Current Status and Evolution of Preclinical Drug Development Models of Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy and the fifth most common cause of female cancer death in the United States. Although important advances in surgical and chemotherapeutic strategies over the last three decades have significantly improved the median survival of EOC patients, the plateau of the survival curve has not changed appreciably. Given that EOC is a genetically and biologically heterogeneous disease, identification of specific molecular abnormalities that can be targeted in each individual ovarian cancer on the basis of predictive biomarkers promises to be an effective strategy to improve outcome in this disease. However, for this promise to materialize, appropriate preclinical experimental platforms that recapitulate the complexity of these neoplasms and reliably predict antitumor activity in the clinic are critically important. In this review, we will present the current status and evolution of preclinical models of EOC, including cell lines, immortalized normal cells, xenograft models, patient-derived xenografts, and animal models, and will discuss their potential for oncology drug development

Morphologic and immunophenotypic evidence of in-situ Kaposi's sarcoma

BACKGROUND: The spectrum of Kaposi's sarcoma (KS) has been expanded to include pre-KS lesions. CASE PRESENTATION: We report, for the first time, a case providing direct histological evidence of the development of early (in-situ) KS from mediastinal lymphatic vessels in the setting of chronic lymphedema in an HIV-positive patient. Spindle-shaped and endothelial cells in these early KS-appearing lesions were immunoreactive for HHV8, D2-40 and CD34. CONCLUSION: Our findings suggest that HHV8-infected spindle-shaped cells associated with lymphangiogenesis that evolve into KS lesions, acquire from the outset an aberrant mixed vascular and lymphatic endothelial cell phenotype

PTGS2 (prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase))

Review on PTGS2 (prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase)), with data on DNA, on the protein encoded, and where the gene is implicated

Resistance to therapy in BRCA2 mutant cells due to loss of the nucleosome remodeling factor CHD4

Hereditary cancers derive from gene defects that often compromise DNA repair. Thus, BRCA-associated cancers are sensitive to DNA-damaging agents such as cisplatin. The efficacy of cisplatin is limited, however, by the development of resistance. One cisplatin resistance mechanism is restoration of homologous recombination (HR), which can result from BRCA reversion mutations. However, in BRCA2 mutant cancers, cisplatin resistance can occur independently of restored HR by a mechanism that remains unknown. Here we performed a genome-wide shRNA screen and found that loss of the nucleosome remodeling factor CHD4 confers cisplatin resistance. Restoration of cisplatin resistance is independent of HR but correlates with restored cell cycle progression, reduced chromosomal aberrations, and enhanced DNA damage tolerance. Suggesting clinical relevance, cisplatin-resistant clones lacking genetic reversion of BRCA2 show de novo loss of CHD4 expression in vitro. Moreover, BRCA2 mutant ovarian cancers with reduced CHD4 expression significantly correlate with shorter progression-free survival and shorter overall survival. Collectively, our findings indicate that CHD4 modulates therapeutic response in BRCA2 mutant cancer cells

Sublethal concentrations of 17-AAG suppress homologous recombination DNA repair and enhance sensitivity to carboplatin and olaparib in HR proficient ovarian cancer cells

The promise of PARP-inhibitors(PARPis) in the management of epithelial ovarian cancer(EOC) is tempered by the fact that approximately 50% of patients with homologous recombination (HR)-proficient tumors do not respond well to these agents. Combination of PARPis with agents that inhibit HR may represent an effective strategy to enhance their activity in HR-proficient tumors. Using a bioinformatics approach, we identified that heat shock protein 90 inhibitors(HSP90i) may suppress HR and thus revert HR-proficient to HR-deficient tumors. Analysis of publicly available gene expression data showed that exposure of HR-proficient breast cancer cell lines to HSP90i 17-AAG(17-allylamino-17-demethoxygeldanamycin) downregulated HR, ATM and Fanconi Anemia pathways. In HR-proficient EOC cells, 17-AAG suppressed HR as assessed using the RAD51 foci formation assay and this was further confirmed using the Direct Repeat-GFP reporter assay. Furthermore, 17-AAG downregulated BRCA1 and/or RAD51 protein levels, and induced significantly more γH2AX activation in combination with olaparib compared to olaparib alone. Finally, sublethal concentrations of 17-AAG sensitized HR-proficient EOC lines to olaparib and carboplatin but did not affect sensitivity of the HR-deficient OVCAR8 line arguing that the 17-AAG mediated sensitization is dependent on suppression of HR. These results provide a preclinical rationale for using a combination of olaparib/17-AAG in HR-proficient EOC

Leiomyosarcoma of the Prostate: Case Report and Review of 54 Previously Published Cases

Prostate leiomyosarcoma is an extremely rare and highly aggressive neoplasm that accounts for less than 0.1% of primary prostate malignancies. We present a patient with primary leiomyosarcoma of the prostate and review 54 cases reported in the literature to discuss the clinical, diagnostic and therapeutic aspects of this uncommon tumor. Median survival was estimated at 17 months (95% C.I. 20.7–43.7 months) and the 1-, 3-, and 5-year actuarial survival rates were 68%, 34%, and 26%, respectively. The only factors predictive of long-term survival were negative surgical margins and absence of metastatic disease at presentation. A multidisciplinary approach is necessary for appropriate management of this dire entity

Analysis of Multiple Sarcoma Expression Datasets: Implications for Classification, Oncogenic Pathway Activation and Chemotherapy Resistance

