Dataset Information

A Comprehensive Molecular and Clinical Analysis of the piRNA Pathway Genes in Ovarian Cancer.

ABSTRACT: Ovarian cancer (OC) is one of the most lethal gynecological malignancies, yet molecular mechanisms underlying its origin and progression remain poorly understood. With increasing reports of piRNA pathway deregulation in various cancers, we aimed to better understand its role in OC through a comprehensive analysis of key genes: PIWIL1-4, DDX4, HENMT1, MAEL, PLD6, TDRD1,9 and mutants of PIWIL1 (P1?17) and PIWIL2 (PL2L60). High-throughput qRT-PCR (n = 45) and CSIOVDB (n = 3431) showed differential gene expression when comparing benign ovarian tumors, low grade OC and high grade serous OC (HGSOC). Significant correlation of disparate piRNA pathway gene expression levels with better progression free, post-progression free and overall survival suggests a complex role of this pathway in OC. We discovered PIWIL3 expression in chemosensitive but not chemoresistant primary HGSOC cells, providing a potential target against chemoresistant disease. As a first, we revealed that follicle stimulating hormone increased PIWIL2 expression in OV-90 cells. PIWIL1, P1?17, PIWIL2, PL2L60 and MAEL overexpression in vitro and in vivo decreased motility and invasion of OVCAR-3 and OV-90 cells. Interestingly, P1?17 and PL2L60, induced increased motility and invasion compared to PIWIL1 and PIWIL2. Our results in HGSOC highlight the intricate role piRNA pathway genes play in the development of malignant neoplasms.

SUBMITTER: Lee E

PROVIDER: S-EPMC7792616 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Comprehensive Molecular and Clinical Analysis of the piRNA Pathway Genes in Ovarian Cancer.

Lee Eunice E Lokman Noor A NA Oehler Martin K MK Ricciardelli Carmela C Grutzner Frank F

Cancers 20201222 1

Ovarian cancer (OC) is one of the most lethal gynecological malignancies, yet molecular mechanisms underlying its origin and progression remain poorly understood. With increasing reports of piRNA pathway deregulation in various cancers, we aimed to better understand its role in OC through a comprehensive analysis of key genes: PIWIL1-4, DDX4, HENMT1, MAEL, PLD6, TDRD1,9 and mutants of PIWIL1 (P1∆17) and PIWIL2 (PL2L60). ...[more]

PMID: 33374923

Similar Datasets

Project description:The importance of the Piwi-interacting RNA (piRNA) pathway for germ cell maintenance, genome integrity, DNA methylation and retrotransposon control raises possible roles of this pathway in cancer. Indeed aberrant expression of human PIWI orthologs and Maelstrom has been observed in various cancers. In this study we explored the expression and function of piRNA pathway genes in human ovarian cancer, based on our recent work, which showed widespread expression of piRNA pathway genes in the mammalian. Our work shows that PIWIL1 and MAEL expression is significantly increased in malignant EOC (n = 25) compared to benign tumor tissues (n = 19) and normal ovarian tissue (n = 8). The expression of PIWIL3 is lower in malignant and benign tissues when compared to normal ovary. Sequencing of PIWIL1 transcript revealed that in many tumors deletion of exon 17 leads to the introduction of a premature stop codon in the PIWI domain, likely due to a splicing error. In situ hybridization on tumor sections revealed that L1, PIWIL1, 2 and MAEL are specifically expressed in epithelial cells (cancerous cells) of EOC. Furthermore, PIWIL2 and MAEL are co-expressed in the stromal cells adjacent to tumor cells. Since PIWIL1 and MAEL are up regulated in malignant EOC and expressed in the epithelial cells, we investigated if these two genes affect invasiveness of ovarian cancer cell lines that do not normally express these genes. PIWIL1 and MAEL were transiently over expressed in the ovarian cancer cell line SKOV3, followed by real-time measurements of cell invasiveness. Surprisingly both PIWIL1 and MAEL over expression decreased the invasiveness of SKOV3 cells. Our findings support a growing body of evidence that shows that genes in this pathway are upregulated in cancer. In ovarian cancer we show for the first time that Piwil1 transcript may often be abnormal result in non functional product. In contrast to what has been observed in other cell types, we found that PIWIL1 and MAEL have a repressive effect on cell invasiveness.

