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Dive into the research topics where Jamie K. Teer is active.

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Featured researches published by Jamie K. Teer.


Nature Medicine | 2013

Mining Exomic Sequencing Data to Identify Mutated Antigens Recognized by Adoptively Transferred Tumor-reactive T cells

Paul F. Robbins; Yong-Chen Lu; Mona El-Gamil; Yong F. Li; Colin Gross; Jared J. Gartner; Jimmy C. Lin; Jamie K. Teer; Paul F. Cliften; Eric Tycksen; Yardena Samuels; Steven A. Rosenberg

Substantial regressions of metastatic lesions have been observed in up to 70% of patients with melanoma who received adoptively transferred autologous tumor-infiltrating lymphocytes (TILs) in phase 2 clinical trials. In addition, 40% of patients treated in a recent trial experienced complete regressions of all measurable lesions for at least 5 years following TIL treatment. To evaluate the potential association between the ability of TILs to mediate durable regressions and their ability to recognize potent antigens that presumably include mutated gene products, we developed a new screening approach involving mining whole-exome sequence data to identify mutated proteins expressed in patient tumors. We then synthesized and evaluated candidate mutated T cell epitopes that were identified using a major histocompatibility complex–binding algorithm for recognition by TILs. Using this approach, we identified mutated antigens expressed on autologous tumor cells that were recognized by three bulk TIL lines from three individuals with melanoma that were associated with objective tumor regressions following adoptive transfer. This simplified approach for identifying mutated antigens recognized by T cells avoids the need to generate and laboriously screen cDNA libraries from tumors and may represent a generally applicable method for identifying mutated antigens expressed in a variety of tumor types.


Nature Genetics | 2011

Exome sequencing identifies GRIN2A as frequently mutated in melanoma

Xiaomu Wei; Vijay Walia; Jimmy Lin; Jamie K. Teer; Todd D. Prickett; Jared J. Gartner; Sean Davis; Katherine Stemke-Hale; Michael A. Davies; Jeffrey E. Gershenwald; William H. Robinson; Steven E. Robinson; Steven A. Rosenberg; Yardena Samuels

The incidence of melanoma is increasing more than any other cancer, and knowledge of its genetic alterations is limited. To systematically analyze such alterations, we performed whole-exome sequencing of 14 matched normal and metastatic tumor DNAs. Using stringent criteria, we identified 68 genes that appeared to be somatically mutated at elevated frequency, many of which are not known to be genetically altered in tumors. Most importantly, we discovered that TRRAP harbored a recurrent mutation that clustered in one position (p. Ser722Phe) in 6 out of 167 affected individuals (∼4%), as well as a previously unidentified gene, GRIN2A, which was mutated in 33% of melanoma samples. The nature, pattern and functional evaluation of the TRRAP recurrent mutation suggest that TRRAP functions as an oncogene. Our study provides, to our knowledge, the most comprehensive map of genetic alterations in melanoma to date and suggests that the glutamate signaling pathway is involved in this disease.


Human Molecular Genetics | 2010

Exome sequencing: the sweet spot before whole genomes

Jamie K. Teer; James C. Mullikin

The development of massively parallel sequencing technologies, coupled with new massively parallel DNA enrichment technologies (genomic capture), has allowed the sequencing of targeted regions of the human genome in rapidly increasing numbers of samples. Genomic capture can target specific areas in the genome, including genes of interest and linkage regions, but this limits the study to what is already known. Exome capture allows an unbiased investigation of the complete protein-coding regions in the genome. Researchers can use exome capture to focus on a critical part of the human genome, allowing larger numbers of samples than are currently practical with whole-genome sequencing. In this review, we briefly describe some of the methodologies currently used for genomic and exome capture and highlight recent applications of this technology.


