Precision Cancer Medicine: Dynamic Learning of Cancer Biology in a Clinically Meaningful Context.

PURPOSE: Precision medicine is revolutionizing healthcare practices, most notably in oncology. With cancer being the second leading cause of death in the USA, it is important to integrate precision oncology content in undergraduate medical education. METHODS: In 2015, we launched a Clinical Cancer Medicine Integrated Science Course (ISC) for post-clerkship medical students at Vanderbilt University School of Medicine (VUSM). In this ISC, students learned cancer biology and clinical oncology concepts through a combination of classroom and patient care activities. Student feedback from mid- and end-of-course surveys and student match data were analyzed and used to develop ongoing course improvements. RESULTS: To date, 72 medical students have taken the Clinical Cancer Medicine ISC. Over 90% of students who completed end-of-course surveys agreed or strongly agreed that this course advanced their foundational science knowledge in clinical cancer medicine, that clinical relevance was provided during non-clinical foundational science learning activities, and that foundational science learning was embedded in course clinical experiences. Students who took this course most commonly matched in Internal Medicine, Pathology, Pediatrics, and Radiation Oncology. VUSM students who matched into Pathology and Radiation Oncology were more likely to take this ISC than students who matched in other specialties. CONCLUSION: The Clinical Cancer Medicine ISC serves as a model for incorporating precision oncology, cancer biology foundational science, and oncology patient care activities in undergraduate medical education. The course prepares students to care for oncology patients in their fields of interests during their future career in medicine.

Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers.

BACKGROUND: Driven by high throughput next generation sequencing technologies and the pressing need to decipher cancer genomes, computational approaches for detecting somatic single nucleotide variants (sSNVs) have undergone dramatic improvements during the past 2 years. The recently developed tools typically compare a tumor sample directly with a matched normal sample at each variant locus in order to increase the accuracy of sSNV calling. These programs also address the detection of sSNVs at low allele frequencies, allowing for the study of tumor heterogeneity, cancer subclones, and mutation evolution in cancer development. METHODS: We used whole genome sequencing (Illumina Genome Analyzer IIx platform) of a melanoma sample and matched blood, whole exome sequencing (Illumina HiSeq 2000 platform) of 18 lung tumor-normal pairs and seven lung cancer cell lines to evaluate six tools for sSNV detection: EBCall, JointSNVMix, MuTect, SomaticSniper, Strelka, and VarScan 2, with a focus on MuTect and VarScan 2, two widely used publicly available software tools. Default/suggested parameters were used to run these tools. The missense sSNVs detected in these samples were validated through PCR and direct sequencing of genomic DNA from the samples. We also simulated 10 tumor-normal pairs to explore the ability of these programs to detect low allelic-frequency sSNVs. RESULTS: Out of the 237 sSNVs successfully validated in our cancer samples, VarScan 2 and MuTect detected the most of any tools (that is, 204 and 192, respectively). MuTect identified 11 more low-coverage validated sSNVs than VarScan 2, but missed 11 more sSNVs with alternate alleles in normal samples than VarScan 2. When examining the false calls of each tool using 169 invalidated sSNVs, we observed >63% false calls detected in the lung cancer cell lines had alternate alleles in normal samples. Additionally, from our simulation data, VarScan 2 identified more sSNVs than other tools, while MuTect characterized most low allelic-fraction sSNVs. CONCLUSIONS: Our study explored the typical false-positive and false-negative detections that arise from the use of sSNV-calling tools. Our results suggest that despite recent progress, these tools have significant room for improvement, especially in the discrimination of low coverage/allelic-frequency sSNVs and sSNVs with alternate alleles in normal samples.

BRAF(L597) mutations in melanoma are associated with sensitivity to MEK inhibitors.

UNLABELLED: Kinase inhibitors are accepted treatment for metastatic melanomas that harbor specific driver mutations in BRAF or KIT, but only 40% to 50% of cases are positive. To uncover other potential targetable mutations, we conducted whole-genome sequencing of a highly aggressive BRAF (V600) and KIT (W557, V559, L576, K642, and D816) wild-type melanoma. Surprisingly, we found a somatic BRAF(L597R) mutation in exon 15. Analysis of BRAF exon 15 in 49 tumors negative for BRAF(V600) mutations as well as driver mutations in KIT, NRAS, GNAQ, and GNA11, showed that two (4%) harbored L597 mutations and another two involved BRAF D594 and K601 mutations. In vitro signaling induced by L597R/S/Q mutants was suppressed by mitogen-activated protein (MAP)/extracellular signal-regulated kinase (ERK) kinase (MEK) inhibition. A patient with BRAF(L597S) mutant metastatic melanoma responded significantly to treatment with the MEK inhibitor, TAK-733. Collectively, these data show clinical significance to BRAF(L597) mutations in melanoma. SIGNIFICANCE: This study shows that cells harboring BRAF(L597R) mutants are sensitive to MEK inhibitor treatment, providing a rationale for routine screening and therapy of BRAF(L597R)-mutant melanoma.

