Katherine E. Hutchinson

Optimization of dosing for EGFR-mutant non-small cell lung cancer with evolutionary cancer modeling.

Predictive models of EGFR-mutant tumor behavior point to alternative drug dosing strategies to prevent and treat acquired resistance. Harnessing Evolution to Improve Lung Cancer Therapy Like any organism under severe evolutionary pressure, a few select members of a cancer cell population acquire molecular changes that strengthen the clan’s chances of survival. Therapeutic drugs exert a powerful selective force on characteristically compliant cancer cells, as the common recurrence of drug-resistant cancers testifies. To learn how to better fight the potent forces of evolution, Chmielecki et al. examined the behavior of non–small cell lung cancer (NSCLC) before and after the cells acquire resistance to targeted therapy, which inevitably they do. The growth characteristics of these cells were consistent with patient tumor behavior, enabling construction of a mathematical model that predicted alternative therapeutic strategies to delay the development of drug-resistant cancer cells. The authors made paired isogenic cell lines that were sensitive and resistant to afatinib and erlotinib—drugs used to treat NSCLC that are directed against the epidermal growth factor receptor (EGFR) tyrosine kinase, which is activated in a subset of NSCLCs. To the authors’ surprise, the drug-resistant cells grew more slowly than their sensitive counterparts, and resistance was not maintained in the absence of selection. Multiple clinical observations corroborated these findings. For example, patients with resistant tumors showed a slow course of disease progression, and patients with acquired resistance have re-responded to tyrosine kinase inhibitor (TKI) therapy after a drug holiday. The authors then constructed an evolutionary mathematical model of tumor behavior based on the differential growth rates of TKI-sensitive and TKI-resistant cells in heterogeneous tumor cell populations. Understanding the growth dynamics of how tumors behave allowed the authors to calculate what would happen under different treatment regimes. Their models predicted that continuous administration of a low-dose EGFR TKI combined with high-dose pulses of an EGFR TKI should delay the onset of resistance. Subsequent cellular studies bore out this prediction. Modeling also indicated the wisdom of prolonging treatment with the EGFR TKI after the development of resistance to prevent fast overgrowth by the sensitive cells, a result also born out in vitro and in vivo. Ultimate proof will have to come from patients. Clinical trials based on these alternative dosing strategies will be the true test of the utility of evolutionary mathematical modeling in designing cancer treatments. If they prove beneficial, individual models based on the characteristics of diverse cancer cell types could offer clues for designing optimal treatment strategies. Non–small cell lung cancers (NSCLCs) that harbor mutations within the epidermal growth factor receptor (EGFR) gene are sensitive to the tyrosine kinase inhibitors (TKIs) gefitinib and erlotinib. Unfortunately, all patients treated with these drugs will acquire resistance, most commonly as a result of a secondary mutation within EGFR (T790M). Because both drugs were developed to target wild-type EGFR, we hypothesized that current dosing schedules were not optimized for mutant EGFR or to prevent resistance. To investigate this further, we developed isogenic TKI-sensitive and TKI-resistant pairs of cell lines that mimic the behavior of human tumors. We determined that the drug-sensitive and drug-resistant EGFR-mutant cells exhibited differential growth kinetics, with the drug-resistant cells showing slower growth. We incorporated these data into evolutionary mathematical cancer models with constraints derived from clinical data sets. This modeling predicted alternative therapeutic strategies that could prolong the clinical benefit of TKIs against EGFR-mutant NSCLCs by delaying the development of resistance.

A Platform for Rapid Detection of Multiple Oncogenic Mutations With Relevance to Targeted Therapy in Non-Small-Cell Lung Cancer

The identification of somatically acquired tumor mutations is increasingly important in the clinical management of cancer because the sensitivity of targeted drugs is related to the genetic makeup of individual tumors. Thus, mutational profiles of tumors can help prioritize anticancer therapy. We report herein the development and validation of two multiplexed assays designed to detect in DNA from FFPE tissue more than 40 recurrent mutations in nine genes relevant to existing and emerging targeted therapies in lung cancer. The platform involves two methods: a screen (SNaPshot) based on multiplex PCR, primer extension, and capillary electrophoresis that was designed to assess for 38 somatic mutations in eight genes (AKT1, BRAF, EGFR, KRAS, MEK1, NRAS, PIK3CA, and PTEN) and a PCR-based sizing assay that assesses for EGFR exon 19 deletions, EGFR exon 20 insertions, and HER2 exon 20 insertions. Both the SNaPshot and sizing assays can be performed rapidly, with minimal amounts of genetic material. Compared with direct sequencing, in which mutant DNA needs to compose 25% or more of the total DNA to easily detect a mutation, the SNaPshot and sizing assays can detect mutations in samples in which mutant DNA composes 1.56% to 12.5% and 1.56% to 6.25% of the total DNA, respectively. These robust, reliable, and relatively inexpensive assays should help accelerate adoption of a genotype-driven approach in the treatment of lung cancer.