Genome Research | 2009

The ClinSeq Project: Piloting large-scale genome sequencing for research in genomic medicine

Leslie G. Biesecker; James C. Mullikin; Flavia M. Facio; Clesson Turner; Praveen F. Cherukuri; Robert W. Blakesley; Gerard G. Bouffard; Peter S. Chines; Pedro Cruz; Nancy F. Hansen; Jamie K. Teer; Baishali Maskeri; Alice C. Young; Teri A. Manolio; Alexander F. Wilson; Toren Finkel; Paul M. Hwang; Andrew E. Arai; Alan T. Remaley; Vandana Sachdev; Robert D. Shamburek; Richard O. Cannon; Eric D. Green

ClinSeq is a pilot project to investigate the use of whole-genome sequencing as a tool for clinical research. By piloting the acquisition of large amounts of DNA sequence data from individual human subjects, we are fostering the development of hypothesis-generating approaches for performing research in genomic medicine, including the exploration of issues related to the genetic architecture of disease, implementation of genomic technology, informed consent, disclosure of genetic information, and archiving, analyzing, and displaying sequence data. In the initial phase of ClinSeq, we are enrolling roughly 1000 participants; the evaluation of each includes obtaining a detailed family and medical history, as well as a clinical evaluation. The participants are being consented broadly for research on many traits and for whole-genome sequencing. Initially, Sanger-based sequencing of 300-400 genes thought to be relevant to atherosclerosis is being performed, with the resulting data analyzed for rare, high-penetrance variants associated with specific clinical traits. The participants are also being consented to allow the contact of family members for additional studies of sequence variants to explore their potential association with specific phenotypes. Here, we present the general considerations in designing ClinSeq, preliminary results based on the generation of an initial 826 Mb of sequence data, the findings for several genes that serve as positive controls for the project, and our views about the potential implications of ClinSeq. The early experiences with ClinSeq illustrate how large-scale medical sequencing can be a practical, productive, and critical component of research in genomic medicine.


Genome Research | 2010

Systematic comparison of three genomic enrichment methods for massively parallel DNA sequencing

Jamie K. Teer; Lori L. Bonnycastle; Peter S. Chines; Nancy F. Hansen; Natsuyo Aoyama; Amy J. Swift; Hatice Ozel Abaan; Thomas J. Albert; Nisc Comparative Sequencing Program; Elliott H. Margulies; Eric D. Green; Francis S. Collins; James C. Mullikin; Leslie G. Biesecker

Massively parallel DNA sequencing technologies have greatly increased our ability to generate large amounts of sequencing data at a rapid pace. Several methods have been developed to enrich for genomic regions of interest for targeted sequencing. We have compared three of these methods: Molecular Inversion Probes (MIP), Solution Hybrid Selection (SHS), and Microarray-based Genomic Selection (MGS). Using HapMap DNA samples, we compared each of these methods with respect to their ability to capture an identical set of exons and evolutionarily conserved regions associated with 528 genes (2.61 Mb). For sequence analysis, we developed and used a novel Bayesian genotype-assigning algorithm, Most Probable Genotype (MPG). All three capture methods were effective, but sensitivities (percentage of targeted bases associated with high-quality genotypes) varied for an equivalent amount of pass-filtered sequence: for example, 70% (MIP), 84% (SHS), and 91% (MGS) for 400 Mb. In contrast, all methods yielded similar accuracies of >99.84% when compared to Infinium 1M SNP BeadChip-derived genotypes and >99.998% when compared to 30-fold coverage whole-genome shotgun sequencing data. We also observed a low false-positive rate with all three methods; of the heterozygous positions identified by each of the capture methods, >99.57% agreed with 1M SNP BeadChip, and >98.840% agreed with the whole-genome shotgun data. In addition, we successfully piloted the genomic enrichment of a set of 12 pooled samples via the MGS method using molecular bar codes. We find that these three genomic enrichment methods are highly accurate and practical, with sensitivities comparable to that of 30-fold coverage whole-genome shotgun data.


