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86 Molecular Diagnostics in Breast Cancer – Getting Beyond ER, PR, HER2 and Proliferation
FEBS Molecular Oncology Supported Symposium
was possible to combine it with standard treatments such as chemotherapy. The answer, now, is past history. The combined use of immunotherapy and chemotherapy is not only possible but, in certain cases, can be advantageous, depending on the drug, the dose and the combination modalities. In order to find the best synergisms between the two treatments and to turn weak immunotherapeutic interventions into potent anticancer instruments, it is mandatory to understand the complex mechanisms responsible for the positive interactions between chemotherapy and immunotherapy. The results of an ensemble of studies carried out in our laboratory as well as by others in both mouse models and patients suggest some novel mechanisms that could be exploited for enhancing the clinical response to cancer immunotherapy.
Tuesday 10 July 2012
S21
european journal of cancer 48, suppl. 5 (2012) S20–S24
09:00−09:45
Meet the Expert 86 Molecular Diagnostics in Breast Cancer − Getting Beyond ER, PR, HER2 and Proliferation J. Reis-Filho1 . 1 Institute of Cancer Research, Breakthrough Breast Cancer Research Centre, London, United Kingdom Breast cancer comprises a collection of different diseases, which have different histological features, molecular profiles, clinical behaviour and response to therapies. In the last 10 years, several lines of evidence, largely stemming from high throughput molecular profiling studies, have demonstrated that oestrogen receptor (ER)-positive and ER-negative breast cancers are fundamentally different diseases. The excitement with novel technologies, in particular gene expression profiling, led to the promise that the potentials of personalised medicine could be realised in an expeditious manner. It should be noted, however, that over a decade after the introduction of microarray-based gene expression profiling, molecular diagnostic methods for the management of breast cancer patients are still restricted to the assessment of ER, progesterone receptor (PR) and HER2 status, and the levels of tumour cell proliferation. Arguably, the main contributions of gene expression profiling were in the unravelling of the molecular heterogeneity of breast cancers, the identification of the differences between ER-positive and ER-negative breast cancers, and the importance of proliferation as one of the main determinants of the outcome of patients with ER-positive disease. Furthermore, this type of approach has led to the implementation of multiparameter predictors of outcome, which are now being used in clinical decision-making, based on either clinicopathological and/ or transcriptomic data. It is now possible to define good prognosis ER-positive breast cancer patients with great accuracy, to the point that research endeavours to refine the prognostication of these patients even further may prove futile. On the other hand, several questions that are germane to the realisation of the potentials of personalised medicine remain to be answered. It is still unclear as to how breast cancer should be subtyped from a molecular standpoint; prediction of response to specific therapeutic agents is still imprecise; and methods to account for the intratumour phenotypic and genetic heterogeneity found in breast cancers remain to be fully developed. In this talk, the state of the art in molecular diagnosis of breast cancer patients, the promise of new technologies, including massively parallel sequencing, and the challenges that lie ahead will be discussed. 87 Biobanking 3 P. Riegman1 , M.M. Morente2 , J.A. Lopez-Guerrero ´ , M. Grazia Daidone4 , T. Soderstr ¨ om ¨ 5 , J. Thompson6 , J. Hall7 , M. Maimuna8 , A. Broeks9 , V.P. Collins10 . 1 Erasmus MC, Department of Pathology, Rotterdam, The Netherlands, 3 Fundacion Centro Nacional de Investigaciones, Molecular Pathology, Valencia, Spain, 4 IRCCS Istituto Nazionale Dei Tumori, Department of Pathology, Milan, Italy, 5 Karolinska Institute, Department of Pathology, Stockholm, Sweden, 6 Karolinska University Hospital, Department of Pathology, Stockholm, Sweden, 7 EORTC, Translational Research and Imaging, Brussels, Belgium, 8 IARC, Laboratory Services and Bio Bank Group, Lyon, France, 9 NKI, Pathology, Amsterdam, The Netherlands, 10 University of Cambridge, Pathology, Cambridge, United Kingdom
Openly sharing human samples collected in a standardized way between hospital integrated biorepositories and their research groups would enable multi center translational cancer research having a high statistical significant impact with possible direct consequences on innovation of patient care. Moreover, the speed in which these experiments could be performed would be unmatched to the standards of today. Sharing samples is seen as a no go area for most investigators (collection stakeholders), afraid to lose on their institutional and departmental investment of resources and it is seen as difficult because institutional bias can disrupt the expected outcome and there are many regulatory issues expected when exchanging samples. Biobanks have tried to set up networks enabling scientists to find samples they need. However, the enthusiasm to upload sample data is not always shared happily without knowing benefits in advance.
