- Email: [email protected]
Initiative for Molecular Profiling and Advanced Cancer Therapy and challenges in the implementation of precision medicine
Author’s Accepted Manuscript Initiative for Molecular Profiling and Advanced Cancer Therapy and Challenges in Implementation of Precision MedicinePersonalized Medicine in a Phase I Clinical Trials Program Apostolia-Maria Tsimberidou www.elsevier.com/locate/cpcancerv
PII: DOI: Reference:
S0147-0272(17)30017-X http://dx.doi.org/10.1016/j.currproblcancer.2017.02.002 YMCN329
To appear in: Current Problems in Cancer Cite this article as: Apostolia-Maria Tsimberidou, Initiative for Molecular Profiling and Advanced Cancer Therapy and Challenges in Implementation of Precision MedicinePersonalized Medicine in a Phase I Clinical Trials Program, Current Problems in Cancer, http://dx.doi.org/10.1016/j.currproblcancer.2017.02.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Initiative for Molecular Profiling and Advanced Cancer Therapy and Challenges in Implementation of Precision Medicine
Apostolia-Maria Tsimberidou, MD, PhD
Department of Investigational Cancer Therapeutics, Phase I Clinical Trials Program, The University of Texas MD Anderson Cancer Center
Running Title: Personalized Medicine in a Phase I Clinical Trials Program Key Words: Personalized medicine, Phase I, Clinical trials, Targeted therapy, Genomic profiling
Corresponding
author:
Apostolia-Maria
Tsimberidou,
M.D.,
Ph.D.,
Associate
Professor, Department of Investigational Cancer Therapeutics, Unit 455, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, Phone: 713-792-4259, Fax: 713-794-3249, Email: [email protected]
Precision medicine is a form of medicine that uses information about a person’s genes, proteins, and environment to prevent, diagnose, and treat disease. Initially, the term “precision medicine” was used to describe targeting tumor molecular abnormalities with drugs known to inhibit the function of a molecular alteration. In recent years, precision medicine has included the development of therapeutic agents that target any biological abnormality that is associated with the development of cancer. Consequently, owing to recent major breakthroughs in immunotherapeutic strategies, the armamentarium of the precision medicine approach now also includes immunotherapy.
The identification of pathways involved in the pathophysiology of carcinogenesis, metastasis, and drug resistance, as well as the emergence of technologies enabling tumor molecular analysis and the discovery of targeted therapies, has stimulated research focusing on the optimal use of targeted agents. The discovery of imatinib for the successful treatment of Philadelphia chromosome–positive chronic myeloid leukemia1 prompted researchers to identify other molecular aberrations in solid tumors 27
.
In 2007, we initiated the IMPACT study (Initiative for Molecular Profiling and Advanced Cancer Therapy), the first personalized medicine program for patients referred to the Phase I Clinic at The University of Texas MD Anderson Cancer Center (Houston, TX) 8. Our goal was to assess whether molecular analysis of advanced cancer to select targeted therapy to counteract the effects of specific aberrations would be associated with improved clinical outcomes. Patients with advanced cancer were treated based on their molecular analysis. Patients whose tumors had an aberration were treated with matched targeted therapy, when available. Treatment assignment was not randomized. In this retrospective analysis, the clinical outcomes of patients with molecular aberrations treated with matched targeted therapy were compared with those of consecutive patients
who were not treated with matched targeted therapy. Of 1,144 patients analyzed, 460 (40.2%) had 1 or more aberration. In patients with 1 molecular aberration, matched therapy (n = 175) compared with treatment without matching (n = 116) was associated with a higher overall response rate (27% vs. 5%; P < 0.0001), longer time-to-treatment failure (TTF; median, 5.2 vs. 2.2 months; P < 0.0001), and longer survival (median, 13.4 vs. 9.0 months; P = 0.017). Matched targeted therapy was associated with longer TTF compared with their prior systemic therapy in patients with 1 mutation (5.2 vs. 3.1 months, respectively; P < 0.0001). In multivariate analysis in patients with 1 molecular aberration, matched therapy was an independent factor predicting response (P = 0.001) and TTF (P = 0.0001)8.
Next, we reported validation and landmark analyses in a subsequent set of patients treated with the personalized medicine approach in our phase I program at MD Anderson9,10. Outcomes of patients who were referred for treatment on phase I clinical trials at MD Anderson from March 2011 to January 2012 were compared between those who had received targeted therapy and those for whom no targeted therapy was available. Two-month landmark analyses for overall and progression-free survival (PFS) combining previously published and validation cohort patient data were performed. The landmark method was used to avoid selection bias in the correlation of survival or PFS with response by type of therapy (matched therapy vs. nonmatched therapy11,12. By this method of evaluating outcome, patients who die early do not prejudicially influence the analysis of a post-diagnosis endpoint
11,12
. In patients with one alteration, matched
therapy (n = 143) compared with treatment without matching (n = 236) was associated with a higher objective response rate (12% vs. 5%; P < 0.0001), longer PFS (median, 3.9 vs. 2.2 months; P = 0.001), and longer survival (median, 11.4 vs. 8.6 months; P = 0.04). In multivariate analysis, matched therapy was an independent factor predicting
response (P < 0.015) and PFS (P < 0.004). Two-month landmark analyses in the matched therapy group demonstrated that the median survival of responders was 30.5 months compared with 11.3 months for non-responders (P = 0.01); and the median PFS was 38.7 months compared with 5.9 months, respectively (P < 0.0001). The respective values in the non-matched therapy group were 9.8 and 9.4 months (P = 0.46) and 8.5 and 4.2 months (P = 0.18). This validation analysis confirmed our previous observations10.
In May 2014, we initiated IMPACT 2 (Initiative for Molecular Profiling and Advanced Cancer Therapy 2)9,13, a randomized study evaluating molecular profiling and targeted agents in patients with metastatic cancer10. The primary objective of this study is to determine whether patients treated with a targeted therapy selected on the basis of a genomic alteration in the tumor have longer PFS than those whose treatment is not selected on the basis of genomic analysis. Patients with metastatic cancer, of any tumor type, and unlimited lines of prior therapy are eligible. Patients must have been treated with established standard-of-care therapy, or physicians have determined that such established therapy is not sufficiently efficacious, or patients have declined to receive standard-of-care therapy. Patients undergo tumor biopsy followed by molecular profiling. If at least one targetable molecular alteration is identified, the patient will be treated as follows: if there is an FDA-approved drug within the labeled indication, the patient will receive it; if there is no FDA-approved drug for the alteration and the tumor type, but there is a commercially available targeted agent or appropriate clinical trial, patients will be randomized to receive targeted therapy versus treatment not selected on the basis of genetic profiling. Patients will be allowed to cross over to the other arm if they develop progressive disease or serious toxicity on the assigned treatment9,13.
In an ideal world, to implement precision medicine complete identification of the complex mechanisms of carcinogenesis for every patient’s tumor should be available and drugs that effectively inhibit the function of the driver biologic alterations should be administered9. Technologic advancements have enabled the development of patient tumor profiles, which include genomic, transcriptomic, proteomic, and immune data. Clinical trials should be immediately available and accessible to all patients. These trials should include drugs with efficacious antitumor activity and limited, if any, toxicity; their design should be dynamic and adaptive, taking into consideration the changing biologic landscape of patients’ tumor profiles in time and metastatic sites and patient comorbidities. These designs should also incorporate therapeutic strategies targeting dynamic changes in tumor biologic abnormalities, eliminating minimal residual disease, and eradicating significant subclones conferring tumor resistance to treatment9.
To accelerate the implementation of precision medicine, the following are needed: increased patient access to clinical trials; affordable tumor biology testing and anticancer therapies; and efficient, non-lengthy regulatory procedures. Furthermore, standardized “N of 1” databases should accurately list patient data in real time, including tumor biology characteristics and treatment and clinical outcomes. Databases should be up to date and include all ongoing clinical trials, eligibility criteria, up-to-date responses and response durations, and overall survival and toxicity data. More importantly, sharing data and knowledge using interoperable “N of 1” databases with patient records would provide an invaluable learning source from previously treated patients to optimize the treatment of subsequent patients with cancer9.
Despite the multitude of available data, the selection of optimal therapy for patients with cancer has not been standardized. The clinical significance of abnormalities identified using genomic, transcriptomic, or proteomic analysis, and of immune markers, varies
significantly on the basis of whether the biologic abnormality is the key driver of carcinogenesis and whether the precision medicine drug effectively targets the abnormality. In academic institutions, tumor boards have been charged with the task of annotating molecular alterations, taking into consideration available published and anecdotal data to offer patients the best treatments possible. The ultimate goal is to accelerate the development of novel targeted and immunotherapeutic agents. Each of the targeted agents and the immunotherapeutic strategies has unique mechanisms of action and unique toxicity profiles. Frequently, comorbidities, adverse events, and tolerance to treatment determine patients’ ability to receive the optimal treatment (whether US Food and Drug Administration (FDA)-approved agents or experimental treatment via clinical trials). Immunotherapeutic agents, although they are associated with prolonged survival in some patients with selected tumor types, are associated with severe toxicity in a significant minority of patients. Therefore, prospective trials should focus on the development of reliable biomarkers that predict response to immunotherapy, pseudoprogression, and more importantly, factors associated with the development of serious toxicities.
In spite of the exponential increase in FDA-approved anticancer therapies and the availability of clinical trials, the vast majority of patients with cancer do not have access to the precision medicine approach. Major limitations to the implementation of precision medicine remain: the disproportionally small numbers of anticancer drugs given the large number of biologic abnormalities identified; the lack of efficient combination regimens that target multiple coexisting biologic abnormalities concurrently or sequentially; and the lack of consecutive tumor biologic analysis to guide the optimization of treatment of minimal residual disease and new significant subclones associated with resistance to treatment.
