scholarly journals Leveraging Genomics, Transcriptomics, and Epigenomics to Understand the Biology and Chemoresistance of Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 4029
Author(s):  
Sandra Muñoz-Galván ◽  
Amancio Carnero
Keyword(s):  
Ovarian Cancer ◽  
Molecular Mechanisms ◽  
Clinical Manifestations ◽  
Therapy Resistance ◽  
Omics Technologies ◽  
Gynecological Malignancy ◽  
Tumor Relapse ◽  
Molecular Features ◽  
Ovarian Cancers ◽  
Late Detection

Ovarian cancer is a major cause of fatality due to a gynecological malignancy. This lethality is largely due to the unspecific clinical manifestations of ovarian cancer, which lead to late detection and to high resistance to conventional therapies based on platinum. In recent years, we have advanced our understanding of the mechanisms provoking tumor relapse, and the advent of so-called omics technologies has provided exceptional tools to evaluate molecular mechanisms leading to therapy resistance in ovarian cancer. Here, we review the contribution of genomics, transcriptomics, and epigenomics techniques to our knowledge about the biology and molecular features of ovarian cancers, with a focus on therapy resistance. The use of these technologies to identify molecular markers and mechanisms leading to chemoresistance in these tumors is discussed, as well as potential further applications.

scholarly journals Targeting Cancer Stem Cells to Overcome Therapy Resistance in Ovarian Cancer

Cells ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1402
Author(s):  
Sandra Muñoz-Galván ◽  
Amancio Carnero
Keyword(s):  
Ovarian Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Current Knowledge ◽  
Therapy Resistance ◽  
High Recurrence Rate ◽  
Therapeutic Approaches ◽  
Ovarian Cancer Stem Cells ◽  
Gynecological Malignancy ◽  
Late Detection

Ovarian cancer is the most lethal gynecological malignancy due to its late detection and high recurrence rate. Resistance to conventional platinum-based therapies and metastasis are attributed to a population of cells within tumors called cancer stem cells, which possess stem-like features and are able to recapitulate new tumors. Recent studies have deepened the understanding of the biology of ovarian cancer stem cells and their special properties and have identified multiple markers and signaling pathways responsible for their self-renewal abilities. Targeting cancer stem cells represents the most promising strategy for overcoming therapy resistance and reducing mortality in ovarian cancer, but further efforts must be made to improve our understanding of the mechanisms involved in therapy resistance. In this review, we summarize our current knowledge about ovarian cancer stem cells, their involvement in metastasis and their interactions with the tumor microenvironment; we also discuss the therapeutic approaches that are being developed to target them to prevent tumor relapse.

scholarly journals Emerging Role of Inhibin as a Biomarker for Ovarian Cancer

2005 ◽  
Vol 1 (1) ◽  
pp. 51-57 ◽  
Author(s):  
David M Robertson ◽  
Martin K Oehler
Keyword(s):  
Ovarian Cancer ◽  
Granulosa Cell ◽  
Early Stage ◽  
Clinical Stage ◽  
Survival Rates ◽  
Ovarian Carcinomas ◽  
Gynecological Malignancy ◽  
Granulosa Cell Tumors ◽  
Ovarian Cancers ◽  
Specificity And Sensitivity

Ovarian cancer is the most lethal gynecological malignancy as it is diagnosed at a late clinical stage in more than 80% of patients. The development of diagnostic tests that can detect all types of ovarian cancers with high specificity and sensitivity, and at an early stage would improve survival rates. Serum inhibin is an ovarian hormone involved in the regulation of fertility, decreasing to undetectable levels after menopause. Certain ovarian malignancies, such as mucinous carcinomas and granulosa cell tumors, continue to produce inhibin, which is detectable in serum. A test for serum inhibin has been developed which is able to diagnose granulosa cell tumors and mucinous carcinomas with high accuracy. When the inhibin assay is used in conjunction with the CA125 test, which detects epithelial ovarian carcinomas, the two tests detect the majority of ovarian cancers with high sensitivity (95%) and specificity (95%). This article discusses the application of the inhibin test in ovarian cancer.

