Drivers Of Drug Resistance Research Articles

Dual direction CRISPR transcriptional regulation screening uncovers gene networks driving drug resistance

Pooled CRISPR–Cas9 knock out screens provide a valuable addition to the methods available for novel drug target identification and validation. However, where gene editing is targeted to amplified loci, the resulting multiple DNA cleavage events can be a cause of false positive hit identification. The generation of nuclease deficient versions of Cas9 has enabled the development of two additional techniques – CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) – that enable the repression or overexpression, respectively, of target genes. Here we report the first direct combination of all three approaches (CRISPRko, CRISPRi and CRISPRa) in the context of genome-wide screens to identify components that influence resistance and sensitivity to the BRAF inhibitor, vemurafenib. The pairing of both loss- and gain-of-function datasets reveals complex gene networks which control drug response and illustrates how such data can add substantial confidence to target identification and validation analyses.

AR-v7 liquid biopsy for treatment stratification in prostate cancer: how close are we?

Recent clinical introduction of the novel antiandrogen, Enzalutamide (Enza), CYP17 inhibitor, Abiraterone (Abi), and the second-generation chemotherapeutic, Cabazitaxel, has increased survival of patients with advanced, metastatic castration-resistant prostate cancer (mCRPC). However, de novo and acquired resistance rates are high. A liquid biopsy that can rapidly, sensitively and robustly identify which patients will respond to treatment in a minimally invasive manner is urgently required to permit switch to a potentially more efficacious drug regimen, thus increasing survival whilst avoiding debilitating side effects associated with unnecessary treatment. This review will highlight recent developments in detection of AR-v7 in circulating mRNA/whole blood and circulating tumour cells (CTCs) as a liquid biopsy for patient-stratification in mCRPC. Continued androgen receptor (AR) activity in mCRPC has been linked to the expression of a number of truncated but constitutively active AR isoforms. One such variant, AR-v7, can drive drug resistance in preclinical models and is correlated with disease progression whilst showing dynamic response to AR-targeting treatments when assessed in blood. It has thus been proposed as an Abi/Enza treatment-response biomarker. AR-v7 liquid biopsy has the potential to transform clinical management of mCRPC and increase patient survival. This review will explore recent efforts to validate AR-v7 as a robust, clinically informative biomarker. I will also address potential limitations of detection and quantification that could frustrate its adoption into routine clinical practise.

Quantitative phosphoproteomic analysis of acquired cancer drug resistance to pazopanib and dasatinib

Acquired drug resistance impacts the majority of patients being treated with tyrosine kinase inhibitors (TKIs) and remains a key challenge in modern anti-cancer therapy. The lack of clinically effective therapies to overcome resistance represents an unmet need. Understanding the signalling that drives drug resistance will facilitate the development of new salvage therapies to treat patients with secondary TKI resistance. In this study, we utilise mass spectrometry to characterise the global phosphoproteomic alterations that accompany the acquisition of resistance to two FDA-approved TKIs, pazopanib and dasatinib, in the A204 rhabdoid tumour cell line. Our analysis finds that only 6% and 9.7% of the quantified phosphoproteome is altered upon the acquisition of pazopanib and dasatinib resistance, respectively. Pazopanib resistant cells display elevated phosphorylation in cytoskeletal regulatory pathways while dasatinib resistant cells show an upregulation of the insulin receptor/IGF-1R signalling pathway. Drug response profiling rediscovers several previously reported vulnerabilities associated with pazopanib and dasatinib resistance and identifies a new dependency to the second generation HSP90 inhibitor NVP-AUY-922. This study provides a useful resource detailing the candidate signalling determinants of acquired TKI resistance; and reveals a therapeutic approach of inhibiting HSP90 function as a means of salvage therapy to overcome pazopanib and dasatinib resistance. SignificancePazopanib and dasatinib are tyrosine kinase inhibitors (TKIs) approved for the treatment of multiple cancer types. Patients who are treated with these drugs are prone to the development of drug resistance and consequently tumour relapse. Here we use quantitative phosphoproteomics to characterise the signalling pathways which are enriched in cells that have acquired resistance to these two drugs. Furthermore, targeted drug screens were used to identify salvage therapies capable of overcoming pazopanib and dasatinib resistance. This data advances our understanding of the mechanisms of TKI resistance and highlights candidate targets for cancer therapy.

Pathogen genetics: Evolutionary dynamics driving drug resistance.

Pathogen genetics: Evolutionary dynamics driving drug resistance.