Although identifying specific molecular abnormalities and selecting therapy based on these abnormalities is associated with encouraging clinical outcomes, the assignment of treatment on clinical trials or FDA-approved drugs based on molecular alterations or biologic characteristics is a complex process. Major challenges remain the poor antitumor activity, if any, of many investigational agents, particularly in phase I and phase II studies; the low initial dose levels of the drugs in phase I studies; concomitant driver biologic characteristics that cannot be detected with the available technology and confer resistance to treatment; patient comorbidities or poor tolerance to investigational or FDA-approved drugs; lack of consistent markers associated with response; and multiple factors associated with tumor biology and patient characteristics that are unknown at the time of assignment of treatment.
Several other challenges in the field of precision medicine exist. Cumulative evidence suggests that molecular analyses of a single metastatic site may provide limited information because of intra-patient heterogeneity, and this heterogeneity may explain tumor adaptation and therapeutic failure14. This limited ability to validate oncologic biomarkers, which is attributed` in part to sampling bias, may be overcome by the identification of alterations associated with the trunk of the phylogenetic tree, which is expected to lead to clinically significant biomarkers. Extensive research in breast cancer has confirmed plasticity and heterogeneity within biologic subtypes of breast tumors15 and the need to determine individual tumor clonal genotypes in triple-negative breast cancer to understand the biology and to select therapy16. Genomic instability-driven carcinogenesis is more common in triple-negative breast cancers than in other breast tumors, even though the majority of all breast tumors demonstrate many DNA copy number alterations. It is thought that the genes that contribute to this instability may prove useful as clinical predictors of response to treatment17. A better understanding of
cancer subgroups and their molecular drivers that integrates genome and transcriptome information such as analysis of copy number and gene expression, like the one reported in breast tumors, will lead to the clinically useful molecular stratification of patients with cancer18. The clinical significance of these dynamic changes in the genome was shown in patients with lung cancer bearing EGFR mutations19. Histologic evolution in addition to genotypic plasticity was documented after treatment with EGFR inhibitors, providing strong evidence that biopsies are needed at the time of progression in order to understand the mechanisms of resistance and to optimize treatment19.
Immunotherapy
In recent years, clinical research focusing on immunotherapy has revolutionized the treatment of cancer. Ipilimumab, a fully human monoclonal antibody that blocks cytotoxic T-lymphocyte antigen 4 (CTLA-4) to augment antitumor immune responses and was approved by the FDA in 2011, has been associated with a plateau in survival in approximately 20% of patients with advanced melanoma, indicating cure20. Other FDAapproved immunotherapeutic agents include immune checkpoint blockade inhibitors and anti-PD-1 (pembrolizumab, nivolumab) and anti-PD-L1 (atezolizumab) agents. Multiple ongoing clinical trials are exploring the antitumor activity of immunotherapy, including novel strategies with T-cell expansion, dendritic vaccine therapy, and personalized immune strategies in patients with cancer.
Early data suggest that anti-PD-1 and anti-PD-L1 inhibitors have antitumor activity against several tumor types, such as melanoma, lung, head and neck, breast, and bladder cancers, but only a subset (10-30%) of patients benefit from these treatments. Prospective trials and correlative studies are expected to elucidate markers of response
and resistance to immunotherapy and to identify baseline characteristics associated with toxicity. Assessment of clinical trial endpoints that are unique to immunotherapies (e.g., delayed response, pseudo-progression) should be standardized. Development of biomarkers21,22, strategies to overcome resistance of tumors unresponsive to immunotherapy, and combination therapies are needed to improve clinical outcomes of patients treated with immunotherapy. Innovative study designs will expedite drug development by improving the efficiency of clinical research.
Ongoing efforts to improve research in this area need to be harmonized in order to establish standardized methodological approaches.
Clinical research focusing on precision medicine incorporates clinical trials with immunotherapy, targeted therapy, and other therapeutic strategies designed for specific patients.
Conclusion During the past decade, unprecedented breakthroughs have been generated in oncology owing to the emergence of technologies that improve our understanding of genomic,
transcriptional,
proteomic,
and
epigenetic
aberrations
and
immune
mechanisms in carcinogenesis. This knowledge has stimulated translational research and the discovery of new drugs that have improved the prognosis of patients with cancer. Genomics and model systems have enabled the validation of novel therapeutic strategies, and exciting new data have been reported in preclinical and clinical studies. Several paradigms in targeted therapy and immunotherapy have emerged from clinical trials. Ongoing research aims to discover the molecular mechanisms associated with resistance to novel therapies and tumor heterogeneity. The basic strategies of anticancer therapy include targeted therapy, immunotherapy, and targeting cancer stem cells, the microenvironment, angiogenesis, and epigenetics. Advances in technology and bioinformatic analyses of complex data to fully characterize tumor biology and function and the highly dynamic tumoral changes in time and space will improve cancer diagnosis and prognosis. We are on the threshold of translating the discoveries in cancer biology into improved clinical outcomes for patients with cancer on a large scale using clinical trials. Increased harmonization between discoveries, policies, and practices will expedite the use of acquired knowledge in oncology practice. In this unique time in history, the optimization of clinical trials and discovery of novel therapeutic approaches that target the molecular basis of cancer will accelerate the implementation of precision medicine and hold the promise to cure cancer by offering dramatically effective treatment with low toxicity in every patient with cancer.
