Person:

Beroukhim, Rameen

Loss of heterozygosity (LOH) of chromosomal regions bearing tumor suppressors is a key event in the evolution of epithelial and mesenchymal tumors. Identification of these regions usually relies on genotyping tumor and counterpart normal DNA and noting regions where heterozygous alleles in the normal DNA become homozygous in the tumor. However, paired normal samples for tumors and cell lines are often not available. With the advent of oligonucleotide arrays that simultaneously assay thousands of single-nucleotide polymorphism (SNP) markers, genotyping can now be done at high enough resolution to allow identification of LOH events by the absence of heterozygous loci, without comparison to normal controls. Here we describe a hidden Markov model-based method to identify LOH from unpaired tumor samples, taking into account SNP intermarker distances, SNP-specific heterozygosity rates, and the haplotype structure of the human genome. When we applied the method to data genotyped on 100 K arrays, we correctly identified 99% of SNP markers as either retention or loss. We also correctly identified 81% of the regions of LOH, including 98% of regions greater than 3 megabases. By integrating copy number analysis into the method, we were able to distinguish LOH from allelic imbalance. Application of this method to data from a set of prostate samples without paired normals identified known regions of prevalent LOH. We have developed a method for analyzing high-density oligonucleotide SNP array data to accurately identify of regions of LOH and retention in tumors without the need for paired normal samples.

Amplification, deletion, and loss of heterozygosity of genomic DNA are hallmarks of cancer. In recent years a variety of studies have emerged measuring total chromosomal copy number at increasingly high resolution. Similarly, loss-of-heterozygosity events have been finely mapped using high-throughput genotyping technologies. We have developed a probe-level allele-specific quantitation procedure that extracts both copy number and allelotype information from single nucleotide polymorphism (SNP) array data to arrive at allele-specific copy number across the genome. Our approach applies an expectation-maximization algorithm to a model derived from a novel classification of SNP array probes. This method is the first to our knowledge that is able to (a) determine the generalized genotype of aberrant samples at each SNP site (e.g., CCCCT at an amplified site), and (b) infer the copy number of each parental chromosome across the genome. With this method, we are able to determine not just where amplifications and deletions occur, but also the haplotype of the region being amplified or deleted. The merit of our model and general approach is demonstrated by very precise genotyping of normal samples, and our allele-specific copy number inferences are validated using PCR experiments. Applying our method to a collection of lung cancer samples, we are able to conclude that amplification is essentially monoallelic, as would be expected under the mechanisms currently believed responsible for gene amplification. This suggests that a specific parental chromosome may be targeted for amplification, whether because of germ line or somatic variation. An R software package containing the methods described in this paper is freely available at http://genome.dfci.harvard.edu/~tlaframb/PLASQ.

Background: Single nucleotide polymorphisms (SNPs) are the most common genetic variations in the human genome and are useful as genomic markers. Oligonucleotide SNP microarrays have been developed for high-throughput genotyping of up to 900,000 human SNPs and have been used widely in linkage and cancer genomics studies. We have previously used Hidden Markov Models (HMM) to analyze SNP array data for inferring copy numbers and loss-of-heterozygosity (LOH) from paired normal and tumor samples and unpaired tumor samples. Results: We proposed and implemented major copy proportion (MCP) analysis of oligonucleotide SNP array data. A HMM was constructed to infer unobserved MCP states from observed allele-specific signals through emission and transition distributions. We used 10 K, 100 K and 250 K SNP array datasets to compare MCP analysis with LOH and copy number analysis, and showed that MCP performs better than LOH analysis for allelic-imbalanced chromosome regions and normal contaminated samples. The major and minor copy alleles can also be inferred from allelic-imbalanced regions by MCP analysis. Conclusion: MCP extends tumor LOH analysis to allelic imbalance analysis and supplies complementary information to total copy numbers. MCP analysis of mixing normal and tumor samples suggests the utility of MCP analysis of normal-contaminated tumor samples. The described analysis and visualization methods are readily available in the user-friendly dChip software.

Background: Protein tyrosine kinases are important regulators of cellular homeostasis with tightly controlled catalytic activity. Mutations in kinase-encoding genes can relieve the autoinhibitory constraints on kinase activity, can promote malignant transformation, and appear to be a major determinant of response to kinase inhibitor therapy. Missense mutations in the EGFR kinase domain, for example, have recently been identified in patients who showed clinical responses to EGFR kinase inhibitor therapy. Methods and Findings: Encouraged by the promising clinical activity of epidermal growth factor receptor (EGFR) kinase inhibitors in treating glioblastoma in humans, we have sequenced the complete EGFR coding sequence in glioma tumor samples and cell lines. We identified novel missense mutations in the extracellular domain of EGFR in 13.6% (18/132) of glioblastomas and 12.5% (1/ 8) of glioblastoma cell lines. These EGFR mutations were associated with increased EGFR gene dosage and conferred anchorage-independent growth and tumorigenicity to NIH-3T3 cells. Cells transformed by expression of these EGFR mutants were sensitive to small-molecule EGFR kinase inhibitors. Conclusions: Our results suggest extracellular missense mutations as a novel mechanism for oncogenic EGFR activation and may help identify patients who can benefit from EGFR kinase inhibitors for treatment of glioblastoma.

