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SP024 Prediction of the efficacy of mTOR targeted therapies
Speakers’ Presentations proteins can be generated, autocrine stimulation can occur, and novel nuclear signalling pathways can be adopted. FGFR signalling has been implicated in a number of different cancer types. Genome wide association studies have identified key SNPs in FGFR2 that associate significantly with risk of developing ER positive breast cancer and, similarly, FGFR1 over-expression has been associated with poor prognosis in ER positive breast cancer. Activating mutations have been reported in several cancer types and, recently, we have identified a role for nuclear FGFRs in regulating cancer cell behaviour. I will discuss the current status of FGFs and FGFRs as markers in cancer and the mechanisms by which they are being targeted therapeutically.
SP024 Prediction of the efficacy of mTOR targeted therapies T. Alain. McGill Cancer Centre, Montréal, Québec, Canada mRNA translation is dysregulated in cancer. This is caused by altered expression of translation factors and the hyperactivated oncogenic pathways that promote protein synthesis (e.g. the mammalian target of rapamycin (mTOR)). Consequently, the loss of translational control results in increased expression of proteins with proliferative, survival, and angiogenic functions. Active-site mTOR inhibitors (asTORi) hold great promise for targeting dysregulated mTOR signaling in cancer. However, because of the multifaceted nature of mTORC1 signaling, identification of reliable biomarkers for the sensitivity of tumors to asTORi is imperative for their clinical implementation. We found that cancer cells acquire resistance to asTORi by downregulating eukaryotic translation initiation factor (eIF4E)-binding proteins (4E-BPs). Loss of 4E-BPs or overexpression of eIF4E renders neoplastic growth and translation of tumor-promoting mRNAs refractory to mTOR inhibition. Conversely, moderate depletion of eIF4E augments the anti-neoplastic effects of asTORi. The anti-proliferative effect of these inhibitors in vitro and in vivo is therefore significantly influenced by perturbations in eIF4E/4E-BP stoichiometry, whereby an increase in the eIF4E/4E-BP ratio dramatically limits the sensitivity of cancer cells to asTORi. We propose that the eIF4E/4E-BP ratio, rather than their individual protein levels or solely their phosphorylation status, should be considered as a paramount predictive marker for forecasting the clinical therapeutic response to mTOR inhibitors.
SP025 Genotype-based combinations of RAS/RAF and PI3K pathway inhibitors U. Banerji. Division of Cancer Therapeutics & Division of Clinical Studies, Institute of Cancer Research & The Royal Marsden, Sutton, United Kingdom Background: There are currently multiple inhibitors targeting the RAS/RAF and PI3K pathways (BRAF, MEK PI3K, AKT and m-TOR inhibitors) in development. Each class of drugs have shown clinical activity in single agent studies and are active in relatively small, defined subsets of tumours which harbour specific mutations. It is hypothesized that combinatorial inhibition of both signalling networks could broaden range of tumours where these drugs could be used in. Our aims included; a) To define tumours which were most likely to respond to the combination compared to each single agent alone b) To define the degree of target inhibition needed to achieve maximal growth inhibition (as it may not be possible to clinically deliver full doses of both drugs in a combination due to overlapping toxicity). Materials and Methods: We used two tool compounds (MEK inhibitor PD0325901 and AKT inhibitor AKT1/2 inhibitor) in an attempt to answer these questions. We exposed a panel of cell lines (4 BRAF mutant, 5 PIK3CA mutant 3 KRAS mutant and 5 cell lines with no mutation in BRAF, PIK3CA or KRAS) to the MEK and AKT inhibitor separately for 24 hours. We then calculated the concentration of the MEK inhibitor required to reduce the phosphorylation of ERK by 25, 50, 75 and 100% of and the concentration of the AKT inhibitor required to reduce phosphorylation of S6 by 25, 