression of Papillary Thyroid Cancer by Targeting PRKACB

Background

Growing evidence shows that dysregulation of miRNAs plays a significant role in papillary thyroid cancer (PTC) tumorigenesis and development. The abnormal expression of miR-384 has been acknowledged in the proliferation or metastasis of some cancers. However, the function and the underlying mechanism of miR-384 in PTC progression remain largely unknown.

Methods

Real-time PCR was conducted to detect miR-384 expression in 58 cases of PTC and their adjacent noncancerous tissues. MTT, soft agar assay Transwell assay, and wound-healing assay were carried out to explore the biological function of miR-384 in PTC cell lines of BCPAP and K1. Bioinformatics analysis, dual-luciferase reporter assay, western blot, and functional complementation analysis were conducted to explore the target gene of miR-384. Moreover, Spearman's correlation analysis was conducted to reveal the correlation between miR-384 and PRKACB mRNA in PTC.

Results

The expression of miR-384 decreased obviously in PTC, especially in the tumors with lymph node metastasis or larger tumor size. The ectopic upregulation of miR-384 significantly suppressed PTC progression, and the inhibition of miR-384 had the opposite effects. Moreover, PRKACB gene was confirmed as the target of miR-384.

Conclusion

The study suggests that miR-384 serves as a tumor suppressor in PTC progression by directly targeting the 3′-UTR of PRKACB gene.

G Protein-Coupled Receptors (GPCRs)-Mediated Calcium Signaling in Ovarian Cancer: Focus on GPCRs activated by Neurotransmitters and Inflammation-Associated Molecules

G-coupled protein receptors (GCPR) involve several signaling pathways, some of them being coupled with intracellular calcium (Ca²⁺) mobilization. GPCRs were involved in migration, invasion and metastasis of different types of cancers, including ovarian cancer. Many studies have discussed the essential contribution of GPCRs activated by steroid hormones in ovarian cancer. However, ovarian cancer is also associated with altered signals coming from the nervous system, the immune system or the inflammatory environment, in which GPCRs are ‘sensing’ these molecular signals. Many studies have been oriented so far on ovarian cell lines (most of them being of human cell lines), and only few studies based on animal models or clinical studies have been devoted to the expression changes or functional role of GPCRs in ovarian cancer. In this paper, we review the alterations of GPCRs activated by neurotransmitters (muscarinic receptors, serotonin receptors, dopamine receptors, adrenoceptors) or inflammation-associated molecules (bradykinin receptors, histamine receptors, chemokine receptors) in ovarian cancer and we discuss their potential as histological biomarkers.

Diagnostic and prognostic value of mRNA expression of phospholipase C β family genes in hepatitis B virus‑associated hepatocellular carcinoma

Four phospholipase C β (PLCB) isoforms, PLCB1, PLCB2, PLCB3 and PLCB4, have been previously investigated regarding their roles in the metabolism of inositol lipids and cancer. The present study aimed to explore the association between PLCB1-4 and hepatocellular carcinoma (HCC). Data from 212 patients with hepatitis B virus-associated HCC were used to analyze the diagnostic and prognostic significance of PLCB genes in. A nomogram predicted the survival probability. Gene set enrichment analysis explored gene ontology terms and the metabolic pathways associated with PLCB genes. Validation of the prognostic values of PLCB genes was performed using the Gene Expression Profiling Interactive Analysis website. PLCB1 and PLCB2 were revealed to have diagnostic value for HCC (0.869 and 0.836 area under the curve, respectively; both P≤0.05). The combination analysis of these genes had an advantage over each alone (0.905 PLCB1 and PLCB2, and 0.877 PLCB1 and PLCB3 area under the curve; P≤0.05). PLCB1 was associated with overall survival (OS) and recurrence-free survival (RFS; adjusted P=0.002 and P=0.001, respectively). A nomogram predicted survival probability of patients with HCC at 1, 3- and 5-years. Gene set enrichment analysis indicated that PLCB1 and PLCB2 are involved in the cell cycle, cell division and the PPAR signaling pathway, among other functions. Validation using GEPIA revealed that PLCB1 and PLCB2 were associated with OS and PLCB1 and PLCB4 were associated with RFS. PLCB1 and PLCB2 exhibited diagnostic value for HCC and their combination had an advantage over each individually. PLCB1 has OS and RFS prognostic value for patients with HCC.

