ABCC9, NKAPL, and TMEM132C are potential diagnostic and prognostic markers in triple-negative breast cancer

Transcriptomic characterization of lung pericytes in systemic sclerosis-associated pulmonary fibrosis

Systemic sclerosis (SSc) is a chronic disease characterized by fibrosis and vascular abnormalities in the skin and internal organs, including the lung. SSc-associated pulmonary fibrosis (SSc-PF) is the leading cause of death in SSc patients. Pericytes are key regulators of vascular integrity and endothelial function. The role that pericytes play in SSc-PF remains unclear. We compared the transcriptome of pericytes from SSc-PF lungs (SScL) to pericytes from normal lungs (NORML). We identified 1,179 differentially expressed genes in SScL pericytes. Pathways enriched in SScL pericytes included prostaglandin, PI3K-AKT, calcium, and vascular remodeling signaling. Decreased cyclic AMP production and altered phosphorylation of AKT in response to prostaglandin E2 in SScL pericytes demonstrate the functional consequence of changes in the prostaglandin pathway that may contribute to fibrosis. The transcriptomic signature of SSc lung pericytes suggests that they promote vascular dysfunction and contribute to the loss of protection against lung inflammation and fibrosis.

Epigenetic alterations in urothelial bladder cancer associated with disease outcomes

OBJECTIVES

Bladder cancer (BLCA) is a molecular heterogeneous disease with known genetic distinctive signatures. However, DNA methylation is highly prevalent across a wide range of tumors, suggesting its potential in oncogenesis. Here, we aimed to interrogate the role of nine epigenetic alterations as diagnostic and prognostic markers in BLCA.

METHODS

DNA methylation, gene expression, and clinicopathological information were retrieved from The Cancer Genome Atlas data portal. Methylation values and gene expression were assessed to determine their association with normal and malignant tissue. Additionally, we studied the association between methylation values and clinicopathological variables. For the prognostic model, Kaplan-Meier Survival curves were generated. Lastly, univariate and multivariate analysis were performed to evaluate the simultaneous impact of methylation and clinicopathological variables on the risk of tumor progression and survival.

RESULTS

Nine CpG sites' methylation β -values involved in our study demonstrated different methylation signatures between normal and malignant urothelium. Hypermethylated CpGs were overrepresented in tumor tissue (p < 0.0001). Opposingly, 4 CpG sites showed lower methylation values in tumor samples (p < 0.0001). Cg12743248high and cg17192862low are risk factors for progression-free survival, whereas cg12374721high (HR:3.003 (1.283-7.030)) also demonstrated to be the most valuable independent risk factor for disease progression and a risk factor for overall survival.

CONCLUSIONS

We have identified that methylated cg12374721 shows promise as a diagnostic and independent prognostic marker in BLCA progression.

Exploring the Role of Surface and Mitochondrial ATP-Sensitive Potassium Channels in Cancer: From Cellular Functions to Therapeutic Potentials

ATP-sensitive potassium (KATP) channels are found in plasma membranes and mitochondria. These channels are a type of ion channel that is regulated by the intracellular concentration of adenosine triphosphate (ATP) and other nucleotides. In cell membranes, they play a crucial role in linking metabolic activity to electrical activity, especially in tissues like the heart and pancreas. In mitochondria, KATP channels are involved in protecting cells against ischemic damage and regulating mitochondrial function. This review delves into the role of KATP channels in cancer biology, underscoring their critical function. Notably responsive to changes in cellular metabolism, KATP channels link metabolic states to electrical activity, a feature that becomes particularly significant in cancer cells. These cells, characterized by uncontrolled growth, necessitate unique metabolic and signaling pathways, differing fundamentally from normal cells. Our review explores the intricate roles of KATP channels in influencing the metabolic and ionic balance within cancerous cells, detailing their structural and operational mechanisms. We highlight the channels' impact on cancer cell survival, proliferation, and the potential of KATP channels as therapeutic targets in oncology. This includes the challenges in targeting these channels due to their widespread presence in various tissues and the need for personalized treatment strategies. By integrating molecular biology, physiology, and pharmacology perspectives, the review aims to enhance the understanding of cancer as a complex metabolic disease and to open new research and treatment avenues by focusing on KATP channels. This comprehensive approach provides valuable insights into the potential of KATP channels in developing innovative cancer treatments.