American Journal of Human Genetics | 2012

Secondary Variants in Individuals Undergoing Exome Sequencing: Screening of 572 Individuals Identifies High-Penetrance Mutations in Cancer-Susceptibility Genes

Jennifer J. Johnston; Wendy S. Rubinstein; Flavia M. Facio; David Ng; Larry N. Singh; Jamie K. Teer; James C. Mullikin; Leslie G. Biesecker

Genome- and exome-sequencing costs are continuing to fall, and many individuals are undergoing these assessments as research participants and patients. The issue of secondary (so-called incidental) findings in exome analysis is controversial, and data are needed on methods of detection and their frequency. We piloted secondary variant detection by analyzing exomes for mutations in cancer-susceptibility syndromes in subjects ascertained for atherosclerosis phenotypes. We performed exome sequencing on 572 ClinSeq participants, and in 37 genes, we interpreted variants that cause high-penetrance cancer syndromes by using an algorithm that filtered results on the basis of mutation type, quality, and frequency and that filtered mutation-database entries on the basis of defined categories of causation. We identified 454 sequence variants that differed from the human reference. Exclusions were made on the basis of sequence quality (26 variants) and high frequency in the cohort (77 variants) or dbSNP (17 variants), leaving 334 variants of potential clinical importance. These were further filtered on the basis of curation of literature reports. Seven participants, four of whom were of Ashkenazi Jewish descent and three of whom did not meet family-history-based referral criteria, had deleterious BRCA1 or BRCA2 mutations. One participant had a deleterious SDHC mutation, which causes paragangliomas. Exome sequencing, coupled with multidisciplinary interpretation, detected clinically important mutations in cancer-susceptibility genes; four of such mutations were in individuals without a significant family history of disease. We conclude that secondary variants of high clinical importance will be detected at an appreciable frequency in exomes, and we suggest that priority be given to the development of more efficient modes of interpretation with trials in larger patient groups.


PLOS Genetics | 2011

Whole-Exome Sequencing Identifies Homozygous AFG3L2 Mutations in a Spastic Ataxia-Neuropathy Syndrome Linked to Mitochondrial m-AAA Proteases

Tyler Mark Pierson; David Adams; Florian Bonn; Paola Martinelli; Praveen F. Cherukuri; Jamie K. Teer; Nancy F. Hansen; Pedro Cruz; Robert W. Blakesley; Gretchen Golas; Justin Y. Kwan; Anthony D. Sandler; Karin Fuentes Fajardo; Thomas C. Markello; Cynthia J. Tifft; Craig Blackstone; Elena I. Rugarli; Thomas Langer; William A. Gahl; Camilo Toro

We report an early onset spastic ataxia-neuropathy syndrome in two brothers of a consanguineous family characterized clinically by lower extremity spasticity, peripheral neuropathy, ptosis, oculomotor apraxia, dystonia, cerebellar atrophy, and progressive myoclonic epilepsy. Whole-exome sequencing identified a homozygous missense mutation (c.1847G>A; p.Y616C) in AFG3L2, encoding a subunit of an m-AAA protease. m-AAA proteases reside in the mitochondrial inner membrane and are responsible for removal of damaged or misfolded proteins and proteolytic activation of essential mitochondrial proteins. AFG3L2 forms either a homo-oligomeric isoenzyme or a hetero-oligomeric complex with paraplegin, a homologous protein mutated in hereditary spastic paraplegia type 7 (SPG7). Heterozygous loss-of-function mutations in AFG3L2 cause autosomal-dominant spinocerebellar ataxia type 28 (SCA28), a disorder whose phenotype is strikingly different from that of our patients. As defined in yeast complementation assays, the AFG3L2Y616C gene product is a hypomorphic variant that exhibited oligomerization defects in yeast as well as in patient fibroblasts. Specifically, the formation of AFG3L2Y616C complexes was impaired, both with itself and to a greater extent with paraplegin. This produced an early-onset clinical syndrome that combines the severe phenotypes of SPG7 and SCA28, in additional to other “mitochondrial” features such as oculomotor apraxia, extrapyramidal dysfunction, and myoclonic epilepsy. These findings expand the phenotype associated with AFG3L2 mutations and suggest that AFG3L2-related disease should be considered in the differential diagnosis of spastic ataxias.