A more detailed understanding of the somatic genetic events that drive gastrointestinal adenocarcinomas is necessary to improve diagnosis and therapy. Using data from high-density genomic profiling arrays, we conducted an analysis of somatic copy-number aberrations (SCNAs) in 486 gastrointestinal adenocarcinomas including 296 esophageal and gastric cancers. Focal amplifications were substantially more prevalent in gastric/esophageal adenocarcinomas than colorectal tumors. We identified 64 regions of significant recurrent amplification and deletion, some shared and others unique to the adenocarcinoma types examined. Amplified genes were noted in 37% of gastric/esophageal tumors, including in therapeutically targetable kinases such as ERBB2, FGFR1, FGFR2, EGFR, and MET, suggesting the potential utility of genomic amplifications as biomarkers to guide therapy of gastric and esophageal cancers where targeted therapeutics have been less developed compared to colorectal cancers. Amplified loci implicated genes with known involvement in carcinogenesis but also pointed to regions harboring potentially novel cancer genes, including a recurrent deletion found in 15% of esophageal tumors where the Runt transcription factor subunit RUNX1 was implicated, including by functional experiments in tissue culture. Together, our results defined genomic features that were common and distinct to various gut-derived adenocarcinomas, potentially informing novel opportunities for targeted therapeutic interventions.

The estrogen receptor alpha (ERα) is highly expressed in both endometrial and breast cancers, and represents the most prevalent therapeutic target in breast cancer. However, anti-estrogen therapy has not been shown to be effective in endometrial cancer. Recently it has been shown that hormone-binding domain alterations of ERα in breast cancer contribute to acquired resistance to anti-estrogen therapy. In analyses of genomic data from The Cancer Genome Atlas (TCGA), we observe that endometrial carcinomas manifest recurrent ESR1 gene amplifications that truncate the hormone-binding domain encoding region of ESR1 and are associated with reduced mRNA expression of exons encoding the hormone-binding domain. These findings support a role for hormone-binding alterations of ERα in primary endometrial cancer, with potentially important therapeutic implications.

Lineage survival oncogenes are activated by somatic DNA alterations in cancers arising from the cell lineages in which these genes play a role in normal development.1,2 Here we show that a peak of genomic amplification on chromosome 3q26.33, found in squamous cell carcinomas (SCCs) of the lung and esophagus, contains the transcription factor gene SOX2—which is mutated in hereditary human esophageal malformations3 and necessary for normal esophageal squamous development4, promotes differentiation and proliferation of basal tracheal cells5 and co-operates in induction of pluripotent stem cells.6,7,8 SOX2 expression is required for proliferation and anchorage-independent growth of lung and esophageal cell lines, as shown by RNA interference experiments. Furthermore, ectopic expression of SOX2 cooperated with FOXE1 or FGFR2 to transform immortalized tracheobronchial epithelial cells. SOX2-driven tumors show expression of markers of both squamous differentiation and pluripotency. These observations identify SOX2 as a novel lineage survival oncogene in lung and esophageal SCC.

Mig6 is a feedback inhibitor that directly binds, inhibits and drives internalization of ErbB-family receptors. Mig6 selectivity targets activated receptors. Here we find that the EGF receptor phosphorylates Mig6 on Tyr394, and that this phosphorylation is primed by prior phosphorylation of an adjacent residue, Tyr395, by Src. Crystal structures of human EGFR–Mig6 complexes reveal the structural basis for enhanced phosphorylation of primed Mig6 and show how Mig6 rearranges after phosphorylation by EGFR to effectively irreversibly inhibit the same receptor that catalyzed its phosphorylation. This dual phosphorylation site allows Mig6 to inactivate EGFR in a manner that requires activation of the target receptor and can be modulated by Src. Loss of Mig6 is a driving event in human cancer; analysis of 1057 gliomas reveals frequent focal deletions of ERRFI, the gene that encodes Mig6, in EGFR-amplified glioblastomas.

Somatic alterations in cellular DNA underlie almost all human cancers1. The prospect of targeted therapies2 and the development of high-resolution, genome-wide approaches3–8 are now spurring systematic efforts to characterize cancer genomes. Here we report a large-scale project to characterize copy-number alterations in primary lung adenocarcinomas. By analysis of a large collection of tumors (n = 371) using dense single nucleotide polymorphism arrays, we identify a total of 57 significantly recurrent events. We find that 26 of 39 autosomal chromosome arms show consistent large-scale copy-number gain or loss, of which only a handful have been linked to a specific gene. We also identify 31 recurrent focal events, including 24 amplifications and 7 homozygous deletions. Only six of these focal events are currently associated with known mutations in lung carcinomas. The most common event, amplification of chromosome 14q13.3, is found in ~12% of samples. On the basis of genomic and functional analyses, we identify NKX2-1 (NK2 homeobox 1, also called TITF1), which lies in the minimal 14q13.3 amplification interval and encodes a lineage-specific transcription factor, as a novel candidate proto-oncogene involved in a significant fraction of lung adenocarcinomas. More generally, our results indicate that many of the genes that are involved in lung adenocarcinoma remain to be discovered.