Background: Diagnosis of soft tissue sarcomas (STS) is challenging. Many remain unclassified (not-otherwise-specified, NOS) or grouped in controversial categories such as malignant fibrous histiocytoma (MFH), with unclear therapeutic value. We analyzed several independent microarray datasets, to identify a predictor, use it to classify unclassifiable sarcomas, and assess oncogenic pathway activation and chemotherapy response. Methodology/Principal Findings: We analyzed 5 independent datasets (325 tumor arrays). We developed and validated a predictor, which was used to reclassify MFH and NOS sarcomas. The molecular “match” between MFH and their predicted subtypes was assessed using genome-wide hierarchical clustering and Subclass-Mapping. Findings were validated in 15 paraffin samples profiled on the DASL platform. Bayesian models of oncogenic pathway activation and chemotherapy response were applied to individual STS samples. A 170-gene predictor was developed and independently validated (80-85% accuracy in all datasets). Most MFH and NOS tumors were reclassified as leiomyosarcomas, liposarcomas and fibrosarcomas. “Molecular match” between MFH and their predicted STS subtypes was confirmed both within and across datasets. This classification revealed previously unrecognized tissue differentiation lines (adipocyte, fibroblastic, smooth-muscle) and was reproduced in paraffin specimens. Different sarcoma subtypes demonstrated distinct oncogenic pathway activation patterns, and reclassified MFH tumors shared oncogenic pathway activation patterns with their predicted subtypes. These patterns were associated with predicted resistance to chemotherapeutic agents commonly used in sarcomas. Conclusions/Significance: STS profiling can aid in diagnosis through a predictor tracking distinct tissue differentiation in unclassified tumors, and in therapeutic management via oncogenic pathway activation and chemotherapy response assessment

EGF-R is Expressed and AP-1 and NF-κ:B Are Activated in Stromal Myofibroblasts Surrounding Colon Adenocarcinomas Paralleling Expression of COX-2 and VEGF

Background:: COX-2 and VEGF are important triggers of colon cancer growth, metastasis and angiogenesis. Cox-2 promoter contains transcriptional regulatory elements for AP-1 and NF-κ:B transcription factors whilst vegf is a known AP-1 downstream target gene. We investigated whether stromal myofibroblasts surrounding colon adenocarcinomas express COX-2 and VEGF and whether activation of AP-1 and NF-κ:B, as well as expression of EGF-R parallel expression of COX-2 and VEGF in these cells. Methods:: Immunohistochemical methodology was performed on archival sections from 40 patients with colon adenocarcinomas. We evaluated c-FOS, p-c-JUN (phosphorylated c-JUN), p-Iκ:B-α (phosphorylated Iκ:B-α), EGF-R, COX-2, NF-κ:B and VEGF expression in stromal myofibroblasts surrounding colon adenocarcinomas. Double immunostaining with a-smooth muscle actin and each antibody was done to verify the expression of these molecules in stromal myofibroblasts. Results:: VEGF, p-Iκ:B-α, NF-κ:B, c-FOS, p-c-JUN, EGF-R and COX-2 were expressed in stromal myofibroblasts surrounding colon adenocarcinomas in the majority of cases. EGF-R, p-Iκ:B-α, NF-κ:B, c-FOS and p-c-JUN correlated positively with COX-2 and VEGF expression. Conclusion:: Stromal myofibroblasts surrounding colon adenocarcinomas are an important source of VEGF and COX-2 production, while AP-1 and NF-κ:B transcription factors are activated and EGF-R is expressed in these cells and associated with COX-2 and VEGF production

Integrated Analysis of Multiple Microarray Datasets Identifies a Reproducible Survival Predictor in Ovarian Cancer

BACKGROUND: Public data integration may help overcome challenges in clinical implementation of microarray profiles. We integrated several ovarian cancer datasets to identify a reproducible predictor of survival. METHODOLOGY/PRINCIPAL FINDINGS: Four microarray datasets from different institutions comprising 265 advanced stage tumors were uniformly reprocessed into a single training dataset, also adjusting for inter-laboratory variation ("batch-effect"). Supervised principal component survival analysis was employed to identify prognostic models. Models were independently validated in a 61-patient cohort using a custom array genechip and a publicly available 229-array dataset. Molecular correspondence of high- and low-risk outcome groups between training and validation datasets was demonstrated using Subclass Mapping. Previously established molecular phenotypes in the 2(nd) validation set were correlated with high and low-risk outcome groups. Functional representational and pathway analysis was used to explore gene networks associated with high and low risk phenotypes. A 19-gene model showed optimal performance in the training set (median OS 31 and 78 months, p < 0.01), 1(st) validation set (median OS 32 months versus not-yet-reached, p = 0.026) and 2(nd) validation set (median OS 43 versus 61 months, p = 0.013) maintaining independent prognostic power in multivariate analysis. There was strong molecular correspondence of the respective high- and low-risk tumors between training and 1(st) validation set. Low and high-risk tumors were enriched for favorable and unfavorable molecular subtypes and pathways, previously defined in the public 2(nd) validation set. CONCLUSIONS/SIGNIFICANCE: Integration of previously generated cancer microarray datasets may lead to robust and widely applicable survival predictors. These predictors are not simply a compilation of prognostic genes but appear to track true molecular phenotypes of good- and poor-outcome

Optimized detection of homologous recombination deficiency improves the prediction of clinical outcomes in cancer

Peer reviewe