Especially in case there are language barriers, annotation problems, regulatory difficulties and quality issues to overcome. The aim of the European project EurocanPlatform is to set up a European translational cancer research platform including biobanking. Bundling of good existing initiatives (e.g. harmonized collection procedures), whereas alternative approaches are to be developed in areas suspect for obstructions. Working on awareness, motivation and even influencing work environments of primary Investigators, collectors and patients through patient representative groups have become one of the key targets. For instance: writing a letter of intent to boards of cancer centres and academic hospitals in which the effects on willingness to exchange samples is described, quality issues are addressed, institutional access rules with external access and the influence of the use of Impact Factors to evaluate scientific achievement. Furthermore, distillation and publication of possible win-win situations in favour of both PI’s and collectors can make both parties aware of opportunities with possible synergistic outcomes. The existing OECI-TuBaFrost project is adapted to serve the EurocanPlatform infrastructure needs. A biobank locator enables searching and contacting biobanks having interesting samples. The role of PI’s involved in local research on the samples is enhanced. Identified banks can join in a closed project sample exchange platform where only data upload of samples that might be used in the project is needed. 88 Systems Biology in Cancer No abstract received.
Tuesday 10 July 2012
10:15−12:00
FEBS Molecular Oncology Supported Symposium
Personalised Medicine 89 Interrogating the Genome to Find Mechanisms of Drug Resistance in Cancer R. Bernards1 , S. Huang1 , A. Prahallad1 , C. Sun1 . 1 The Netherlands Cancer Institute, Division of Molecular Carcinog. H-2, Amsterdam, The Netherlands Background: Unresponsiveness to therapy remains a significant problem in the treatment of cancer, also with the new classes of cancer drugs. In my laboratory, we use functional genetic approaches to identify biomarkers that can predict responsiveness to targeted cancer therapeutics; drugs that specifically inhibit molecules or pathways that are often activated in cancer. Nevertheless, it remains poorly explained why a significant number of tumors do not respond to these therapies. Material and Methods: We aim to elucidate the molecular pathways that contribute to unresponsiveness to targeted cancer therapeutics using a functional genetic approach. This will yield biomarkers that may be useful to predict how individual patients will respond to these drugs. Furthermore, this work may allow the development of drugs that act in synergy with the established drug to prevent or overcome drug resistance. To identify biomarkers that control tumor cell responsiveness to cancer therapeutics, we use multiple complementary approaches. First, we use genome wide loss-of-function genetic screens (with shRNA interference libraries) in cancer cells that are sensitive to the drug-of-interest to search for genes whose down-regulation confers resistance to the drug-of-interest (resistance screens). In addition, we use shRNA screens with a low dose of the drug to screen for genes whose inhibition enhances the toxicity of the cancer drug (sensitizer screens). As a third approach, we use gain of function genetic screens in which we search for genes whose over-expression modulates drug responsiveness. Once we have identified candidate drug response biomarkers in relevant cell line models, we ask if the expression of these genes is correlated with clinical response to the drug-of-interest. For this, we use tumor samples of cancer patients treated with the drug in question and whose response to therapy is documented. Results: We have used functional genetic screens to identify kinases that enhance the cytotoxic effects of the BRAF inhibitor vemurafenib in BRAF mutant colon cancers. We identified EGFR as a critical kinase whose activity must be inhibited together with BRAF to elicit a therapeutic benefit in BRAF mutant colon cancer. We found that BRAF inhibition activates EGFR through a feedback loop, thereby activating PI3K-AKT signaling. Our data demonstrate that simultaneous inhibition of BRAF and EGFR leads to potently synergistic anti cancer effects, both in vitro and in vivo. Conclusions: Functional genetic approaches can identify strongly synergistic drug combinations in cancer. These studies can identify unexpected combination therapies based on insights in the genetic dependencies between signalling pathways.
was possible to combine it with standard treatments such as chemotherapy. The answer, now, is past history. The combined use of immunotherapy and chemotherapy is not only possible but, in certain cases, can be advantageous, depending on the drug, the dose and the combination modalities. In order to find the best synergisms between the two treatments and to turn weak immunotherapeutic interventions into potent anticancer instruments, it is mandatory to understand the complex mechanisms responsible for the positive interactions between chemotherapy and immunotherapy. The results of an ensemble of studies carried out in our laboratory as well as by others in both mouse models and patients suggest some novel mechanisms that could be exploited for enhancing the clinical response to cancer immunotherapy.
Tuesday 10 July 2012
S21
european journal of cancer 48, suppl. 5 (2012) S20–S24
09:00−09:45
Meet the Expert 86 Molecular Diagnostics in Breast Cancer − Getting Beyond ER, PR, HER2 and Proliferation J. Reis-Filho1 . 1 Institute of Cancer Research, Breakthrough Breast Cancer Research Centre, London, United Kingdom Breast cancer comprises a collection of different diseases, which have different histological features, molecular profiles, clinical behaviour and response to therapies. In the last 10 years, several lines of evidence, largely stemming from high throughput molecular profiling studies, have demonstrated that oestrogen receptor (ER)-positive and ER-negative breast cancers are fundamentally different diseases. The excitement with novel technologies, in particular gene expression profiling, led to the promise that the potentials of personalised medicine could be realised in an expeditious manner. It should be noted, however, that over a decade after the introduction of microarray-based gene expression profiling, molecular diagnostic methods for the management of breast cancer patients are still restricted to the assessment of ER, progesterone receptor (PR) and HER2 status, and the levels of tumour cell proliferation. Arguably, the main contributions of gene expression profiling were in the unravelling of the molecular heterogeneity of breast cancers, the identification of the differences between ER-positive and ER-negative breast cancers, and the importance of proliferation as one of the main determinants of the outcome of patients with ER-positive disease. Furthermore, this type of approach has led to the implementation of multiparameter predictors of outcome, which are now being used in clinical decision-making, based on either clinicopathological and/ or transcriptomic data. It is now possible to define good prognosis ER-positive breast cancer patients with great accuracy, to the point that research endeavours to refine the prognostication of these patients even further may prove futile. On the other hand, several questions that are germane to the realisation of the potentials of personalised medicine remain to be answered. It is still unclear as to how breast cancer should be subtyped from a molecular standpoint; prediction of response to specific therapeutic agents is still imprecise; and methods to account for the intratumour phenotypic and genetic heterogeneity found in breast cancers remain to be fully developed. In this talk, the state of the art in molecular diagnosis of breast cancer patients, the promise of new technologies, including massively parallel sequencing, and the challenges that lie ahead will be discussed. 87 Biobanking 3 P. Riegman1 , M.M. Morente2 , J.A. Lopez-Guerrero ´ , M. Grazia Daidone4 , T. Soderstr ¨ om ¨ 5 , J. Thompson6 , J. Hall7 , M. Maimuna8 , A. Broeks9 , V.P. Collins10 . 1 Erasmus MC, Department of Pathology, Rotterdam, The Netherlands, 3 Fundacion Centro Nacional de Investigaciones, Molecular Pathology, Valencia, Spain, 4 IRCCS Istituto Nazionale Dei Tumori, Department of Pathology, Milan, Italy, 5 Karolinska Institute, Department of Pathology, Stockholm, Sweden, 6 Karolinska University Hospital, Department of Pathology, Stockholm, Sweden, 7 EORTC, Translational Research and Imaging, Brussels, Belgium, 8 IARC, Laboratory Services and Bio Bank Group, Lyon, France, 9 NKI, Pathology, Amsterdam, The Netherlands, 10 University of Cambridge, Pathology, Cambridge, United Kingdom
Openly sharing human samples collected in a standardized way between hospital integrated biorepositories and their research groups would enable multi center translational cancer research having a high statistical significant impact with possible direct consequences on innovation of patient care. Moreover, the speed in which these experiments could be performed would be unmatched to the standards of today. Sharing samples is seen as a no go area for most investigators (collection stakeholders), afraid to lose on their institutional and departmental investment of resources and it is seen as difficult because institutional bias can disrupt the expected outcome and there are many regulatory issues expected when exchanging samples. Biobanks have tried to set up networks enabling scientists to find samples they need. However, the enthusiasm to upload sample data is not always shared happily without knowing benefits in advance.
