Dikla Atias

Exclusive destruction of mitotic spindles in human cancer cells

We identified target proteins modified by phenanthrenes that cause exclusive eradication of human cancer cells. The cytotoxic activity of the phenanthrenes in a variety of human cancer cells is attributed by these findings to post translational modifications of NuMA and kinesins HSET/kifC1 and kif18A. Their activity prevented the binding of NuMA to α-tubulin and kinesins in human cancer cells, and caused aberrant spindles. The most efficient cytotoxic activity of the phenanthridine PJ34, caused significantly smaller aberrant spindles with disrupted spindle poles and scattered extra-centrosomes and chromosomes. Concomitantly, PJ34 induced tumor growth arrest of human malignant tumors developed in athymic nude mice, indicating the relevance of its activity for cancer therapy.

Pancreatic cancer ascites xenograft–an expeditious model mirroring advanced therapeutic resistant disease

Pancreatic ductal adenocarcinoma has limited treatment options. There is an urgent need for developing appropriate pre-clinical models recapitulating metastatic disease, the most common clinical scenario at presentation. Ascites accumulation occurs in up to 20–30% of patients with pancreatic cancer; this milieu represents a highly cellular research resource of metastatic peritoneal spread. In this study, we utilized pancreatic ascites/pleural effusion cancer cells to establish patient derived xenografts. Ascites/pleural effusion-patient derived xenografts were established from twelve independent cases. Xenografts were serially passed in nude mice and tissue bio-specimen banking has been established. Histopathology of emergent tumors demonstrates poorly to moderately differentiated, glandular and mucin producing tumors, mirroring morphology of primary pancreatic cancer tumors. Whole genome sequencing of six patient derived xenografts samples demonstrates common mutations and structural variations similar to those reported in primary pancreatic cancer. Xenograft tumors were dissociated to single-cells and in-vitro drug sensitivity screen assays demonstrated chemo-resistance, correlating with patient clinical scenarios, thus serving as a platform for clinically relevant translational research. Therefore, establishment of this novel ascites/pleural effusion patient derived xenograft model, with extensive histopathology and genomic characterization, opens an opportunity for the study of advanced aggressive pancreatic cancer. Characterization of metastatic disease and mechanisms of resistance to therapeutics may lead to the development of novel drug combinations.

Recapitulating the clinical scenario of BRCA-associated pancreatic cancer in pre-clinical models: BRCAmut PDAC in-vivo response to PARPi

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. BRCA‐associated PDAC comprises a clinically relevant subtype. A portion of these patients are highly susceptible to DNA damaging therapeutics, however, responses are heterogeneous and clinical resistance evolves. We have developed unique patient‐derived xenograft (PDX) models from metastatic lesions of germline BRCA‐mutated patients obtained at distinct time points; before treatment and at progression. Thus, closely mimicking clinical scenarios, to further investigate treatment naïve and resistant patients. DNA was isolated from six BRCA‐mutated PDXs and classified by whole‐genome sequencing to stable‐genome or homologous recombination deficient (HRD)‐genome. The sensitivity to DNA‐damaging agents was evaluated in vivo in three BRCA‐associated PDAC PDXs models: (1) HRD‐genome naïve to treatments; (2) stable‐genome naïve to treatment; (3) HRD‐genome resistant to treatment. Correlation between disease course at tissue acquisition and response to PARP inhibitor (PARPi)/platinum was demonstrated in PDXs in vivo. Only the HRD‐genome PDX, naïve to treatment, was sensitive to PARP inhibitor/cisplatin treatments. Our results demonstrate heterogeneous responses to DNA damaging agents/PARPi in BRCA‐associated PDX thus reflecting the wide clinical spectrum. An HRD‐genome PDX generated from a naïve to treatment biopsy was sensitive to platinum/PARPi whereas no benefit was observed in treating a HRD‐genome PDXs generated from a patient that had acquired resistance nor stable‐genome PDXs.

Abstract PR09: Harnessing synthetic lethality to predict clinical outcomes of cancer treatment

Significance: The identification of Synthetic Lethal interactions (SLi) have long been considered a foundation for the advancement of cancer treatment. The rapidly accumulating large-scale patient data now provides a golden opportunity to infer SLi directly from patient samples. Here we present a new data-driven approach termed ISLE for identifying SLi, which is then shown to be predictive of clinical outcomes of cancer treatment in an unsupervised manner, for the first time. Methods: ISLE consists of four inference steps, analyzing tumor, cell line and gene evolutionary data: It first identifies putative SL gene pairs whose co-inactivation is underrepresented in tumors, testifying that they are selected against. Second, it further prioritizes candidate SL pairs whose co-inactivation is associated with better prognosis in patients, testifying that they may hamper tumor progression. Finally, it eliminates false positive SLi using gene essentiality screens (testifying to causal SLi relations) and prioritizing SLi paired genes with similar evolutionary phylogenetic profiles. Results: We applied ISLE to analyze the TCGA tumor collection and generated the first clinically-derived pan-cancer SL-network, composed of SLi common across many cancer types. We validated that these SLi match the known, experimentally identified SLi (AUC=0.87), and show that the SL-network is predictive of patient survival in an independent breast cancer dataset (METABRIC). Based on the predicted SLi, we predicted drug response in a wide variety of in vitro, mouse xenograft and patient data, altogether encompassing >700 single drugs and >5,000 drug combinations in >1,000 cell lines, 375 xenograft models and >5,000 patient samples. Importantly, these predictions were performed in an unsupervised manner, reducing the known risk of over-fitting the data commonly associated with supervised prediction methods. SL-derived predictions are based on computing an SL-score that estimates the efficacy of a given drug in a given tumor based on the latter9s omics data. The SL-score counts the number of inactive SL-partners of a given drug target(s) in the given tumor, reflecting the notion that a drug is likely to be more effective in tumors where many of its targets9 SL-partners are inactive. The predicted SL-scores show significant correlations (R > 0.4) with large-scale in vitro and in vivo drug response screens for the majority of drugs tested. Based on the conjecture that synergism between drugs may be mediated by underlying SLi between their targets, we additionally provide accurate predictions of drug synergism for both in vitro and in vivo drug combination screens (AUC~0.8). Most importantly, we demonstrate for the first time that an SL-network can successfully predict the treatment outcome in cancer patients in multiple large-scale patient datasets including the TCGA, where SLis successfully predict patients9 response for 75% of cancer drugs. Conclusions: ISLE is predictive of the patients9 response for the majority of current cancer drugs. Of paramount importance, the predictions of ISLE are based on SLi between (potentially) all genes in the cancer genome, thus prioritizing treatments for patients whose tumors do not bear specific actionable mutations in cancer driver genes, offering a novel approach to precision-based cancer therapy. The predictive performance of ISLE is likely to further improve with the expected rapid accumulation of additional cancer omics and clinical phenotypic data. Citation Format: Joo Sang Lee, Avinash Das, Livnat Jerby-Arnon, Dikla Atias, Arnaud Amzallag, Cyril H. Benes, Talia Golan, Eytan Ruppin. Harnessing synthetic lethality to predict clinical outcomes of cancer treatment [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr PR09.

Abstract B124: Isolation and characterization of ascitic derived primary pancreatic cancer cell cultures from different patients as a platform for personalized medicine.

Discovery and development of effective cancer treatments in pancreatic cancer (PC) has been hampered by the lack of reliable predictive preclinical models to assess the therapeutic efficacy of candidate agents, mostly due to the genomic heterogeneity in these patients. Therefore alternative models that recapitulate this complex disease need to be developed. Approximately a third of patients with PC have a tendency to produce ascites in advanced disease. The ascitic fluid contains viable tumor cells, and therefore we decided to develop an investigational model based on primary tumor cells obtained from patients9 ascites. Ascitic fluid was obtained from 20 patients with PC undergoing palliative paracentesis, in 4 patients ascites was obtained several times during the course of their disease (totaling 44 ascitic fluids obtained). Ascitic-derived primary pancreatic cancer cells were isolated and cultures were grown for each individual patient. We identified the PC cells and examined the cells9 morphological characteristics, phenotypes, invasive properties and the effect of various therapeutic agents. We successfully established ascitic-derived primary cell cultures in 84% (37/44). Positive staining by IHC of epithelial marker (CK-7) and negative staining for CK-5/6 was demonstrated in the majority of cells in the culture. Cytokeratin staining by FACS was observed in 90–95% of the isolated cells supporting the presence of homogeneous epithelial PC enriched cell culture. We observed a wide range in doubling time and migration properties among the patients9 ascites derived cell cultures and even among cultures from the same patient along the course of his disease. A correlation between high migratory potential and long doubling time was observed. The cells were treated with different chemotherapies and biological agents. The diverse nature of each individual patient9s primary pancreatic cancer cell cultures were further demonstrated by varying responses to the therapeutic agents examined. Morphological changes were also observed at different stages of disease, most cells initially displayed a characteristic epithelial morphology, but with more advanced disease a mixed morphological appearance ‘epithelial-mesenchymal’ was seen. The expression of epithelial-mesenchymal-transition (EMT) markers was examined by real-time PCR. Up regulation of Zeb-1, Zeb-2, Twist, Slug and Dab2 were observed in the cells displaying ‘epithelial-mesenchymal’ like appearance. We have developed a unique primary ascitic-derived pancreatic cancer cell culture model that enables a diverse range of patients-related cell cultures. These cell lines has the potential to serve as a relevant model to study signaling pathways in PC progression. Additionally, this model could be used to assess the sensitivity to therapeutic agents in a short time frame, therefore supporting personalized treatment decisions. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr B124.