Abstract 3887: GNA13 is a theranostic target that drives drug resistance and cancer stem-like phenotypes in solid tumors

Abstract Treatment failure in solid tumors occurs due to the survival of specific subpopulations of cells that possess stem cell-like (CSC) phenotypes. Studies have implicated G protein-coupled-receptors (GPCRs) in cancer progression and the acquisition of aggressive phenotypes. Many of the implicated GPCRs signal through the G12 subfamily, comprised of GNA12 and GNA13. In this study, we demonstrate that GNA13 is upregulated in many solid tumors and impacts survival and metastases in these patients. Consistent with this, we show that GNA13 expression modulates drug resistance through its effect on the CSC sub-population in a panel of patient-derived head and neck (HNSCC) and breast cancer cells. These data were validated in vivo, where GNA13 over-expression in patient-derived xenografts increased tumor initiating capacity, tumorigenicity and drug resistance, with no effect on growth or proliferation. Signaling through NFKB and MAPK pathways appear to be critical to the observed phenotype. Importantly, blockade of GNA13 expression, or select downstream pathways using small-molecule inhibitors, abrogates GNA13-induced CSCs, rendering cells vulnerable to standard-of-care cytotoxic therapy for these cancers. Taken together, these data indicate that GNA13 expression is a potential prognostic biomarker, and interfering with GNA13-induced signaling provides a novel strategy to block CSCs and drug resistance in solid tumors. Citation Format: Suhail Ahmed Kabeer Rasheed, Hui Sun Leong, Manikandan Lakshmanan, Anandhkumar Raju, Dhivya Dadlani, Fui-Teen Chong, Ravisankar Rajarethinam, Thakshayeni Skanthakumar, Ern Yu Tan, Jacqueline Siok Gek Hwang, Kok Hing Lim, Daniel Shao-Weng Tan, Paolo Ceppi, Mei Wang, Vinay Tergaonkar, Patrick J. Casey, N. Gopalakrishna Iyer. GNA13 is a theranostic target that drives drug resistance and cancer stem-like phenotypes in solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3887. doi:10.1158/1538-7445.AM2017-3887

Abstract 3142: Aberrantly expressed microRNAs drive the development of acquired Erlotinib resistance in non-small cell lung cancer

Abstract Lung cancer is the leading cause of cancer-related deaths in the world. Non-small cell lung cancer (NSCLC) accounts for ~85% of the cases. NSCLC patients frequently harbor causal gene mutations. Epidermal Growth Factor Receptor (EGFR), an NSCLC causal gene, is mutated in 10-35% of NSCLC patients. Patients with EGFR activating mutation are treated with a tyrosine-kinase inhibitor, Erlotinib, specifically targeting EGFR. However, most patients develop Erlotinib resistance within a year. Although multiple mechanisms are involved in the development of Erlotinib resistance, the role of microRNAs in mediating Erlotinib resistance is largely unexplored. MicroRNAs (miRNAs) are small non-coding RNAs that regulate normal cellular physiology. In cancers, miRNAs are severely dysregulated, contributing to multiple cancer processes, including drug response. Despite the involvement of miRNAs in cancer, their direct role as drivers of drug resistance remain understudied, therefore, there is a critical need to understand the role of miRNAs in inducing Erlotinib resistance. To this end, we propose an unbiased two-prong approach to identify the miRNAs that drive the development of Erlotinib resistance. Therefore, miRNAs are either being (i) overexpressed, or (ii) silenced in Erlotinib sensitive cells with the hypothesis that perturbed miRNA levels will drive Erlotinib resistance. Erlotinib sensitive NSCLC cell lines, EKVX and H322M were identified from the NCI-60 Developmental Therapeutics Project and their Erlotinib dose response curves were established. To perform the miRNA overexpression screen, EKVX and H322M cells stably expressing renilla and firefly luciferase genes were generated, which will be used to monitor cell number and transfection efficiency, respectively. The luciferase-expressing cells will be transfected with a library of 2,019 individually arrayed human miRNAs and cell growth in the presence of Erlotinib will be monitored. The second prong of the study will identify miRNAs, that when lost, confer Erlotinib resistance. 400-fold coverage of small guide RNA (sgRNA) library of the CRISPR-Cas9 system was transduced in Cas9 overexpressing EKVX cells, to knockout ~21,000 human encoded genes (~1800 miRNA genes). Cells are being cultured in the presence of 75% or 90% growth inhibitory concentrations (GI75 or GI90) of Erlotinib so that only cells with sgRNAs against genes critical for Erlotinib response, survive and grow due to acquired resistance. DNA from these cells will be harvested, the sgRNAs sequenced, and compared to the sgRNAs present in Erlotinib-untreated cells. Successful completion of this project will identify miRNAs that drive Erlotinib resistance and may contribute towards development of miRNA therapeutics to enhance Erlotinib sensitivity of NSCLC tumors. Citation Format: Arpita S. Pal, Alejandra Agredo, Andrea L. Kasinski. Aberrantly expressed microRNAs drive the development of acquired Erlotinib resistance in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3142. doi:10.1158/1538-7445.AM2017-3142

