Elevated phosphorylation of EGFR in NSCLC due to mutations in PTPRH.

The role of EGFR in lung cancer is well described with numerous activating mutations that result in phosphorylation and tyrosine kinase inhibitors that target EGFR. While the role of the EGFR kinase in non-small cell lung cancer (NSCLC) is appreciated, control of EGFR signaling pathways through dephosphorylation by phosphatases is not as clear. Through whole genome sequencing we have uncovered conserved V483M Ptprh mutations in PyMT induced tumors. Profiling the downstream events of Ptprh mutant tumors revealed AKT activation, suggesting a key target of PTPRH was EGFR tyrosine 1197. Given the role of EGFR in lung cancer, we explored TCGA data which revealed that a subset of PTPRH mutant tumors shared gene expression profiles with EGFR mutant tumors, but that EGFR mutations and PTPRH mutations were mutually exclusive. Generation of a PTPRH knockout NSCLC cell line resulted in Y1197 phosphorylation of EGFR, and a rescue with expression of wild type PTPRH returned EGFR phosphorylation to parental line values while rescue with catalytically dead PTPRH did not. A dose response curve illustrated that two human NSCLC lines with naturally occurring PTPRH mutations responded to EGFR tyrosine kinase inhibition. Osimertinib treatment of these tumors resulted in a reduction of tumor volume relative to vehicle controls. PTPRH mutation resulted in nuclear pEGFR as seen in immunohistochemistry, suggesting that there may also be a role for EGFR as a transcriptional co-factor. Together these data suggest mutations in PTPRH in NSCLC is inhibitory to PTPRH function, resulting in aberrant EGFR activity and ultimately may result in clinically actionable alterations using existing therapies.

Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers.

Human breast cancer has been characterized by extensive transcriptional heterogeneity, with dominant patterns reflected in the intrinsic subtypes. Mouse models of breast cancer also have heterogeneous transcriptomes and we noted that specific histological subtypes were associated with particular subsets. We hypothesized that unique sets of genes define each tumor histological type across mouse models of breast cancer. Using mouse models that contained both gene expression data and expert pathologist classification of tumor histology on a sample by sample basis, we predicted and validated gene expression signatures for Papillary, EMT, Microacinar and other histological subtypes. These signatures predict known histological events across murine breast cancer models and identify counterparts of mouse mammary tumor types in subtypes of human breast cancer. Importantly, the EMT, Adenomyoepithelial, and Solid signatures were predictive of clinical events in human breast cancer. In addition, a pan-cancer comparison revealed that the histological signatures were active in a variety of human cancers such as lung, oral, and esophageal squamous tumors. Finally, the differentiation status and transcriptional activity implicit within these signatures was identified. These data reveal that within tumor histology groups are unique gene expression profiles of differentiation and pathway activity that stretch well beyond the transgenic initiating events and that have clear applicability to human cancers. As a result, our work provides a predictive resource and insights into possible mechanisms that govern tumor heterogeneity.

How to Choose a Mouse Model of Breast Cancer, a Genomic Perspective.

Human breast cancer is a heterogeneous disease with numerous subtypes that have been defined through immunohistological, histological, and gene expression patterns. The diversity of breast cancer has made the study of its various underlying causes complex. To facilitate the examination of particular facets of breast cancer, mouse models have been generated, ranging from carcinogen induced models to genetically engineered mice. While mouse models have been generated to mimic the initiating event, including p53 loss, BRCA loss, or overexpression of HER2 / Neu / erbB2, other genomic events are often not well characterized. However, these secondary genetic events are often critical to the mouse tumor evolution, subtype, and outcome, just as they are in human breast cancer. As such, these other genomic events are a critical component of what models are chosen to study specific subtypes of human breast cancer. Here we review the genomic analyses that have been completed for various genetically engineered mouse models, how they compare to human breast cancer, and detail how this information can be used in choosing a mouse model for analysis.

Protomer selectivity of type II RAF inhibitors within the RAS/RAF complex.

RAF dimer inhibitors offer therapeutic potential in RAF- and RAS-driven cancers. The utility of such drugs is predicated on their capacity to occupy both RAF protomers in the RAS-RAF signaling complex. Here we describe a method to conditionally quantify drug-target occupancy at selected RAF protomers within an active RAS-RAF complex in cells. RAF target engagement can be measured in the presence or absence of any mutant KRAS allele, enabling the high-affinity state of RAF dimer inhibitors to be quantified in the cellular milieu. The intracellular protomer selectivity of clinical-stage type II RAF inhibitors revealed that ARAF protomer engagement, but not engagement of BRAF or CRAF, is commensurate with inhibition of MAPK signaling in various mutant RAS cell lines. Our results support a fundamental role for ARAF in mutant RAS signaling and reveal poor ARAF protomer vulnerability for a cohort of RAF inhibitors undergoing clinical evaluation.

Metastasis is altered through multiple processes regulated by the E2F1 transcription factor.

The E2F family of transcription factors is important for many cellular processes, from their canonical role in cell cycle regulation to other roles in angiogenesis and metastasis. Alteration of the Rb/E2F pathway occurs in various forms of cancer, including breast cancer. E2F1 ablation has been shown to decrease metastasis in MMTV-Neu and MMTV-PyMT transgenic mouse models of breast cancer. Here we take a bioinformatic approach to determine the E2F1 regulated genomic alterations involved in the metastatic cascade, in both Neu and PyMT models. Through gene expression analysis, we reveal few transcriptome changes in non-metastatic E2F1-/- tumors relative to transgenic tumor controls. However investigation of these models through whole genome sequencing found numerous differences between the models, including differences in the proposed tumor etiology between E2F1-/- and E2F1+/+ tumors induced by Neu or PyMT. For example, loss of E2F1 within the Neu model led to an increased contribution of the inefficient double stranded break repair signature to the proposed etiology of the tumors. While the SNV mutation burden was higher in PyMT mouse tumors than Neu mouse tumors, there was no statistically significant differences between E2F WT and E2F1 KO mice. Investigating mutated genes through gene set analysis also found a significant number of genes mutated in the cell adhesion pathway in E2F1-/- tumors, indicating this may be a route for disruption of metastasis in E2F1-/- tumors. Overall, these findings illustrate the complicated nature of uncovering drivers of the metastatic process.

E2F1 Drives Breast Cancer Metastasis by Regulating the Target Gene FGF13 and Altering Cell Migration.

In prior work we demonstrated that loss of E2F transcription factors inhibits metastasis. Here we address the mechanisms for this phenotype and identify the E2F regulated genes that coordinate tumor cell metastasis. Transcriptomic profiling of E2F1 knockout tumors identified a role for E2F1 as a master regulator of a suite of pro-metastatic genes, but also uncovered E2F1 target genes with an unknown role in pulmonary metastasis. High expression of one of these genes, Fgf13, is associated with early human breast cancer metastasis in a clinical dataset. Together these data led to the hypothesis that Fgf13 is critical for breast cancer metastasis, and that upregulation of Fgf13 may partially explain how E2F1 promotes breast cancer metastasis. To test this hypothesis we ablated Fgf13 via CRISPR. Deletion of Fgf13 in a MMTV-PyMT breast cancer cell line reduces colonization of the lungs in a tail vein injection. In addition, loss of Fgf13 reduced in vitro cell migration, suggesting that Fgf13 may be critical for tumor cells to escape the primary tumor and to colonize the distal sites. The significance of this work is twofold: we have both uncovered genomic features by which E2F1 regulates metastasis and we have identified new pro-metastatic functions for the E2F1 target gene Fgf13.