Bruce A. Chabner, M.D.In this issue of , we begin a series of articles that consider the often problematic challenge of understanding and applying genomic information to the practice of oncology. Bardia et al. [1] describe the genomic findings from a patient with estrogen receptor (ER)-positive breast cancer after progression on hormonal therapy. In this case, tumor profiling revealed an ESR1 mutation that conferred constitutive receptor activation. The authors discuss the significance of this mutation within the spectrum of hormonal resistance and its implications for further therapy.The past decade has produced an explosion of such information about the mutations, translocations, and amplifications that drive tumor growth and promote drug resistance. Some of these changes can be exploited as targets for new therapies, and the list of “targeted agents” available to the practicing oncologist will soon surpass 100, as 15–20 new drugs are given marketing indications each year. Many cancer centers as well as industrial vendors offer tumor genomic platforms, and these results are increasingly available to oncologists in the community as well as those in academic practices. The use of such platforms is now routine for many metastatic epithelial tumors, such as lung, melanoma, colon, thyroid, prostate, and breast cancers.The interpretation of these results in some cases is relatively straightforward. A V600EBRAF genetic mutation in a patient with metastatic melanoma calls for a BRAF kinase inhibitor backbone, nowadays in combination with a MEK inhibitor [2], whereas an EML-4ALK translocation in lung cancer is best treated with one of several approved ALK tyrosine kinase inhibitors [3]. However, for many patients with the same mutations in tumors of other histology, or for tumors having unusual genomic findings, the implications of these tests may not be obvious [4-6]. To understand genomic reports and make appropriate clinical decisions, the oncologist must understand the language of genomics, the techniques used to discover genomic variants, and the importance of test results. The best way to achieve this understanding is to use the case method. In our new series, led by Dr. Aditya Bardia, we will recruit papers from leading genomic centers to present interesting, teachable cases and interpret the molecular findings regarding implications for prognosis and therapy selection for a general oncologist.Underlying this new effort is this editor’s conviction that genomic medicine is neither totally precise nor completely rational at this point in its development; collective sharing of findings and experiences among institutions will help improve the precision of precision medicine. We increasingly understand that the drugs are not “precisely” targeted. We have learned that targeted agents have multiple sites of action and unanticipated side effects. New generations of drugs, such as the new series of PI3K and EGFR inhibitors, reduce side effects and narrow their spectrum of action. In addition, the multiplicity of mutations in a single tumor and clonal evolution of tumors at different metastatic sites lead to further imprecision in treatment planning. Analysis of circulating tumor cells and cell-free, circulating DNA may provide a more complete picture than a single biopsy [7, 8]. At the heart of our dilemma is the need to understand and plan for the rational treatment of cancer based on new technology and a more complete genomic profile, to maximize therapeutic efficacy while minimizing toxicity, and thus achieving one day a truly precise practice of oncology. To facilitate communication between practicing oncologists and laboratories, we have initiated this series; at the same time, we solicit our readers' comments and contributions to the goal of integrating genomics into the practice of cancer medicine.
Authors: Adrian G Sacher; Cloud Paweletz; Suzanne E Dahlberg; Ryan S Alden; Allison O'Connell; Nora Feeney; Stacy L Mach; Pasi A Jänne; Geoffrey R Oxnard Journal: JAMA Oncol Date: 2016-08-01 Impact factor: 31.777
Authors: Eunice L Kwak; Leanne G Ahronian; Giulia Siravegna; Benedetta Mussolin; Darrell R Borger; Jason T Godfrey; Nicholas A Jessop; Jeffrey W Clark; Lawrence S Blaszkowsky; David P Ryan; Jochen K Lennerz; A John Iafrate; Alberto Bardelli; Theodore S Hong; Ryan B Corcoran Journal: Cancer Discov Date: 2015-10-02 Impact factor: 39.397
Authors: Margaret Soucheray; Marzia Capelletti; Inés Pulido; Yanan Kuang; Cloud P Paweletz; Jeffrey H Becker; Eiki Kikuchi; Chunxiao Xu; Tarun B Patel; Fatima Al-Shahrour; Julián Carretero; Kwok-Kin Wong; Pasi A Jänne; Geoffrey I Shapiro; Takeshi Shimamura Journal: Cancer Res Date: 2015-08-17 Impact factor: 12.701
Authors: Georgina V Long; Jeffrey S Weber; Jeffrey R Infante; Kevin B Kim; Adil Daud; Rene Gonzalez; Jeffrey A Sosman; Omid Hamid; Lynn Schuchter; Jonathan Cebon; Richard F Kefford; Donald Lawrence; Ragini Kudchadkar; Howard A Burris; Gerald S Falchook; Alain Algazi; Karl Lewis; Igor Puzanov; Nageatte Ibrahim; Peng Sun; Elizabeth Cunningham; Amy S Kline; Heather Del Buono; Diane Opatt McDowell; Kiran Patel; Keith T Flaherty Journal: J Clin Oncol Date: 2016-01-25 Impact factor: 44.544
Authors: Pasi A Jänne; James Chih-Hsin Yang; Dong-Wan Kim; David Planchard; Yuichiro Ohe; Suresh S Ramalingam; Myung-Ju Ahn; Sang-We Kim; Wu-Chou Su; Leora Horn; Daniel Haggstrom; Enriqueta Felip; Joo-Hang Kim; Paul Frewer; Mireille Cantarini; Kathryn H Brown; Paul A Dickinson; Serban Ghiorghiu; Malcolm Ranson Journal: N Engl J Med Date: 2015-04-30 Impact factor: 91.245
Authors: A Fatih Sarioglu; Nicola Aceto; Nikola Kojic; Maria C Donaldson; Mahnaz Zeinali; Bashar Hamza; Amanda Engstrom; Huili Zhu; Tilak K Sundaresan; David T Miyamoto; Xi Luo; Aditya Bardia; Ben S Wittner; Sridhar Ramaswamy; Toshi Shioda; David T Ting; Shannon L Stott; Ravi Kapur; Shyamala Maheswaran; Daniel A Haber; Mehmet Toner Journal: Nat Methods Date: 2015-05-18 Impact factor: 28.547