Reducing stock-outs of essential tuberculosis medicines: a system dynamics modelling approach to supply chain management.

The under-performance of supply chains presents a significant hindrance to disease control in developing countries. Stock-outs of essential medicines lead to treatment interruption which can force changes in patient drug regimens, drive drug resistance and increase mortality. This study is one of few to quantitatively evaluate the effectiveness of supply chain policies in reducing shortages and costs. This study develops a systems dynamics simulation model of the downstream supply chain for amikacin, a second-line tuberculosis drug using 10 years of South African data. We evaluate current supply chain performance in terms of reliability, responsiveness and agility, following the widely-used Supply Chain Operation Reference framework. We simulate 141 scenarios that represent different combinations of supplier characteristics, inventory management strategies and demand forecasting methods to identify the Pareto optimal set of management policies that jointly minimize the number of shortages and total cost. Despite long supplier lead times and unpredictable demand, the amikacin supply chain is 98% reliable and agile enough to accommodate a 20% increase in demand without a shortage. However, this is accomplished by overstocking amikacin by 167%, which incurs high holding costs. The responsiveness of suppliers is low: only 57% of orders are delivered to the central provincial drug depot within one month. We identify three Pareto optimal safety stock management policies. Short supplier lead time can produce Pareto optimal outcomes even in the absence of other optimal policies. This study produces concrete, actionable guidelines to cost-effectively reduce stock-outs by implementing optimal supply chain policies. Preferentially selecting drug suppliers with short lead times accommodates unexpected changes in demand. Optimal supply chain management should be an essential component of national policy to reduce the mortality rate.

Cep70 drives taxol drug resistance through regulating the acetylation α-tubulin to reduce microtubule stability

Objective To explore the Cep70 by adjusting the stability of acetylated alpha tubulin, participate in breast cancer drug resistance mechanisms. Methods ⑴ In order to induce taxol drug resistance cell line Michigan cancer foundation-7 (MCF-7)/pac, high-dose shock treatments taxol MCF-7 was used for 6 months, until the cells can grow in 3.5 μmol/L of paclitaxel. ⑵ The 3-(4, 5-dimenthylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) method was used to detect inhibition rate by taxol to MCF-7 and MCF-7/pac cell. ⑶ Immunofluorescence and Western blot were used to test acetylated alpha-tubulin and Cep70 expression levels in MCF-7 and MCF-7/pac cells. ⑷ Chemical intervention was used to acetylate apha-tubulin expression, Western blot and polymerase chain reaction (PCR) were used to detect the change of acetylated alpha-tubulin and Cep70 in MCF-7 and MCF-7/pac groups. Flow cytometry and Western blot were used to detect the change of cell cycle. Results ⑴ IC50 of MCF-7 and MCF-7/pac was 22.47 μmol/L and 31.38 μmol/L, respectively. ⑵ Immunofluorescence and Western blot results showed that the expression of acetylation of alpha-tubulin in resistant MCF-7 cell/pac was obviously decreased. ⑶ Real time polymerase chain reaction (RT-PCR) and Western blot showed Cep70 expression was consistent of acetylation of alpha-tubulin. ⑷ After incubation with paclitaxel for 24 hours, the expressions of acetylation of alpha-tubulin and Cep70 in MCF-7 and MCF-7/pac were increased, but the extent of MCF-7 cell was much higher. Instead, incubation with nocodazole after 24 hours, the acetylation of alpha-tubulin and Cep70 in MCF-7 and MCF-7/pac cells were obviously lowered. ⑸ After paclitaxel intervention, compared to the same group MCF-7 cells, the G2 phase ratio in MCF-7/pac cells was lower. In addition, given nocodazole after the intervention, compared to the same group MCF-7 cells, the ratio of G2 phase in MCF-7 cell/pac was significantly decreased. Conclusions Cep70 decreased the expression of the acetylated alpha-tubulin, reduced the stability of microtubules, which could be an important mechanism of taxol drug resistance. Key words: Centrosome; Tubulin; Breast neoplasms/DT/ME; Taxoids; Drug resistance, neoplasm

Mutation L1196M-induced conformational changes and the drug resistant mechanism of anaplastic lymphoma kinase studied by free energy perturbation and umbrella sampling.