ACGH detects distinct genomic alterations of primary intrahepatic cholangiocarcinomas and matched lymph node metastases and identifies a poor prognosis subclass

Lymph node metastases (LNM) are an important prognostic factor for patients with intrahepatic cholangiocarcinoma, but underlying genetic alterations are poorly understood. Whole genome array comparative genomic hybridization (aCGH) was performed in 37 tumors and 14 matched LNM. Genomic analyses of tumors confirmed known and identified new (gains in 19q) copy number alterations (CNA). Tumors with LNM (N1) had more alterations and exclusive gains (3p, 4q, 5p, 13q) and losses (17p and 20p). LNM shared most alterations with their matched tumors (86%), but 79% acquired new isolated gains [12q14 (36%); 1p13, 2p23, 7p22, 7q11, 11q12, 13q13 and 14q12 (>20%)]. Unsupervised clustering revealed a poor prognosis subclass with increased alterations significantly associated to tumor differentiation and survival. TP53 and KRAS mutations occurred in 19% of tumors and 6% of metastases. Pathway analyses revealed association to cancer-associated pathways. Advanced tumor stage, microvascular/perineural invasion, and microscopic positive resection margin (R1) were significantly correlated to metastases, while N1-status, R1-resection, and poor tumor differentiation were significantly correlated to survival. ACGH identified clear differences between N0 (no LNM) and N1 tumors, while N1 tumors and matched LNM displayed high clonality with exclusive gains in the metastases. A novel subclass with increased CNAs and poor tumor differentiation was significantly correlated to survival.

Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer

Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRNAs and 1,766 mRNAs differentially expressed between thyroid cancer tissues and normal thyroid tissues and evaluated their prognostic values using Kaplan-Meier survival curves by log-rank test. Seven microRNAs (miR-146b, miR-184, miR-767, miR-6730, miR-6860, miR-196a-2 and miR-509-3) were associated with the overall survival. Among them, three microRNAs were linked with six differentially expressed mRNAs (miR-767 was predicted to target COL10A1, PLAG1 and PPP1R1C; miR-146b was predicted to target MMP16; miR-196a-2 was predicted to target SYT9). To identify the key genes in the protein-protein interaction network , we screened out the top 10 hub genes (NPY, NMU, KNG1, LPAR5, CCR3, SST, PPY, GABBR2, ADCY8 and SAA1) with higher degrees. Only LPAR5 was associated with the overall survival. Multivariate analysis demonstrated that miR-184, miR-146b, miR-509-3 and LPAR5 were an independent risk factors for prognosis. Our results of the present study identified a series of prognostic microRNAs and mRNAs that have the potential to be the targets for treatment of thyroid cancer.

Identification of Metabolomic Biomarkers for Endometrial Cancer and Its Recurrence after Surgery in Postmenopausal Women

Endometrial cancer (EC) is the most frequent gynecological cancer in developed countries. Most EC occurs after menopause and is diagnosed as endometrioid (type I) carcinomas, which exhibit a favorable prognosis. In contrast, non-endometrioid (type II) carcinomas such as serous tumors have a poor prognosis. Our goal was to identify novel blood-based markers associated with EC subtypes and recurrence after surgery in postmenopausal women. Using mass spectrometry-based untargeted metabolomics, we examined preoperative serum metabolites among control women (n = 18) and those with non-recurrent (NR) and recurrent (R) cases of type I endometrioid (n = 24) and type II serous (n = 12) carcinomas. R and NR cases were similar with respect to pathological characteristics, body mass index, and age. A total of 1,592 compounds were analyzed including 14 different lipid classes. When we compared EC cases with controls, 137 metabolites were significantly different. A combination of spermine and isovalerate resulted in an age-adjusted area under the receiver-operating characteristic curve (AUC_adj) of 0.914 (P < 0.001) for EC detection. The combination of 2-oleoylglycerol and TAG42:2-FA12:0 allowed the distinction of R cases from NR cases with an AUC_adj of 0.901 (P < 0.001). Type I R cases were also characterized by much lower levels of bile acids and elevated concentrations of phosphorylated fibrinogen cleavage peptide, whereas type II R cases displayed higher levels of ceramides. The findings from our pilot study provide a detailed metabolomics study of EC and identify putative serum biomarkers for defining clinically relevant risk groups.