Especially in case there are language barriers, annotation problems, regulatory difficulties and quality issues to overcome. The aim of the European project EurocanPlatform is to set up a European translational cancer research platform including biobanking. Bundling of good existing initiatives (e.g. harmonized collection procedures), whereas alternative approaches are to be developed in areas suspect for obstructions. Working on awareness, motivation and even influencing work environments of primary Investigators, collectors and patients through patient representative groups have become one of the key targets. For instance: writing a letter of intent to boards of cancer centres and academic hospitals in which the effects on willingness to exchange samples is described, quality issues are addressed, institutional access rules with external access and the influence of the use of Impact Factors to evaluate scientific achievement. Furthermore, distillation and publication of possible win-win situations in favour of both PI’s and collectors can make both parties aware of opportunities with possible synergistic outcomes. The existing OECI-TuBaFrost project is adapted to serve the EurocanPlatform infrastructure needs. A biobank locator enables searching and contacting biobanks having interesting samples. The role of PI’s involved in local research on the samples is enhanced. Identified banks can join in a closed project sample exchange platform where only data upload of samples that might be used in the project is needed. 88 Systems Biology in Cancer No abstract received.
Tuesday 10 July 2012
10:15−12:00
FEBS Molecular Oncology Supported Symposium
Personalised Medicine 89 Interrogating the Genome to Find Mechanisms of Drug Resistance in Cancer R. Bernards1 , S. Huang1 , A. Prahallad1 , C. Sun1 . 1 The Netherlands Cancer Institute, Division of Molecular Carcinog. H-2, Amsterdam, The Netherlands Background: Unresponsiveness to therapy remains a significant problem in the treatment of cancer, also with the new classes of cancer drugs. In my laboratory, we use functional genetic approaches to identify biomarkers that can predict responsiveness to targeted cancer therapeutics; drugs that specifically inhibit molecules or pathways that are often activated in cancer. Nevertheless, it remains poorly explained why a significant number of tumors do not respond to these therapies. Material and Methods: We aim to elucidate the molecular pathways that contribute to unresponsiveness to targeted cancer therapeutics using a functional genetic approach. This will yield biomarkers that may be useful to predict how individual patients will respond to these drugs. Furthermore, this work may allow the development of drugs that act in synergy with the established drug to prevent or overcome drug resistance. To identify biomarkers that control tumor cell responsiveness to cancer therapeutics, we use multiple complementary approaches. First, we use genome wide loss-of-function genetic screens (with shRNA interference libraries) in cancer cells that are sensitive to the drug-of-interest to search for genes whose down-regulation confers resistance to the drug-of-interest (resistance screens). In addition, we use shRNA screens with a low dose of the drug to screen for genes whose inhibition enhances the toxicity of the cancer drug (sensitizer screens). As a third approach, we use gain of function genetic screens in which we search for genes whose over-expression modulates drug responsiveness. Once we have identified candidate drug response biomarkers in relevant cell line models, we ask if the expression of these genes is correlated with clinical response to the drug-of-interest. For this, we use tumor samples of cancer patients treated with the drug in question and whose response to therapy is documented. Results: We have used functional genetic screens to identify kinases that enhance the cytotoxic effects of the BRAF inhibitor vemurafenib in BRAF mutant colon cancers. We identified EGFR as a critical kinase whose activity must be inhibited together with BRAF to elicit a therapeutic benefit in BRAF mutant colon cancer. We found that BRAF inhibition activates EGFR through a feedback loop, thereby activating PI3K-AKT signaling. Our data demonstrate that simultaneous inhibition of BRAF and EGFR leads to potently synergistic anti cancer effects, both in vitro and in vivo. Conclusions: Functional genetic approaches can identify strongly synergistic drug combinations in cancer. These studies can identify unexpected combination therapies based on insights in the genetic dependencies between signalling pathways.