scholarly journals Promotion of Cell Death in Cisplatin-Resistant Ovarian Cancer Cells through KDM1B-DCLRE1B Modulation

2019 ◽  
Vol 20 (10) ◽  
pp. 2443 ◽  
Author(s):  
Yeon Kyu Lee ◽  
Jinyeong Lim ◽  
So Young Yoon ◽  
Jong Cheon Joo ◽  
Soo Jung Park ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cell Death ◽  
Cancer Cells ◽  
Molecular Mechanisms ◽  
Ovarian Cancer Cells ◽  
Repair Gene ◽  
Gynecological Malignancy ◽  
Downstream Target ◽  
Dna Repair Gene ◽  
Cisplatin Sensitivity

Ovarian cancer is the gynecological malignancy with the poorest prognosis, in part due to its high incidence of recurrence. Platinum agents are widely used as a first-line treatment against ovarian cancer. Recurrent tumors, however, frequently demonstrate acquired chemo-resistance to platinum agent toxicity. To improve chemo-sensitivity, combination chemotherapy regimens have been investigated. This study examined anti-tumor effects and molecular mechanisms of cytotoxicity of Oldenlandia diffusa (OD) extracts on ovarian cancer cells, in particular, cells resistant to cisplatin. Six ovarian cancer cells including A2780 and cisplatin-resistant A2780 (A2780cis) as representative cell models were used. OD was extracted with water (WOD) or 50% methanol (MOD). MOD significantly induced cell death in both cisplatin-sensitive cells and cisplatin-resistant cells. The combination treatment of MOD with cisplatin reduced viability in A2780cis cells more effectively than treatment with cisplatin alone. MOD in A2780cis cells resulted in downregulation of the epigenetic modulator KDM1B and the DNA repair gene DCLRE1B. Transcriptional suppression of KDM1B and DCLRE1B induced cisplatin sensitivity. Knockdown of KDM1B led to downregulation of DCLRE1B expression, suggesting that DCLRE1B was a KDM1B downstream target. Taken together, OD extract effectively promoted cell death in cisplatin-resistant ovarian cancer cells under cisplatin treatment through modulating KDM1B and DCLRE1B.

scholarly journals MOATAI-VIR - an AI algorithm that predicts severe adverse events and molecular features for COVID-19’s complications

2021 ◽  
Author(s):  
Courtney Astore ◽  
Hongyi Zhou ◽  
Joshy Jacob ◽  
Jeffrey Skolnick
Keyword(s):  
Adverse Events ◽  
Molecular Mechanisms ◽  
Chromosomal Abnormalities ◽  
Clinical Manifestations ◽  
Host Responses ◽  
Molecular Features ◽  
Disease Protein ◽  
Human Proteins ◽  
Severe Adverse Events ◽  
Patients Experience

AbstractFollowing SARS-CoV-2 infection, some COVID-19 patients experience severe adverse events caused by pathogenic host responses. To treat these complications, their underlying etiology must be identified. Thus, a novel AI-based methodology, MOATAI-VIR, which predicts disease-protein-pathway relationships for 22 clinical manifestations attributed to COVID-19 was developed. SARS-CoV-2 interacting human proteins and GWAS identified respiratory failure associated risk genes provide the input from which the mode-of-action (MOA) proteins/pathways of the resulting disease comorbidities are predicted. These comorbidities are then mapped to their clinical manifestations. Three uncharacterized manifestation categories are found: neoplasms, mental and behavioral disorders, and congenital malformations, deformations, and chromosomal abnormalities. The prevalence of neoplasms suggests a possible association between COVID-19 and cancer, whether by shared molecular mechanisms between oncogenesis and viral replication, or perhaps, SARS-CoV-2 is an oncovirus. To assess the molecular basis of each manifestation, the proteins shared across each group of comorbidities were prioritized and subject to global pathway analysis. From these most frequent pathways, the molecular features associated with hallmark COVID-19 phenotypes, such as loss of sense of smell/taste, unusual neurological symptoms, cytokine storm, and blood clots were explored. Results of MOATAI-VIR are available for academic users at: http://pwp.gatech.edu/cssb/MOATAI-VIR/.

scholarly journals Can Stemness and Chemoresistance be Therapeutically Targeted via Signaling Pathways in Ovarian Cancer?

2018 ◽  
Author(s):  
Lynn Roy ◽  
Karen Cowden Dahl
Keyword(s):  
Ovarian Cancer ◽  
Stem Cell ◽  
Signaling Pathways ◽  
Tumor Metastasis ◽  
Molecular Mechanisms ◽  
Side Population ◽  
Survival Rates ◽  
Accurate Identification ◽  
Poor Overall Survival ◽  
Gynecological Malignancy

Ovarian cancer is the most lethal gynecological malignancy. Poor overall survival, particularly for patients with high grade serous (HGS) ovarian cancer, are often attributed to late stage at diagnosis and relapse following chemotherapy. HGS ovarian cancer is a heterogenous disease in that few genes are consistently mutated between patients. Additionally, HGS ovarian cancer is characterized by high genomic instability. For these reasons personalized approaches may be necessary for effective treatment and cure. Understanding the molecular mechanisms that contribute to tumor metastasis and chemoresistance are essential to improve survival rates. One favored model for tumor metastasis and chemoresistance is the cancer stem cell (CSC) model. CSCs are cells with enhanced self-renewal properties that are enriched following chemotherapy. Elimination of this cell population is thought to be a mechanism to increase therapeutic response. Therefore, accurate identification of stem cell populations that are most clinically relevant is necessary. While many CSC identifiers (ALDH, OCT4, CD133, and side population) have been established, it is still not clear which population(s) will be most beneficial to targeted in patients. Therefore, there is a critical need to characterize CSCs with reliable markers and find their weaknesses that will make the CSCs amenable to therapy. Many signaling pathways are implicated for their roles in CSC initiation and maintenance. Therapeutically targeting pathways needed for CSC initiation or maintenance may be an effective way of treating HGS ovarian cancer patients. In conclusion, the prognosis for HGS ovarian cancer may be improved by combining CSC phenotyping with targeted therapies for pathways involved in CSC maintenance.

Multiomics-based energy metabolism heterogeneity and its regulation by antiparasite drug ivermectin.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e18080-e18080
Author(s):  
Na Li ◽  
Xianquan Zhan
Keyword(s):  
Ovarian Cancer ◽  
Energy Metabolism ◽  
Cell Cycle Progression ◽  
Molecular Mechanisms ◽  
Differentially Expressed ◽  
Molecular Networks ◽  
Differentially Expressed Proteins ◽  
Proteomics Data ◽  
Lactate Shuttle ◽  
Ovarian Cancers

e18080 Background: Energy metabolism heterogeneity is a hallmark in ovarian cancer, namely the Warburg effect and the reverse Warburg effects coexist in ovarian cancer. Exploration of energy metabolism heterogeneity benefits for discovery of the effective biomarkers for ovarian cancers. Methods: Comprehensive analysis of mitochondrial proteomics data (1198 mitochondrial differentially expressed proteins), mitochondrial phosphorpoteomics data (67 mitochondrial phosphorproteins), proteomics data (205 differentially expressed proteins), and transcriptomics data (20115 genes in 419 ovarian cancer samples) was useful. Results: It revealed (i) the upregulations of rate-limiting enzymes PKM2 in glycolysis, IDH2 in Kreb’s cycle, and UQCRH in oxidative phosphorylation (OXPHOS) pathways, (ii) the upregulation of PDHB that converts pyruvate from glycolysis into acetyl-CoA in Kreb’s cycle. Anti-parasite drug ivermectin demonstrated its strong abilities to inhibit proliferation and cell cycle progression and promote apoptosis in EOC cells, through molecular networks to target PFKP in glycolysis, IDH2 and IDH3B in Kreb’s cycle, ND2, ND5, CYTB, and UQCRH in OXPHOS, and MCT1 and MCT4 in lactate shuttle to inhibit EOC growth. Those results were further confirmed in the ovarian cancer cell models and tissues. Conclusions: It clearly concluded that ivermectin might have new potential for ovarian cancer treatment through regulating energy metabolism pathways. These findings provide more accurate understanding of molecular mechanisms of ovarian cancers and discovery of effective energy-metabolism-heterogeneity-based therapeutic drugs for ovarian cancers.

