Tammi L. Vickery
Washington University in St. Louis
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Featured researches published by Tammi L. Vickery.
Nature | 2008
Li Ding; Gad Getz; David A. Wheeler; Elaine R. Mardis; Michael D. McLellan; Kristian Cibulskis; Carrie Sougnez; Heidi Greulich; Donna M. Muzny; Margaret Morgan; Lucinda Fulton; Robert S. Fulton; Qunyuan Zhang; Michael C. Wendl; Michael S. Lawrence; David E. Larson; Ken Chen; David J. Dooling; Aniko Sabo; Alicia Hawes; Hua Shen; Shalini N. Jhangiani; Lora Lewis; Otis Hall; Yiming Zhu; Tittu Mathew; Yanru Ren; Jiqiang Yao; Steven E. Scherer; Kerstin Clerc
Determining the genetic basis of cancer requires comprehensive analyses of large collections of histopathologically well-classified primary tumours. Here we report the results of a collaborative study to discover somatic mutations in 188 human lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are probably involved in carcinogenesis. The frequently mutated genes include tyrosine kinases, among them the EGFR homologue ERBB4; multiple ephrin receptor genes, notably EPHA3; vascular endothelial growth factor receptor KDR; and NTRK genes. These data provide evidence of somatic mutations in primary lung adenocarcinoma for several tumour suppressor genes involved in other cancers—including NF1, APC, RB1 and ATM—and for sequence changes in PTPRD as well as the frequently deleted gene LRP1B. The observed mutational profiles correlate with clinical features, smoking status and DNA repair defects. These results are reinforced by data integration including single nucleotide polymorphism array and gene expression array. Our findings shed further light on several important signalling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment.
The New England Journal of Medicine | 2009
Elaine R. Mardis; Li Ding; David J. Dooling; David E. Larson; Michael D. McLellan; Ken Chen; Daniel C. Koboldt; Robert S. Fulton; Kim D. Delehaunty; Sean McGrath; Lucinda A. Fulton; Devin P. Locke; Vincent Magrini; Rachel Abbott; Tammi L. Vickery; Jerry S. Reed; Jody S. Robinson; Todd Wylie; Scott M. Smith; Lynn K. Carmichael; James M. Eldred; Christopher C. Harris; Jason Walker; Joshua B. Peck; Feiyu Du; Adam F. Dukes; Gabriel E. Sanderson; Anthony M. Brummett; Eric Clark; Joshua F. McMichael
BACKGROUND The full complement of DNA mutations that are responsible for the pathogenesis of acute myeloid leukemia (AML) is not yet known. METHODS We used massively parallel DNA sequencing to obtain a very high level of coverage (approximately 98%) of a primary, cytogenetically normal, de novo genome for AML with minimal maturation (AML-M1) and a matched normal skin genome. RESULTS We identified 12 acquired (somatic) mutations within the coding sequences of genes and 52 somatic point mutations in conserved or regulatory portions of the genome. All mutations appeared to be heterozygous and present in nearly all cells in the tumor sample. Four of the 64 mutations occurred in at least 1 additional AML sample in 188 samples that were tested. Mutations in NRAS and NPM1 had been identified previously in patients with AML, but two other mutations had not been identified. One of these mutations, in the IDH1 gene, was present in 15 of 187 additional AML genomes tested and was strongly associated with normal cytogenetic status; it was present in 13 of 80 cytogenetically normal samples (16%). The other was a nongenic mutation in a genomic region with regulatory potential and conservation in higher mammals; we detected it in one additional AML tumor. The AML genome that we sequenced contains approximately 750 point mutations, of which only a small fraction are likely to be relevant to pathogenesis. CONCLUSIONS By comparing the sequences of tumor and skin genomes of a patient with AML-M1, we have identified recurring mutations that may be relevant for pathogenesis.