Anaplastic lymphoma kinase (ALK) has been regarded as a promising drug target in the treatment of tumors and the mutation L1196M induces different levels of drug resistance toward the existing inhibitors. Free energy perturbation (FEP) coupled with umbrella sampling simulation is used to investigate the conformational change of ALK induced by L1196M and drug-resistant mechanisms of L1196M on four inhibitors VGH, 3U9, 5P8 and IV7. Dynamics analysis shows that L119M produces significant influences on the flexibility of the loops L1 and L2 in ALK. FEP calculations suggest that the drug-resistant intensity of L1196M toward inhibitors decreases in the order 3U9 > VGH > 5P8 > IV7, in accordance with the experimentally determined results. Moreover, statistical analysis of hydrophobic contacts of inhibitors with separate residues in ALK further demonstrates that the decrease in the hydrophobic interactions of inhibitors with L1256 mostly drives drug resistance of L1196M toward inhibitors. The calculations of potential of mean force (PMF) based on umbrella sampling simulations indicate that the free energies of inhibitor-L1196M ALKs are lower than those of inhibitor-wild ALKs. This study is expected to provide significant theoretical support which would help in the design of potent inhibitors alleviating the drug resistance of L1196M in ALK.

Medicine Quality: the harder you look the worse it gets

<p><span style="font-family: Calibri; font-size: medium;">The Minilab protocol is an excellent method of identifying falsified medicines, and two per cent (18 out of 899 samples) were falsified. However, as the data in this paper show, it considerably underestimates (by roughly 4.5%) the amount of substandard medicines in the market (roughly 12 per cent), especially among medicines made by Indian companies. In addition to considerable patient death, substandard antimicrobial medicines are likely to drive drug resistance. Policymakers should redouble efforts to identify and combat such medicines.</span></p>

Measurement of Phosphorylated ERK As a Prognostic and Predictive Marker for MEK Inhibition in Pediatric B-Lymphoblastic Leukemia: A Pilot Study

Abstract Background: Outcomes for patients with relapsed B- acute lymphoblastic leukemia (B-ALL) remain suboptimal. We and others have identified the Mitogen activated protein kinase/ Extracellular signal regulated kinase (MAPK/ERK) pathway as a primary driver of drug resistance in pediatric B-ALL. Constitutive activation of ERK has been found to be an independent predictor of complete response and is associated with other poor prognostic factors in adults with B-ALL. Mutations that affect activation of the Ras/Raf/MEK/ERK pathway have been found in up to 40% of children with newly diagnosed and relapsed ALL and these mutations correlate with early relapse and poor overall survival. However, we have demonstrated MAPK activation in the absence of Ras pathway mutations, suggesting alternative mechanisms of activation. Hypothesis: We hypothesize that activation of the MAPK pathway drives drug resistance in pediatric B-ALL. Activation of this pathway at diagnosis may portend a high likelihood of relapse and inhibition of the MAPK pathway may restore chemosensitivity to conventional agents. Methods: For our initial pilot study, a total of 24 patient samples from initial diagnosis obtained from Children's Oncology Group cell bank and from NYU, were thawed and placed either in serum-free media or media containing Trametinib (MEK1/2 inhibitor) at 1µM for 4 hours. Samples were then stimulated with Phorbol 12-myristate 13-acetate (PMA), a specific activator of Protein Kinase C, which activates MEK via Ras. Samples were then fixed with 4% paraformaldehyde, permeabilized with 95% methanol, and stained for Caspase 3, CD10, phosphorylated ERK (p-ERK), and p-AKT. All samples were simultaneously processed on the BD LSRII HTS and analyzed on FlowJo software (Treestar, V.10). Viable leukemic blasts were identified as CD10 positive and Caspase 3 negative cells, which were gated on for further analysis. Median fluorescence intensity (MFI) for phosphorylated proteins was measured, expressed as a ratio to isotype controls and compared between samples. MAPK activation was defined by maximal p-ERK levels upon stimulation with PMA. Inhibition was quantified as percentage decrease in maximal p-ERK levels (upon PMA stimulation) after treatment with Trametinib. Targeted Sanger sequencing of commonly mutated exons of Ras pathway genes (NRAS, KRAS, FLT3 and PTPN11) was performed on 14 samples based on availability of DNA. Results: Of our 24 samples, 4 samples were excluded from analysis due to poor viability (<40% live cells), giving an assay success rate of 83.3%. We were able to successfully measure p-ERK in all 20 viable patient samples and also measure levels of baseline p-AKT in 16 samples. A wide range of p-ERK levels and MAPK activation was observed within patient samples (median activation ratio 12.3, range 4.4-44.7) and 7 samples showed markedly higher levels of activation with ratios between 21.9 - 44.78. Levels of inhibition by Trametinib ranged from 0-82.2%, with a median of 43%. Greater degree of MAPK activation was found to correlate strongly with higher levels of inhibition by Trametinib (overall correlation coefficient 0.72). In 2 samples, the levels of inhibition by Trametinib seemed lower than anticipated for levels of MAPK activation, but both of these samples showed higher than average levels of p-AKT (p-AKT to isotype ratio of 12.3-12.9, median of 2.4 in rest of the samples), suggesting a possible alternative mechanism of activation via the PI3K/AKT signaling pathway. DNA was obtained for Sanger sequencing in 14 of the 20 viable patient samples. Three of the 14 samples had point mutations in Ras pathway genes of which two had mutations in exon 2 of NRAS while one had a mutation in exon 14 of FLT3. Two of the seven patient samples with the highest MAPK activation had Ras mutations, which is consistent with our prior data showing that additional mechanisms of pathway activation are operative. Conclusion: We have successfully established a phospho-flow protocol that enables the measurement of MAPK activation in real time in patient samples. Based on our pilot data, we also conclude that MAPK activation in itself serves as a better predictive marker for susceptibility to MAPK inhibition, as opposed to Ras pathway mutation status alone. Ongoing investigation will allow correlation with outcome and the assay could serve in the future to identify those patients who might benefit from MEK inhibition or other nodes in the pathway. Disclosures Loh: Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding.

Stochasticity in the Genotype-Phenotype Map: Implications for the Robustness and Persistence of Bet-Hedging.

Nongenetic variation in phenotypes, or bet-hedging, has been observed as a driver of drug resistance in both bacterial infections and cancers. Here, we study how bet-hedging emerges in genotype–phenotype (GP) mapping through a simple interaction model: a molecular switch. We use simple chemical reaction networks to implement stochastic switches that map gene products to phenotypes, and investigate the impact of structurally distinct mappings on the evolution of phenotypic heterogeneity. Bet-hedging naturally emerges within this model, and is robust to evolutionary loss through mutations to both the expression of individual genes, and to the network itself. This robustness explains an apparent paradox of bet-hedging—why does it persist in environments where natural selection necessarily acts to remove it? The structure of the underlying molecular mechanism, itself subject to selection, can slow the evolutionary loss of bet-hedging to ensure a survival mechanism against environmental catastrophes even when they are rare. Critically, these properties, taken together, have profound implications for the use of treatment-holidays to combat bet-hedging-driven resistant disease, as the efficacy of breaks from treatment will ultimately be determined by the structure of the GP mapping.

Melatonin Represses Metastasis in Her2-Postive Human Breast Cancer Cells by Suppressing RSK2 Expression.

Melatonin inhibition of Rsk2 represses the metastatic phenotype in breast cancer cells suppressing EMT or inhibiting other mechanisms that promote metastasis; disruption of the melatonin signal may promote metastatic progression in breast cancer. Mol Cancer Res; 14(11); 1159-69. ©2016 AACR.

Antibiotic Use in Small Community Hospitals

Antibiotic use and misuse is driving drug resistance. Much of US healthcare takes place in small community hospitals (SCHs); 70% of all US hospitals have <200 beds. Antibiotic use in SCHs is poorly described. We evaluated antibiotic use using data from the National Healthcare and Safety Network antimicrobial use option from the Centers for Disease Control and Prevention. We used Intermountain Healthcare's monthly antibiotic use reports for 19 hospitals from 2011 to 2013. Hospital care units were categorized as intensive care, medical/surgical, pediatric, or miscellaneous. Antibiotics were categorized based on spectrum of coverage. Antibiotic use rates, expressed as days of therapy per 1000 patient-days (DOT/1000PD), were calculated for each SCH and compared with rates in large community hospitals (LCHs). Negative-binomial regression was used to relate antibiotic use to predictor variables. Total antibiotic use rates varied widely across the 15 SCHs (median, 436 DOT/1000PD; range, 134-671 DOT/1000PD) and were similar to rates in 4 LCHs (509 DOT/1000PD; 406-597 DOT/1000PD). The proportion of patient-days spent in the respective unit types varied substantially within SCHs and had a large impact on facility-level rates. Broad-spectrum antibiotics accounted for 26% of use in SCHs (range, 8%-36%), similar to the proportion in LCHs (32%; range, 26%-37%). Case mix index, proportion of patient-days in specific unit types, and season were significant predictors of antibiotic use. There is substantial variation in patterns of antibiotic use among SCHs. Overall usage in SCHs is similar to usage in LCHs. Small hospitals need to become a focus of stewardship efforts.

