Principles of Resistance to Targeted Cancer Therapy: Lessons from Basic and Translational Cancer Biology

Abstract

Identification of the genomic drivers of cancer has led to the clinical development of targeted therapies that strike at the heart of many malignancies. Nonetheless, many cancers outsmart such precision-medicine efforts, and thus therapeutic resistance contributes significantly to cancer mortality. Attempts to understand the basis for resistance in patient samples and laboratory models has yielded two major benefits: one, more effective chemical inhibitors and rational combination therapies are now employed to prevent or circumvent resistance pathways; and two, our understanding of how oncogenic mutations drive cancer cell survival and oncogene addiction is deeper and broader, highlighting downstream or parallel cellular programs that shape these phenotypes. This review discusses emerging principles of resistance to therapies targeted against key oncogenic drivers.

Keywords: cancer; oncogene addiction; resistance; tyrosine kinase inhibitors.

Figure 1.. Drivers of malignant melanoma and non-small cell lung cancer.

A schematic of signaling pathways that promote oncogenic transformation when aberrantly activated by mutations in malignant melanoma (blue box) or non-small cell lung cancer (NSCLC; red box).

Figure 2.. Upstream or downstream activation of signaling as a mechanism of targeted therapy resistance.

A) In melanoma cells treated with BRAF inhibitors, downstream Mitogen Activated Protein (MAP) kinase signaling is attenuated (grayed out MEK and ERK). Amplification of RAS or loss of its negative regulator NF1 can restore MAP kinase signaling through parallel signal transduction using other RAF forms. B) In non-small cell lung cancer expressing the fusion oncogene EML4-ALK, ALK kinase inhibitors block activation of RAS from chimeric ALK proteins. Resistance can emerge through amplification of RAS, as in panel A, but in this case, it serves to activate MAP kinase downstream of the inhibited oncoprotein. Green: cancer-initiating mutant proteins; red, effects of targeted therapy; blue, resistance mechanisms.

Figure 3.. Parallel pathways to restore oncogenic signaling.

A) inhibition of EGFR in EGFR mutant non-small cell lung cancer can lead to amplification of ERBB3 or MET. Both of these receptor tyrosine kinases can then restore PI3K-AKT signaling independently of EGFR, conferring resistance. B) Androgen receptor (AR) normally drive a tumorigenic transcriptional program upon binding to androgens. Androgen receptor inhibitors may prevent AR from executing this program, but glucocorticoid receptor can compensate to restore the transcription of a number of common target genes, thus overcoming AR antagonists. Colors are coded as in Figure 2.

Figure 4.. Genetic and non-genetic reshaping of cancer cell lineage.

EGFR mutant non-small cell lung cancer can adapt through either RB1 loss and small cell transformation (top), or transcriptional reprogramming to promote epithelial-to-mesenchymal transformation (EMT; bottom). Both states promote EGFR inhibitor resistance, through downregulation of the mutant receptor, upregulation of alternative RTKs such as UFO, encoded by AXL, and other as yet undefined mechanisms. Colors are coded as in Figure 2.

Figure 5.. Strategies to overcome clinical acquired resistance in cancer.

A) Schematic of the current clinical approach: a biopsy may identify a driver mutation that is in the majority of cancer cells (black outline), but miss pre-existing resistance pathways (purple) and permit the outgrowth of others (blue). The result is a transient response that invariably gives rise to lethal resistance. B) Newer approaches may alter this trajectory; liquid biopsy might identify the heterogeneity that gives rise to early or later drug resistance, permitting combination therapy at diagnosis (black + purple arrows). Biopsy or resection of diseased tissue during therapy may permit the identification of a new resistant clone or demonstrate resolution of a prior one. An adaptive clinical trial design would permit testing of biomarker-driven, tailored therapy (black + blue arrows) on an individual patient level.