A view on drug resistance in cancer

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.

Fig. 1 |. A framework for understanding drug resistance.

a, Biological determinants of drug resistance. Tumours are heterogeneous and are situated in a milieu that comprises the basement membrane, vasculature, immune cells and tumour microenvironment, among other components. Changes in the physical parameters, genome and surrounding environment of the tumour drive drug resistance. b, Standard of care and emerging approaches to managing the biological determinants of resistance. The determinants of resistance can be targeted by a number of clinical diagnostic and therapeutic strategies.

Fig. 2 |. Proposed solutions to the problem of drug resistance in cancer.

a–d, Proposed solutions. Many technologies—including plasma-based tumour diagnostics, more-potent pharmacological strategies, computational and systems biology modelling and genetic screening—may help to prevent cancer drug resistance through interceding earlier; enhancing therapeutic efficacy; ascertaining disease burden and changing therapies; and beginning to detail the behaviour of cancer cells under therapy. Early detection and treatment of cancer (a), deeper therapeutic responses (b), therapeutic monitoring with adaptive interventions (c) and mapping cancer dependencies (d) can alter the natural history of cancer or its initial therapeutic trajectory to increase the probability of cure (solid blue lines). Grey solid lines show the trajectory before the indicated intervention; grey dashed lines show the trajectory if the indicated intervention were not performed (a, c) or performed less effectively (b).