Efficient and carefully designed innovative clinical trials hold the promise of expediting the development of novel anticancer drugs and the hope of curing cancer. In recent years, breakthroughs in cancer therapy include strategies that include targeted therapy and immunotherapy. Consecutively, biomarkers are being integrated into early-phase clinical trials with targeted agents and immunotherapy for optimal patient selection. The changing biologic basis of cancer in patients who are undergoing therapy requires continued testing of tumor biology and optimization of treatment to select a strategy or drug that will inhibit the function of the emerging tumor’s biologic drivers of disease progression.
Acknowledgment The author would like to thank Elangovan Krishnan, MBBS, MS, PhD, Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center for valuable assistance with the technical editing of the manuscript.
References 1.
Druker BJ, Talpaz M, Resta DJ, et al: Efficacy and safety of a specific
inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N Engl J Med 344:1031-7, 2001 2.
Beroukhim R, Mermel CH, Porter D, et al: The landscape of somatic
copy-number alteration across human cancers. Nature 463:899-905, 2010 3.
Davies H, Bignell GR, Cox C, et al: Mutations of the BRAF gene in human
cancer. Nature 417:949-54, 2002
4.
Lynch TJ, Bell DW, Sordella R, et al: Activating mutations in the
epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 350:2129-39, 2004 5.
Samuels Y, Wang Z, Bardelli A, et al: High frequency of mutations of the
PIK3CA gene in human cancers. Science 304:554, 2004 6.
Soda M, Choi YL, Enomoto M, et al: Identification of the transforming
EML4-ALK fusion gene in non-small-cell lung cancer. Nature 448:561-6, 2007 7.
Shimizu K, Birnbaum D, Ruley MA, et al: Structure of the Ki-ras gene of
the human lung carcinoma cell line Calu-1. Nature 304:497-500, 1983 8.
Tsimberidou AM, Iskander NG, Hong DS, et al: Personalized medicine in
a phase I clinical trials program: the MD Anderson Cancer Center initiative. Clin Cancer Res 18:6373-83, 2012 9.
Tsimberidou AM, Eggermont AM, Schilsky RL: Precision cancer
medicine: the future is now, only better. Am Soc Clin Oncol Educ Book:61-9, 2014 10.
Tsimberidou AM, Wen S, Hong DS, et al: Personalized medicine for
patients with advanced cancer in the phase I program at MD Anderson: validation and landmark analyses. Clin Cancer Res 20:4827-36, 2014 11.
Anderson JR, Cain KC, Gelber RD: Analysis of survival by tumor
response. J Clin Oncol 1:710-9, 1983 12.
Anderson JR, Cain KC, Gelber RD: Analysis of survival by tumor
response and other comparisons of time-to-event by outcome variables. J Clin Oncol 26:3913-5, 2008 13.
IMPACT 2: Randomized Study Evaluating Molecular Profiling and
Targeted Agents in Metastatic Cancer, (ed 05/21/2014), 2014 14.
Gerlinger M, Rowan AJ, Horswell S, et al: Intratumor heterogeneity and
branched evolution revealed by multiregion sequencing. N Engl J Med 366:883-92, 2012
15.
Cancer Genome Atlas N: Comprehensive molecular portraits of human
breast tumours. Nature 490:61-70, 2012 16.
Shah SP, Roth A, Goya R, et al: The clonal and mutational evolution
spectrum of primary triple-negative breast cancers. Nature 486:395-9, 2012 17.
Weigman VJ, Chao HH, Shabalin AA, et al: Basal-like Breast cancer DNA
copy number losses identify genes involved in genomic instability, response to therapy, and patient survival. Breast Cancer Res Treat 133:865-80, 2012 18.
Curtis C, Shah SP, Chin SF, et al: The genomic and transcriptomic
architecture of 2,000 breast tumours reveals novel subgroups. Nature 486:346-52, 2012 19.
Sequist LV, Waltman BA, Dias-Santagata D, et al: Genotypic and
histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Transl Med 3:75ra26, 2011 20.
Larkin J, Chiarion-Sileni V, Gonzalez R, et al: Combined Nivolumab and
Ipilimumab or Monotherapy in Untreated Melanoma. N Engl J Med 373:23-34, 2015 21.
Hayes DF, Allen J, Compton C, et al: Breaking a vicious cycle. Sci Transl
Med 5:196cm6, 2013 22.