Chipping away at the lung cancer genome

Kinase inhibitors are now standard treatment for patients with lung cancer whose tumors harbor specific mutant kinases. Four recent studies, including three in this issue (pages 375–384), have identified new fusion proteins involving another receptor tyrosine kinase that may potentially be responsive to existing targeted therapies.

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.

BRAF Fusions Define a Distinct Molecular Subset of Melanomas with Potential Sensitivity to MEK Inhibition

Purpose: Recurrent “driver” mutations at specific loci in BRAF, NRAS, KIT, GNAQ, and GNA11 define clinically relevant molecular subsets of melanoma, but more than 30% are “pan-negative” for these recurrent mutations. We sought to identify additional potential drivers in “pan-negative” melanoma. Experimental Design: Using a targeted next-generation sequencing (NGS) assay (FoundationOne™) and targeted RNA sequencing, we identified a novel PAPSS1-BRAF fusion in a “pan-negative” melanoma. We then analyzed NGS data from 51 additional melanomas genotyped by FoundationOne™, as well as melanoma RNA, whole-genome and whole-exome sequencing data in The Cancer Genome Atlas (TCGA), to determine the potential frequency of BRAF fusions in melanoma. We characterized the signaling properties of confirmed molecular alterations by ectopic expression of engineered cDNAs in 293H cells. Results: Activation of the mitogen-activated protein kinase (MAPK) pathway in cells by ectopic expression of PAPSS1-BRAF was abrogated by mitogen-activated protein kinase kinase (MEK) inhibition but not by BRAF inhibition. NGS data analysis of 51 additional melanomas revealed a second BRAF fusion (TRIM24-BRAF) in a “pan-negative” sample; MAPK signaling induced by TRIM24-BRAF was also MEK inhibitor sensitive. Through mining TCGA skin cutaneous melanoma dataset, we further identified two potential BRAF fusions in another 49 “pan-negative” cases. Conclusions: BRAF fusions define a new molecular subset of melanoma, potentially comprising 4% to 8% of “pan-negative” cases. Their presence may explain an unexpected clinical response to MEK inhibitor therapy or assist in selecting patients for MEK-directed therapy. Clin Cancer Res; 19(24); 6696–702. ©2013 AACR.

A Meta-analysis of Somatic Mutations from Next Generation Sequencing of 241 Melanomas: A Road Map for the Study of Genes with Potential Clinical Relevance

Next generation sequencing (NGS) has been used to characterize the overall genomic landscape of melanomas. Here, we systematically examined mutations from recently published melanoma NGS data involving 241 paired tumor-normal samples to identify potentially clinically relevant mutations. Melanomas were characterized according to an in-house clinical assay that identifies well-known specific recurrent mutations in five driver genes: BRAF (affecting V600), NRAS (G12, G13, and Q61), KIT (W557, V559, L576, K642, and D816), GNAQ (Q209), and GNA11 (Q209). Tumors with none of these mutations are termed “pan negative.” We then mined the driver mutation-positive and pan-negative melanoma NGS data for mutations in 632 cancer genes that could influence existing or emerging targeted therapies. First, we uncovered several genes whose mutations were more likely associated with BRAF- or NRAS-driven melanomas, including TP53 and COL1A1 with BRAF, and PPP6C, KALRN, PIK3R4, TRPM6, GUCY2C, and PRKAA2 with NRAS. Second, we found that the 69 “pan-negative” melanoma genomes harbored alternate infrequent mutations in the five known driver genes along with many mutations in genes encoding guanine nucleotide binding protein α-subunits. Third, we identified 12 significantly mutated genes in “pan-negative” samples (ALK, STK31, DGKI, RAC1, EPHA4, ADAMTS18, EPHA7, ERBB4, TAF1L, NF1, SYK, and KDR), including five genes (RAC1, ADAMTS18, EPHA7, TAF1L, and NF1) with a recurrent mutation in at least two “pan-negative” tumor samples. This meta-analysis provides a road map for the study of additional potentially actionable genes in both driver mutation-positive and pan-negative melanomas. Mol Cancer Ther; 13(7); 1918–28. ©2014 AACR.