Kinin B1 receptors as a therapeutic target for inflammation

INTRODUCTION

Kinins are peptide mediators exerting their pro-inflammatory actions by the selective stimulation of two distinct G-protein coupled receptors, termed BKB1R and BKB2R. While BKB2R is constitutively expressed in a multitude of tissues, BKB1R is hardly expressed at baseline but highly inducible by inflammatory mediators. In particular, BKB1R was shown to be involved in the pathogenesis of numerous inflammatory diseases. Areas covered: This review intends to evaluate the therapeutic potential of substances interacting with the BKB1R. To this purpose we summarize the published literature on animal studies with antagonists and knockout mice for this receptor. Expert Opinion: In most cases the pharmacological inhibition of BKB1R or its genetic deletion was beneficial for the outcome of the disease in animal models. Therefore, several companies have developed BKB1R antagonists and tested them in phase I and II clinical trials. However, none of the developed BKB1R antagonists was further developed for clinical use. We discuss possible reasons for this failure of translation of preclinical findings on BKB1R antagonists into the clinic.

Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance

BACKGROUND

Identification of genes whose basal mRNA expression predicts the sensitivity of tumor cells to cytotoxic treatments can play an important role in individualized cancer medicine. It enables detailed characterization of the mechanism of action of drugs. Furthermore, screening the expression of these genes in the tumor tissue may suggest the best course of chemotherapy or a combination of drugs to overcome drug resistance.

RESULTS

We developed a computational method called ProGENI to identify genes most associated with the variation of drug response across different individuals, based on gene expression data. In contrast to existing methods, ProGENI also utilizes prior knowledge of protein-protein and genetic interactions, using random walk techniques. Analysis of two relatively new and large datasets including gene expression data on hundreds of cell lines and their cytotoxic responses to a large compendium of drugs reveals a significant improvement in prediction of drug sensitivity using genes identified by ProGENI compared to other methods. Our siRNA knockdown experiments on ProGENI-identified genes confirmed the role of many new genes in sensitivity to three chemotherapy drugs: cisplatin, docetaxel, and doxorubicin. Based on such experiments and extensive literature survey, we demonstrate that about 73% of our top predicted genes modulate drug response in selected cancer cell lines. In addition, global analysis of genes associated with groups of drugs uncovered pathways of cytotoxic response shared by each group.

CONCLUSIONS

Our results suggest that knowledge-guided prioritization of genes using ProGENI gives new insight into mechanisms of drug resistance and identifies genes that may be targeted to overcome this phenomenon.

Molecular Pap smear: HPV genotype and DNA methylation of ADCY8, CDH8, and ZNF582 as an integrated biomarker for high-grade cervical cytology

BACKGROUND

The Pap smear has remained the foundation for cervical cancer screening for over 70 years. With advancements in molecular diagnostics, primary high-risk human papillomavirus (hrHPV) screening has recently become an accepted stand-alone or co-test with conventional cytology. However, both diagnostic tests have distinct limitations. The aim of this study was to determine the association between HPV genotypes and cellular epigenetic modifications in three grades of cervical cytology for screening biomarker discovery.

METHODS

This prospective, cross-sectional study used residual liquid-based cytology samples for HPV genotyping and epigenetic analysis. Extracted DNA was subjected to parallel polymerase chain reactions using three primer sets (MY09/11, FAP59/64, E6-E7 F/B) for HPV DNA amplification. HPV+ samples were genotyped by DNA sequencing. Promoter methylation of four candidate tumor suppressor genes (adenylate cyclase 8 (ADCY8), cadherin 8, type 2 (CDH8), MGMT, and zinc finger protein 582 (ZNF582)) out of 48 genes screened was quantified by bisulfite-pyrosequencing of genomic DNA. Independent validation of methylation profiles was performed by analyzing data from cervical cancer cell lines and clinical samples from The Cancer Genome Atlas (TCGA).

