Jennifer L. Harris

Bio: Jennifer L. Harris is an academic researcher from Genomics Institute of the Novartis Research Foundation. The author has contributed to research in topics: Protease & Proteases. The author has an hindex of 36, co-authored 72 publications receiving 10688 citations. Previous affiliations of Jennifer L. Harris include Scripps Research Institute.

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

Abstract: The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.

The ALK Inhibitor Ceritinib Overcomes Crizotinib Resistance in Non–Small Cell Lung Cancer

Abstract: Non-small cell lung cancers (NSCLC) harboring anaplastic lymphoma kinase (ALK) gene rearrangements invariably develop resistance to the ALK tyrosine kinase inhibitor (TKI) crizotinib. Herein, we report the first preclinical evaluation of the next-generation ALK TKI, ceritinib (LDK378) in the setting of crizotinib resistance. Interrogation of in vitro and in vivo models of acquired resistance to crizotinib, including cell lines established from biopsies of crizotinib-resistant NSCLC patients revealed that ceritinib potently overcomes crizotinib resistance mutations. In particular, ceritinib effectively inhibits ALK harboring L1196M, G1269A, I1171T and S1206Y mutations, and a co-crystal of ceritinib bound to ALK provides structural bases for this increased potency. However, we observed that ceritinib did not overcome two crizotinib-resistant ALK mutations, G1202R and F1174C, and one of these mutations were identified in 5 out of 11 biopsies from patients with acquired resistance to ceritinib. Altogether our results demonstrate that ceritinib can overcome crizotinib resistance, consistent with clinical data showing marked efficacy of ceritinib in patients with crizotinib-resistant disease.

Targeting Wnt-driven cancer through the inhibition of Porcupine by LGK974

Abstract: Wnt signaling is one of the key oncogenic pathways in multiple cancers, and targeting this pathway is an attractive therapeutic approach. However, therapeutic success has been limited because of the lack of therapeutic agents for targets in the Wnt pathway and the lack of a defined patient population that would be sensitive to a Wnt inhibitor. We developed a screen for small molecules that block Wnt secretion. This effort led to the discovery of LGK974, a potent and specific small-molecule Porcupine (PORCN) inhibitor. PORCN is a membrane-bound O-acyltransferase that is required for and dedicated to palmitoylation of Wnt ligands, a necessary step in the processing of Wnt ligand secretion. We show that LGK974 potently inhibits Wnt signaling in vitro and in vivo, including reduction of the Wnt-dependent LRP6 phosphorylation and the expression of Wnt target genes, such as AXIN2. LGK974 is potent and efficacious in multiple tumor models at well-tolerated doses in vivo, including murine and rat mechanistic breast cancer models driven by MMTV-Wnt1 and a human head and neck squamous cell carcinoma model (HN30). We also show that head and neck cancer cell lines with loss-of-function mutations in the Notch signaling pathway have a high response rate to LGK974. Together, these findings provide both a strategy and tools for targeting Wnt-driven cancers through the inhibition of PORCN.

Overcoming EGFR(T790M) and EGFR(C797S) resistance with mutant-selective allosteric inhibitors

Abstract: The epidermal growth factor receptor (EGFR)-directed tyrosine kinase inhibitors (TKIs) gefitinib, erlotinib and afatinib are approved treatments for non-small cell lung cancers harbouring activating mutations in the EGFR kinase, but resistance arises rapidly, most frequently owing to the secondary T790M mutation within the ATP site of the receptor. Recently developed mutant-selective irreversible inhibitors are highly active against the T790M mutant, but their efficacy can be compromised by acquired mutation of C797, the cysteine residue with which they form a key covalent bond. All current EGFR TKIs target the ATP-site of the kinase, highlighting the need for therapeutic agents with alternative mechanisms of action. Here we describe the rational discovery of EAI045, an allosteric inhibitor that targets selected drug-resistant EGFR mutants but spares the wild-type receptor. The crystal structure shows that the compound binds an allosteric site created by the displacement of the regulatory C-helix in an inactive conformation of the kinase. The compound inhibits L858R/T790M-mutant EGFR with low-nanomolar potency in biochemical assays. However, as a single agent it is not effective in blocking EGFR-driven proliferation in cells owing to differential potency on the two subunits of the dimeric receptor, which interact in an asymmetric manner in the active state. We observe marked synergy of EAI045 with cetuximab, an antibody therapeutic that blocks EGFR dimerization, rendering the kinase uniformly susceptible to the allosteric agent. EAI045 in combination with cetuximab is effective in mouse models of lung cancer driven by EGFR(L858R/T790M) and by EGFR(L858R/T790M/C797S), a mutant that is resistant to all currently available EGFR TKIs. More generally, our findings illustrate the utility of purposefully targeting allosteric sites to obtain mutant-selective inhibitors.

Synthesis, Structure–Activity Relationships, and in Vivo Efficacy of the Novel Potent and Selective Anaplastic Lymphoma Kinase (ALK) Inhibitor 5-Chloro-N2-(2-isopropoxy-5-methyl-4-(piperidin-4-yl)phenyl)-N4-(2-(isopropylsulfonyl)phenyl)pyrimidine-2,4-diamine (LDK378) Currently in Phase 1 and Phase 2 Clinical Trials

Abstract: The synthesis, preclinical profile, and in vivo efficacy in rat xenograft models of the novel and selective anaplastic lymphoma kinase inhibitor 15b (LDK378) are described. In this initial report, preliminary structure–activity relationships (SARs) are described as well as the rational design strategy employed to overcome the development deficiencies of the first generation ALK inhibitor 4 (TAE684). Compound 15b is currently in phase 1 and phase 2 clinical trials with substantial antitumor activity being observed in ALK-positive cancer patients.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal

Abstract: The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

Abstract: A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era

The Molecular Signatures Database Hallmark Gene Set Collection

Abstract: The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of “hallmark” gene sets as part of MSigDB. Each hallmark in this collection consists of a “refined” gene set, derived from multiple “founder” sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

The cancer genome atlas pan-cancer analysis project

Abstract: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.