50, 75 and 100%. We then exposed the panel of cell lines to various concentrations of the combinations of the MEK and AKT inhibitors known to inhibit pre-defined degrees of signalling output for 96 hours and studied growth inhibition using sulforhodamine assays. Results: In 4/4 BRAF mutant cells, there was significantly more growth inhibition caused by maximal inhibition of MEK as compared to maximal inhibition of AKT and in 5/5 PIK3CA mutant cells, there was significantly more growth inhibition caused by maximal inhibition of AKT as compared to maximal inhibition of MEK. Interestingly, in 4/5 cell lines with no BRAF,
S7 PIK3CA or KRAS mutations, cells were significantly more susceptible to AKT inhibition compare to MEK inhibition and 1/5 of these cell lines were equally susceptible to AKT and MEK inhibition. Further 1/3 cell lines with KRAS mutations were more sensitive to MEK inhibition, 1/3 more susceptible to AKT Inhibition and 1/3 were equally sensitive to maximal MEK or AKT Inhibition. Further experiments are being conducted to expand the cell line panel to 20 and study the inhibition of different combinations of MEK and AKT inhibitors known to inhibit MEK and AKT by different degrees. This will help to define the cells most likely to respond to the combination and further define the degree of target inhibition needed while designing these combinations. Conclusion: Combinations of MEK and AKT inhibitors are likely to be more effective than single agents only in defined subsets of cancers and this information is crucial to the design of clinical trials evaluating the efficacy of these combinations.
Topic 8: Genomics driven approaches SP026 Genomic wide biomarker discovery in personalized patient derived xenografts M. Hidalgo. Centro Integtral Oncologico Clara Campal, Madrid, Spain Pancreatic cancer (PDAC) remains one of the most deadly cancers. Over the last few years, the genomic landscape of pancreatic cancer as well as precursor pancreatic cancer lesions have been deciphered in great depth. These studies show that PDAC develops as the consequence of accumulation of mutations in key oncogenes and tumour suppressor genes. The disease, once established, is characterized by high complexity, heterogeneity and genomic instability. Despite this facts, some patients harbour actionable mutations which targeting has resulted in significant clinical benefit. Indeed, one of the most active areas of research in PDAC is the development of strategies and approaches to personalize the treatment of patients. This is a complex field that can be tackle from many complementary angles. Our group has been interested in using patient derive xenogaft (PDX) models, aka Avatar mouse models, to guide cancer treatment. A piece of freshly collected tumour is implanted in immunodeficient mouse models, expanded, treated with different anticancer agents alone and in combination to select the most effective drug/regimen to treat the patient cancer. Our data show that the approach is highly predicted but, because of complexity and cost issues, not widely applicable to clinical practice at the present stage. To solve some of these limitations we are working on different aspects. One area is technological development to increase the take rate of tumours and to speed time to engraftment and expansion time. Currently, these figures are approximately 60–80% and 5–7 months. Studies are in progress to optimize this aspect. Another key question is the selection of agents, both alone and in combination, to be tested in the model. In this regard, it is important to integrate biomarker assessment in the tumour to pre-select a series of treatment candidates that can then be tested in the PDX models. To this end, we have now integrated next generation sequencing and assessment of copy number variation in patient’s tumour. These studies provide us with an unbiased overview of the tumour genomic landscape. From this data, using different bioinformatics and biological methods we extract the most relevant drug targets that are then bench tested against the patient Avatar mouse model to select the most effective treatment.
SP027 RAS mutations as markers of resistance for colorectal cancer patients treated with the anti-EGFR monoclonal antibody panitumumab K. Oliner. Medical Sciences – In Vitro Diagnostics, Amgen Inc., Thousand Oaks, USA Panitumumab (pmab) is an anti-EGFR antibody that is now indicated in the EU for the treatment of adult patients with WT RAS (KRAS and NRAS) metastatic colorectal cancer. Data will be presented from analyses of tumor RAS mutations from three randomized pmab studies. The hypothesis generating study was a multigene analysis of the phase 3 monotherapy study of Pmab vs. best supportive care. Final RAS result ascertainment of this study employing a combination of next-generation sequencing, Sanger sequencing and WAVE-based SURVEYOR® analysis was 75%. This study suggested that RAS mutations beyond the most commonly tested KRAS codons 12 & 13 might be predictive of lack of response to Pmab therapy (Peeters, 2013 and Patterson, 2013). This led to two prespecified analyses of the RAS
SP024 Prediction of the efficacy of mTOR targeted therapies T. Alain. McGill Cancer Centre, Montréal, Québec, Canada mRNA translation is dysregulated in cancer. This is caused by altered expression of translation factors and the hyperactivated oncogenic pathways that promote protein synthesis (e.g. the mammalian target of rapamycin (mTOR)). Consequently, the loss of translational control results in increased expression of proteins with proliferative, survival, and angiogenic functions. Active-site mTOR inhibitors (asTORi) hold great promise for targeting dysregulated mTOR signaling in cancer. However, because of the multifaceted nature of mTORC1 signaling, identification of reliable biomarkers for the sensitivity of tumors to asTORi is imperative for their clinical implementation. We found that cancer cells acquire resistance to asTORi by downregulating eukaryotic translation initiation factor (eIF4E)-binding proteins (4E-BPs). Loss of 4E-BPs or overexpression of eIF4E renders neoplastic growth and translation of tumor-promoting mRNAs refractory to mTOR inhibition. Conversely, moderate depletion of eIF4E augments the anti-neoplastic effects of asTORi. The anti-proliferative effect of these inhibitors in vitro and in vivo is therefore significantly influenced by perturbations in eIF4E/4E-BP stoichiometry, whereby an increase in the eIF4E/4E-BP ratio dramatically limits the sensitivity of cancer cells to asTORi. We propose that the eIF4E/4E-BP ratio, rather than their individual protein levels or solely their phosphorylation status, should be considered as a paramount predictive marker for forecasting the clinical therapeutic response to mTOR inhibitors.
SP025 Genotype-based combinations of RAS/RAF and PI3K pathway inhibitors U. Banerji. Division of Cancer Therapeutics & Division of Clinical Studies, Institute of Cancer Research & The Royal Marsden, Sutton, United Kingdom Background: There are currently multiple inhibitors targeting the RAS/RAF and PI3K pathways (BRAF, MEK PI3K, AKT and m-TOR inhibitors) in development. Each class of drugs have shown clinical activity in single agent studies and are active in relatively small, defined subsets of tumours which harbour specific mutations. It is hypothesized that combinatorial inhibition of both signalling networks could broaden range of tumours where these drugs could be used in. Our aims included; a) To define tumours which were most likely to respond to the combination compared to each single agent alone b) To define the degree of target inhibition needed to achieve maximal growth inhibition (as it may not be possible to clinically deliver full doses of both drugs in a combination due to overlapping toxicity). Materials and Methods: We used two tool compounds (MEK inhibitor PD0325901 and AKT inhibitor AKT1/2 inhibitor) in an attempt to answer these questions. We exposed a panel of cell lines (4 BRAF mutant, 5 PIK3CA mutant 3 KRAS mutant and 5 cell lines with no mutation in BRAF, PIK3CA or KRAS) to the MEK and AKT inhibitor separately for 24 hours. We then calculated the concentration of the MEK inhibitor required to reduce the phosphorylation of ERK by 25, 50, 75 and 100% of and the concentration of the AKT inhibitor required to reduce phosphorylation of S6 by 25, 50, 75 and 100%. We then exposed the panel of cell lines to various concentrations of the combinations of the MEK and AKT inhibitors known to inhibit pre-defined degrees of signalling output for 96 hours and studied growth inhibition using sulforhodamine assays. Results: In 4/4 BRAF mutant cells, there was significantly more growth inhibition caused by maximal inhibition of MEK as compared to maximal inhibition of AKT and in 5/5 PIK3CA mutant cells, there was significantly more growth inhibition caused by maximal inhibition of AKT as compared to maximal inhibition of MEK. Interestingly, in 4/5 cell lines with no BRAF,
S7 PIK3CA or KRAS mutations, cells were significantly more susceptible to AKT inhibition compare to MEK inhibition and 1/5 of these cell lines were equally susceptible to AKT and MEK inhibition. Further 1/3 cell lines with KRAS mutations were more sensitive to MEK inhibition, 1/3 more susceptible to AKT Inhibition and 1/3 were equally sensitive to maximal MEK or AKT Inhibition. Further experiments are being conducted to expand the cell line panel to 20 and study the inhibition of different combinations of MEK and AKT inhibitors known to inhibit MEK and AKT by different degrees. This will help to define the cells most likely to respond to the combination and further define the degree of target inhibition needed while designing these combinations. Conclusion: Combinations of MEK and AKT inhibitors are likely to be more effective than single agents only in defined subsets of cancers and this information is crucial to the design of clinical trials evaluating the efficacy of these combinations.
Topic 8: Genomics driven approaches SP026 Genomic wide biomarker discovery in personalized patient derived xenografts M. Hidalgo. Centro Integtral Oncologico Clara Campal, Madrid, Spain Pancreatic cancer (PDAC) remains one of the most deadly cancers. Over the last few years, the genomic landscape of pancreatic cancer as well as precursor pancreatic cancer lesions have been deciphered in great depth. These studies show that PDAC develops as the consequence of accumulation of mutations in key oncogenes and tumour suppressor genes. The disease, once established, is characterized by high complexity, heterogeneity and genomic instability. Despite this facts, some patients harbour actionable mutations which targeting has resulted in significant clinical benefit. Indeed, one of the most active areas of research in PDAC is the development of strategies and approaches to personalize the treatment of patients. This is a complex field that can be tackle from many complementary angles. Our group has been interested in using patient derive xenogaft (PDX) models, aka Avatar mouse models, to guide cancer treatment. A piece of freshly collected tumour is implanted in immunodeficient mouse models, expanded, treated with different anticancer agents alone and in combination to select the most effective drug/regimen to treat the patient cancer. Our data show that the approach is highly predicted but, because of complexity and cost issues, not widely applicable to clinical practice at the present stage. To solve some of these limitations we are working on different aspects. One area is technological development to increase the take rate of tumours and to speed time to engraftment and expansion time. Currently, these figures are approximately 60–80% and 5–7 months. Studies are in progress to optimize this aspect. Another key question is the selection of agents, both alone and in combination, to be tested in the model. In this regard, it is important to integrate biomarker assessment in the tumour to pre-select a series of treatment candidates that can then be tested in the PDX models. To this end, we have now integrated next generation sequencing and assessment of copy number variation in patient’s tumour. These studies provide us with an unbiased overview of the tumour genomic landscape. From this data, using different bioinformatics and biological methods we extract the most relevant drug targets that are then bench tested against the patient Avatar mouse model to select the most effective treatment.
SP027 RAS mutations as markers of resistance for colorectal cancer patients treated with the anti-EGFR monoclonal antibody panitumumab K. Oliner. Medical Sciences – In Vitro Diagnostics, Amgen Inc., Thousand Oaks, USA Panitumumab (pmab) is an anti-EGFR antibody that is now indicated in the EU for the treatment of adult patients with WT RAS (KRAS and NRAS) metastatic colorectal cancer. Data will be presented from analyses of tumor RAS mutations from three randomized pmab studies. The hypothesis generating study was a multigene analysis of the phase 3 monotherapy study of Pmab vs. best supportive care. Final RAS result ascertainment of this study employing a combination of next-generation sequencing, Sanger sequencing and WAVE-based SURVEYOR® analysis was 75%. This study suggested that RAS mutations beyond the most commonly tested KRAS codons 12 & 13 might be predictive of lack of response to Pmab therapy (Peeters, 2013 and Patterson, 2013). This led to two prespecified analyses of the RAS