Nature | 2012
Li Ding; Timothy J. Ley; David E. Larson; Christopher A. Miller; Daniel C. Koboldt; John S. Welch; Julie Ritchey; Margaret A. Young; Tamara Lamprecht; Michael D. McLellan; Joshua F. McMichael; John W. Wallis; Charles Lu; Dong Shen; Christopher C. Harris; David J. Dooling; Robert S. Fulton; Lucinda Fulton; Ken Chen; Heather K. Schmidt; Joelle Kalicki-Veizer; Vincent Magrini; Lisa Cook; Sean McGrath; Tammi L. Vickery; Michael C. Wendl; Sharon Heath; Mark A. Watson; Daniel C. Link; Michael H. Tomasson
Most patients with acute myeloid leukaemia (AML) die from progressive disease after relapse, which is associated with clonal evolution at the cytogenetic level. To determine the mutational spectrum associated with relapse, we sequenced the primary tumour and relapse genomes from eight AML patients, and validated hundreds of somatic mutations using deep sequencing; this allowed us to define clonality and clonal evolution patterns precisely at relapse. In addition to discovering novel, recurrently mutated genes (for example, WAC, SMC3, DIS3, DDX41 and DAXX) in AML, we also found two major clonal evolution patterns during AML relapse: (1) the founding clone in the primary tumour gained mutations and evolved into the relapse clone, or (2) a subclone of the founding clone survived initial therapy, gained additional mutations and expanded at relapse. In all cases, chemotherapy failed to eradicate the founding clone. The comparison of relapse-specific versus primary tumour mutations in all eight cases revealed an increase in transversions, probably due to DNA damage caused by cytotoxic chemotherapy. These data demonstrate that AML relapse is associated with the addition of new mutations and clonal evolution, which is shaped, in part, by the chemotherapy that the patients receive to establish and maintain remissions.
Nature | 2010
Li Ding; Matthew J. Ellis; Shunqiang Li; David E. Larson; Ken Chen; John W. Wallis; Christopher C. Harris; Michael D. McLellan; Robert S. Fulton; Lucinda Fulton; Rachel Abbott; Jeremy Hoog; David J. Dooling; Daniel C. Koboldt; Heather K. Schmidt; Joelle Kalicki; Qunyuan Zhang; Lei Chen; Ling Lin; Michael C. Wendl; Joshua F. McMichael; Vincent Magrini; Lisa Cook; Sean McGrath; Tammi L. Vickery; Elizabeth L. Appelbaum; Katherine DeSchryver; Sherri R. Davies; Therese Guintoli; Li Lin
Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumour progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The metastasis contained two de novo mutations and a large deletion not present in the primary tumour, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumour mutations and displayed a mutation enrichment pattern that resembled the metastasis. Two overlapping large deletions, encompassing CTNNA1, were present in all three tumour samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared with the primary tumour indicate that secondary tumours may arise from a minority of cells within the primary tumour.
Nature | 2012
Matthew J. Ellis; Li Ding; Dong Shen; Jingqin Luo; Vera J. Suman; John W. Wallis; Brian A. Van Tine; Jeremy Hoog; Reece J. Goiffon; Theodore C. Goldstein; Sam Ng; Li Lin; Robert Crowder; Jacqueline Snider; Karla V. Ballman; Jason D. Weber; Ken Chen; Daniel C. Koboldt; Cyriac Kandoth; William Schierding; Joshua F. McMichael; Christopher A. Miller; Charles Lu; Christopher C. Harris; Michael D. McLellan; Michael C. Wendl; Katherine DeSchryver; D. Craig Allred; Laura Esserman; Gary Unzeitig
To correlate the variable clinical features of oestrogen-receptor-positive breast cancer with somatic alterations, we studied pretreatment tumour biopsies accrued from patients in two studies of neoadjuvant aromatase inhibitor therapy by massively parallel sequencing and analysis. Eighteen significantly mutated genes were identified, including five genes (RUNX1, CBFB, MYH9, MLL3 and SF3B1) previously linked to haematopoietic disorders. Mutant MAP3K1 was associated with luminal A status, low-grade histology and low proliferation rates, whereas mutant TP53 was associated with the opposite pattern. Moreover, mutant GATA3 correlated with suppression of proliferation upon aromatase inhibitor treatment. Pathway analysis demonstrated that mutations in MAP2K4, a MAP3K1 substrate, produced similar perturbations as MAP3K1 loss. Distinct phenotypes in oestrogen-receptor-positive breast cancer are associated with specific patterns of somatic mutations that map into cellular pathways linked to tumour biology, but most recurrent mutations are relatively infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing.
