Cytotoxic capacity of a novel glycosylated antitumor ether lipid in chemotherapy-resistant high grade serous ovarian cancer in vitro and in vivo.
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ABSTRACT:
SUBMITTER: Nachtigal MW
PROVIDER: S-EPMC8379490 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Epithelial ovarian cancer (OC) ranks first in the number of deaths among diseases of the female reproductive organs. Identification of OC at early stages is highly beneficial for the treatment but is highly challenging due to the asymptomatic or low-symptom disease development. In this study, lipid extracts of venous blood samples from 41 female volunteers, including 28 therapy-naive patients with histologically verified high-grade serous ovarian cancer at different stages (5 patients with I-II stages; 23 patients with III-IV stages) and 13 apparently healthy women of reproductive age, were profiled by high-performance liquid chromatography mass spectrometry (HPLC-MS). Based on MS signals of 128 differential lipid species with statistically significant level variation between the OC patients and control group, an OPLS-DA model was developed for the recognition of OC with 100% sensitivity and specificity R 2 = 0.87 and Q2 = 0.80. The second OPLS-DA model was developed for the differentiation between I-II OC stages and control group with R 2 = 0.97 and Q2 = 0.86 based on the signal levels of 108 differential lipid species. The third OPLS-DA model was developed for the differentiation between I-II OC stages and III-IV stages based on the signal levels of 99 differential lipid species. Various lipid classes (diglycerides, triglycerides, phosphatidylchlorines, ethanolamines, sphingomyelins, ceramides, phosphatidylcholines and phosphoinositols) in blood plasma samples display distinctly characteristic profiles in I-II OC, which indicates the possibility of their use as marker oncolipids in diagnostic molecular panels of early OC stages. Our results suggest that lipid profiling by HPLC-MS can improve identification of early-stage OC and thus increase the efficiency of treatment.
| S-EPMC9048792 | biostudies-literature
Project description:While high-grade serous ovarian carcinoma (HGSOC) is the most common histologic subtype of ovarian cancer, significant tumor heterogeneity exists. In addition, chemotherapy induces changes in gene expression and alters the mutational profile. To evaluate the notion that patients with HGSOC could be better classified for optimal treatment based on gene expression, we compared genetic variants [by DNA next-generation sequencing (NGS) using a 50 gene Ion Torrent panel] and gene expression (using the NanoString PanCancer 770 gene Panel) in the tumor from 20 patients with HGSOC before and after neoadjuvant chemotherapy (NACT). NGS was performed on plasma cell free DNA (cfDNA) on a select group of patients (n = 14) to assess the utility of using cfDNA to monitor these changes. A total of 86 genes had significant changes in RNA expression after NACT. Thirty-eight genetic variants (including SNPs) from 6 genes were identified in tumors pre-NACT, while 59 variants from 19 genes were detected in the cfDNA. The number of DNA variants were similar after NACT. Of the 59 variants in the plasma pre-NACT, only 6 persisted, whereas 33 of 38 specific variants in the tumor DNA remained unchanged. Pathway analysis showed the most significant alterations in the cell cycle and DNA damage pathways.Implications: Gene expression profiles at the time of interval debulking provide additional genetic information that could help impact treatment decisions after NACT; although, continued collection and analysis of matched tumor and cfDNA from multiple time points are needed to determine the role of cfDNA in the management of HGSOC. Mol Cancer Res; 16(5); 813-24. ©2018 AACR.
| S-EPMC6497146 | biostudies-literature
Project description:Ovarian cancer is a very severe type of disease with poor prognosis. Treatment of ovarian cancer is challenging because of the lack of tests for early detection and effective therapeutic targets. Thus, new biomarkers are needed for both diagnostics and better understanding of the cellular processes of the disease. Small molecules, consisting of metabolites or lipids, have shown emerging potential for ovarian cancer diagnostics. Here we performed comprehensive lipidomic profiling of serum and tumor tissue samples from high-grade serous ovarian cancer patients to find lipids that were altered due to cancer and also associated with progression of the disease. Ovarian cancer patients exhibited an overall reduction of most lipid classes in their serum as compared to a control group. Despite the overall reduction, there were also specific lipids showing elevation, and especially alterations in ceramide and triacylglycerol lipid species were dependent on their fatty acyl side chain composition. Several lipids showed progressive alterations in patients with more advanced disease and poorer overall survival, and outperformed CA-125 as prognostic markers. The abundance of many serum lipids correlated with their abundance in tumor tissue samples. Furthermore, we found a negative correlation of serum lipids with 3-hydroxybutyric acid, suggesting an association between decreased lipid levels and fatty acid oxidation. In conclusion, here we present a comprehensive analysis of lipid metabolism alterations in ovarian cancer patients, with clinical implications.