Genomic alterations as independent prognostic factors to predict the type of lung cancer recurrence

INTRODUCTION

33-70% of lung cancer (LC) patients develop recurrence after radical treatment. Previous studies have shown the importance of clinical-pathological characteristics for the risk of recurrence. The role of molecular mechanisms remains unclear. The aim was analyzing genomic features in LC patients with local (LR) versus distant recurrence (DR) to predict the risk and type of recurrence.

MATERIALS AND METHODS

Patients previously curatively treated with LC recurrences from 2015 to 2017 were retrospectively enrolled. Histological specimens collected at the time of LC diagnosis were sent for whole exome sequencing (WES). Genomic data was analyzed for single nucleotide polymorphisms (SNPs) and insertion-deletion mutations (INDELs).

RESULTS

191 patients were included. 33% of patients had LR and 67% DR, with median recurrence-free survival (RFS) 15.4 versus 11.2 months (p = 0.20) and overall survival (OS) after recurrence 12.9 versus 8.5 months (p = 0.007), respectively. Of various laboratory parameters studied, lymphocytes were significantly decreased at recurrence (p < 0.0001) in the DR group. In genetic analysis, significantly enriched INDEL mutations were found in 38 and 98 genes and SNP mutations in 63 and 179 genes in DR and LR groups, respectively. DMXL2 and ABCC9 gene mutations caused by INDELs appeared exclusively in the DR group. Enrichment analysis detected genes, like KNTC1, CLASP1, CLASP2 and CENPE, responsible of microtubule disturbance in the DR group. Furthermore, genes related to cytosolic Ca2+ such as STIM1, ITPR3 and RYR3, were significantly enriched in DR group whereas in LR group enrichment of pathways related to endoplasmic/sarcoplasmic reticulum Ca2+ was observed.

CONCLUSION

Our findings indicate distinct genomic signatures in the LR and DR cohorts, with microtubule disturbance and calcium regulation playing a crucial role in invasiveness in DR of LC. Understanding molecular mechanisms of LC recurrence may lead to the discovery of novel drug targets that could potentially stop spread of cancer cells.

Expression profiling of luminal B breast tumor in Indian women

PURPOSE

In this study, we aimed at profiling of luminal B breast cancer specific gene expression pattern in Indian women using mRNA-seq and validation based on TCGA expression data.

METHODS

RNA isolated from luminal B tumor and adjacent normal tissues was used for library construction and sequencing. Reference-based assemblies of these reads were used for differential gene expression analysis using DeSeq2. The DEGs were evaluated using TCGA expression data. Kaplan-Meier survival method was used to evaluate association between genes showing luminal B specific differential expression pattern and breast cancer prognosis and statistical significance was assessed using log-rank test. Alternate splicing analysis was done using rmats.

RESULTS

Differential expression analysis identified 2371 differentially expressed genes (DEGs) in luminal B breast tumors in comparison with adjacent normal tissues of Indian Women. Of them, 1692 DEGs were validated using TCGA luminal B paired samples. Integration of this data with the DEGs obtained by comparative analysis of unpaired luminal B with luminal A unpaired samples from TCGA resulted in 291 DEGs showing luminal B specific expression pattern. Further, 26 genes of prognostic value were identified. Differential splicing analysis between luminal B tumors and adjacent normal tissues in our cohort led to the identification of 687 genes showing significant differential alternate splicing events.

CONCLUSION

This study profiled gene expression pattern of luminal B tumors of Indian women and identified 26 key genes of prognostic value for luminal B breast cancer. This study also profiled differential alternate splicing and identified important alternate splicing events in luminal B breast cancer.

Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers

Combining omics data from different layers using integrative methods provides a better understanding of the biology of a complex disease such as cancer. The discovery of biomarkers related to cancer development or prognosis helps to find more effective treatment options. This study integrates multi-omics data of different cancer types with a network-based approach to explore common gene modules among different tumors by running community detection methods on the integrated network. The common modules were evaluated by several biological metrics adapted to cancer. Then, a new prognostic scoring method was developed by weighting mRNA expression, methylation, and mutation status of genes. The survival analysis pointed out statistically significant results for GNG11, CBX2, CDKN3, ARHGEF10, CLN8, SEC61G and PTDSS1 genes. The literature search reveals that the identified biomarkers are associated with the same or different types of cancers. Our method does not only identify known cancer-specific biomarker genes, but also proposes new potential biomarkers. Thus, this study provides a rationale for identifying new gene targets and expanding treatment options across cancer types.

Immunohistochemical, pharmacovigilance, and omics analyses reveal the involvement of ATP-sensitive K+ channel subunits in cancers: role in drug-disease interactions

Background: ATP-sensitive-K+ channels (KATP) are involved in diseases, but their role in cancer is poorly described. Pituitary macroadenoma has been observed in Cantu' syndrome (C.S.), which is associated with the gain-of-function mutations of the ABCC9 and KCNJ8 genes. We tested the role of the ABCC8/Sur1, ABCC9/Sur2A/B, KCNJ11/Kir6.2, and KCNJ8/Kir6.1 genes experimentally in a minoxidil-induced renal tumor in male rats and in the female canine breast cancer, a spontaneous animal model of disease, and in the pharmacovigilance and omics databases. Methods: We performed biopsies from renal tissues of male rats (N = 5) following a sub-chronic high dosing topical administration of minoxidil (0.777-77.7 mg/kg/day) and from breast tissues of female dogs for diagnosis (N = 23) that were analyzed by immunohistochemistry. Pharmacovigilance and omics data were extracted from EudraVigilance and omics databases, respectively. Results: An elevated immunohistochemical reactivity to Sur2A-mAb was detected in the cytosol of the Ki67+/G3 cells other than in the surface membrane in the minoxidil-induced renal tumor and the breast tumor samples. KCNJ11, KCNJ8, and ABCC9 genes are upregulated in cancers but ABCC8 is downregulated. The Kir6.2-Sur2A/B-channel opener minoxidil showed 23 case reports of breast cancer and one case of ovarian cancer in line with omics data reporting, respectively, and the negative and positive prognostic roles of the ABCC9 gene in these cancers. Sulfonylureas and glinides blocking the pancreatic Kir6.2-Sur1 subunits showed a higher risk for pancreatic cancer in line with the positive prognostic role of the ABCC8 gene but low risks for common cancers. Glibenclamide, repaglinide, and glimepiride show a lower cancer risk within the KATP channel blockers. The Kir6.2-Sur1 opener diazoxide shows no cancer reactions. Conclusion: An elevated expression of the Sur2A subunit was found in proliferating cells in two animal models of cancer. Immunohistochemistry/omics/pharmacovigilance data reveal the role of the Kir6.1/2-Sur2A/B subunits as a drug target in breast/renal cancers and in C.S.

Unveiling the epigenomic mechanisms of acquired platinum-resistance in high-grade serous ovarian cancer

Resistance to platinum-based chemotherapy is the major cause of death from high-grade serous ovarian cancer (HGSOC). We hypothesise that detection of specific DNA methylation changes may predict platinum resistance in HGSOC. Using a publicly available "discovery" dataset we examined epigenomic and transcriptomic alterations between primary platinum-sensitive (n = 32) and recurrent acquired drug resistant HGSOC (n = 28) and identified several genes involved in immune and chemoresistance-related pathways. Validation via high-resolution melt analysis of these findings, in cell lines and HGSOC tumours, demonstrated the most consistent changes were observed in three of the genes: APOBEC3A, NKAPL and PDCD1. Plasma samples from an independent HGSOC cohort (n = 17) were analysed using droplet digital PCR. Hypermethylation of NKAPL was detected in 46% and hypomethylation of APOBEC3A in 69% of plasma samples taken from women with relapsed HGSOC (n = 13), with no alterations identified in disease-free patients (n = 4). Following these results, and using a CRISPR-Cas9 approach, we were also able to demonstrate that in vitro NKAPL promoter demethylation increased platinum sensitivity by 15%. Overall, this study demonstrates the importance of aberrant methylation, especially of the NKAPL gene, in acquired platinum resistance in HGSOC.