Clinical Cancer Research | 2010
Torsten O. Nielsen; Joel S. Parker; Samuel Leung; K. David Voduc; Mark T.W. Ebbert; Tammi L. Vickery; Sherri R. Davies; Jacqueline Snider; Inge J. Stijleman; Jerry S. Reed; Maggie Cheang; Elaine R. Mardis; Charles M. Perou; Philip S. Bernard; Matthew J. Ellis
Purpose: To compare clinical, immunohistochemical (IHC), and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor (ER)–positive breast cancers from patients uniformly treated with adjuvant tamoxifen. Experimental Design: Quantitative real-time reverse transcription-PCR (qRT-PCR) assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median follow-up, 11.7 years) and IHC [ER, progesterone receptor (PR), HER2, and Ki67] data. Performance of predefined intrinsic subtype and risk-of-relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrells C-index was used to compare fixed models trained in independent data sets, including proliferation signatures. Results: Despite clinical ER positivity, 10% of cases were assigned to nonluminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease-specific survival over the first 5 years of follow-up, relative to the most common luminal A subtype, are 1.99 [95% confidence interval (CI), 1.09-3.64] for luminal B, 3.65 (95% CI, 1.64-8.16) for HER2-enriched subtype, and 17.71 (95% CI, 1.71-183.33) for the basal-like subtype. For node-negative disease, PAM50 qRT-PCR–based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10-year survival without chemotherapy. In node-positive disease, PAM50-based prognostic models were also superior. Conclusion: The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed, paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and IHC using standard cut points. Clin Cancer Res; 16(21); 5222–32. ©2010 AACR.
Clinical Cancer Research | 2012
Stephen Chia; Vivien Bramwell; Dongsheng Tu; Lois E. Shepherd; Shan Jiang; Tammi L. Vickery; Elaine R. Mardis; Samuel Leung; Karen Ung; Kathleen I. Pritchard; Joel S. Parker; Philip S. Bernard; Charles M. Perou; Matthew J. Ellis; Torsten O. Nielsen
Purpose: Gene expression profiling classifies breast cancer into intrinsic subtypes based on the biology of the underlying disease pathways. We have used material from a prospective randomized trial of tamoxifen versus placebo in premenopausal women with primary breast cancer (NCIC CTG MA.12) to evaluate the prognostic and predictive significance of intrinsic subtypes identified by both the PAM50 gene set and by immunohistochemistry. Experimental Design: Total RNA from 398 of 672 (59%) patients was available for intrinsic subtyping with a quantitative reverse transcriptase PCR (qRT-PCR) 50-gene predictor (PAM50) for luminal A, luminal B, HER-2–enriched, and basal-like subtypes. A tissue microarray was also constructed from 492 of 672 (73%) of the study population to assess a panel of six immunohistochemical IHC antibodies to define the same intrinsic subtypes. Results: Classification into intrinsic subtypes by the PAM50 assay was prognostic for both disease-free survival (DFS; P = 0.0003) and overall survival (OS; P = 0.0002), whereas classification by the IHC panel was not. Luminal subtype by PAM50 was predictive of tamoxifen benefit [DFS: HR, 0.52; 95% confidence interval (CI), 0.32–0.86 vs. HR, 0.80; 95% CI, 0.50–1.29 for nonluminal subtypes], although the interaction test was not significant (P = 0.24), whereas neither subtyping by central immunohistochemistry nor by local estrogen receptor (ER) or progesterone receptor (PR) status were predictive. Risk of relapse (ROR) modeling with the PAM50 assay produced a continuous risk score in both node-negative and node-positive disease. Conclusions: In the MA.12 study, intrinsic subtype classification by qRT-PCR with the PAM50 assay was superior to IHC profiling for both prognosis and prediction of benefit from adjuvant tamoxifen. Clin Cancer Res; 18(16); 4465–72. ©2012 AACR.
