Aneuploidy and copy-number alterations (CNAs) are a hallmark of human cancer. Although genetically engineered mouse models (GEMMs) are commonly used to model human cancer, their chromosomal landscapes remain underexplored. Here we use gene expression profiles to infer CNAs in 3,108 samples from 45 mouse models, providing the first comprehensive catalogue of chromosomal aberrations in cancer GEMMs. Mining this resource, we find that most chromosomal aberrations accumulate late during breast tumorigenesis, and observe marked differences in CNA prevalence between mouse mammary tumours initiated with distinct drivers. Some aberrations are recurrent and unique to specific GEMMs, suggesting distinct driver-dependent routes to tumorigenesis. Synteny-based comparison of mouse and human tumours narrows critical regions in CNAs, thereby identifying candidate driver genes. We experimentally validate that loss of Stratifin (SFN) promotes HER2-induced tumorigenesis in human cells. These results demonstrate the power of GEMM CNA analysis to inform the pathogenesis of human cancer.

IMPORTANCE: Randomized clinical trials demonstrate no benefit for epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors in unselected patients with head and neck squamous cell carcinoma (HNSCC). However, a patient with stage IVA HNSCC received 13 days of neoadjuvant erlotinib and experienced a near-complete histologic response. OBJECTIVE: To determine a mechanism of exceptional response to erlotinib therapy in HNSCC. DESIGN, SETTING, AND PARTICIPANTS: Single patient with locally advanced HNSCC who received erlotinib monotherapy in a window-of-opportunity clinical trial (patients scheduled to undergo primary cancer surgery are treated briefly with an investigational agent). Whole-exome sequencing of pretreatment tumor and germline patient samples was performed at a quaternary care academic medical center, and a candidate somatic variant was experimentally investigated for mediating erlotinib response. INTERVENTION: A brief course of erlotinib monotherapy followed by surgical resection. MAIN OUTCOMES AND MEASURES: Identification of pretreatment tumor somatic alterations that may contribute to the exceptional response to erlotinib. Hypotheses were formulated regarding enhanced erlotinib response in preclinical models harboring the patient tumor somatic variant MAPK1 E322K following the identification of tumor somatic variants. RESULTS: No EGFR alterations were observed in the pretreatment tumor DNA. Paradoxically, the tumor harbored an activating MAPK1 E322K mutation (allelic fraction 0.13), which predicts ERK activation and erlotinib resistance in EGFR-mutant lung cancer. The HNSCC cells with MAPK1 E322K exhibited enhanced EGFR phosphorylation and erlotinib sensitivity compared with wild-type MAPK1 cells. CONCLUSIONS AND RELEVANCE: Selective erlotinib use in HNSCC may be informed by precision oncology approaches.

Large-scale tumor sequencing projects enabled the identification of many new cancer gene candidates through computational approaches. Here, we describe a general method to detect cancer genes based on significant 3D clustering of mutations relative to the structure of the encoded protein products. The approach can also be used to search for proteins with an enrichment of mutations at binding interfaces with a protein, nucleic acid, or small molecule partner. We applied this approach to systematically analyze the PanCancer compendium of somatic mutations from 4,742 tumors relative to all known 3D structures of human proteins in the Protein Data Bank. We detected significant 3D clustering of missense mutations in several previously known oncoproteins including HRAS, EGFR, and PIK3CA. Although clustering of missense mutations is often regarded as a hallmark of oncoproteins, we observed that a number of tumor suppressors, including FBXW7, VHL, and STK11, also showed such clustering. Beside these known cases, we also identified significant 3D clustering of missense mutations in NUF2, which encodes a component of the kinetochore, that could affect chromosome segregation and lead to aneuploidy. Analysis of interaction interfaces revealed enrichment of mutations in the interfaces between FBXW7-CCNE1, HRAS-RASA1, CUL4B-CAND1, OGT-HCFC1, PPP2R1A-PPP2R5C/PPP2R2A, DICER1-Mg2+, MAX-DNA, SRSF2-RNA, and others. Together, our results indicate that systematic consideration of 3D structure can assist in the identification of cancer genes and in the understanding of the functional role of their mutations.

Jesse Boehm and Todd Golub call for an international effort to establish >10,000 cancer cell line models as a community resource. Cancer cell line factories will facilitate the creation of a cancer dependency map, connecting cancer genomics to therapeutic dependencies.

Crystallization of a maltose-binding protein MCL1 fusion has yielded a robust crystallography platform that generated the first apo MCL1 crystal structure, as well as five ligand-bound structures. The ability to obtain fragment-bound structures advances structure-based drug design efforts that, despite considerable effort, had previously been intractable by crystallography. In the ligand-independent crystal form we identify inhibitor binding modes not observed in earlier crystallographic systems. This MBP-MCL1 construct dramatically improves the structural understanding of well-validated MCL1 ligands, and will likely catalyze the structure-based optimization of high affinity MCL1 inhibitors.

Novel therapeutic approaches are urgently required for multiple myeloma (MM). We used a phenotypic screening approach using co-cultures of MM cells with bone marrow stromal cells to identify compounds that overcome stromal resistance. One such compound, BRD9876, displayed selectivity over normal hematopoietic progenitors and was discovered to be an unusual ATP non-competitive kinesin-5 (Eg5) inhibitor. A novel mutation caused resistance, suggesting a binding site distinct from known Eg5 inhibitors, and BRD9876 inhibited only microtubule-bound Eg5. Eg5 phosphorylation, which increases microtubule binding, uniquely enhanced BRD9876 activity. MM cells have greater phosphorylated Eg5 than hematopoietic cells, consistent with increased vulnerability specifically to BRD9876's mode of action. Thus, differences in Eg5-microtubule binding between malignant and normal blood cells may be exploited to treat multiple myeloma. Additional steps are required for further therapeutic development, but our results indicate that unbiased chemical biology approaches can identify therapeutic strategies unanticipated by prior knowledge of protein targets.

High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cell-based and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.

For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites.

The selectivity of an enzyme inhibitor is a key determinant of its usefulness as a tool compound or its safety as a drug. Yet selectivity is never assessed comprehensively in the early stages of the drug discovery process, and only rarely in the later stages, because technical limitations prohibit doing otherwise. Here, we report EnPlex, an efficient, high-throughput method for simultaneously assessing inhibitor potency and specificity, and pilot its application to 96 serine hydrolases. EnPlex analysis of widely used serine hydrolase inhibitors revealed numerous previously unrecognized off-target interactions, some of which may help to explain previously confounding adverse effects. In addition, EnPlex screening of a hydrolase-directed library of boronic acid- and nitrile-containing compounds provided structure-activity relationships in both potency and selectivity dimensions from which lead candidates could be more effectively prioritized. Follow-up of a series of dipeptidyl peptidase 4 inhibitors showed that EnPlex indeed predicted efficacy and safety in animal models. These results demonstrate the feasibility and value of high-throughput, superfamily-wide selectivity profiling and suggest that such profiling can be incorporated into the earliest stages of drug discovery.