Showing papers by "Todd R. Golub published in 2013"

Mutational heterogeneity in cancer and the search for new cancer-associated genes

Abstract: Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer. These studies involve the sequencing of matched tumour-normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour-normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.

Exome and whole-genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity

Abstract: The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. With a 5-year survival rate of ~15%, the identification of new therapeutic targets for EAC is greatly important. We analyze the mutation spectra from whole-exome sequencing of 149 EAC tumor-normal pairs, 15 of which have also been subjected to whole-genome sequencing. We identify a mutational signature defined by a high prevalence of A>C transversions at AA dinucleotides. Statistical analysis of exome data identified 26 significantly mutated genes. Of these genes, five (TP53, CDKN2A, SMAD4, ARID1A and PIK3CA) have previously been implicated in EAC. The new significantly mutated genes include chromatin-modifying factors and candidate contributors SPG20, TLR4, ELMO1 and DOCK2. Functional analyses of EAC-derived mutations in ELMO1 identifies increased cellular invasion. Therefore, we suggest the potential activation of the RAC1 pathway as a contributor to EAC tumorigenesis.

Exome and whole-genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity

Abstract: National Human Genome Research Institute (U.S.) (Large Scale Sequencing Program Grant U54 HG003067)

Tight coordination of protein translation and HSF1 activation supports the anabolic malignant state.

Abstract: A unifying characteristic of aggressive cancers is a profound anabolic shift in metabolism to enable sustained proliferation and biomass expansion. The ribosome is centrally situated to sense metabolic states but whether it impacts systems that promote cellular survival is unknown. Here, through integrated chemical-genetic analyses, we find that a dominant transcriptional effect of blocking protein translation in cancer cells is complete inactivation of heat shock factor 1 (HSF1), a multifaceted transcriptional regulator of the heat-shock response and many other cellular processes essential for tumorigenesis. Translational flux through the ribosome reshapes the transcriptional landscape and links the fundamental anabolic processes of protein production and energy metabolism with HSF1 activity. Targeting this link deprives cancer cells of their energy and chaperone armamentarium thereby rendering the malignant phenotype unsustainable.

Multiplex cytological profiling assay to measure diverse cellular states.

Abstract: Computational methods for image-based profiling are under active development, but their success hinges on assays that can capture a wide range of phenotypes. We have developed a multiplex cytological profiling assay that “paints the cell” with as many fluorescent markers as possible without compromising our ability to extract rich, quantitative profiles in high throughput. The assay detects seven major cellular components. In a pilot screen of bioactive compounds, the assay detected a range of cellular phenotypes and it clustered compounds with similar annotated protein targets or chemical structure based on cytological profiles. The results demonstrate that the assay captures subtle patterns in the combination of morphological labels, thereby detecting the effects of chemical compounds even though their targets are not stained directly. This image-based assay provides an unbiased approach to characterize compound- and disease-associated cell states to support future probe discovery.

Niche-based screening identifies small-molecule inhibitors of leukemia stem cells

Abstract: Efforts to develop more effective therapies for acute leukemia may benefit from high-throughput screening systems that reflect the complex physiology of the disease, including leukemia stem cells (LSCs) and supportive interactions with the bone marrow microenvironment. The therapeutic targeting of LSCs is challenging because LSCs are highly similar to normal hematopoietic stem and progenitor cells (HSPCs) and are protected by stromal cells in vivo. We screened 14,718 compounds in a leukemia-stroma co-culture system for inhibition of cobblestone formation, a cellular behavior associated with stem-cell function. Among those compounds that inhibited malignant cells but spared HSPCs was the cholesterol-lowering drug lovastatin. Lovastatin showed anti-LSC activity in vitro and in an in vivo bone marrow transplantation model. Mechanistic studies demonstrated that the effect was on target, via inhibition of HMG-CoA reductase. These results illustrate the power of merging physiologically relevant models with high-throughput screening.

Compositions, Kits, and Methods for the Identification, Assessment, Prevention, and Therapy of Cancer

Abstract: The present invention relates to compositions, kits, and methods for detecting, characterizing, preventing, and treating cancer (e.g., hematological malignancies in humans). A variety of biomarker chromosomal number alterations (CNAs) and biomarkers corresponding thereto, are provided, wherein alterations in the copy number of one or more of the biomarker CNAs and/or alterations in the amount, structure, and/or activity of one or more of the biomarkers comprised within the CNAs is associated with cancer status.