Journal of Clinical Investigation | 2011
Lukas D. Wartman; David E. Larson; Zhifu Xiang; Li Ding; Ken Chen; Ling Lin; Patrick Cahan; Jeffery M. Klco; John S. Welch; Cheng Li; Jacqueline E. Payton; Geoffrey L. Uy; Nobish Varghese; Rhonda E. Ries; Mieke Hoock; Daniel C. Koboldt; Michael D. McLellan; Heather K. Schmidt; Robert S. Fulton; Rachel Abbott; Lisa Cook; Sean McGrath; Xian Fan; Adam F. Dukes; Tammi L. Vickery; Joelle Kalicki; Tamara Lamprecht; Timothy A. Graubert; Michael H. Tomasson; Elaine R. Mardis
Acute promyelocytic leukemia (APL) is a subtype of acute myeloid leukemia (AML). It is characterized by the t(15;17)(q22;q11.2) chromosomal translocation that creates the promyelocytic leukemia-retinoic acid receptor α (PML-RARA) fusion oncogene. Although this fusion oncogene is known to initiate APL in mice, other cooperating mutations, as yet ill defined, are important for disease pathogenesis. To identify these, we used a mouse model of APL, whereby PML-RARA expressed in myeloid cells leads to a myeloproliferative disease that ultimately evolves into APL. Sequencing of a mouse APL genome revealed 3 somatic, nonsynonymous mutations relevant to APL pathogenesis, of which 1 (Jak1 V657F) was found to be recurrent in other affected mice. This mutation was identical to the JAK1 V658F mutation previously found in human APL and acute lymphoblastic leukemia samples. Further analysis showed that JAK1 V658F cooperated in vivo with PML-RARA, causing a rapidly fatal leukemia in mice. We also discovered a somatic 150-kb deletion involving the lysine (K)-specific demethylase 6A (Kdm6a, also known as Utx) gene, in the mouse APL genome. Similar deletions were observed in 3 out of 14 additional mouse APL samples and 1 out of 150 human AML samples. In conclusion, whole genome sequencing of mouse cancer genomes can provide an unbiased and comprehensive approach for discovering functionally relevant mutations that are also present in human leukemias.
BMC Medical Genomics | 2015
Brett Wallden; James Storhoff; Torsten O. Nielsen; Naeem Dowidar; Carl Schaper; Sean Ferree; Shuzhen Liu; Samuel Leung; Gary Geiss; Jacqueline Snider; Tammi L. Vickery; Sherri R. Davies; Elaine R. Mardis; Michael Gnant; Ivana Sestak; Matthew J. Ellis; Charles M. Perou; Philip S. Bernard; Joel S. Parker
BackgroundThe four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories.Methods514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies.ResultsThe gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online.ConclusionsThe results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumors intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.
British Journal of Cancer | 2014
Aleix Prat; Ana Lluch; Joan Albanell; William T. Barry; C Fan; J I Chacón; Joel S. Parker; L Calvo; A Plazaola; A Arcusa; M A Seguí-Palmer; O Burgues; N Ribelles; Álvaro Rodríguez-Lescure; A Guerrero; Manuel Ruiz-Borrego; Blanca Munárriz; J A López; B Adamo; Maggie Cheang; Y Li; Zhiyuan Hu; M L Gulley; M J Vidal; Brandy Pitcher; Minetta C. Liu; Marc L. Citron; Matthew J. Ellis; Elaine R. Mardis; Tammi L. Vickery
Background:In this study, we evaluated the ability of gene expression profiles to predict chemotherapy response and survival in triple-negative breast cancer (TNBC).Methods:Gene expression and clinical–pathological data were evaluated in five independent cohorts, including three randomised clinical trials for a total of 1055 patients with TNBC, basal-like disease (BLBC) or both. Previously defined intrinsic molecular subtype and a proliferation signature were determined and tested. Each signature was tested using multivariable logistic regression models (for pCR (pathological complete response)) and Cox models (for survival). Within TNBC, interactions between each signature and the basal-like subtype (vs other subtypes) for predicting either pCR or survival were investigated.Results:Within TNBC, all intrinsic subtypes were identified but BLBC predominated (55–81%). Significant associations between genomic signatures and response and survival after chemotherapy were only identified within BLBC and not within TNBC as a whole. In particular, high expression of a previously identified proliferation signature, or low expression of the luminal A signature, was found independently associated with pCR and improved survival following chemotherapy across different cohorts. Significant interaction tests were only obtained between each signature and the BLBC subtype for prediction of chemotherapy response or survival.Conclusions:The proliferation signature predicts response and improved survival after chemotherapy, but only within BLBC. This highlights the clinical implications of TNBC heterogeneity, and suggests that future clinical trials focused on this phenotypic subtype should consider stratifying patients as having BLBC or not.