A view on drug resistance in cancer
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A reductionist approach is taken to define and separate the key determinants of drug resistance, which include tumour burden and growth kinetics; tumour heterogeneity; physical barriers; the immune system and the microenvironment; undruggable cancer drivers; and the many consequences of applying therapeutic pressures.Abstract:
The problem of resistance to therapy in cancer is multifaceted. Here we take a reductionist approach to define and separate the key determinants of drug resistance, which include tumour burden and growth kinetics; tumour heterogeneity; physical barriers; the immune system and the microenvironment; undruggable cancer drivers; and the many consequences of applying therapeutic pressures. We propose four general solutions to drug resistance that are based on earlier detection of tumours permitting cancer interception; adaptive monitoring during therapy; the addition of novel drugs and improved pharmacological principles that result in deeper responses; and the identification of cancer cell dependencies by high-throughput synthetic lethality screens, integration of clinico-genomic data and computational modelling. These different approaches could eventually be synthesized for each tumour at any decision point and used to inform the choice of therapy. A review of drug resistance in cancer analyses each biological determinant of resistance separately and discusses existing and new therapeutic strategies to combat the problem as a whole.read more
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Signatures of mutational processes in human cancer
Ludmil B. Alexandrov,Serena Nik-Zainal,Serena Nik-Zainal,David C. Wedge,Samuel Aparicio,Sam Behjati,Sam Behjati,Andrew V. Biankin,Graham R. Bignell,Niccolo Bolli,Niccolo Bolli,Åke Borg,Anne Lise Børresen-Dale,Anne Lise Børresen-Dale,Sandrine Boyault,Birgit Burkhardt,Adam Butler,Carlos Caldas,Helen Davies,Christine Desmedt,Roland Eils,Jorunn E. Eyfjord,John A. Foekens,Mel Greaves,Fumie Hosoda,Barbara Hutter,Tomislav Ilicic,Sandrine Imbeaud,Sandrine Imbeaud,Marcin Imielinsk,Natalie Jäger,David T. W. Jones,David T. Jones,Stian Knappskog,Stian Knappskog,Marcel Kool,Sunil R. Lakhani,Carlos López-Otín,Sancha Martin,Nikhil C. Munshi,Nikhil C. Munshi,Hiromi Nakamura,Paul A. Northcott,Marina Pajic,Elli Papaemmanuil,Angelo Paradiso,John V. Pearson,Xose S. Puente,Keiran Raine,Manasa Ramakrishna,Andrea L. Richardson,Andrea L. Richardson,Julia Richter,Philip Rosenstiel,Matthias Schlesner,Ton N. Schumacher,Paul N. Span,Jon W. Teague,Yasushi Totoki,Andrew Tutt,Rafael Valdés-Mas,Marit M. van Buuren,Laura van ’t Veer,Anne Vincent-Salomon,Nicola Waddell,Lucy R. Yates,Icgc PedBrain,Jessica Zucman-Rossi,Jessica Zucman-Rossi,P. Andrew Futreal,Ultan McDermott,Peter Lichter,Matthew Meyerson,Matthew Meyerson,Sean M. Grimmond,Reiner Siebert,Elias Campo,Tatsuhiro Shibata,Stefan M. Pfister,Stefan M. Pfister,Peter J. Campbell,Peter J. Campbell,Peter J. Campbell,Michael R. Stratton,Michael R. Stratton +84 more
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Journal ArticleDOI
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Naiyer A. Rizvi,Naiyer A. Rizvi,Matthew D. Hellmann,Matthew D. Hellmann,Alexandra Snyder,Alexandra Snyder,Pia Kvistborg,Vladimir Makarov,Jonathan J. Havel,William Lee,Jianda Yuan,Phillip Wong,Teresa S. Ho,Martin L. Miller,Natasha Rekhtman,Andre L. Moreira,Fawzia Ibrahim,Cameron Bruggeman,Billel Gasmi,Roberta Zappasodi,Yuka Maeda,Chris Sander,Edward B. Garon,Taha Merghoub,Jedd D. Wolchok,Jedd D. Wolchok,Ton N. Schumacher,Timothy A. Chan,Timothy A. Chan +28 more
TL;DR: Treatment efficacy was associated with a higher number of mutations in the tumors, and a tumor-specific T cell response paralleled tumor regression in one patient, suggesting that the genomic landscape of lung cancers shapes response to anti–PD-1 therapy.