Routine multiplex mutational profiling of melanomas enables enrollment in genotype-driven therapeutic trials.

PURPOSE: Knowledge of tumor mutation status is becoming increasingly important for the treatment of cancer, as mutation-specific inhibitors are being developed for clinical use that target only sub-populations of patients with particular tumor genotypes. Melanoma provides a recent example of this paradigm. We report here development, validation, and implementation of an assay designed to simultaneously detect 43 common somatic point mutations in 6 genes (BRAF, NRAS, KIT, GNAQ, GNA11, and CTNNB1) potentially relevant to existing and emerging targeted therapies specifically in melanoma. METHODS: The test utilizes the SNaPshot method (multiplex PCR, multiplex primer extension, and capillary electrophoresis) and can be performed rapidly with high sensitivity (requiring 5-10% mutant allele frequency) and minimal amounts of DNA (10-20 nanograms). The assay was validated using cell lines, fresh-frozen tissue, and formalin-fixed paraffin embedded tissue. Clinical characteristics and the impact on clinical trial enrollment were then assessed for the first 150 melanoma patients whose tumors were genotyped in the Vanderbilt molecular diagnostics lab. RESULTS: Directing this test to a single disease, 90 of 150 (60%) melanomas from sites throughout the body harbored a mutation tested, including 57, 23, 6, 3, and 2 mutations in BRAF, NRAS, GNAQ, KIT, and CTNNB1, respectively. Among BRAF V600 mutations, 79%, 12%, 5%, and 4% were V600E, V600K, V600R, and V600M, respectively. 23 of 54 (43%) patients with mutation harboring metastatic disease were subsequently enrolled in genotype-driven trials. CONCLUSION: We present development of a simple mutational profiling screen for clinically relevant mutations in melanoma. Adoption of this genetically-informed approach to the treatment of melanoma has already had an impact on clinical trial enrollment and prioritization of therapy for patients with the disease.

Modulators of prostate cancer cell proliferation and viability identified by short-hairpin RNA library screening.

There is significant need to identify novel prostate cancer drug targets because current hormone therapies eventually fail, leading to a drug-resistant and fatal disease termed castration-resistant prostate cancer. To functionally identify genes that, when silenced, decrease prostate cancer cell proliferation or induce cell death in combination with antiandrogens, we employed an RNA interference-based short hairpin RNA barcode screen in LNCaP human prostate cancer cells. We identified and validated four candidate genes (AKT1, PSMC1, STRADA, and TTK) that impaired growth when silenced in androgen receptor positive prostate cancer cells and enhanced the antiproliferative effects of antiandrogens. Inhibition of AKT with a pharmacologic inhibitor also induced apoptosis when combined with antiandrogens, consistent with recent evidence for PI3K and AR pathway crosstalk in prostate cancer cells. Recovery of hairpins targeting a known prostate cancer pathway validates the utility of shRNA library screening in prostate cancer as a broad strategy to identify new candidate drug targets.

RAF265 inhibits the growth of advanced human melanoma tumors.

PURPOSE: The purpose of this preclinical study was to determine the effectiveness of RAF265, a multikinase inhibitor, for treatment of human metastatic melanoma and to characterize traits associated with drug response. EXPERIMENTAL DESIGN: Advanced metastatic melanoma tumors from 34 patients were orthotopically implanted to nude mice. Tumors that grew in mice (17 of 34) were evaluated for response to RAF265 (40 mg/kg, every day) over 30 days. The relation between patient characteristics, gene mutation profile, global gene expression profile, and RAF265 effects on tumor growth, mitogen-activated protein/extracellular signal-regulated kinase (MEK)/extracellular signal-regulated kinase (ERK) phosphorylation, proliferation, and apoptosis markers was evaluated. RESULTS: Nine of the 17 tumors that successfully implanted (53%) were mutant BRAF (BRAF(V600E/K)), whereas eight of 17 (47%) tumors were BRAF wild type (BRAF(WT)). Tumor implants from 7 of 17 patients (41%) responded to RAF265 treatment with more than 50% reduction in tumor growth. Five of the 7 (71%) responders were BRAF(WT), of which 1 carried c-KIT(L576P) and another N-RAS(Q61R) mutation, while only 2 (29%) of the responding tumors were BRAF(V600E/K). Gene expression microarray data from nonimplanted tumors revealed that responders exhibited enriched expression of genes involved in cell growth, proliferation, development, cell signaling, gene expression, and cancer pathways. Although response to RAF265 did not correlate with pERK1/2 reduction, RAF265 responders did exhibit reduced pMEK1, reduced proliferation based upon reduced Ki-67, cyclin D1 and polo-like kinase1 levels, and induction of the apoptosis mediator BCL2-like 11. CONCLUSIONS: Orthotopic implants of patient tumors in mice may predict prognosis and treatment response for melanoma patients. A subpopulation of human melanoma tumors responds to RAF265 and can be characterized by gene mutation and gene expression profiles.