Project description:Background: Ovarian cancer is one of the leading causes of cancer-related death in women. The incidence of ovarian cancer is insidious, and the recurrence rate is high. The survival rate of ovarian cancer has not significantly improved over the past decade. Recently, immune checkpoint inhibitors such as those targeting CTLA-4, PD-1, or PD-L1 have been used to treat ovarian cancer. Therefore, a full analysis of the immune biomarkers associated with this malignancy is necessary.Methods: In this study, we used data from The Cancer Genome Atlas (TCGA) database to analyze the infiltration patterns of specific immune cell types in tumor samples. Data from the Gene Expression Omnibus (GEO) database was used for external validation. According to the invasion patterns of immune cells, we divided the ovarian cancer microenvironment into two clusters: A and B. These tumor microenvironment (TME) subtypes were associated with genomic and clinicopathological characteristics. Subsequently, a random forest classification model was established. Differential genomic features, functional enrichment, and DNA methylation were analyzed between the two clusters. The characteristics of immune cell infiltration and the expression of immune-related cytokines or markers were analyzed. Somatic mutation analysis was also performed between clusters A and B. Finally, multivariate Cox analysis was used to analyze independent prognostic factors.Results: The ovarian cancer TME cluster A was characterized by less infiltration of immune cells and sparse distribution and low expression of immunomodulators. In contrast, cytotoxic T cells and immunosuppressive cells were significantly increased in the ovarian cancer TME cluster B. Additionally, immune-related cytokines or markers, including IFN-? and TNF-?, were also expressed in large quantities. In total, 35 differentially methylated and expressed genes (DMEGs) were identified. Functional enrichment analyses revealed that the DMEGs in cluster B participated in important biological processes and immune-related pathways. The mutation load in cluster B was insignificantly higher than that of cluster A (p = 0.076). Multivariate Cox analysis showed that TME was an independent prognostic factor for ovarian cancer (hazard ratio: 1.33, 95% confidence interval: 1.01-1.75, p = 0.041).Conclusion: This study described and classified basic information about the immune invasion pattern of ovarian cancer and integrated biomarkers related to different immunophenotypes to reveal interactions between ovarian cancer and the immune system.

Project description:BackgroundTumor molecular profile analysis by Next Generation Sequencing technology is currently widely applied in clinical practice and has enabled the detection of predictive biomarkers of response to targeted treatment. In parallel with targeted therapies, immunotherapies are also evolving, revolutionizing cancer therapy, with Programmed Death-ligand 1 (PD-L1), Microsatellite instability (MSI), and Tumor Mutational Burden (TMB) analysis being the biomarkers employed most commonly.MethodsIn the present study, tumor molecular profile analysis was performed using a 161 gene NGS panel, containing the majority of clinically significant genes for cancer treatment selection. A variety of tumor types have been analyzed, including aggressive and hard to treat cancers such as pancreatic cancer. Besides, the clinical utility of immunotherapy biomarkers (TMB, MSI, PD-L1), was also studied.ResultsMolecular profile analysis was conducted in 610 cancer patients, while in 393 of them a at least one biomarker for immunotherapy response was requested. An actionable alteration was detected in 77.87% of the patients. 54.75% of them received information related to on-label or off-label treatment (Tiers 1A.1, 1A.2, 2B, and 2C.1) and 21.31% received a variant that could be used for clinical trial inclusion. The addition to immunotherapy biomarker to targeted biomarkers' analysis in 191 cases increased the number of patients with an on-label treatment recommendation by 22.92%, while an option for on-label or off-label treatment was provided in 71.35% of the cases.ConclusionsTumor molecular profile analysis using NGS is a first-tier method for a variety of tumor types and provides important information for decision making in the treatment of cancer patients. Importantly, simultaneous analysis for targeted therapy and immunotherapy biomarkers could lead to better tumor characterization and offer actionable information in the majority of patients. Furthermore, our data suggest that one in two patients may be eligible for on-label ICI treatment based on biomarker analysis. However, appropriate interpretation of results from such analysis is essential for implementation in clinical practice and accurate refinement of treatment strategy.

Dataset Information

A Comprehensive Molecular and Clinical Analysis of the piRNA Pathway Genes in Ovarian Cancer.

Publications

A Comprehensive Molecular and Clinical Analysis of the piRNA Pathway Genes in Ovarian Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets