scholarly journals DIAGNOSTIC ROLE OF MORPHOMETRIC ASSESSMENT OF TUMORASSOCIATED STROMA COMPONENTS OF SEROUS OVARIAN CARCINOMAS IN THE PROGNOSIS OF TUMOR PROGRESSION

2021 ◽  
Vol 30 (4) ◽  
pp. 35-42
Author(s):  
Alexei Alexandrovich Votintsev ◽  
Keyword(s):  
Ovarian Cancer ◽  
Primary Tumor ◽  
Tumor Tissue ◽  
Low Density ◽  
Serous Ovarian Cancer ◽  
Ovarian Carcinomas ◽  
Diagnostic Role ◽  
Computer Morphometry ◽  
Morphometric Assessment

The method of computer morphometry of stroma components and evaluation of stromal-parenchymal relationships in the primary tumor node of serous ovarian cancer was used. A high potential for malignancy of tumor tissue, characterized by the resumption of tumor growth after radical treatment, is observed with the predominance of the epithelial component over the stroma, with a small number of necrosis in the tumor node, low density of microcirculatory vessels in the tumor, and the predominance of fi broblastic elements in the cellular microenvironment of the tumorassociated stroma.

scholarly journals Evaluating Targeted Therapies in Ovarian Cancer Metabolism: Novel Role for PCSK9 and Second Generation mTOR Inhibitors

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3727
Author(s):  
Dafne Jacome Sanz ◽  
Juuli Raivola ◽  
Hanna Karvonen ◽  
Mariliina Arjama ◽  
Harlan Barker ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Lipid Metabolism ◽  
Cell Survival ◽  
Drug Testing ◽  
Cancer Metabolism ◽  
Ex Vivo ◽  
Specific Inhibitor ◽  
Low Grade ◽  
Serous Ovarian Cancer

Background: Dysregulated lipid metabolism is emerging as a hallmark in several malignancies, including ovarian cancer (OC). Specifically, metastatic OC is highly dependent on lipid-rich omentum. We aimed to investigate the therapeutic value of targeting lipid metabolism in OC. For this purpose, we studied the role of PCSK9, a cholesterol-regulating enzyme, in OC cell survival and its downstream signaling. We also investigated the cytotoxic efficacy of a small library of metabolic (n = 11) and mTOR (n = 10) inhibitors using OC cell lines (n = 8) and ex vivo patient-derived cell cultures (PDCs, n = 5) to identify clinically suitable drug vulnerabilities. Targeting PCSK9 expression with siRNA or PCSK9 specific inhibitor (PF-06446846) impaired OC cell survival. In addition, overexpression of PCSK9 induced robust AKT phosphorylation along with increased expression of ERK1/2 and MEK1/2, suggesting a pro-survival role of PCSK9 in OC cells. Moreover, our drug testing revealed marked differences in cytotoxic responses to drugs targeting metabolic pathways of high-grade serous ovarian cancer (HGSOC) and low-grade serous ovarian cancer (LGSOC) PDCs. Our results show that targeting PCSK9 expression could impair OC cell survival, which warrants further investigation to address the dependency of this cancer on lipogenesis and omental metastasis. Moreover, the differences in metabolic gene expression and drug responses of OC PDCs indicate the existence of a metabolic heterogeneity within OC subtypes, which should be further explored for therapeutic improvements.

scholarly journals KLF7: a new candidate biomarker and therapeutic target for high-grade serous ovarian cancer

2020 ◽  
Vol 39 (1) ◽  
Author(s):  
Marta De Donato ◽  
Gabriele Babini ◽  
Simona Mozzetti ◽  
Marianna Buttarelli ◽  
Alessandra Ciucci ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Prognostic Marker ◽  
Late Stage ◽  
Therapeutic Target ◽  
Family Members ◽  
High Grade ◽  
Serous Ovarian Cancer

Abstract Background In spite of great progress in the surgical and clinical management, until now no significant improvement in overall survival of High-Grade Serous Ovarian Cancer (HGSOC) patients has been achieved. Important aspects for disease control remain unresolved, including unclear pathogenesis, high heterogeneity and relapse resistance after chemotherapy. Therefore, further research on molecular mechanisms involved in cancer progression are needed to find new targets for disease management. The Krüppel-like factors (KLFs) are a family of transcriptional regulators controlling several basic cellular processes, including proliferation, differentiation and migration. They have been shown to play a role in various cancer-relevant processes, in a context-dependent way. Methods To investigate a possible role of KLF family members as prognostic biomarkers, we carried out a bioinformatic meta-analysis of ovarian transcriptome datasets in different cohorts of late-stage HGSOC patients. In vitro cellular models of HGSOC were used for functional studies exploring the role of KLF7 in disease development and progression. Finally, molecular modelling and virtual screening were performed to identify putative KLF7 inhibitors. Results Bioinformatic analysis highlighted KLF7 as the most significant prognostic gene, among the 17 family members. Univariate and multivariate analyses identified KLF7 as an unfavourable prognostic marker for overall survival in late-stage TCGA-OV and GSE26712 HGSOC cohorts. Functional in vitro studies demonstrated that KLF7 can play a role as oncogene, driving tumour growth and dissemination. Mechanistic targets of KLF7 included genes involved in epithelial to mesenchymal transition, and in maintaining pluripotency and self-renewal characteristics of cancer stem cells. Finally, in silico analysis provided reliable information for drug-target interaction prediction. Conclusions Results from the present study provide the first evidence for an oncogenic role of KLF7 in HGSOC, suggesting it as a promising prognostic marker and therapeutic target.

Abstract B71: Investigating the role of PAX8 in modulating the tumor microenvironment of high-grade serous ovarian cancer

2020 ◽  
Author(s):  
Amrita Salvi ◽  
Laura Hardy ◽  
Samantha Watry ◽  
Melissa Pergande ◽  
Stephanie M. Cologna ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Tumor Microenvironment ◽  
High Grade ◽  
Serous Ovarian Cancer

scholarly journals Development and Validation of a Novel 11-Gene Prognostic Model for Serous Ovarian Carcinomas Based on Lipid Metabolism Expression Profile

2020 ◽  
Vol 21 (23) ◽  
pp. 9169
Author(s):  
Mingjun Zheng ◽  
Heather Mullikin ◽  
Anna Hester ◽  
Bastian Czogalla ◽  
Helene Heidegger ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Lipid Metabolism ◽  
Prognostic Model ◽  
Molecular Subtypes ◽  
Gene Signature ◽  
Functional Enrichment ◽  
Serous Ovarian Cancer ◽  
Ovarian Carcinomas ◽  
Comparable Amount ◽  
Lipid Metabolism Genes

(1) Background: Biomarkers might play a significant role in predicting the clinical outcomes of patients with ovarian cancer. By analyzing lipid metabolism genes, future perspectives may be uncovered; (2) Methods: RNA-seq data for serous ovarian cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The non-negative matrix factorization package in programming language R was used to classify molecular subtypes of lipid metabolism genes and the limma package in R was performed for functional enrichment analysis. Through lasso regression, we constructed a multi-gene prognosis model; (3) Results: Two molecular subtypes were obtained and an 11-gene signature was constructed (PI3, RGS, ADORA3, CH25H, CCDC80, PTGER3, MATK, KLRB1, CCL19, CXCL9 and CXCL10). Our prognostic model shows a good independent prognostic ability in ovarian cancer. In a nomogram, the predictive efficiency was notably superior to that of traditional clinical features. Related to known models in ovarian cancer with a comparable amount of genes, ours has the highest concordance index; (4) Conclusions: We propose an 11-gene signature prognosis prediction model based on lipid metabolism genes in serous ovarian cancer.

Circulating tumor DNA analysis using targeted sequencing of 508 clinically actionable genes in patients with high grade serous ovarian cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 5582-5582
Author(s):  
Anniina Färkkilä ◽  
Liina Salminen ◽  
Kaisa Huhtinen ◽  
Sakari Hietanen ◽  
Seija Elisa Grenman ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Tumor Tissue ◽  
Genetic Alterations ◽  
Gene Panel ◽  
Targeted Sequencing ◽  
Primary Therapy ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Cancer Genes ◽  
Treatment Toxicity

5582 Background: The prediction of tumor chemoresponse and treatment toxicity is crucial for optimal patient care in high grade serous ovarian cancer (HGSC). We employed a targeted sequencing panel of 508 clinically annotated cancer genes to screen for actionable genetic variants in tumor tissue and ctDNA of patients with advanced HGSC. Methods: Tumor tissue, and serial plasma samples at diagnosis and during primary therapy were obtained from five patients with FIGO Stage IIIc HGSC. All patients were surgically debulked and received standard carboplatin and paclitaxel chemotherapy. DNA isolated from tumor tissue and plasma was analyzed for genetic alterations by targeted deep-sequencing of 508 previously annotated cancer genes. Somatic variants were systematically reported for alterations related to drug sensitivity and treatment toxicity, and analyzed with respect to clinical parameters and primary therapy outcomes. Results: In tumor tissues, and the corresponding pre-treatment ctDNA, oncogenic mutations were detected at a median of 13.0 and 1.6 allelic frequencies, respectively. The mutation frequency was higher, and also more unique mutations were detected in ctDNA of patients presenting with high tumor spread. Interestingly, a de-novo ctDNA MAPK1 mutation was detected in a sample taken during chemotherapy with partial response, while, no new mutations emerged in a patient with complete response. Analysis of the pretreatment plasma ctDNA revealed profiles of low and high drug sensitivities consistent with the clinical course of the patients. In two patients, increased risk profiles for treatment toxicities were identified via e.g. GSTP1. Consistently, these two patients were forced to discontinue standard therapy. Conclusions: Panel-based targeted sequencing of ctDNA identified potentially actionable mutations, and reflected tumor heterogeneity of HGSC. Further, the ctDNA gene panel annotations showed concordance with the chemoresponse- and treatment toxicity profiles, suggesting that ctDNA gene panel maybe a feasible approach to individualize treatment of HGSC patients.