Curcumin alters distinct molecular pathways in breast cancer subtypes revealed by integrated miRNA/mRNA expression analysis

BACKGROUND

Curcumin is well known for its anticancer properties. Its cytotoxic activity has been documented in several cancer cell lines, including breast cancer. The pleiotropic activity of curcumin as an antioxidant, an antiangiogenic, antiproliferative, and pro-apoptotic, is due to its diverse targets, such as signaling pathways, protein/enzyme, or noncoding gene.

AIM

This study aimed to identify key miRNAs and mRNAs induced by curcumin in breast cancer cells MCF7, T47D (hormone positive), versus MDA-MB231 (hormone negative) using comparative analysis of global gene expression profiles.

METHODS

RNA was isolated and subjected to mRNA and miRNA library sequencing to study the global gene expression profile of curcumin-treated breast cancer cells. The differential expression of gene and miRNA was performed using the DESeq R package. The enriched pathways were studied using cluster profileR, and integrated miRNA-mRNA analysis was carried out using miRtarvis and miRmapper tools.

RESULTS

Curcumin treatment led to upregulation of 59% TSGs in MCF7, 21% in MDA-MB-231 cells, and 36% TSGs in T47D, and downregulation of 57% oncogenes in MCF7, 76% in MDA-MB-231, and 91% in T47D. Similarly, curcumin treatment led to upregulation of 32% TSmiRs in MCF7, 37.5% in MDA-MB231, and 62.5% in T47D, and downregulation of 77% oncomiRs in MCF7, 50% in MDA-MB231 and 28.6% in T47D. Integrated analysis of miRNA-mRNA led to the identification of a common NFKB pathway altered by curcumin in all three cell lines. Analysis of uniquely enriched pathway revealed non-integrin membrane-ECM interactions and laminin interactions in MCF7; extracellular matrix organization and degradation in MDA-MB-231 and cell cycle arrest and G2/M transition in T47D.

CONCLUSION

Curcumin regulates miRNA and mRNA in a cell type-specific manner. The integrative analysis led to the detection of miRNAs and mRNAs pairs, which can be used as biomarkers associated with carcinogenesis, diagnostic, and treatment response in breast cancer.

Robust analysis of cancer heterogeneity for high-dimensional data

Cancer heterogeneity plays an important role in the understanding of tumor etiology, progression, and response to treatment. To accommodate heterogeneity, cancer subgroup analysis has been extensively conducted. However, most of the existing studies share the limitation that they cannot accommodate heavy-tailed or contaminated outcomes and also high dimensional covariates, both of which are not uncommon in biomedical research. In this study, we propose a robust subgroup identification approach based on M-estimators together with concave and pairwise fusion penalties, which advances from existing studies by effectively accommodating high-dimensional data containing some outliers. The penalties are applied on both latent heterogeneity factors and covariates, where the estimation is expected to achieve subgroup identification and variable selection simultaneously, with the number of subgroups being apriori unknown. We innovatively develop an algorithm based on parallel computing strategy, with a significant advantage of capable of processing large-scale data. The convergence property of the proposed algorithm, oracle property of the penalized M-estimators, and selection consistency of the proposed BIC criterion are carefully established. Simulation and analysis of TCGA breast cancer data demonstrate that the proposed approach is promising to efficiently identify underlying subgroups in high-dimensional data.