Comprehensive genomic profiling of pancreatic acinar cell carcinomas identifies recurrent RAF fusions and frequent inactivation of DNA repair genes

UNLABELLED Pancreatic acinar cell carcinomas (PACC) account for approximately 1% (∼500 cases) of pancreatic cancer diagnoses annually in the United States. Oncogenic therapuetic targets have proven elusive in this disease, and chemotherapy and radiotherapy have demonstrated limited efficacy against these tumors. Comprehensive genomic profiling of a large series of PACCs (n=44) identified recurrent rearrangements involving BRAF and RAF1 (CRAF) in approximately 23% of tumors. The most prevalent fusion, SND1-BRAF, resulted in activation of the MAPK pathway, which was abrogated with MEK inhibition. SND1-BRAF-transformed cells were sensitive to treatment with the MEK inhibitor trametinib. PACCs lacking RAF rearrangements were significantly enriched for genomic alterations, causing inactivation of DNA repair genes (45%); these genomic alterations have been associated with sensitivity to platinum-based therapies and PARP inhibitors. Collectively, these results identify potentially actionable genomic alterations in the majority of PACCs and provide a rationale for using personalized therapies in this disease. SIGNIFICANCE PACC is genomically distinct from other pancreatic cancers. Fusions in RAF genes and mutually exclusive inactivation of DNA repair genes represent novel potential therapeutic targets that are altered in over two thirds of these tumors.

The receptor tyrosine kinase ErbB3 maintains the balance between luminal and basal breast epithelium

ErbB3 harbors weak kinase activity, but strongly activates downstream phosphatidylinositol 3-kinase/Akt signaling through heterodimerization with and activation by other ErbB receptor tyrosine kinases. We report here that ErbB3 loss in the luminal mammary epithelium of mice impaired Akt and MAPK signaling and reduced luminal cell proliferation and survival. ERBB3 mRNA expression levels were highest in luminal mammary populations and lowest in basal cell/stem cell populations. ErbB3 loss in mammary epithelial cells shifted gene expression patterns toward a mammary basal cell/stem cell signature. ErbB3 depletion-induced gene expression changes were rescued upon activation of Akt and MAPK signaling. Interestingly, proliferation and expansion of the mammary basal epithelium (BE) occurred upon ErbB3 targeting in the luminal epithelium, but not upon its targeting in the BE. Multiple cytokines, including interleukin 6, were induced upon ErbB3 depletion in luminal epithelium cells, which increased growth of BE cells. Taken together, these results suggest that ErbB3 regulates the balance of differentiated breast epithelial cell types by regulating their growth and survival through autocrine- and paracrine-signaling mechanisms.

Targeted next-generation sequencing of DNA regions proximal to a conserved GXGXXG signaling motif enables systematic discovery of tyrosine kinase fusions in cancer

Tyrosine kinase (TK) fusions are attractive drug targets in cancers. However, rapid identification of these lesions has been hampered by experimental limitations. Our in silico analysis of known cancer-derived TK fusions revealed that most breakpoints occur within a defined region upstream of a conserved GXGXXG kinase motif. We therefore designed a novel DNA-based targeted sequencing approach to screen systematically for fusions within the 90 human TKs; it should detect 92% of known TK fusions. We deliberately paired ‘in-solution’ DNA capture with 454 sequencing to minimize starting material requirements, take advantage of long sequence reads, and facilitate mapping of fusions. To validate this platform, we analyzed genomic DNA from thyroid cancer cells (TPC-1) and leukemia cells (KG-1) with fusions known only at the mRNA level. We readily identified for the first time the genomic fusion sequences of CCDC6-RET in TPC-1 cells and FGFR1OP2-FGFR1 in KG-1 cells. These data demonstrate the feasibility of this approach to identify TK fusions across multiple human cancers in a high-throughput, unbiased manner. This method is distinct from other similar efforts, because it focuses specifically on targets with therapeutic potential, uses only 1.5 µg of DNA, and circumvents the need for complex computational sequence analysis.

ErbB3 downregulation enhances luminal breast tumor response to antiestrogens

Aberrant regulation of the erythroblastosis oncogene B (ErbB) family of receptor tyrosine kinases (RTKs) and their ligands is common in human cancers. ErbB3 is required in luminal mammary epithelial cells (MECs) for growth and survival. Since breast cancer phenotypes may reflect biological traits of the MECs from which they originate, we tested the hypothesis that ErbB3 drives luminal breast cancer growth. We found higher ERBB3 expression and more frequent ERBB3 gene copy gains in luminal A/B breast cancers compared with other breast cancer subtypes. In cell culture, ErbB3 increased growth of luminal breast cancer cells. Targeted depletion of ErbB3 with an anti-ErbB3 antibody decreased 3D colony growth, increased apoptosis, and decreased tumor growth in vivo. Treatment of clinical breast tumors with the antiendocrine drug fulvestrant resulted in increased ErbB3 expression and PI3K/mTOR signaling. Depletion of ErbB3 in fulvestrant-treated tumor cells reduced PI3K/mTOR signaling, thus decreasing tumor cell survival and tumor growth. Fulvestrant treatment increased phosphorylation of all ErbB family RTKs; however, phospho-RTK upregulation was not seen in tumors treated with both fulvestrant and anti-ErbB3. These data indicate that upregulation of ErbB3 in luminal breast cancer cells promotes growth, survival, and resistance to fulvestrant, thus suggesting ErbB3 as a target for breast cancer treatment.