scholarly journals Mechanisms of Apoptosis-Related Long Non-coding RNAs in Ovarian Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Toshihiko Takeiwa ◽  
Kazuhiro Ikeda ◽  
Kuniko Horie-Inoue ◽  
Satoshi Inoue
Keyword(s):  
Ovarian Cancer ◽  
Cancer Cells ◽  
Molecular Mechanisms ◽  
Therapy Resistance ◽  
Therapeutic Strategies ◽  
Regulatory Mechanisms ◽  
Ovarian Cancer Cells ◽  
Regulation Of Transcription ◽  
Advanced Stages ◽  
Non Coding Rnas

Ovarian cancer is a health-threatening malignancy of ovary in female reproductive systems and one of the most common gynecological malignancies worldwide. Due to rare early symptoms, ovarian cancers are often diagnosed at advanced stages and exhibit poor prognosis. Thus, efforts have been paid to develop alternative diagnostic and therapeutic strategies for the disease. Recent studies have presented that some long non-coding RNAs (lncRNAs) play roles in apoptosis of ovarian cancer cells through various mechanisms involved in the regulation of transcription factors, histone modification complexes, miRNAs, and protein stability. Because evasion of apoptosis in cancer cells facilitates to promote tumor progression and therapy resistance, apoptosis regulatory mechanisms of lncRNAs may be promising new targets in ovarian cancer. In this review, we introduce the recent findings in regard to the molecular mechanisms of apoptosis-related lncRNAs in ovarian cancer cells.

AEG -1 Overexpression: A Novel Indicator for Peritoneal Dissemination and Lymph Node Metastasis in Epithelial Ovarian Cancers

2011 ◽  
Vol 21 (4) ◽  
pp. 602-608 ◽  
Author(s):  
Cong Li ◽  
Junjun Liu ◽  
Renbo Lu ◽  
Ge Yu ◽  
Xiaochuan Wang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Confidence Interval ◽  
Predictive Value ◽  
Peritoneal Dissemination ◽  
Gynecological Malignancy ◽  
Node Metastasis ◽  
Ovarian Cancers ◽  
Stage Disease

Objective:Despite advances in chemotherapy and cytoreductive surgery, ovarian cancer remains the most lethal gynecological malignancy with a 5-year survival rate of 25% to 30% in advanced stage disease. Our purpose is to evaluate whether astrocyte elevated gene-1 (AEG-1) is a novel predictor of peritoneal dissemination and lymph node metastasis in epithelial ovarian cancer (EOC), which was not previously studied by others.Materials and Methods:Through immunohistochemical and Western blot analysis, AEG-1 expression was evaluated in 25 normal ovarian and 157 EOC specimens. The relationship between AEG-1 expression and EOC metastasis was determined by univariate and multivariate analyses.Results:Western blotting analysis revealed that AEG-1 was overexpressed in metastatic tissues from patients with ovarian cancers. Immunohistochemistry results showed that 83 (95.4%) presented peritoneal dissemination; 41 (47.1%) had lymph node metastasis among 87 patients with AEG-1 overexpression. Univariate and multivariate logistic regression analyses demonstrated that AEG-1 overexpression correlated with peritoneal dissemination and lymph node metastasis in EOC. We further found that the positive and specificity predictive value of AEG-1 staining were better for peritoneal metastasis, whereas the negative and sensitivity predictive value of AEG-1 staining were better for lymph node metastasis. The odds ratio of high-to-low expression for peritoneal dissemination was 8.541 (95% confidence interval, 2.561-37.461), and that for lymph node metastasis was 9.581 (95% confidence interval, 2.613-23.214).Conclusions:The present findings indicate that AEG-1 is overexpressed in a great portion of EOC patients with peritoneal dissemination and/or lymph node metastasis and may be clinically useful for predicting metastasis in EOC. Our findings might provide some benefits for metastatic EOC patients in the clinic.