Identification of hub genes and immune cell infiltration characteristics in chronic rhinosinusitis with nasal polyps: Bioinformatics analysis and experimental validation

The aim of our study is to reveal the hub genes related to the pathogenesis of chronic rhinosinusitis with nasal polyps (CRSwNP) and their association with immune cell infiltration through bioinformatics analysis combined with experimental validation. In this study, through differential gene expression analysis, 1,516 upregulated and 1,307 downregulated DEG were obtained from dataset GSE136825 of the GEO database. We identified 14 co-expressed modules using weighted gene co-expression network analysis (WGCNA), among which the most significant positive and negative correlations were MEgreen and MEturquoise modules, containing 1,540 and 3,710 genes respectively. After the intersection of the two modules and DEG, two gene sets—DEG-MEgreen and DEG-MEturquoise—were obtained, containing 395 and 1,168 genes respectively. Through GO term analysis, it was found that immune response and signal transduction are the most important biological processes. We found, based on KEGG pathway enrichment analysis, that osteoclast differentiations, cytokine–cytokine receptor interactions, and neuroactive ligand–receptor interactions are the most important in the two gene sets. Through PPI network analysis, we listed the top-ten genes for the concentrated connectivity of the two gene sets. Next, a few genes were verified by qPCR experiments, and FPR2, ITGAM, C3AR1, FCER1G, CYBB in DEG-MEgreen and GNG4, NMUR2, and GNG7 in DEG-MEturquoise were confirmed to be related to the pathogenesis of CRSwNP. NP immune cell infiltration analysis revealed a significant difference in the proportion of immune cells between the NP group and control group. Finally, correlation analysis between target hub genes and immune cells indicated that FPR2 and GNG7 had a positive or negative correlation with some specific immune cells. In summary, the discoveries of these new hub genes and their association with immune cell infiltration are of great significance for uncovering the specific pathogenesis of CRSwNP and searching for disease biomarkers and potential therapeutic targets.

Differential expression of the Tmem132 family genes in the developing mouse nervous system

The family of novel transmembrane proteins (TMEM) 132 have been associated with multiple neurological disorders and cancers in humans, but have hardly been studied in vivo. Here we report the expression patterns of the five Tmem132 genes (a, b, c, d and e) in developing mouse nervous system with RNA in situ hybridization in wholemount embryos and tissue sections. Our results reveal differential and partially overlapping expression of multiple Tmem132 family members in both the central and peripheral nervous system, suggesting potential partial redundancy among them.

Inhibition of ABCC9 by zinc oxide nanoparticles induces ferroptosis and inhibits progression, attenuates doxorubicin resistance in breast cancer

Background

Zinc oxide nanoparticles (ZONs) are a type of nanomaterial that has presented anti-cancer properties in breast cancer (BC). However, the function of ABCC9 in BC and its correlation with ZONs are still elusive.

Methods

Here, we identified the crucial role of ABCC9 in modulating ferroptosis and doxorubicin (Dox) resistance in BC and the targeted function of ZONs to ABCC9.

Results

The silencing of ABCC9 significantly repressed the viability of BC cells. The knockdown of ABCC9 decreased the numbers of Edu-positive BC cells. Conversely, BC cell apoptosis was increased by the inhibition of ABCC9. Besides, the silencing of ABCC9 reduced the capability of migration and invasion of BC cells. Significantly, tumorigenicity analysis demonstrated that the tumor growth of BC cells was suppressed by the depletion of ABCC9 in the xenograft model of nude mice. Moreover, the treatment of ferroptosis activator erastin repressed cell viability of BC cells and ABCC9 overexpression rescued the repression. Similarly, the numbers of Edu-positive BC cells were inhibited by erastin and the overexpression of ABCC9 reversed the inhibitory effect of erastin. The levels of GSH were decreased and MDA, lipid ROS, and iron levels were increased by the treatment of erastin, while the ABCC9 overexpression could reverse these results in BC cells. Consistently, erastin suppressed the expression of ferroptosis inhibitory factors, including GPX4 and SLC7A11, in BC cells and the overexpression of ABCC9 rescued the expression. The IC50 value of Dox was reduced by the knockdown of ABCC9 in Dox-resistant BC cells (BC/Dox). The numbers of Edu-positive BC/Dox cells were attenuated by the depletion of ABCC9. Meanwhile, the apoptosis of BC/Dox cells was stimulated by the silencing of ABCC9. Furthermore, the treatment of ZONs attenuated Dox resistance of BC cells. ZONs remarkably repressed the expression of ABCC9 in BC/Dox cells. ZONs inhibited the cell viability of BC/Dox cells and the overexpression of ABCC9 reversed the repression. Moreover, the treatment of ZONs reduced GSH levels and enhanced MDA, lipid ROS, and iron levels in erastin-stimulated BC/Dox cells.

