Enigmas in tumor resistance to kinase inhibitors and calculation of the drug resistance index for cancer (DRIC). (August 2017)

• Record Type: Journal Article
• Authors: Smith, C.I. Edvard
• Is Part Of: Seminars in cancer biology. Volume 45(2017)
• Page Start: 36
• Page End: 49
• Publication Date: 2017-08
• Subjects: Acalabrutinib -- Alectinib -- Brigatinib -- Ceritinib -- Crizotinib -- Dabrafenib -- Dasatinib -- Erlotinib -- Gefitinib -- Ibrutinib -- Imatinib -- Lorlatinib -- Nilotinib -- Osimertinib -- Rociletinib -- Trametinib -- Vemurafenib; Cancer -- Periodicals; Neoplasms -- Periodicals; Review Literature; Cancer -- Périodiques; Electronic journals; 616.994
• DOI: 10.1016/j.semcancer.2016.11.008
• Languages: English
• ISSNs: 1044-579X

Abstract

Abstract: Darwinian selection is also applicable when antibiotics, the immune system or other host factors shape the repertoire of microorganisms, and similarly, clonal selection is the hallmark of tumor evolution. The ongoing revolution in new anti-cancer treatment modalities, combined with an unprecedented precision in characterizing malignant clones at the level below one percent, profoundly improves the understanding of repertoire-tuning mechanisms. There is no fundamental difference between selection of the tumor cells in the presence, or absence, of therapy. However, under treatment the influence of a single agent can be measured, simplifying the analysis. Because of their beneficial and selective therapeutic effect, the focus in this review is set on protein kinase inhibitors (PKIs), predominantly tyrosine kinase inhibitors (TKIs). This is one of the most rapidly growing families of novel cancer medicines. In order to limit the number of drugs, the following representative target kinases are included: ALK, BCR-ABL, BRAF, BTK, and EGFR. A key therapeutic challenge is how to reduce tumor growth after treatment, since this is rate-limiting for the generation and expansion of more malignant escape mutants. Thus, upon efficient treatment, tumor cell loss often enables a profoundly increased growth rate among resistant cells. Strategies to reduce this risk, such as concomitant, competitive outgrowth of non-transformed cells, are described. Seven parameters: 1. Drug type, 2. tumor type, 3. presence of metastases or phenotypic change, 4. tumor cell number, 5. net growth rate (proliferation minus cell death), 6. inherited genetic- and 7. epigenetic- variations are crucial for drug responses. It is envisaged that it might become possible to calculate a clinically relevant Drug Resistance Index for Cancer (DRIC) for each patient.