Project description:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients. Gene expression was measured for 32 ovarian cancer cell lines using the GeneChip Human Exon 1.0 ST Array (Affymetrix). Morphological subtypes were assigned based on cell morphology, size, growth pattern and proliferation rate during culturing of the cell lines.

Project description:<h4>Background</h4>Cancer metabolism is emerging as an important focus area in cancer research. However, the in vitro cell culture conditions under which much cellular metabolism research is performed differ drastically from in vivo tumor conditions, which are characterized by variations in the levels of oxygen, nutrients like glucose, and other molecules like chemotherapeutics. Moreover, it is important to know how the diverse cell types in a tumor, including cancer stem cells that are believed to be a major cause of cancer recurrence, respond to these variations. Here, in vitro environmental perturbations designed to mimic different aspects of the in vivo environment were used to characterize how an ovarian cancer cell line and its derived, isogenic cancer stem cells metabolically respond to environmental cues.<h4>Results</h4>Mass spectrometry was used to profile metabolite levels in response to in vitro environmental perturbations. Docetaxel, the chemotherapeutic used for this experiment, caused significant metabolic changes in amino acid and carbohydrate metabolism in ovarian cancer cells, but had virtually no metabolic effect on isogenic ovarian cancer stem cells. Glucose deprivation, hypoxia, and the combination thereof altered ovarian cancer cell and cancer stem cell metabolism to varying extents for the two cell types. Hypoxia had a much larger effect on ovarian cancer cell metabolism, while glucose deprivation had a greater effect on ovarian cancer stem cell metabolism. Core metabolites and pathways affected by these perturbations were identified, along with pathways that were unique to cell types or perturbations.<h4>Conclusions</h4>The metabolic responses of an ovarian cancer cell line and its derived isogenic cancer stem cells differ greatly under most conditions, suggesting that these two cell types may behave quite differently in an in vivo tumor microenvironment. While cancer metabolism and cancer stem cells are each promising potential therapeutic targets, such varied behaviors in vivo would need to be considered in the design and early testing of such treatments.

Project description:PD-0332991 is a selective inhibitor of the CDK4/6 kinases with the ability to block retinoblastoma (Rb) phosphorylation in the low nanomolar range. Here we investigate the role of CDK4/6 inhibition in human ovarian cancer. We examined the effects of PD-0332991 on proliferation, cell-cycle, apoptosis, and Rb phosphorylation using a panel of 40 established human ovarian cancer cell lines. Molecular markers for response prediction, including p16 and Rb, were studied using gene expression profiling, Western blot, and arrayCGH. Multiple drug effect analysis was used to study interactions with chemotherapeutic drugs. Expression of p16 and Rb was studied using immunohistochemistry in a large clinical cohort ovarian cancer patients. Concentration-dependent anti-proliferative effects of PD-0332991were seen in all ovarian cancer cell lines, but varied significantly between individual lines. Rb proficient cell lines with low p16 expression were most responsive to CDK4/6 inhibition. Copy number variations of CDKN2A, Rb, CCNE1, and CCND1 were associated with response to PD-0332991. CDK4/6 inhibition induced G0/G1 cell cycle arrest, blocked Rb phosphorylation in a concentration and time dependent manner, and enhanced the effects of chemotherapy. Rb proficiency with low p16 expression was seen in 97/262 (37%) of ovarian cancer patients and associated with adverse clinical outcome (progression free survival, adjusted relative risk 1.49, 95%CI 0.99-2.22, p =0.054). PD-0332991 shows promising biologic activity in ovarian cancer cell lines. Assessment of Rb and p16 expression may help select patients most likely to benefit from CDK4/6 inhibition in ovarian cancer. Gene expression of 40 individual ovarian cell lines relative to an ovarian cell line reference mix containing equal amounts of 41 ovarian cell lines (including OCC-1 which was later identified as originating from mouse). The expression data was correllated with cell line growth response to CDK 4/6 inhibitor PD-0332991 to identify genes associated with drug sensitivity and resistance.

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Expression data from human ovarian cancer cell line

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