Abstract 4383: SOCRATES: integrating ex vivo and in silico analysis to identify optimal drug combinations for patients

Abstract Recent work on cancer heterogeneity and evolution has greatly enhanced our understanding of drivers of drug resistance, but this has also highlighted the need to move away from generic, “one-size-fits-all” treatment regimes. It is clear that we should tailor therapy to individual patients at different stages of disease based on the current behaviour of their tumour cells, yet detailed experimental characterisation and analysis of patient tissue is impractical and costly. Predictive computational models that can produce patient-specific recommendations of drug combinations would therefore be of great value to the field of personalised medicine. In silico modelling has already been used to successfully predict synergistic drug combinations in single cell lines in the lab, but such approaches have not yet been translated to dynamic, real patient data in the clinic. The SOCRATES project (Signalling output to rationalise combinations of targeted anticancer therapies) integrates experimental data and computational analysis to predict context-specific synergistic drug combinations. Here we present ambitious computational modelling of dynamic signalling network changes in response to ex vivo exposure of seven targeted drugs used singly at clinically appropriate concentrations. We also apply our adaptive modelling to genomics and proteomics data from 54 proteins in over 30 non small-cell lung cancer cell lines and ten patient samples to predict and experimentally validate personalised, context specific drug combinations. We will describe our adaptive, in silico modelling for predicting response to drug combinations, including novel methods utilizing network topology. We have predicted over 50 synergistic drug combinations and will present our predictions alongside initial results of experimental validation in the lab. We will also illustrate the differences observed in various cell lines and patient derived cells depending on genetic context. SOCRATES is, to our knowledge, the first project of its kind and is a prototype for the future of adaptive, individualised cancer treatment. Citation Format: Elizabeth A. Coker, Adam Stewart, Anna Minchom, Mary O’Brien, Timothy Yap, Paul Workman, Udai Banerji, Bissan Al-Lazikani. SOCRATES: integrating ex vivo and in silico analysis to identify optimal drug combinations for patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4383.

Vascular endothelial growth factor A as predictive marker for mTOR inhibition in relapsing high-grade serous ovarian cancer.

BackgroundDevelopment of resistance against first line drug therapy including cisplatin and paclitaxel in high-grade serous ovarian cancer (HGSOC) presents a major challenge. Identifying drug candidates breaking resistance, ideally combined with predictive biomarkers allowing precision use are needed for prolonging progression free survival of ovarian cancer patients.Modeling of molecular processes driving drug resistance in tumor tissue further combined with mechanism of action of drugs provides a strategy for identification of candidate drugs and associated predictive biomarkers.ResultsConsolidation of transcriptomics profiles and biomedical literature mining results provides 1242 proteins linked with ovarian cancer drug resistance. Integrating this set on a protein interaction network followed by graph segmentation results in a molecular process model representation of drug resistant HGSOC embedding 409 proteins in 24 molecular processes. Utilizing independent transcriptomics profiles with follow-up data on progression free survival allows deriving molecular biomarker-based classifiers for predicting recurrence under first line therapy. Biomarkers of specific relevance are identified in a molecular process encapsulating TGF-beta, mTOR, Jak-STAT and Neurotrophin signaling. Mechanism of action molecular model representations of cisplatin and paclitaxel embed the very same signaling components, and specifically proteins afflicted with the activation status of the mTOR pathway become evident, including VEGFA. Analyzing mechanism of action interference of the mTOR inhibitor sirolimus shows specific impact on the drug resistance signature imposed by cisplatin and paclitaxel, further holding evidence for a synthetic lethal interaction to paclitaxel mechanism of action involving cyclin D1.ConclusionsStratifying drug resistant high grade serous ovarian cancer via VEGFA, and specifically treating with mTOR inhibitors in case of activation of the pathway may allow adding precision for overcoming resistance to first line therapy.

Hedgehog pathway maintains cell survival under stress conditions, and drives drug resistance in lung adenocarcinoma

Hedgehog (HH) pathway plays an important role in embryonic development, but is largely inactive in adult except for tissue repair. Aberrant activation of HH pathway has been found in a variety of cancer types. In non-small cell lung cancer, however, the role and importance of HH pathway remain controversial. In the current study, we found that HH pathway was maintained in low activity in lung adenocarcinoma (LAC) cells under normal culture condition, but was highly induced in response to stress conditions. Activation of HH pathway promoted cell survival, growth, and invasion partially through HGF and MET signaling. Hedgehog-Interacting Protein (HHIP), a cell-surface negative regulator of HH pathway, was epigenetically silenced in LAC. Overexpression of HHIP blocked the activation of HH and HGF/MET pathways, and made cells significantly more susceptible to stress conditions. In LAC cells with acquired resistance to Epidermal Growth Factor Receptor Tyrosin Kinase Inhibitor (EGFR-TKI), we found that a part of tumor cells were much more sensitive to HH or HGF/MET inhibitors, suggesting an oncogenic addiction shift from EGFR to HH and HGF/MET pathways. In conclusion, this study showed that HH pathway is a survival signaling that drives LAC cell growth under stress conditions, and HHIP is a key regulator to block the induction of HH pathway. Targeting the HH pathway through inhibitors or HHIP thus holds promise to address EGFR-TKI resistance in LAC in clinic.

The Novel VEGF121-VEGF165 Fusion Attenuates Angiogenesis and Drug Resistance via Targeting VEGFR2-HIF-1α-VEGF165/Lon Signaling Through PI3K-AKT-mTOR Pathway.

Anti-angiogenesis therapy is one major approach of cancer therapies nowadays. Unfortunately, anti-angiogenesis therapy targeting VEGF-A was recently stumbled by the drugresistance that results from adaptive mechanisms, such as intratumor hypoxia. To obtain a more efficient therapeutic response, we created and identified a novel chimeric fusion of VEGF121 and VEGF165, which was connected by Fc region of human IgG1 to enhance dimerization. We found that the treatment of VEGF121-VEGF165 chimeric protein reduces proliferation, migration, invasion, and tube formation in endothelial and/or cancer cells through competing VEGF165 homodimer in a paracrine and an autocrine manner. Furthermore, the fusion protein attenuated autocrine VEGFR2-HIF-1α-VEGF165/Lon signaling through PI3KAKT- mTOR pathway in cancer cells. In conclusion, our data demonstrated that the chimeric VEGF121-VEGF165 arrests the tube formation of endothelial cells and interferes with tumor cell growth, migration and invasion, suggesting that it could be a potential drug as an angiogenesis antagonist in cancer therapy. The VEGF121-VEGF165 targets not only paracrine angiogenic cascade of endothelial cells but also autocrine PI3K-AKT-mTOR-mediated VEGFR2-HIF-1α- VEGF165/Lon signaling that drives drug resistance in tumor cells. Our study will open up the patient opportunities to combat drug resistance to antiangiogenic therapy.

Abstract A31: High-grade serous ovarian cancer subtyping identifies pathways for targeted therapy.

