Precision Medicine—An Inevitable (Though Challenging) Goal!
Andre Goy, MD
Oncology & Biotech News
Chairman and Director
Lymphoma Division Chief John Theurer Cancer Center at HackensackUMC
Chief Science Officer and Director of Research and Innovation Regional Cancer Care Associates
Professor of Medicine,
From then on, many new compounds (mostly cytotoxics) were established using the standard clinical trial approach. Combination regimens appeared in the mid-1960s, thanks to Holland, Freireich, and Frei, who hypothesized that cancer chemotherapy should follow the strategy of antibiotic therapy for tuberculosis. Subsequently, all combination chemotherapy regimens were developed empirically by using drugs with distinct mechanisms of action affecting DNA (directly or indirectly) or cells’ microtubules. Retrospectively, it seems oncologists had hit a wall in terms of results for several decades, though dramatic progress was being made toward understanding the mechanisms underlying cancer.
The enormous progress of cell biology applied to cancer cells led to the publication of the initial classic six hallmarks of cancer in 2000, which then appeared much more complex in the updated version a decade later (Cell. 2011;144:646- 674). Meanwhile, it was conceptualized then that cancer cells relied on deregulated pathways—particularly either loss of tumor suppressor genes or gain of oncogenes function, leading to the concept of oncogene addiction—which in itself provided an obvious rationale for targeted intervention.
The Human Genome Project, completed in 2003, mapped the 25,000 genes in the genetic code and ushered in the era of personalized medicine. The era of targeted therapy was launched with targeting HER2 with trastuzumab in breast cancer (Slamon et al. N Engl J Med. 2001;344:783-792.) and with targeting BCRABL with imatinib in chronic myeloid leukemia (Druker et al. N Engl J Med. 2001;344:1031-1037). Since then, an impressive number of targeted approaches have been developed that either help pick a drug (eg, crizotinib for ALK-positive NSCLC, erlotinib for EGFR-positive NSCLC, PARPi in BRCA1/2-mutated malignancies, vemurafenib in BRAF V600E-positive melanoma) or identify patients for whom a drug is unlikely to benefit (eg, patients with KRAS-positive colorectal cancer are unlikely to benefit from anti- EGFR therapy).
Though these examples are quite dramatic, unfortunately they represent only a true minority of patients. The Human Genome Project will definitely remain as a landmark in the evolution of medicine at large, though a dramatic acceleration has taken place since then. The high throughput technologies developed then have led to the genomics of cancer, which have revealed a daunting diversity, both interpatient, but also within a patient (clonal heterogeneity).
The heterogeneity of cancer arises in large part from genetic variation, where the random mutation frequency in human cancer cells is over 100- to 500-fold greater than in adjacent tumor cells. The mutational landscape (insertions, deletions, fusions, etc) of cancer is extremely complex (beyond the point of this editorial) and multilayered -omics have emerged from DNA, RNA, and epigenetic differences, to metabolomics and eventually, functional proteomics. This remarkable tumor heterogeneity will likely represent a major challenge to personalized medicine and biomarkers development.
It is clear, however, that even for tumors with thousands of mutations, a limited number of them are critical in cancer cell behavior—driver mutations—while many others are considered passenger mutations—potential noise in data interpretation. While the price of whole genome sequencing has dramatically improved—Illumina launched its HiSeq X Ten sequencer this year, which delivers the first $1000 genome at 30x coverage— the difficulty resides in the interpretation of the data from complex bioinformatics to actionable items in routine practice. Massive parallel sequencing or next generation sequencing offers a platform that can deliver answers (profiles) within 2 weeks and usually focuses on mutations (a few hundred) believed to be relevant in cancer cell biology.