| S-EPMC5732699 | biostudies-literature
Project description:In the early 2000s a two-tier grading system was introduced for serous ovarian cancer. Since then, we have increasingly come to accept that low-grade serous ovarian carcinoma (LGSOC) is a separate entity with a unique mutational landscape and clinical behaviour. As less than 10% of serous carcinomas of the ovary are low-grade, they are present in only a small number of patients in clinical trials for ovarian cancer. Therefore the current treatment of LGSOC is based on smaller trials, retrospective series, and subgroup analysis of large clinical trials on ovarian cancer. Surgery plays a major role in the treatment of patients with LGSOC. In the systemic treatment of LGSOC, hormonal treatment and targeted therapies seem to play an important role.
| S-EPMC6195427 | biostudies-literature
Project description:BackgroundPatients treated with neoadjuvant chemotherapy (NACT) for advanced high-grade serous ovarian carcinoma (HGSC) have a higher rate and shorter time to platinum-resistant recurrence compared to patients treated with primary cytoreductive surgery (PCS) and adjuvant chemotherapy. The purpose of this study is to determine the impact of NACT on somatic mutation status in platinum-sensitive and resistant HGSC. Patients with advanced HGSC who had a documented response to platinum-based NACT, a banked blood sample, and a banked tumor sample before and after NACT were identified. Whole exome and/or targeted deep sequencing was performed in matched normal and pre/post-NACT tumor samples from 3 platinum-resistant and 2 platinum-sensitive patients to identify somatic non-synonymous mutations at each time point.ResultsWhen comparing exonic non-synonymous mutations in pre-NACT and post-NACT samples from the same patient, an average of 41% (1-68%) of genes were mutated at both time points. There were no trends detected in the mutational burden following exposure to NACT in platinum-resistant vs. platinum-sensitive cases. The majority of mutated genes were unique to each case. We identified several genes that were commonly mutated in pre-NACT samples specific to platinum-resistant (CSPG4, SLC35G5, TUBA3D) or sensitive (CYP2D6, NUTM1, DNAH5) cases. Four mutated genes emerged exclusively in the platinum-resistant cases (ADGRV1, MUC17, MUC20, PAK2) following NACT.ConclusionsPatients with advanced HGSC present with significant intra-tumor heterogeneity. NACT significantly impacts the somatic mutation status irrespective of the time to recurrence. The mutated genes detected in chemo-naive pre-NACT tumor samples from either resistant or sensitive cases could potentially have a role in the prediction of chemotherapy response in patients scheduled to receive NACT; larger studies are required to further validate these genes.
| S-EPMC9059396 | biostudies-literature
Project description:ObjectivesTo test the hypothesis that glucocorticoid receptor (GR) activation increases resistance to chemotherapy in high-grade serous ovarian cancer (HGS-OvCa) and that treatment with a GR antagonist will improve sensitivity to chemotherapy.MethodsGR expression was assessed in OvCa cell lines by qRT-PCR and Western blot analysis and in xenografts and primary human tumors using immunohistochemistry (IHC). We also examined the effect of GR activation versus inhibition on chemotherapy-induced cytotoxicity in OvCa cell lines and in a xenograft model.ResultsWith the exception of IGROV-1 cells, all OvCa cell lines tested had detectable GR expression by Western blot and qRT-PCR analysis. Twenty-five out of the 27 human primary HGS-OvCas examined expressed GR by IHC. No cell line expressed detectable progesterone receptor (PR) or androgen receptor (AR) by Western blot analysis. In vitro assays showed that in GR-positive HeyA8 and SKOV3 cells, dexamethasone (100nM) treatment upregulated the pro-survival genes SGK1 and MKP1/DUSP1 and inhibited carboplatin/gemcitabine-induced cell death. Concurrent treatment with two GR antagonists, either mifepristone (100nM) or CORT125134 (100nM), partially reversed these effects. There was no anti-apoptotic effect of dexamethasone on chemotherapy-induced cell death in IGROV-1 cells, which did not have detectable GR protein. Mifepristone treatment alone was not cytotoxic in any cell line. HeyA8 OvCa xenograft studies demonstrated that adding mifepristone to carboplatin/gemcitabine increased tumor shrinkage by 48% compared to carboplatin/gemcitabine treatment alone (P=0.0004).ConclusionsThese results suggest that GR antagonism sensitizes GR+ OvCa to chemotherapy-induced cell death through inhibition of GR-mediated cell survival pathways.