Abstract Introduction: We recently identified three prognostic groups for high-grade serous ovarian cancers (HGS-OvCa) patients treated with platinum and taxane using transcriptomics and clinical data (Chen, Huhtinen, et al. Cancer Res. 2015). In this contribution we first use pathway analysis methods to identify transcript markers and pathways that drive resistance to platinum and experimentally inhibit of the key pathways to restore sensitivity to platinum. Two of the prognostic groups (Poor I and Poor II) were associated with poor survival but have distinct expression profiles. Poor II express high stromal response genes and confirms the C1 subtype characterized by Tothill et al. (2008), whereas Poor I is previously unidentified and characterized by genome-wide hypermethylation. Our objectives here are to: 1) identify key pathways for Poor I and Poor II based on transcriptomics data (data unpublished), 2) inhibit the herein identified pathways to suggest combinatorial therapeutics options for platinum resistance HGS-OvCa patients (data unpublished), 3) test the impact of hypermethylation drug Decitabine to platinum resistance in vitro (data partially unpublished). Methods: Expression levels were qRT-PCR validated using well described prospective patient cohort. The role of hypermethylation and specific pathways on cell viability were studied in vitro using commercial (CAOV4, NIHOVCAR3, OVCAR8, TYKnu) and spheroidal primary HGS-OvCa cell lines. Results: Poor I subtype presents with significantly higher methylation of CpG loci (p &amp;lt; 0.001) as compared with Good or Poor II subtypes. We observed significant up-regulation of three isoforms of DNA methyltransferase 3B (DNMT3B) in Poor I samples. The role of hypermethylation was further validated in vitro using patient derived cell lines with platinum resistance. Inhibition of methylation by Decitabine exhibited strong effect on cell viability specifically on Poor I characteristic HGS-OvCa cell lines. The data suggests that clinical trials testing the effect of Decitabine should be focused to patients with Poor I disease. To evaluate signaling pathways that are associated with platinum-taxane resistance we evaluated common pathways enriched in Poor I and Poor II using the transcriptomics data available at The Cancer Genome Atlas repository. The most prominent pathway is MAPK signaling pathway of which four genes (FAS, MAPK1, AKT and NR4A1) emerged from the analysis. Pathway analysis further suggested ERK5 and AKT as upstream regulators for NR4A1 in platinum-taxane resistance in HGS-OvCa. The impact of ERK5 and AKT pathways on platinum resistance was evaluated in vitro using commercial and primary HGS-OvCa cell lines with wild-type BRCA1/2. The combination of AKT-inhibitor API-2 and Cisplatin resulted in a marked decrease in cell viability over Cisplatin alone whereas AKT-inhibitor alone had only little effect. In contrast, ERK5 inhibition with XMD8-92 combined with Cisplatin did not have an effect on HGS-OvCa cell viability. However, XMD8-92 enhanced the effect of API-2 in subset of the cell lines. Thus, we tested whether combination of the three drugs results in better response. In general, the addition of XMD8-92 did not improve the effect of API-2 and Cisplatin. However, in two highly platinum resistant cell lines, CAOV-4 and M022i primary cell line, the combination of API-2, XMD8-92 and Cisplatin produced the highest reduction in cell viability. In conclusion, we have identified pathways that are likely driving drug resistance in HGS-OvCa and tested the impact of platinum combined with targeted AKT and ERK5 inhibition in vitro. We further show that the Poor I type HGS-OvCa cells are sensitive to Decitabine. Thus, Decitabine may be an effective (combinatorial) treatment option for patients with the Poor I subtype disease. Combination of AKT and ERK5 inhibitors with platinum can also be effective for a subset of platinum resistant ovarian cancer patients. Citation Format: Kaisa Huhtinen, Ping Chen, Katja Kaipio, Piia Mikkonen, Viljami Aittomäki, Rony Lindell, Johanna Hynninen, Annika Auranen, Seija Grenman, Rainer Lehtonen, Sampsa Hautaniemi, Olli Carpén. High-grade serous ovarian cancer subtyping identifies pathways for targeted therapy. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr A31.

Abstract IA12: Determinants of resistance and response in high-grade serous ovarian cancer.

Abstract In contrast to other solid cancers, overall survival for patients with high-grade serous ovarian cancer (HGSC) is little changed over the last 30 years and it has been difficult to advance beyond platinum-based combination chemotherapy. As HGSC are driven by genomic copy number change rather than recurrent point mutation, we undertook whole genome sequence (WGS) analysis of a large HGSC cohort in order to survey structural variation at high resolution. Utilizing 114 tumors from 92 patients, we performed transcriptome, methylation, and miRNA expression analyses to support the WGS data, and compared resistant, refractory, and sensitive primary disease. We evaluated tumor and normal DNA samples from patients with primary refractory, primary resistant or primary sensitive disease to better understand the drivers of these clinical phenotypes. We also characterized paired pre-treatment chemosensitive and post-resistance samples, and end-stage HGSC obtained from patients who underwent a research autopsy. We found that gene breakage involving tumor suppressors such as NF1 and RB1 is a common form of inactivation in HGSC and in other circumstances contributes to acquired chemotherapy resistance in some patients. We found evidence of a chemotherapy footprint in the genome of recurrent tumor samples. We observed a striking degree of diversity of other mechanisms of acquired resistance, including multiple independent germline BRCA1 or BRCA2 reversion events in individual patients, loss of BRCA1 promoter methylation, a shift in molecular subtype to a desmoplastic phenotype, and a recurrent promoter fusion associated with overexpression of a driver of drug resistance, validated in an independent dataset. Collectively these findings underscore the plasticity of the HGSC genome and indicate that pre-empting resistance by modifying current first line therapy or countering it when it emerges will require a diversity of approaches. Citation Format: David D. L. Bowtell. Determinants of resistance and response in high-grade serous ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr IA12.