Conclusions

In conclusion, we discovered that the inhibition of ABCC9 by zinc oxide nanoparticles induces ferroptosis and attenuates Dox resistance in BC.

In silico study of cancer stage-specific DNA methylation pattern in White breast cancer patients based on TCGA dataset

BACKGROUND

Breast cancer is one of the most common types of cancer among women. As current breast cancer treatments are still ineffective, we assess the methylation pattern of White breast cancer patients across cancer stage based on The Cancer Genome Atlas (TCGA) dataset. Significant hypermethylation and hypomethylation can regulate the gene expression, thus becoming potential biomarkers in breast cancer tumorigenesis.

METHODS

DNA methylation data was downloaded using TCGA Assembler 2 based on race-specific metadata of TCGA - Breast Invasive Carcinoma (TCGA-BRCA) project from Genomic Data Commons (GDC) Data Portal. After the data was divided into each cancer stage, duplicated data of each patient was removed using OMICSBind, while differentially-expressed probes were identified using edgeR. The resulting probes were validated based on correlation and regression analysis with the gene expression, ANOVA between cancer stages, ROC curve per stage, as well as databases.

RESULTS

Based on the White dataset, we found 66 significant hypermethylated genes with logFC > 1.8 between Stage I-III. From this number, three epigenetic-regulated, stage-specific genes are proposed to be the detection biomarkers of breast cancer due to significant aberrant gene expression and/or low mutation ratio among breast cancer patients: ABCC9 (Stage III), SHISA3 (Stage II), and POU4F1 (Stage I-II).

CONCLUSIONS

Our study shows that ABCC9, SHISA3, and POU4F1 are potential stage-specific detection biomarkers of breast cancer for White individuals, whereas their roles in other races need to be studied further.

Feature Selection for Breast Cancer Classification by Integrating Somatic Mutation and Gene Expression

Exploring the molecular mechanisms of breast cancer is essential for the early prediction, diagnosis, and treatment of cancer patients. The large scale of data obtained from the high-throughput sequencing technology makes it difficult to identify the driver mutations and a minimal optimal set of genes that are critical to the classification of cancer. In this study, we propose a novel method without any prior information to identify mutated genes associated with breast cancer. For the somatic mutation data, it is processed to a mutated matrix, from which the mutation frequency of each gene can be obtained. By setting a reasonable threshold for the mutation frequency, a mutated gene set is filtered from the mutated matrix. For the gene expression data, it is used to generate the gene expression matrix, while the mutated gene set is mapped onto the matrix to construct a co-expression profile. In the stage of feature selection, we propose a staged feature selection algorithm, using fold change, false discovery rate to select differentially expressed genes, mutual information to remove the irrelevant and redundant features, and the embedded method based on gradient boosting decision tree with Bayesian optimization to obtain an optimal model. In the stage of evaluation, we propose a weighted metric to modify the traditional accuracy to solve the sample imbalance problem. We apply the proposed method to The Cancer Genome Atlas breast cancer data and identify a mutated gene set, among which the implicated genes are oncogenes or tumor suppressors previously reported to be associated with carcinogenesis. As a comparison with the integrative network, we also perform the optimal model on the individual gene expression and the gold standard PMA50. The results show that the integrative network outperforms the gene expression and PMA50 in the average of most metrics, which indicate the effectiveness of our proposed method by integrating multiple data sources, and can discover the associated mutated genes in breast cancer.

Assessment of Significant Pathway Signaling and Prognostic Value of GNG11 in Ovarian Serous Cystadenocarcinoma

BACKGROUND

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.