| S-EPMC4556542 | biostudies-literature
Project description:High grade serous ovarian carcinoma (HGSOC) is a highly heterogeneous disease that typically presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to predicting response to neoadjuvant chemotherapy (NACT) and understanding critical determinants of response. Here we present a framework to predict the response of HGSOC patients to NACT integrating baseline clinical, blood-based, and radiomic biomarkers extracted from all primary and metastatic lesions. We use an ensemble machine learning model trained to predict the change in total disease volume using data obtained at diagnosis (n = 72). The model is validated in an internal hold-out cohort (n = 20) and an independent external patient cohort (n = 42). In the external cohort the integrated radiomics model reduces the prediction error by 8% with respect to the clinical model, achieving an AUC of 0.78 for RECIST 1.1 classification compared to 0.47 for the clinical model. Our results emphasize the value of including radiomics data in integrative models of treatment response and provide methods for developing new biomarker-based clinical trials of NACT in HGSOC.
| S-EPMC10598212 | biostudies-literature
Project description:While high-grade serous ovarian carcinoma (HGSOC) is the most common histological subtype of ovarian cancer, significant tumor heterogeneity exists. In addition, chemotherapy induces changes in gene expression and alters the mutational profile. To evaluate the notion that patients with HGSOC could be better classified for optimal treatment based on gene expression, we compared genetic variants (by DNA next-generation sequencing [NGS] using a 50 gene Ion Torrent panel) and gene expression (using the NanoString® PanCancer 770 gene Panel) in the tumor from 20 patients with HGSOC before and after neoadjuvant chemotherapy (NACT). NGS was performed on plasma cell free DNA (cfDNA) on a select group of patients (n=14) in order to assess the utility of using cfDNA to monitor these changes. A total of 86 genes had significant changes in RNA expression after NACT. Thirty-eight genetic variants (including SNPs) from 6 genes were identified in tumors pre-NACT, while 59 variants from 19 genes were detected in the cfDNA. The number of DNA variants were similar after NACT. Of the 59 variants in the plasma pre-NACT, only 6 persisted; whereas 33 of 38 specific variants in the tumor DNA remained unchanged. Pathway analysis showed the most significant alterations in the cell cycle and DNA damage pathways.
2018-02-01 | GSE109934 | GEO
Project description:While PARP inhibitor (PARPi) therapies have shown promising results in the treatment of high-grade serous ovarian cancer (HGSOC) harboring homologous recombination deficiencies, primary resistance to PARPi frequently occurs and even initial responders may eventually become resistant. Therefore, the development of novel effective combinatorial strategies to treat HGSOC is urgently needed. Here, we report that H2O2-induced oxidative stress sensitized HGSOC cells to PARPi BMN 673. Furthermore, Phenethyl isothiocyanate (PEITC) as a ROS-inducing agent significantly enhanced the cytotoxic effects of BMN 673. Mechanistically, combined use of PEITC and BMN 673 resulted in ROS overproduction and accumulation, enhanced DNA damage, G2/M arrest and apoptosis, all of which were significantly reversed by the ROS scavenger N-Acetyl-L-cysteine. We also showed that while PEITC did not further enhance the ability of BMN 673 on PARP1 trapping in HGSOC cells, the therapeutic effects of the PEITC/BMN 673 combination were at least in part dependent on the presence of PARP1. Importantly, the PEITC/BMN 673 combination potently abrogated the growth of HGSOC tumor spheroids and patient-derived organoid models of HGSOC and cervical cancer. Our findings provide a basis for further investigation of the utility of PARPi combination regimen in HGSOC and cervical cancer through ROS-mediated mechanisms.
| S-EPMC8825372 | biostudies-literature
Project description:High-grade serous ovarian carcinoma (HGSOC) is an epithelial cancer that accounts for most ovarian cancer deaths. Metabolic abnormalities such as extensive aerobic glycolysis and aberrant lipid metabolism are well-known characteristics of cancer cells. Indeed, accumulation of lipid droplets (LDs) in certain types of malignant tumors has been known for more than 50 years. Here, we investigated the correlation between LD accumulation and clinical prognosis. In 96 HGSOC patients, we found that high expression of the LD marker adipophilin was associated with poor progression-free and overall survival (p = 0.0022 and p = 0.014, respectively). OVCAR-3 ovarian carcinoma cells accumulated LDs in a glucose-dependent manner, which suggested the involvement of aerobic glycolysis and subsequently enhanced lipogenesis, with a result being LD accumulation. The acyl-CoA: cholesterol acyltransferase 1 inhibitor K604 and the hydroxymethylglutaryl-CoA reductase inhibitor pitavastatin blocked LD accumulation in OVCAR-3 cells and reduced phosphorylation of the survival-related kinases Akt and ERK1/2, both of which have been implicated in malignancy. Our cell-based assays thus suggested that enhanced aerobic glycolysis resulted in LD accumulation and activation of survival-related kinases. Overall, our results support the idea that cancers with lipogenic phenotypes are associated with poor clinical prognosis, and we suggest that adipophilin may serve as an independent indicator of a poor prognosis in HGSOC.
| S-EPMC8533764 | biostudies-literature