Multiplex methods to assay mixed cell populations simultaneously

Abstract: Methods to simultaneously test and screen multiplexed, mixed cell populations, e.g., populations comprising genetically heterogeneous cancer cells, in common conditions.

Abstract 4017: Dissecting the clonal hierarchy of cancer-driving genomic lesions.

Abstract: Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Characterizing the genomic evolution of cancer is critical to understanding disease progression and identifying potential therapeutic targets. By examining the clonal hierarchy of genomic lesions in common tumors, it would be possible to reconstruct the path of oncogenic events that drive carcinogenesis. Reliable assessment of such paths from high-throughput genome sequencing data is complicated by the admixture of normal DNA in tumor samples and by reduced data signal for highly subclonal events. We introduce an approach that exploits individuals’ genetic background by using the abundant germline SNP genotype data provided by whole genome sequence coverage to assess the clonality of genomic alterations, including copy number changes, rearrangements, and point mutations. We developed a novel algorithm, CLONET (CLONality Estimate in Tumors), which analyzes patient-specific heterozygous SNP loci (informative SNPs) and mono-allelic somatic deletions to assess levels of stromal DNA admixture and infer the clonal status of each aberration. For every mono allelic deletion, CLONET assesses the allelic fractions of informative SNPs to determine the apparent proportion of normal cells DNA. Next, through a conservative use of simulation-based error estimates, deletions with the lowest proportions of normal DNA reads are considered clonal. For point mutations, the tumor allelic fraction is corrected for stromal DNA admixture level and subclonality is inferred when it differs significantly from the expected value for clonal lesions. Similarly, the proportions of reads that span each side of a putative breakpoint involved in a rearrangement are matched against the expected values. CLONET also addresses tumor aneuploidy by searching for chromosomes with coverage and allelic fractions of informative SNPs not consistent with a diploid genome. CLONET was tested on 55 whole genome sequences from prostate cancers, a highly heterogeneous tumor type, to catalogue the accumulation of somatic alterations during oncogenesis and progression. In 98% of the cases CLONET made confident assessment of admixture and clonality. We observed consistent clonal lesions involving NKX3-1, the 3Mb region between TMPRSS2 and ERG and FOXP1, as well as early point mutations in SPOP and FOXA1. Overall, we observed a higher rate of subclonal protein-coding point mutation versus deletions (p-value < 10−7). We validated this approach by IHC and FISH for predicted clonal and sub-clonal events. A predicted subclonal homozygous deletion of CHD1 was confirmed by FISH that demonstrated the presence of both nuclei with homozygous and with hemizygous deletion of CHD1. Finally, to assess the general validity of CLONET, we analyzed data from 53 additional tumor genomes, including 25 melanomas and 28 lung adenocarcinomas. In summary, our results imply the existence of consensus paths of tumor carcinogenesis that favor dysregulation of cancer genes in a defined sequence. Citation Format: Davide Prandi, Sylvan C. Baca, Michael S. Lawrence, Juan Miguel Mosquera, Alessandro Romanel, Yotam Drier, Kyung Park, Naoki Kitabayashi, Theresa Y. MacDonald, Eliezer Van Allen, Gregory V. Kryukov, Jean-Philippe Theurillat, T. David Soong, Elizabeth Nickerson, Daniel Auclair, Ashutosh Tewari, Himisha Beltran, Robert C. Onofrio, Gunther Boysen, Candace Guiducci, Christopher E. Barbieri, Kristian Cibulskis, Andrey Sivachenko, Scott L. Carter, Gordon Saksena, Douglas Voet, Alex H. Ramos, Wendy Winckler, Michelle Cipicchio, Kristin Ardlie, Philip W. Kantoff, Michael F. Berger, Stacey B. Gabriel, Todd R. Golub, Matthew Meyerson, Eric S. Lander, Olivier Elemento, Gad Getz, Francesca Demichelis, Mark A. Rubin, Levi A. Garraway. Dissecting the clonal hierarchy of cancer-driving genomic lesions. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4017. doi:10.1158/1538-7445.AM2013-4017