RESULTS

Two hundred seventy-seven quality cytology samples were analyzed. HPV was detected in 31/100 (31 %) negative for intraepithelial lesion or malignancy (NILM), 95/100 (95 %) low-grade squamous intraepithelial lesion (LSIL), and 71/77 (92 %) high-grade squamous intraepithelial lesion (HSIL) samples. The proportion of IARC-defined carcinogenic HPV types in sequenced samples correlated with worsening grade: NILM 7/29 (24 %), LSIL 53/92 (58 %), and HSIL 65/70 (93 %). Promoter methylation of ADCY8, CDH8, and ZNF582 was measured in 170 samples: NILM (N = 33), LSIL (N = 70), and HSIL (N = 67) also correlated with worsening grade. Similar hypermethylation patterns were found in cancer cell lines and TCGA samples. The combination of four biomarkers, i.e., HPV genotype and three-gene promoter methylation, predicted HSIL (AUC 0.89) better than HPV alone (AUC 0.74) by logistic regression and probabilistic modeling.

CONCLUSIONS

HPV genotype and DNA methylation of ADCY8, CDH8, and ZNF582 are correlated with cytological grade. Collectively, these biomarkers may serve as a molecular classifier of Pap smears.

Effects of intravitreal ranibizumab on the untreated eye and systemic gene expression profile in age-related macular degeneration

The purpose of this study was to evaluate the systemic effects of intravitreal ranibizumab (Lucentis) treatment in patients with neovascular age-related macular degeneration (AMD). The impact of intravitreal ranibizumab injections on central retinal thickness (CRT) of treated and contralateral untreated eyes, and differences in gene expression patterns in the peripheral blood mononuclear cells were analyzed. The study included 29 patients aged 50 years old and over with diagnosed neovascular AMD. The treatment was defined as 0.5 mg of ranibizumab injected intravitreally in the form of one injection every month during the period of 3 months. CRT was measured by optical coherence tomography. The gene expression profile was assigned using oligonucleotide microarrays of Affymetrix HG-U133A. Studies have shown that there was a change of CRT between treated and untreated eyes, and there were differences in CRT at baseline and after 1, 2, and 3 months of ranibizumab treatment. Three months after intravitreal injection, mean CRT was reduced in the treated eyes from 331.97±123.62 to 254.31±58.75 μm, while mean CRT in the untreated fellow eyes reduced from 251.07±40.29 to 235.45±36.21 μm at the same time. Furthermore, the research has shown that among all transcripts, 3,097 expresses change after the ranibizumab treatment in relation to controls. Among these transcripts, 1,339 were up-regulated, whereas 1,758 were down-regulated. Our results show the potential systemic effects of anti-VEGF therapy for AMD. Moreover, our study indicated different gene expression in peripheral blood mononuclear cells before and after intravitreal ranibizumab treatment.

U-73122 reduces the cell growth in cultured MG-63 ostesarcoma cell line involving Phosphoinositide-specific Phospholipases C

The definition of the number and nature of the signal transduction pathways involved in the pathogenesis and the identification of the molecules promoting metastasis spread might improve the knowledge of the natural history of osteosarcoma, also allowing refine the prognosis and opening the way to novel therapeutic strategies. Phosphatydil inositol (4,5) bisphosphate (PIP2), belonging to the Phosphoinositide (PI) signal transduction pathway, was related to the regulation of ezrin, an ezrin-radixin-moesin protein involved in metastatic osteosarcoma spread. The levels of PIP2 are regulated by means of the PI-specific Phospholipase C (PLC) enzymes. Recent literature data suggested that in osteosarcoma the panel of expression of PLC isoforms varies in a complex and unclear manner and is related to ezrin, probably networking with Ras GTPases, such as RhoA and Rac1. We analyzed the expression and the subcellular localization of PLC enzymes in cultured human osteosarcoma MG-63 cells, commonly used as an experimental model for human osteoblasts, using U-73122 PLC inhibitor, U-73343 inactive analogue, and by silencing ezrin. The treatment with U-73122 significantly reduces the number of MG-63 viable cells and contemporarily modifies the expression and the subcellular localization of selected PLC isoforms. U-73122 reduces the cell growth in cultured MG-63 ostesarcoma cell line involving PI-specific Phospholipases C.

Profiling of Discrete Gynecological Cancers Reveals Novel Transcriptional Modules and Common Features Shared by Other Cancer Types and Embryonic Stem Cells

Studies on individual types of gynecological cancers (GCs), utilizing novel expression technologies, have revealed specific pathogenetic patterns and gene markers for cervical (CC), endometrial (EC) and vulvar cancer (VC). Although the clinical phenotypes of the three types of gynecological cancers are discrete, the fact they originate from a common embryological origin, has led to the hypothesis that they might share common features reflecting regression to early embryogenesis. To address this question, we performed a comprehensive comparative analysis of their profiles. Our data identified both common features (pathways and networks) and novel distinct modules controlling the same deregulated biological processes in all three types. Specifically, four novel transcriptional modules were discovered regulating cell cycle and apoptosis. Integration and comparison of our data with other databases, led to the identification of common features among cancer types, embryonic stem (ES) cells and the newly discovered cell population of squamocolumnar (SC) junction of the cervix, considered to host the early cancer events. Conclusively, these data lead us to propose the presence of common features among gynecological cancers, other types of cancers, ES cells and the pre-malignant SC junction cells, where the novel E2F/NFY and MAX/CEBP modules play an important role for the pathogenesis of gynecological carcinomas.

Non-canonical signalling and roles of the vasoactive peptides angiotensins and kinins

GPCRs (G-protein-coupled receptors) are among the most important targets for drug discovery due to their ubiquitous expression and participation in cellular events under both healthy and disease conditions. These receptors can be activated by a plethora of ligands, such as ions, odorants, small ligands and peptides, including angiotensins and kinins, which are vasoactive peptides that are classically involved in the pathophysiology of cardiovascular events. These peptides and their corresponding GPCRs have been reported to play roles in other systems and under pathophysiological conditions, such as cancer, central nervous system disorders, metabolic dysfunction and bone resorption. More recently, new mechanisms have been described for the functional regulation of GPCRs, including the transactivation of other signal transduction receptors and the activation of G-protein-independent pathways. The existence of such alternative mechanisms for signal transduction and the discovery of agonists that can preferentially trigger one signalling pathway over other pathways (called biased agonists) have opened new perspectives for the discovery and development of drugs with a higher specificity of action and, therefore, fewer side effects. The present review summarizes the current knowledge on the non-canonical signalling and roles of angiotensins and kinins.

The role of kinin receptors in cancer and therapeutic opportunities

Kinins are generated within inflammatory tissue microenvironments, where they exert diverse functions, including cell proliferation, leukocyte activation, cell migration, endothelial cell activation and nociception. These pleiotropic functions depend on signaling through two cross talking receptors, the constitutively expressed kinin receptor 2 (B2R) and the inducible kinin receptor 1 (B1R). We have reviewed evidence, which supports the concept that kinin receptors, especially kinin receptor 1, are promising targets for cancer therapy, since (1) many tumor cells express aberrantly high levels of these receptors; (2) some cancers produce kinins and use them as autocrine factors to stimulate their growth; (3) activation of kinin receptors leads to activation of macrophages, dendritic cells and other cells from the tumor microenvironment; (4) kinins have pro-angiogenic properties; (5) kinin receptors have been implicated in cancer migration, invasion and metastasis; and (6) selective antagonists for either B1R or B2R have shown anti-proliferative, anti-inflammatory, anti-angiogenic and anti-migratory properties. The multiple cross talks between kinin receptors and renin-angiotensin system (RAS) as well as its implications for targeting KKS or RAS for the treatment of malignancies are also discussed. It is expected that B1R antagonists would interfere less with housekeeping functions and therefore would be attractive compounds to treat selected types of cancer. Reliable clinical studies are needed to establish the translatability of these data to human settings and the usefulness of kinin receptor antagonists.