Lyman GH, Moses HL: Biomarker Tests for Molecularly Targeted
Therapies--The Key to Unlocking Precision Medicine. N Engl J Med 375:4-6, 2016
PII: DOI: Reference:
S0147-0272(17)30017-X http://dx.doi.org/10.1016/j.currproblcancer.2017.02.002 YMCN329
To appear in: Current Problems in Cancer Cite this article as: Apostolia-Maria Tsimberidou, Initiative for Molecular Profiling and Advanced Cancer Therapy and Challenges in Implementation of Precision MedicinePersonalized Medicine in a Phase I Clinical Trials Program, Current Problems in Cancer, http://dx.doi.org/10.1016/j.currproblcancer.2017.02.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Initiative for Molecular Profiling and Advanced Cancer Therapy and Challenges in Implementation of Precision Medicine
Apostolia-Maria Tsimberidou, MD, PhD
Department of Investigational Cancer Therapeutics, Phase I Clinical Trials Program, The University of Texas MD Anderson Cancer Center
Running Title: Personalized Medicine in a Phase I Clinical Trials Program Key Words: Personalized medicine, Phase I, Clinical trials, Targeted therapy, Genomic profiling
Corresponding
author:
Apostolia-Maria
Tsimberidou,
M.D.,
Ph.D.,
Associate
Professor, Department of Investigational Cancer Therapeutics, Unit 455, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, Phone: 713-792-4259, Fax: 713-794-3249, Email: [email protected]
Precision medicine is a form of medicine that uses information about a person’s genes, proteins, and environment to prevent, diagnose, and treat disease. Initially, the term “precision medicine” was used to describe targeting tumor molecular abnormalities with drugs known to inhibit the function of a molecular alteration. In recent years, precision medicine has included the development of therapeutic agents that target any biological abnormality that is associated with the development of cancer. Consequently, owing to recent major breakthroughs in immunotherapeutic strategies, the armamentarium of the precision medicine approach now also includes immunotherapy.
The identification of pathways involved in the pathophysiology of carcinogenesis, metastasis, and drug resistance, as well as the emergence of technologies enabling tumor molecular analysis and the discovery of targeted therapies, has stimulated research focusing on the optimal use of targeted agents. The discovery of imatinib for the successful treatment of Philadelphia chromosome–positive chronic myeloid leukemia1 prompted researchers to identify other molecular aberrations in solid tumors 27
.
In 2007, we initiated the IMPACT study (Initiative for Molecular Profiling and Advanced Cancer Therapy), the first personalized medicine program for patients referred to the Phase I Clinic at The University of Texas MD Anderson Cancer Center (Houston, TX) 8. Our goal was to assess whether molecular analysis of advanced cancer to select targeted therapy to counteract the effects of specific aberrations would be associated with improved clinical outcomes. Patients with advanced cancer were treated based on their molecular analysis. Patients whose tumors had an aberration were treated with matched targeted therapy, when available. Treatment assignment was not randomized. In this retrospective analysis, the clinical outcomes of patients with molecular aberrations treated with matched targeted therapy were compared with those of consecutive patients
who were not treated with matched targeted therapy. Of 1,144 patients analyzed, 460 (40.2%) had 1 or more aberration. In patients with 1 molecular aberration, matched therapy (n = 175) compared with treatment without matching (n = 116) was associated with a higher overall response rate (27% vs. 5%; P < 0.0001), longer time-to-treatment failure (TTF; median, 5.2 vs. 2.2 months; P < 0.0001), and longer survival (median, 13.4 vs. 9.0 months; P = 0.017). Matched targeted therapy was associated with longer TTF compared with their prior systemic therapy in patients with 1 mutation (5.2 vs. 3.1 months, respectively; P < 0.0001). In multivariate analysis in patients with 1 molecular aberration, matched therapy was an independent factor predicting response (P = 0.001) and TTF (P = 0.0001)8.
Next, we reported validation and landmark analyses in a subsequent set of patients treated with the personalized medicine approach in our phase I program at MD Anderson9,10. Outcomes of patients who were referred for treatment on phase I clinical trials at MD Anderson from March 2011 to January 2012 were compared between those who had received targeted therapy and those for whom no targeted therapy was available. Two-month landmark analyses for overall and progression-free survival (PFS) combining previously published and validation cohort patient data were performed. The landmark method was used to avoid selection bias in the correlation of survival or PFS with response by type of therapy (matched therapy vs. nonmatched therapy11,12. By this method of evaluating outcome, patients who die early do not prejudicially influence the analysis of a post-diagnosis endpoint
11,12
. In patients with one alteration, matched
therapy (n = 143) compared with treatment without matching (n = 236) was associated with a higher objective response rate (12% vs. 5%; P < 0.0001), longer PFS (median, 3.9 vs. 2.2 months; P = 0.001), and longer survival (median, 11.4 vs. 8.6 months; P = 0.04). In multivariate analysis, matched therapy was an independent factor predicting
response (P < 0.015) and PFS (P < 0.004). Two-month landmark analyses in the matched therapy group demonstrated that the median survival of responders was 30.5 months compared with 11.3 months for non-responders (P = 0.01); and the median PFS was 38.7 months compared with 5.9 months, respectively (P < 0.0001). The respective values in the non-matched therapy group were 9.8 and 9.4 months (P = 0.46) and 8.5 and 4.2 months (P = 0.18). This validation analysis confirmed our previous observations10.
