Epithelial ovarian cancer: the molecular genetics of epithelial ovarian cancer

Krzystyniak, Joanna; Ceppi, Lorenzo; Dizon, Don S.; Birrer, Michael J.

doi:10.1093/annonc/mdw083

Cited by 52 publications

(56 citation statements)

References 44 publications

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“…Among gynaecological malignancies, ovarian cancer is the most lethal one. 79 The high mortality due to ovarian cancer is attributed to the late diagnosis of the disease (up to 75% of women have advanced disease at diagnosis) and chemoresistance. 80 The treatment strategy employed for ovarian cancer involves an initial debulking surgery followed by chemotherapy.…”

Section: Complement In Ovarian Cancermentioning

confidence: 99%

Complement system's role in cancer and its therapeutic potential in ovarian cancer

Bareke

Akbuğa

2018

Scand J Immunol

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Cancer immunotherapy is a strong candidate for the long-awaited new edition to standard cancer therapies. For an effective immunotherapy, it is imperative to delineate the players of antitumour immune response. As an important innate immune system effector mechanism, complement is highly likely to play a substantial role in cancer immunity. Studies suggest that there may be two different "states of complement" that show opposing effects on cancer cells; a complement profile that has antitumour effects with low expression of membrane-bound complement regulator proteins (mCRPs), lytic membrane attack complex (MAC) concentration and moderate C5a concentration, and a complement profile that has protumour effects with high expression of mCRPs, sublytic MAC and high concentrations of C5a. One of the cancers that urgently require innovative therapeutic approaches is ovarian cancer, and complement has a potential to be a good target for this purpose. A combinatorial approach where the complement cascade is fine-tuned by inhibiting some of its activities while promoting the others can prove to be a fruitful approach. Herein, we will briefly discuss the cancer-immune system interaction and then present a discussion of complement system's role in tumour immunity and its therapeutic potential for ovarian cancer immunotherapy.

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Section: Complement In Ovarian Cancermentioning

confidence: 99%

Complement system's role in cancer and its therapeutic potential in ovarian cancer

Bareke

Akbuğa

2018

Scand J Immunol

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“…Over the past decades, various finding and focused research has been carried out to understand the underlying molecular mechanism of the ovarian cancer and its diagnosis (Hibbs, 2004;Cai et al, 2015;Krzystyniak et al, 2016;Willis et al, 2016, Singh andSom, 2019). Moreover, a single gene-based biomarker method is not sufficient to predict all the variations of a heterogeneous disease like ovarian cancer (Koutsogiannouli et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Identification of potential biomarkers in subtypes of epithelial ovarian cancer

Singh

Som

2020

Preprint

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Epithelial ovarian cancer (EOC) is the most lethal gynecological cancer. Due to the lack of specific symptoms, ~80% of epithelial ovarian cancer is diagnosed at an advanced stage and often metastasize to the distant organ. Epithelial ovarian cancer is a heterogeneous disease that is classified into four major histological subtypes namely, serous carcinoma (SC), endometrioid carcinoma (EC), mucinous carcinoma (MC), and clear cell carcinoma (CCC).Ovarian cancer treatment is complicated due to the heterogeneity of the tumors. Patients with different subtypes respond differently to the same treatment and also have different prognoses. This diversity extends to various clinical outcomes of the disease. Thus, identifying new reliable potential biomarkers irrespective of their subtypes is an urgent need for the diagnosis and prognosis of epithelial ovarian cancer. In this study, we performed comparative gene expression analysis for identifying potential biomarkers in four histological subtypes of epithelial ovarian cancer (EOC) that include serous, endometrioid, mucinous, and clear cell carcinomas. Differentially expressed genes (DEGs) between cancerous and normal tissue samples were identified by considering the criteria of absolute logarithmic fold change |log2fc|>1 and adjusted p (padj) value<0.05. Pathway enrichment analysis of the DEGs showed that pathways in cancer, PI3K-AKT signaling pathway, RAP1 signaling pathway, cell cycle, cell adhesion molecules, and proteoglycans in cancer were common among the selected cancer subtypes. Further, we constructed the co-expression network of DEGs and identified 15 candidate genes. Finally, based on the survival analysis of the candidate genes, a total of nine genes namely ASPM, CDCA8, CENPM, CEP55, HMMR, RACGAP1, TPX2, UBE2C, and ZWINT with significant prognostic value was proposed as the potential biomarker.

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“…Today, Epithelial Ovarian Cancer (EOC) [1] can be considered as a stressful and challenging disease among all women in the world. EOC is diagnosed annually in nearly a quarter of a million women, and it is responsible for 140,000 deaths each year [2].…”

Section: Introductionmentioning

confidence: 99%

Gene expression profiles and pathway enrichment analysis to identification of differentially expressed gene and signaling pathways in epithelial ovarian cancer based on high-throughput RNA-seq data

Siavoshi

Taghizadeh

Dookhe

et al. 2019

Preprint

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Epithelial ovarian cancer (EOC) can be considered as a stressful and challenging disease among all women in the world, which has been associated with a poor prognosis and its molecular pathogenesis has remained unclear. In recent years, RNA Sequencing (RNA-seq) has become a functional and amazing technology for profiling gene expression. In the present study, RNA-seq raw data from Sequence Read Archive (SRA) of six tumor and normal ovarian sample was extracted, and then analysis and statistical interpretation was done with Linux and R Packages from the open-source Bioconductor. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of key genes and pathways involved in EOC. We identified 1091 Differential Expression Genes (DEGs) which have been reported in various studies of ovarian cancer as well as other types of cancer. Among them, 333 genes were up-regulated and 273 genes were downregulated. In addition, Differentially Expressed Genes (DEGs) including RPL41, ALDH3A2, ERBB2, MIEN1, RBM25, ATF4, UPF2, DDIT3, HOXB8 and IL17D as well as Ribosome and Glycolysis/Gluconeogenesis pathway have had the potentiality to be used as targets for EOC diagnosis and treatment. In this study, unlike that of any other studies on various cancers, ALDH3A2 was most down-regulated gene in most KEGG pathways, and ATF4 was most up-regulated gene in leucine zipper domain binding term. In the other hand, RPL41 as a regulatory of cellular ATF4 level was up-regulated in many term and pathways and augmentation of ATF4 could justify the increase of RPL41 in the EOC. Pivotal pathways and significant genes, which were identified in the present study, can be used for adaptation of different EOC study. However, further molecular biological experiments and computational processes are required to confirm the function of the identified genes associated with EOC.

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Epithelial ovarian cancer: the molecular genetics of epithelial ovarian cancer

Cited by 52 publications

References 44 publications

Complement system's role in cancer and its therapeutic potential in ovarian cancer

Complement system's role in cancer and its therapeutic potential in ovarian cancer

Identification of potential biomarkers in subtypes of epithelial ovarian cancer

Gene expression profiles and pathway enrichment analysis to identification of differentially expressed gene and signaling pathways in epithelial ovarian cancer based on high-throughput RNA-seq data

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