scholarly journals High-Throughput Phenotyping Toolkit for Characterizing Cellular Models of Hypertrophic Cardiomyopathy in Vitro

2019 ◽  
Vol 2 (4) ◽  
pp. 83 ◽  
Author(s):  
Mosqueira ◽  
Lis-Slimak ◽  
Denning
Keyword(s):  
Hypertrophic Cardiomyopathy ◽  
High Throughput ◽  
Molecular Mechanisms ◽  
Clinical Manifestations ◽  
Cellular Models ◽  
Molecular Features ◽  
High Throughput Drug Screening ◽  
High Throughput Phenotyping ◽  
Screening Approaches

Hypertrophic cardiomyopathy (HCM) is a prevalent and complex cardiovascular disease characterised by multifarious hallmarks, a heterogeneous set of clinical manifestations, and several molecular mechanisms. Various disease models have been developed to study this condition, but they often show contradictory results, due to technical constraints and/or model limitations. Therefore, new tools are needed to better investigate pathological features in an unbiased and technically refined approach, towards improving understanding of disease progression. Herein, we describe three simple protocols to phenotype cellular models of HCM in vitro, in a high-throughput manner where technical artefacts are minimized. These are aimed at investigating: (1) Hypertrophy, by measuring cell volume by flow cytometry; (2) HCM molecular features, through the analysis of a hypertrophic marker, multinucleation, and sarcomeric disarray by high-content imaging; and (3) mitochondrial respiration and content via the Seahorse™ platform. Collectively, these protocols comprise straightforward tools to evaluate molecular and functional parameters of HCM phenotypes in cardiomyocytes in vitro. These facilitate greater understanding of HCM and high-throughput drug screening approaches and are accessible to all researchers of cardiac disease modelling. Whilst HCM is used as an exemplar, the approaches described are applicable to other cellular models where the investigation of identical biological changes is paramount.

scholarly journals Combined Poziotinib with Manidipine Treatment Suppresses Ovarian Cancer Stem-Cell Proliferation and Stemness

2020 ◽  
Vol 21 (19) ◽  
pp. 7379
Author(s):  
Heejin Lee ◽  
Jun Woo Kim ◽  
Dong-Seok Lee ◽  
Sang-Hyun Min
Keyword(s):  
Ovarian Cancer ◽  
Survival Rate ◽  
Combination Treatment ◽  
Molecular Mechanisms ◽  
Combined Treatment ◽  
Growth Factor Receptor ◽  
Channel Blockers ◽  
Gynecological Malignancy ◽  
Induced Apoptosis ◽  
And Function

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy in women worldwide, with an overall 5 year survival rate below 30%. The low survival rate is associated with the persistence of cancer stem cells (CSCs) after chemotherapy. Therefore, CSC-targeting strategies are required for successful EOC treatment. Pan-human epidermal growth factor receptor 4 (HER4) and L-type calcium channels are highly expressed in ovarian CSCs, and treatment with the pan-HER inhibitor poziotinib or calcium channel blockers (CCBs) selectively inhibits the growth of ovarian CSCs via distinct molecular mechanisms. In this study, we tested the hypothesis that combination treatment with poziotinib and CCBs can synergistically inhibit the growth of ovarian CSCs. Combined treatment with poziotinib and manidipine (an L-type CCB) synergistically suppressed ovarian CSC sphere formation and viability compared with either drug alone. Moreover, combination treatment synergistically reduced the expression of stemness markers, including CD133, KLF4, and NANOG, and stemness-related signaling molecules, such as phospho-STAT5, phospho-AKT, phospho-ERK, and Wnt/β-catenin. Moreover, poziotinib with manidipine dramatically induced apoptosis in ovarian CSCs. Our results suggest that the combinatorial use of poziotinib with a CCB can effectively inhibit ovarian CSC survival and function.

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