Predictive role of biology in the feasibility of optimal versus suboptimal cytoreduction in advanced serous ovarian cancer

2013 ◽  
Vol 130 (1) ◽  
pp. e9
Author(s):  
R. Abdallah ◽  
N. Bou Zgheib ◽  
I. Ramirez-Diaz ◽  
S. Apte ◽  
P. Judson Lancaster ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Serous Ovarian Cancer ◽  
Predictive Role

scholarly journals Ascitis as a unique microenvironment of tumors in ovarian cancer: interaction with prognosis and chemoresistance

2019 ◽  
Vol 6 (2) ◽  
pp. 8-20
Author(s):  
A. B. Villert ◽  
L. A. Kolomiets ◽  
N. V. Yunusova
Keyword(s):  
Ovarian Cancer ◽  
Ascitic Fluid ◽  
Tumor Tissue ◽  
Molecular Genetic ◽  
Biomarker Detection ◽  
Ovarian Carcinomas ◽  
System Parameters ◽  
Igf System ◽  
Genetic Level ◽  
Igfbp 3

The severe heterogeneity of ovarian carcinomas on the molecular genetic level is associated with the absence of specific markers of chemoresistance. At the same time, ascites is an attractive biomarker detection fluid because it is easily obtained. The review is dedicated to the latest advances in the study of components characteristics of ascitic fluid in terms of their relationship with chemoresistance. Оwn data are submitted regarding the contents of the IFR system parameters (free IGFs, as well as IGFBP-3, IGFBP-4 and PAPP-A) in ascitic fluids and tumor tissue in disseminated ovarian cancer, which show the importance of their study. It is shown that the proteins level of the IGF system substantially depend on the volume of ascitic fluid. Studying the features of ascitic fluid in ovarian cancer is directly related to the prospect of new opportunities for disseminated ovarian cancer treatment.

scholarly journals Role of integrins in the metastatic spread of high-grade serous ovarian cancer

2021 ◽  
Author(s):  
Slavomir Krajnak ◽  
Jörg Jäkel ◽  
Katharina Anić ◽  
Roxana Schwab ◽  
Marcus Schmidt ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Primary Tumor ◽  
High Expression ◽  
Metastatic Spread ◽  
Clinicopathological Parameters ◽  
Integrin Expression ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Integrin Α4 ◽  
Integrin Α2

Abstract Purpose Integrins may be involved in the metastatic spread of high-grade serous ovarian cancer (HGSOC) which determines the therapeutical approach and prognosis. We investigated the integrin expression in primary tumor and metastases of advanced HGSOC. Methods The expression of integrin α2, α4, α5, α6, and β1 was assessed by immunostaining in tumor samples of the ovary, omentum, and peritoneum of each patient. Differences in integrin expression among tumor localizations and their association with clinicopathological parameters were examined by Fisher’s exact test. The impact of integrin expression on progression-free survival (PFS) and overall survival (OS) was examined by Cox regression and Kaplan–Meier analyses. Results Hundred and thirteen tumor samples of 40 HGSOC patients were examined. The expression of the integrins did not differ between the three tumor localizations (all p values > 0.05) with the exception of high expression of integrin α4 in primary tumor and omentum (52.5% versus 47.5%, p = 0.008) and primary tumor and peritoneum (52.5% versus 47.5%, p = 0.050). High expression of integrin α4 in peritoneum was associated with poorer PFS (HR 2.02 95% CI 1.01–4.05, p = 0.047), younger age (p = 0.047), and death (p = 0.046). Median PFS in patients with high expression of integrin α4 was 13.00 months, whereas median PFS in patients without high expression of integrin α4 was 21.00 months (p = 0.040). Expression of other integrins did not correlate with PFS or OS. Conclusion Expression of integrin α4 may be altered during the metastatic spread of HGSOC and affect prognosis, whereas expression of integrin α2, α5, α6, and β1 did not reveal any prognostic value.

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