Nature Genetics | 2011

Exon capture analysis of G protein-coupled receptors identifies activating mutations in GRM3 in melanoma.

Todd D. Prickett; Xiaomu Wei; Isabel Cardenas-Navia; Jamie K. Teer; Jimmy Lin; Vijay Walia; Jared J. Gartner; Jiji Jiang; Praveen F. Cherukuri; Alfredo A. Molinolo; Michael A. Davies; Jeffrey E. Gershenwald; Katherine Stemke-Hale; Steven A. Rosenberg; Elliott H. Margulies; Yardena Samuels

G protein-coupled receptors (GPCRs), the largest human gene family, are important regulators of signaling pathways. However, knowledge of their genetic alterations is limited. In this study, we used exon capture and massively parallel sequencing methods to analyze the mutational status of 734 GPCRs in melanoma. This investigation revealed that one family member, GRM3, was frequently mutated and that one of its mutations clustered within one position. Biochemical analysis of GRM3 alterations revealed that mutant GRM3 selectively regulated the phosphorylation of MEK, leading to increased anchorage-independent growth and migration. Melanoma cells expressing mutant GRM3 had reduced cell growth and cellular migration after short hairpin RNA–mediated knockdown of GRM3 or treatment with a selective MEK inhibitor, AZD-6244, which is currently being used in phase 2 clinical trials. Our study yields the most comprehensive map of genetic alterations in the GPCR gene family.


American Journal of Human Genetics | 2010

Massively Parallel Sequencing of Exons on the X Chromosome Identifies RBM10 as the Gene that Causes a Syndromic Form of Cleft Palate

Jennifer J. Johnston; Jamie K. Teer; Praveen F. Cherukuri; Nancy F. Hansen; Stacie K. Loftus; Karen Chong; James C. Mullikin; Leslie G. Biesecker

Micrognathia, glossoptosis, and cleft palate comprise one of the most common malformation sequences, Robin sequence. It is a component of the TARP syndrome, talipes equinovarus, atrial septal defect, Robin sequence, and persistent left superior vena cava. This disorder is X-linked and severe, with apparently 100% pre- or postnatal lethality in affected males. Here we characterize a second family with TARP syndrome, confirm linkage to Xp11.23-q13.3, perform massively parallel sequencing of X chromosome exons, filter the results via a number of criteria including the linkage region, use a unique algorithm to characterize sequence changes, and show that TARP syndrome is caused by mutations in the RBM10 gene, which encodes RNA binding motif 10. We further show that this previously uncharacterized gene is expressed in midgestation mouse embryos in the branchial arches and limbs, consistent with the human phenotype. We conclude that massively parallel sequencing is useful to characterize large candidate linkage intervals and that it can be used successfully to allow identification of disease-causing gene mutations.


Bioinformatics | 2012

VarSifter: Visualizing and analyzing exome-scale sequence variation data on a desktop computer

Jamie K. Teer; Eric D. Green; James C. Mullikin; Leslie G. Biesecker

UNLABELLED VarSifter is a graphical software tool for desktop computers that allows investigators of varying computational skills to easily and quickly sort, filter, and sift through sequence variation data. A variety of filters and a custom query framework allow filtering based on any combination of sample and annotation information. By simplifying visualization and analyses of exome-scale sequence variation data, this program will help bring the power and promise of massively-parallel DNA sequencing to a broader group of researchers. AVAILABILITY AND IMPLEMENTATION VarSifter is written in Java, and is freely available in source and binary versions, along with a User Guide, at http://research.nhgri.nih.gov/software/VarSifter/.

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Sean J. Yoder

University of South Florida

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Eric A. Welsh

Washington University in St. Louis

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James C. Mullikin

National Institutes of Health

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Yonghong Zhang

University of South Florida

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Leslie G. Biesecker

National Institutes of Health

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Eric B. Haura

University of South Florida

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Praveen F. Cherukuri

National Institutes of Health

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Steven A. Rosenberg

National Institutes of Health

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Howard L. McLeod

Washington University in St. Louis

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Michael J. Schell

University of South Florida

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