Person:

Benes, Cyril

It is becoming increasingly apparent that cancer drug therapies can only reach their full potential through appropriate patient selection. Matching drugs and cancer patients has proven to be a complex challenge, due in large part to the substantial molecular heterogeneity inherent to human cancers. This is not only a major hurdle to the improvement of the use of current treatments but also for the development of novel therapies and the ability to steer them to the relevant clinical indications. In this commentary we discuss recent studies from Kuo et al., published this month in BMC Medicine, in which they used a panel of cancer cell lines as a model for capturing patient heterogeneity at the genomic and proteomic level in order to identify potential biomarkers for predicting the clinical activity of a novel candidate chemotherapeutic across a patient population. The findings highlight the ability of a 'systems approach' to develop a better understanding of the properties of novel candidate therapeutics and to guide clinical testing and application. See the associated research paper by Kuo et al: http://www.biomedcentral.com/1741-7015/7/77

Background: The development of resistance to chemotherapies represents a significant barrier to successful cancer treatment. Resistance mechanisms are complex, can involve diverse and often unexpected cellular processes, and can vary with both the underlying genetic lesion and the origin or type of tumor. For these reasons developing experimental strategies that could be used to understand, identify and predict mechanisms of resistance in different malignant cells would be a major advance. Methods: Here we describe a gain-of-function forward genetic approach for identifying mechanisms of resistance. This approach uses a modified piggyBac transposon to generate libraries of mutagenized cells, each containing transposon insertions that randomly activate nearby gene expression. Genes of interest are identified using next-gen high-throughput sequencing and barcode multiplexing is used to reduce experimental cost. Results: Using this approach we successfully identify genes involved in paclitaxel resistance in a variety of cancer cell lines, including the multidrug transporter ABCB1, a previously identified major paclitaxel resistance gene. Analysis of co-occurring transposons integration sites in single cell clone allows for the identification of genes that might act cooperatively to produce drug resistance a level of information not accessible using RNAi or ORF expression screening approaches. Conclusion: We have developed a powerful pipeline to systematically discover drug resistance in mammalian cells in vitro. This cost-effective approach can be readily applied to different cell lines, to identify canonical or context specific resistance mechanisms. Its ability to probe complex genetic context and non-coding genomic elements as well as cooperative resistance events makes it a good complement to RNAi or ORF expression based screens.

The mammalian target of rapamycin (mTOR) regulates cell growth by integrating nutrient and growth factor signaling and is strongly implicated in cancer. But mTOR is not an oncogene, and which tumors will be resistant or sensitive to new ATP-competitive mTOR inhibitors now in clinical trials remains unknown. We screened a panel of over 600 human cancer cell lines to identify markers of resistance and sensitivity to the mTOR inhibitor PP242. RAS and PIK3CA mutations were the most significant genetic markers for resistance and sensitivity to PP242, respectively; colon origin was the most significant marker for resistance based on tissue type. Among colon cancer cell lines, those with KRAS mutations were most resistant to PP242, while those without KRAS mutations most sensitive. Surprisingly, cell lines with co-mutation of PIK3CA and KRAS had intermediate sensitivity. Immunoblot analysis of the signaling targets downstream of mTOR revealed that the degree of cellular growth inhibition induced by PP242 was correlated with inhibition of phosphorylation of the translational repressor 4E-BP1, but not ribosomal protein S6. In a tumor growth inhibition trial of PP242 in patient-derived colon cancer xenografts, resistance to PP242 induced inhibition of 4E-BP1 phosphorylation and xenograft growth was again observed in KRAS mutant tumors without PIK3CA co-mutation, compared to KRAS WT controls. We show that, in the absence of PIK3CA co-mutation, KRAS mutations are associated with resistance to PP242 and that this is specifically linked to changes in the level of phosphorylation of 4E-BP1.