In May 2014, we initiated IMPACT 2 (Initiative for Molecular Profiling and Advanced Cancer Therapy 2)9,13, a randomized study evaluating molecular profiling and targeted agents in patients with metastatic cancer10. The primary objective of this study is to determine whether patients treated with a targeted therapy selected on the basis of a genomic alteration in the tumor have longer PFS than those whose treatment is not selected on the basis of genomic analysis. Patients with metastatic cancer, of any tumor type, and unlimited lines of prior therapy are eligible. Patients must have been treated with established standard-of-care therapy, or physicians have determined that such established therapy is not sufficiently efficacious, or patients have declined to receive standard-of-care therapy. Patients undergo tumor biopsy followed by molecular profiling. If at least one targetable molecular alteration is identified, the patient will be treated as follows: if there is an FDA-approved drug within the labeled indication, the patient will receive it; if there is no FDA-approved drug for the alteration and the tumor type, but there is a commercially available targeted agent or appropriate clinical trial, patients will be randomized to receive targeted therapy versus treatment not selected on the basis of genetic profiling. Patients will be allowed to cross over to the other arm if they develop progressive disease or serious toxicity on the assigned treatment9,13.
In an ideal world, to implement precision medicine complete identification of the complex mechanisms of carcinogenesis for every patient’s tumor should be available and drugs that effectively inhibit the function of the driver biologic alterations should be administered9. Technologic advancements have enabled the development of patient tumor profiles, which include genomic, transcriptomic, proteomic, and immune data. Clinical trials should be immediately available and accessible to all patients. These trials should include drugs with efficacious antitumor activity and limited, if any, toxicity; their design should be dynamic and adaptive, taking into consideration the changing biologic landscape of patients’ tumor profiles in time and metastatic sites and patient comorbidities. These designs should also incorporate therapeutic strategies targeting dynamic changes in tumor biologic abnormalities, eliminating minimal residual disease, and eradicating significant subclones conferring tumor resistance to treatment9.
To accelerate the implementation of precision medicine, the following are needed: increased patient access to clinical trials; affordable tumor biology testing and anticancer therapies; and efficient, non-lengthy regulatory procedures. Furthermore, standardized “N of 1” databases should accurately list patient data in real time, including tumor biology characteristics and treatment and clinical outcomes. Databases should be up to date and include all ongoing clinical trials, eligibility criteria, up-to-date responses and response durations, and overall survival and toxicity data. More importantly, sharing data and knowledge using interoperable “N of 1” databases with patient records would provide an invaluable learning source from previously treated patients to optimize the treatment of subsequent patients with cancer9.
Despite the multitude of available data, the selection of optimal therapy for patients with cancer has not been standardized. The clinical significance of abnormalities identified using genomic, transcriptomic, or proteomic analysis, and of immune markers, varies
significantly on the basis of whether the biologic abnormality is the key driver of carcinogenesis and whether the precision medicine drug effectively targets the abnormality. In academic institutions, tumor boards have been charged with the task of annotating molecular alterations, taking into consideration available published and anecdotal data to offer patients the best treatments possible. The ultimate goal is to accelerate the development of novel targeted and immunotherapeutic agents. Each of the targeted agents and the immunotherapeutic strategies has unique mechanisms of action and unique toxicity profiles. Frequently, comorbidities, adverse events, and tolerance to treatment determine patients’ ability to receive the optimal treatment (whether US Food and Drug Administration (FDA)-approved agents or experimental treatment via clinical trials). Immunotherapeutic agents, although they are associated with prolonged survival in some patients with selected tumor types, are associated with severe toxicity in a significant minority of patients. Therefore, prospective trials should focus on the development of reliable biomarkers that predict response to immunotherapy, pseudoprogression, and more importantly, factors associated with the development of serious toxicities.
In spite of the exponential increase in FDA-approved anticancer therapies and the availability of clinical trials, the vast majority of patients with cancer do not have access to the precision medicine approach. Major limitations to the implementation of precision medicine remain: the disproportionally small numbers of anticancer drugs given the large number of biologic abnormalities identified; the lack of efficient combination regimens that target multiple coexisting biologic abnormalities concurrently or sequentially; and the lack of consecutive tumor biologic analysis to guide the optimization of treatment of minimal residual disease and new significant subclones associated with resistance to treatment.
