Barbara L. Weber

Bio: Barbara L. Weber is an academic researcher from Novartis. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 21, co-authored 46 publications receiving 9616 citations. Previous affiliations of Barbara L. Weber include Harvard University & University of Utah.

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.

COT drives resistance to RAF inhibition through MAP kinase pathway reactivation

Abstract: Oncogenic mutations in the serine/threonine kinase B-RAF (also known as BRAF) are found in 50-70% of malignant melanomas. Pre-clinical studies have demonstrated that the B-RAF(V600E) mutation predicts a dependency on the mitogen-activated protein kinase (MAPK) signalling cascade in melanoma-an observation that has been validated by the success of RAF and MEK inhibitors in clinical trials. However, clinical responses to targeted anticancer therapeutics are frequently confounded by de novo or acquired resistance. Identification of resistance mechanisms in a manner that elucidates alternative 'druggable' targets may inform effective long-term treatment strategies. Here we expressed ∼600 kinase and kinase-related open reading frames (ORFs) in parallel to interrogate resistance to a selective RAF kinase inhibitor. We identified MAP3K8 (the gene encoding COT/Tpl2) as a MAPK pathway agonist that drives resistance to RAF inhibition in B-RAF(V600E) cell lines. COT activates ERK primarily through MEK-dependent mechanisms that do not require RAF signalling. Moreover, COT expression is associated with de novo resistance in B-RAF(V600E) cultured cell lines and acquired resistance in melanoma cells and tissue obtained from relapsing patients following treatment with MEK or RAF inhibitors. We further identify combinatorial MAPK pathway inhibition or targeting of COT kinase activity as possible therapeutic strategies for reducing MAPK pathway activation in this setting. Together, these results provide new insights into resistance mechanisms involving the MAPK pathway and articulate an integrative approach through which high-throughput functional screens may inform the development of novel therapeutic strategies.

Metabolic monitoring of breast cancer chemohormonotherapy using positron emission tomography: initial evaluation.

Abstract: PURPOSEWe assessed the feasibility of noninvasive metabolic monitoring of cancer chemohormonotherapy using sequential quantitative positron emission tomographic (PET) scans of tumor glucose metabolism with the glucose analog 2-[18F]-fluoro-2-deoxy-D-glucose (FDG).PATIENTS AND METHODSEleven women with newly diagnosed primary breast cancers larger than 3 cm in diameter beginning a chemohormonotherapy program underwent a baseline and four follow-up quantitative PET scans during the first three cycles of treatment (days 0 to 63). Tumor response was sequentially determined clinically, radiographically, and then pathologically after nine treatment cycles.RESULTSEight patients had partial or complete pathologic responses. Their maximal tumor uptake of FDG assessed by PET decreased promptly with treatment to the following: day 8, 78 +/- 9.2% (P < .03); day 21, 68.1 +/- 7.5% (P < .025); day 42, 60 +/- 5.1% (P < .001); day 63, 52.4 +/- 4.4% (P < .0001) of the basal values. Tumor diameter did not decrease significan...

A Collaborative Survey of 80 Mutations in the BRCA1 Breast and Ovarian Cancer Susceptibility Gene: Implications for Presymptomatic Testing and Screening

Abstract: Objectives. —To report the initial experience of an international group of investigators in identifying mutations in theBRCA1breast and ovarian cancer susceptibility gene, to assess the spectrum of such mutations in samples from patients with different family histories of cancer, and to determine the frequency of recurrent mutations. Design. —Nine laboratories in North America and the United Kingdom tested forBRCA 1mutations in DNA samples obtained from a total of 372 unrelated patients with breast or ovarian cancer largely chosen from high-risk families. Three of these laboratories also analyzed a total of 714 additional samples from breast or ovarian cancer cases, including 557 unselected for family history, for two specific mutations that had been found to recur in familial samples. Participants. —A total of 1086 women with either breast or ovarian cancer. Main Outcome Measure. —The detection of sequence variation in patients' DNA samples that is not found in sets of control samples. Results. —BRCA 1mutations have now been identified in a total of 80 patient samples. Thirty-eight distinct mutations were found among 63 mutations identified through a complete screen of theBRCA 1gene. Three specific mutations appeared relatively common, occurring eight, seven, and five times, respectively. When specific tests for the two most common mutations were performed in larger sets of samples, they were found in 17 additional patients. Mutations predicted to result in a truncated protein accounted for 86% of the mutations detected by complete screening. Conclusions. —The high frequency of protein-terminating mutations and the observation of many recurrent mutations found in a diverse set of samples could lead to a relatively simple diagnostic test forBRCA 1mutations. More data must be accumulated to address specifically the sensitivity and specificity of such a diagnostic testing procedure and to better estimate the age-specific risk for breast and ovarian cancer associated with such mutations. (JAMA. 1995;273:535-541)

Erratum: Addendum: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity (Nature (2012) 483 7391 (603-607))

Abstract: Jordi Barretina, Giordano Caponigro, Nicolas Stransky, Kavitha Venkatesan, Adam A. Margolin, Sungjoon Kim, Christopher J. Wilson, Joseph Lehár, Gregory V. Kryukov, Dmitriy Sonkin, Anupama Reddy, Manway Liu, Lauren Murray, Michael F. Berger, John E. Monahan, Paula Morais, Jodi Meltzer, Adam Korejwa, Judit Jané-Valbuena, Felipa A. Mapa, Joseph Thibault, Eva Bric-Furlong, Pichai Raman, Aaron Shipway, Ingo H. Engels, Jill Cheng, Guoying K. Yu, Jianjun Yu, Peter Aspesi Jr, Melanie de Silva, Kalpana Jagtap, Michael D. Jones, Li Wang, Charles Hatton, Emanuele Palescandolo, Supriya Gupta, Scott Mahan, Carrie Sougnez, Robert C. Onofrio, Ted Liefeld, Laura MacConaill, Wendy Winckler, Michael Reich, Nanxin Li, Jill P. Mesirov, Stacey B. Gabriel, Gad Getz, Kristin Ardlie, Vivien Chan, Vic E. Myer, Barbara L. Weber, Jeff Porter, Markus Warmuth, Peter Finan, Jennifer L. Harris, Matthew Meyerson, Todd R. Golub, Michael P. Morrissey, William R. Sellers, Robert Schlegel & Levi A. Garraway

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.

Improved Survival with Vemurafenib in Melanoma with BRAF V600E Mutation

Abstract: At 6 months, overall survival was 84% (95% confidence interval [CI], 78 to 89) in the vemurafenib group and 64% (95% CI, 56 to 73) in the dacarbazine group. In the interim analysis for overall survival and final analysis for progression-free survival, vemurafenib was associated with a relative reduction of 63% in the risk of death and of 74% in the risk of either death or disease progression, as compared with dacarbazine (P<0.001 for both comparisons). After review of the interim analysis by an independent data and safety monitoring board, crossover from dacarbazine to vemurafenib was recommended. Response rates were 48% for vemurafenib and 5% for dacarbazine. Common adverse events associated with vemurafenib were arthralgia, rash, fatigue, alopecia, keratoacanthoma or squamous-cell carcinoma, photosensitivity, nausea, and diarrhea; 38% of patients required dose modification because of toxic effects. Conclusions Vemurafenib produced improved rates of overall and progression-free survival in patients with previously untreated melanoma with the BRAF V600E mutation. (Funded by Hoffmann–La Roche; BRIM-3 ClinicalTrials.gov number, NCT01006980.)

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.

Enrichr: Interactive and collaborative HTML5 gene list enrichment analysis tool

Abstract: System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr .