Cancer Diagnostics: The Future Ain't What It Used to Be

Abstract

Cancer is a genomic disease. Most cancers contain multiple genetics alterations that drive their unrestrained proliferation, progression and metastatic capacity. For most cancer types, it is known what these alterations are and what their frequency is. Genomics technologies have made it possible to identify these genetic alterations on an individual patient level in a short time frame. This is a major breakthrough, as it allows the clinical implementation of genomics-driven personalized or precision medicine. This means that the genomic data are used for the selection of the best treatment strategy for each patient. Another development that fuels this implementation is the growing repertoire of effective cancer therapies targeted against these drivers or driver signaling pathways. However, we know that targeted therapies are only effective in a subgroup of patients and that observed responses are often not durable. I reviewed the mechanisms of drug resistance to targeted therapies and discussed the lessons that we have learned for future developments. One of these developments is to combine multiple targeted therapies to increase effectiveness and delay or eventually overcome drug resistance. I identified a novel combination of the multikinase inhibitor sorafenib with the antidiabetic drug metformin that can be used in the treatment of lung cancer. I uncovered the mechanism underlying the combinatorial effect of these drugs and found that these compounds synergistically activate the AMP-activate protein kinase (AMPK) and thereby inhibit mTOR signaling. The subsequent chapters focus on the identification of molecular subgroups of breast cancer and bladder cancer. I studied a subgroup of ERα-positive breast cancers that are classified as basal-type instead of luminal-type. I found that those cancer express relatively high levels of the dominant-negative splice variant ERΔ7. The finding that the estrogen receptor signaling in these cancers is inactive, suggests that patients with ERα-positive basal-type breast cancer may not benefit from estrogen receptor antagonists (e.g. tamoxifen). Furthermore, I found that those patients have a high risk of developing disease recurrence. I discovered that activating ERBB2 missense mutations characterize a subgroup of muscle-invasive bladder cancer patients with complete response to neoadjuvant chemotherapy. This is important, as chemotherapy is currently the only approved drug therapy for bladder cancer. ERBB2 missense mutations can be used as a genomic biomarker to select patients who will benefit from neoadjuvant chemotherapy. In addition, I describe the identification of specific DNA copy number alterations that correlate with response to neoadjuvant chemotherapy. Together, the studies described contribute to a better selection of patients that will benefit from the anti-cancer therapy. My thesis is concluded with a general discussion on the clinical applicability of cancer genotyping for personalized medicine. This approach has completely changed the future of cancer diagnostics and therapeutics.