Although identifying specific molecular abnormalities and selecting therapy based on these abnormalities is associated with encouraging clinical outcomes, the assignment of treatment on clinical trials or FDA-approved drugs based on molecular alterations or biologic characteristics is a complex process. Major challenges remain the poor antitumor activity, if any, of many investigational agents, particularly in phase I and phase II studies; the low initial dose levels of the drugs in phase I studies; concomitant driver biologic characteristics that cannot be detected with the available technology and confer resistance to treatment; patient comorbidities or poor tolerance to investigational or FDA-approved drugs; lack of consistent markers associated with response; and multiple factors associated with tumor biology and patient characteristics that are unknown at the time of assignment of treatment.
Several other challenges in the field of precision medicine exist. Cumulative evidence suggests that molecular analyses of a single metastatic site may provide limited information because of intra-patient heterogeneity, and this heterogeneity may explain tumor adaptation and therapeutic failure14. This limited ability to validate oncologic biomarkers, which is attributed` in part to sampling bias, may be overcome by the identification of alterations associated with the trunk of the phylogenetic tree, which is expected to lead to clinically significant biomarkers. Extensive research in breast cancer has confirmed plasticity and heterogeneity within biologic subtypes of breast tumors15 and the need to determine individual tumor clonal genotypes in triple-negative breast cancer to understand the biology and to select therapy16. Genomic instability-driven carcinogenesis is more common in triple-negative breast cancers than in other breast tumors, even though the majority of all breast tumors demonstrate many DNA copy number alterations. It is thought that the genes that contribute to this instability may prove useful as clinical predictors of response to treatment17. A better understanding of
cancer subgroups and their molecular drivers that integrates genome and transcriptome information such as analysis of copy number and gene expression, like the one reported in breast tumors, will lead to the clinically useful molecular stratification of patients with cancer18. The clinical significance of these dynamic changes in the genome was shown in patients with lung cancer bearing EGFR mutations19. Histologic evolution in addition to genotypic plasticity was documented after treatment with EGFR inhibitors, providing strong evidence that biopsies are needed at the time of progression in order to understand the mechanisms of resistance and to optimize treatment19.
Immunotherapy
In recent years, clinical research focusing on immunotherapy has revolutionized the treatment of cancer. Ipilimumab, a fully human monoclonal antibody that blocks cytotoxic T-lymphocyte antigen 4 (CTLA-4) to augment antitumor immune responses and was approved by the FDA in 2011, has been associated with a plateau in survival in approximately 20% of patients with advanced melanoma, indicating cure20. Other FDAapproved immunotherapeutic agents include immune checkpoint blockade inhibitors and anti-PD-1 (pembrolizumab, nivolumab) and anti-PD-L1 (atezolizumab) agents. Multiple ongoing clinical trials are exploring the antitumor activity of immunotherapy, including novel strategies with T-cell expansion, dendritic vaccine therapy, and personalized immune strategies in patients with cancer.
Early data suggest that anti-PD-1 and anti-PD-L1 inhibitors have antitumor activity against several tumor types, such as melanoma, lung, head and neck, breast, and bladder cancers, but only a subset (10-30%) of patients benefit from these treatments. Prospective trials and correlative studies are expected to elucidate markers of response
and resistance to immunotherapy and to identify baseline characteristics associated with toxicity. Assessment of clinical trial endpoints that are unique to immunotherapies (e.g., delayed response, pseudo-progression) should be standardized. Development of biomarkers21,22, strategies to overcome resistance of tumors unresponsive to immunotherapy, and combination therapies are needed to improve clinical outcomes of patients treated with immunotherapy. Innovative study designs will expedite drug development by improving the efficiency of clinical research.
Ongoing efforts to improve research in this area need to be harmonized in order to establish standardized methodological approaches.
Clinical research focusing on precision medicine incorporates clinical trials with immunotherapy, targeted therapy, and other therapeutic strategies designed for specific patients.
Conclusion During the past decade, unprecedented breakthroughs have been generated in oncology owing to the emergence of technologies that improve our understanding of genomic,
transcriptional,
proteomic,
and
epigenetic
aberrations
and
immune
mechanisms in carcinogenesis. This knowledge has stimulated translational research and the discovery of new drugs that have improved the prognosis of patients with cancer. Genomics and model systems have enabled the validation of novel therapeutic strategies, and exciting new data have been reported in preclinical and clinical studies. Several paradigms in targeted therapy and immunotherapy have emerged from clinical trials. Ongoing research aims to discover the molecular mechanisms associated with resistance to novel therapies and tumor heterogeneity. The basic strategies of anticancer therapy include targeted therapy, immunotherapy, and targeting cancer stem cells, the microenvironment, angiogenesis, and epigenetics. Advances in technology and bioinformatic analyses of complex data to fully characterize tumor biology and function and the highly dynamic tumoral changes in time and space will improve cancer diagnosis and prognosis. We are on the threshold of translating the discoveries in cancer biology into improved clinical outcomes for patients with cancer on a large scale using clinical trials. Increased harmonization between discoveries, policies, and practices will expedite the use of acquired knowledge in oncology practice. In this unique time in history, the optimization of clinical trials and discovery of novel therapeutic approaches that target the molecular basis of cancer will accelerate the implementation of precision medicine and hold the promise to cure cancer by offering dramatically effective treatment with low toxicity in every patient with cancer.