Background: Preclinical studies have documented antitumor activity of PARP inhibition both in vitro and in vivo, against Ewing sarcoma cells. This study aimed to translate that observation into a clinical trial to assess the efficacy and tolerability of olaparib, a PARP inhibitor, in patients with advanced Ewing sarcoma (EWS) progressing after prior chemotherapy. Methods: In this nonrandomized phase II trial, adult participants with radiographically measureable metastatic EWS received olaparib tablets, 400 mg orally twice daily, until disease progression or drug intolerance. Tumor measurements were determined by CT or MRI at 6 and 12 weeks after starting olaparib administration, and then every 8 weeks thereafter. Tumor response determinations were made according to RECIST 1.1, and adverse event determinations were made according to CTCAE, version 4.0. A total of 22 participants were planned to be enrolled using a conventional 2-step phase II study design. If no objective responses were observed after 12 participants had been followed for at least 3 months, further accrual would be stopped. Results: 12 participants were enrolled, and all were evaluable. There were no objective responses (PR/CR), 4 SD (duration 10.9, 11.4, 11.9, and 17.9 wks), and 8 PD as best response. Of the SD, 2 had minor responses (−9% and −11.7% by RECIST 1.1). The median time to disease progression was 5.7 weeks. Further enrollment was therefore discontinued. No significant or unexpected toxicities were observed with olaparib, with only a single case each of grade 3 anemia and grade 3 thrombocytopenia observed. Conclusions: This study is the first report of a prospective phase II trial to evaluate the safety and efficacy of a PARP inhibitor in patients with advanced Ewing sarcoma after failure of standard chemotherapy. Olaparib administration was safe and well tolerated when administered to this small heavily pre-treated cohort at the 400 mg BID dose, although the median duration of dosing was for only 5.7 weeks. No significant responses or durable disease control was seen, and the short average interval to disease progression underscores the aggressiveness of this disease. Other studies to combine cytotoxic chemotherapy with PARP inhibition in EWS are actively ongoing. Trial registration ClinicalTrials.gov Identifier: NCT01583543

Tumor oncogenes include transcription factors that co-opt the general transcriptional machinery to sustain the oncogenic state1, but direct pharmacological inhibition of transcription factors has thus far proven difficult2. However, the transcriptional machinery contains various enzymatic co-factors that can be targeted for development of new therapeutic candidates3, including cyclin-dependent kinases (CDKs)4. Here we present the discovery and characterization of the first covalent CDK7 inhibitor, THZ1, which has the unprecedented ability to target a remote cysteine residue located outside of the canonical kinase domain, providing an unanticipated means of achieving selectivity for CDK7. Cancer cell line profiling indicates that a subset of cancer cell lines, including T-ALL, exhibit exceptional sensitivity to THZ1. Genome-wide analysis in Jurkat T-ALL shows that THZ1 disproportionally affects transcription of RUNX1 and suggests that sensitivity to THZ1 may be due to vulnerability conferred by the RUNX1 super-enhancer and this transcription factor’s key role in the core transcriptional regulatory circuitry of these tumor cells. Pharmacological modulation of CDK7 kinase activity may thus provide an approach to identify and treat tumor types exhibiting extreme dependencies on transcription for maintenance of the oncogenic state.

Alterations in cancer genomes strongly influence clinical responses to treatment and in many instances are potent biomarkers for response to drugs. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) is the largest public resource for information on drug sensitivity in cancer cells and molecular markers of drug response. Data are freely available without restriction. GDSC currently contains drug sensitivity data for almost 75 000 experiments, describing response to 138 anticancer drugs across almost 700 cancer cell lines. To identify molecular markers of drug response, cell line drug sensitivity data are integrated with large genomic datasets obtained from the Catalogue of Somatic Mutations in Cancer database, including information on somatic mutations in cancer genes, gene amplification and deletion, tissue type and transcriptional data. Analysis of GDSC data is through a web portal focused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer drugs or cancer genes. Graphical representations of the data are used throughout with links to related resources and all datasets are fully downloadable. GDSC provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies.

Predicting the response of a specific cancer to a therapy is a major goal in modern oncology that should ultimately lead to a personalised treatment. High-throughput screenings of potentially active compounds against a panel of genomically heterogeneous cancer cell lines have unveiled multiple relationships between genomic alterations and drug responses. Various computational approaches have been proposed to predict sensitivity based on genomic features, while others have used the chemical properties of the drugs to ascertain their effect. In an effort to integrate these complementary approaches, we developed machine learning models to predict the response of cancer cell lines to drug treatment, quantified through IC50 values, based on both the genomic features of the cell lines and the chemical properties of the considered drugs. Models predicted IC50 values in a 8-fold cross-validation and an independent blind test with coefficient of determination R2 of 0.72 and 0.64 respectively. Furthermore, models were able to predict with comparable accuracy (R2 of 0.61) IC50s of cell lines from a tissue not used in the training stage. Our in silico models can be used to optimise the experimental design of drug-cell screenings by estimating a large proportion of missing IC50 values rather than experimentally measuring them. The implications of our results go beyond virtual drug screening design: potentially thousands of drugs could be probed in silico to systematically test their potential efficacy as anti-tumour agents based on their structure, thus providing a computational framework to identify new drug repositioning opportunities as well as ultimately be useful for personalized medicine by linking the genomic traits of patients to drug sensitivity.

ONC201 is the founding member of a novel class of anti-cancer compounds called imipridones that is currently in Phase II clinical trials in multiple advanced cancers. Since the discovery of ONC201 as a p53-independent inducer of TRAIL gene transcription, preclinical studies have determined that ONC201 has anti-proliferative and pro-apoptotic effects against a broad range of tumor cells but not normal cells. The mechanism of action of ONC201 involves engagement of PERK-independent activation of the integrated stress response, leading to tumor upregulation of DR5 and dual Akt/ERK inactivation, and consequent Foxo3a activation leading to upregulation of the death ligand TRAIL. ONC201 is orally active with infrequent dosing in animals models, causes sustained pharmacodynamic effects, and is not genotoxic. The first-in-human clinical trial of ONC201 in advanced aggressive refractory solid tumors confirmed that ONC201 is exceptionally well-tolerated and established the recommended phase II dose of 625 mg administered orally every three weeks defined by drug exposure comparable to efficacious levels in preclinical models. Clinical trials are evaluating the single agent efficacy of ONC201 in multiple solid tumors and hematological malignancies and exploring alternative dosing regimens. In addition, chemical analogs that have shown promise in other oncology indications are in pre-clinical development. In summary, the imipridone family that comprises ONC201 and its chemical analogs represent a new class of anti-cancer therapy with a unique mechanism of action being translated in ongoing clinical trials.

Sorafenib is a RAF inhibitor approved for several cancers, including hepatocellular carcinoma (HCC). Inhibition of RAF kinases can induce a dose-dependent “paradoxical” upregulation of the downstream mitogen-activated protein kinase (MAPK) pathway in cancer cells. It is unknown whether “paradoxical” ERK activation occurs after sorafenib therapy in HCC, and if so, if it impacts the therapeutic efficacy. Here, we demonstrate that RAF inhibition by sorafenib rapidly leads to RAF dimerization and ERK activation in HCCs, which contributes to treatment evasion. The transactivation of RAF dimers and ERK signaling promotes HCC cell survival, prevents apoptosis via downregulation of BIM and achieves immunosuppression by MAPK/NF-kB-dependent activation of PD-L1 gene expression. To overcome treatment evasion and reduce systemic effects, we developed CXCR4-targeted nanoparticles to co-deliver sorafenib with the MEK inhibitor AZD6244 in HCC. Using this approach, we preferentially and efficiently inactivated RAF/ERK, upregulated BIM and down-regulated PD-L1 expression in HCC, and facilitated intra-tumoral infiltration of cytotoxic CD8+ T cells. These effects resulted in a profound delay in tumor growth. Thus, this nano-delivery strategy to selectively target tumors and prevent the paradoxical ERK activation could increase the feasibility of dual RAF/MEK inhibition to overcome sorafenib treatment escape in HCC.

Circulating tumor cells (CTCs) in women with advanced estrogen receptor-positive/HER2-negative breast cancer acquire a HER2-positive subpopulation following multiple courses of therapy1,2. In contrast to HER2-amplified primary breast cancer, which is highly sensitive to HER2-targeted therapy, the clinical significance of acquired HER2 heterogeneity during the evolution of metastatic breast cancer is unknown. Here, we analyzed CTCs from 19 ER+/HER2− patients, 84% of whom had acquired CTCs expressing HER2. Cultured CTCs maintain discrete HER2+ and HER2− subpopulations: HER2+ CTCs are more proliferative but not addicted to HER2, consistent with activation of multiple signaling pathways. HER2− CTCs show activation of Notch and DNA damage pathways, exhibiting resistance to cytotoxic chemotherapy, but sensitivity to Notch inhibition. HER2+ and HER2− CTCs interconvert spontaneously, with cells of one phenotype producing daughters of the opposite within four cell doublings. While HER2+ and HER2− CTCs have comparable tumor initiating potential, differential proliferation favors the HER2+ state, while oxidative stress or cytotoxic chemotherapy enhances transition to the HER2− phenotype. Simultaneous treatment with paclitaxel and Notch inhibitors achieves sustained suppression of tumorigenesis in orthotopic CTC-derived tumor models. Together, these results point to distinct yet interconverting phenotypes within patient-derived CTCs, contributing to progression of breast cancer and acquisition of drug resistance.