Efficient and carefully designed innovative clinical trials hold the promise of expediting the development of novel anticancer drugs and the hope of curing cancer. In recent years, breakthroughs in cancer therapy include strategies that include targeted therapy and immunotherapy. Consecutively, biomarkers are being integrated into early-phase clinical trials with targeted agents and immunotherapy for optimal patient selection. The changing biologic basis of cancer in patients who are undergoing therapy requires continued testing of tumor biology and optimization of treatment to select a strategy or drug that will inhibit the function of the emerging tumor’s biologic drivers of disease progression.
Acknowledgment The author would like to thank Elangovan Krishnan, MBBS, MS, PhD, Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center for valuable assistance with the technical editing of the manuscript.
References 1.
Druker BJ, Talpaz M, Resta DJ, et al: Efficacy and safety of a specific
inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N Engl J Med 344:1031-7, 2001 2.
Beroukhim R, Mermel CH, Porter D, et al: The landscape of somatic
copy-number alteration across human cancers. Nature 463:899-905, 2010 3.
Davies H, Bignell GR, Cox C, et al: Mutations of the BRAF gene in human
cancer. Nature 417:949-54, 2002
4.
Lynch TJ, Bell DW, Sordella R, et al: Activating mutations in the
epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 350:2129-39, 2004 5.
Samuels Y, Wang Z, Bardelli A, et al: High frequency of mutations of the
PIK3CA gene in human cancers. Science 304:554, 2004 6.
Soda M, Choi YL, Enomoto M, et al: Identification of the transforming
EML4-ALK fusion gene in non-small-cell lung cancer. Nature 448:561-6, 2007 7.
Shimizu K, Birnbaum D, Ruley MA, et al: Structure of the Ki-ras gene of
the human lung carcinoma cell line Calu-1. Nature 304:497-500, 1983 8.
Tsimberidou AM, Iskander NG, Hong DS, et al: Personalized medicine in
a phase I clinical trials program: the MD Anderson Cancer Center initiative. Clin Cancer Res 18:6373-83, 2012 9.
Tsimberidou AM, Eggermont AM, Schilsky RL: Precision cancer
medicine: the future is now, only better. Am Soc Clin Oncol Educ Book:61-9, 2014 10.
Tsimberidou AM, Wen S, Hong DS, et al: Personalized medicine for
patients with advanced cancer in the phase I program at MD Anderson: validation and landmark analyses. Clin Cancer Res 20:4827-36, 2014 11.
Anderson JR, Cain KC, Gelber RD: Analysis of survival by tumor
response. J Clin Oncol 1:710-9, 1983 12.
Anderson JR, Cain KC, Gelber RD: Analysis of survival by tumor
response and other comparisons of time-to-event by outcome variables. J Clin Oncol 26:3913-5, 2008 13.
IMPACT 2: Randomized Study Evaluating Molecular Profiling and
Targeted Agents in Metastatic Cancer, (ed 05/21/2014), 2014 14.
Gerlinger M, Rowan AJ, Horswell S, et al: Intratumor heterogeneity and
branched evolution revealed by multiregion sequencing. N Engl J Med 366:883-92, 2012
15.
Cancer Genome Atlas N: Comprehensive molecular portraits of human
breast tumours. Nature 490:61-70, 2012 16.
Shah SP, Roth A, Goya R, et al: The clonal and mutational evolution
spectrum of primary triple-negative breast cancers. Nature 486:395-9, 2012 17.
Weigman VJ, Chao HH, Shabalin AA, et al: Basal-like Breast cancer DNA
copy number losses identify genes involved in genomic instability, response to therapy, and patient survival. Breast Cancer Res Treat 133:865-80, 2012 18.
Curtis C, Shah SP, Chin SF, et al: The genomic and transcriptomic
architecture of 2,000 breast tumours reveals novel subgroups. Nature 486:346-52, 2012 19.
Sequist LV, Waltman BA, Dias-Santagata D, et al: Genotypic and
histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Transl Med 3:75ra26, 2011 20.
Larkin J, Chiarion-Sileni V, Gonzalez R, et al: Combined Nivolumab and
Ipilimumab or Monotherapy in Untreated Melanoma. N Engl J Med 373:23-34, 2015 21.
Hayes DF, Allen J, Compton C, et al: Breaking a vicious cycle. Sci Transl
Med 5:196cm6, 2013 22.
Lyman GH, Moses HL: Biomarker Tests for Molecularly Targeted
Therapies--The Key to Unlocking Precision Medicine. N Engl J Med 375:4-6, 2016