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Dive into the research topics where Jacqueline Snider is active.

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Featured researches published by Jacqueline Snider.


Journal of the National Cancer Institute | 2009

Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancer

Maggie Cheang; Stephen Chia; David Voduc; Dongxia Gao; Samuel Leung; Jacqueline Snider; Mark A. Watson; Sherri R. Davies; Philip S. Bernard; Joel S. Parker; Charles M. Perou; Matthew J. Ellis; Torsten O. Nielsen

Background Gene expression profiling of breast cancer has identified two biologically distinct estrogen receptor (ER)-positive subtypes of breast cancer: luminal A and luminal B. Luminal B tumors have higher proliferation and poorer prognosis than luminal A tumors. In this study, we developed a clinically practical immunohistochemistry assay to distinguish luminal B from luminal A tumors and investigated its ability to separate tumors according to breast cancer recurrence-free and disease-specific survival. Methods Tumors from a cohort of 357 patients with invasive breast carcinomas were subtyped by gene expression profile. Hormone receptor status, HER2 status, and the Ki67 index (percentage of Ki67-positive cancer nuclei) were determined immunohistochemically. Receiver operating characteristic curves were used to determine the Ki67 cut point to distinguish luminal B from luminal A tumors. The prognostic value of the immunohistochemical assignment for breast cancer recurrence-free and disease-specific survival was investigated with an independent tissue microarray series of 4046 breast cancers by use of Kaplan–Meier curves and multivariable Cox regression. Results Gene expression profiling classified 101 (28%) of the 357 tumors as luminal A and 69 (19%) as luminal B. The best Ki67 index cut point to distinguish luminal B from luminal A tumors was 13.25%. In an independent cohort of 4046 patients with breast cancer, 2847 had hormone receptor–positive tumors. When HER2 immunohistochemistry and the Ki67 index were used to subtype these 2847 tumors, we classified 1530 (59%, 95% confidence interval [CI] = 57% to 61%) as luminal A, 846 (33%, 95% CI = 31% to 34%) as luminal B, and 222 (9%, 95% CI = 7% to 10%) as luminal–HER2 positive. Luminal B and luminal–HER2-positive breast cancers were statistically significantly associated with poor breast cancer recurrence-free and disease-specific survival in all adjuvant systemic treatment categories. Of particular relevance are women who received tamoxifen as their sole adjuvant systemic therapy, among whom the 10-year breast cancer–specific survival was 79% (95% CI = 76% to 83%) for luminal A, 64% (95% CI = 59% to 70%) for luminal B, and 57% (95% CI = 47% to 69%) for luminal–HER2 subtypes. Conclusion Expression of ER, progesterone receptor, and HER2 proteins and the Ki67 index appear to distinguish luminal A from luminal B breast cancer subtypes.


Nature | 2010

Genome remodelling in a basal-like breast cancer metastasis and xenograft.

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

Whole Genome Analysis Informs Breast Cancer Response to Aromatase Inhibition

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

A Comparison of PAM50 Intrinsic Subtyping with Immunohistochemistry and Clinical Prognostic Factors in Tamoxifen-Treated Estrogen Receptor-Positive Breast Cancer

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.


Journal of Clinical Oncology | 2011

Randomized Phase II Neoadjuvant Comparison Between Letrozole, Anastrozole, and Exemestane for Postmenopausal Women With Estrogen Receptor–Rich Stage 2 to 3 Breast Cancer: Clinical and Biomarker Outcomes and Predictive Value of the Baseline PAM50-Based Intrinsic Subtype—ACOSOG Z1031

Matthew J. Ellis; Vera J. Suman; Jeremy Hoog; Li Lin; Jacqueline Snider; Aleix Prat; Joel S. Parker; Jingqin Luo; Katherine DeSchryver; D. Craig Allred; Laura Esserman; Gary Unzeitig; Julie A. Margenthaler; Gildy Babiera; P. Kelly Marcom; Joseph M. Guenther; Mark A. Watson; Marilyn Leitch; Kelly K. Hunt; John A. Olson

PURPOSE Preoperative aromatase inhibitor (AI) treatment promotes breast-conserving surgery (BCS) for estrogen receptor (ER)-positive breast cancer. To study this treatment option, responses to three AIs were compared in a randomized phase II neoadjuvant trial designed to select agents for phase III investigations. PATIENTS AND METHODS Three hundred seventy-seven postmenopausal women with clinical stage II to III ER-positive (Allred score 6-8) breast cancer were randomly assigned to receive neoadjuvant exemestane, letrozole, or anastrozole. The primary end point was clinical response. Secondary end points included BCS, Ki67 proliferation marker changes, the Preoperative Endocrine Prognostic Index (PEPI), and PAM50-based intrinsic subtype analysis. RESULTS On the basis of clinical response rates, letrozole and anastrozole were selected for further investigation; however, no other differences in surgical outcome, PEPI score, or Ki67 suppression were detected. The BCS rate for mastectomy-only patients at presentation was 51%. PAM50 analysis identified AI-unresponsive nonluminal subtypes (human epidermal growth factor receptor 2 enriched or basal-like) in 3.3% of patients. Clinical response and surgical outcomes were similar in luminal A (LumA) versus luminal B tumors; however, a PEPI of 0 (best prognostic group) was highest in the LumA subset (27.1% v 10.7%; P = .004). CONCLUSION Neoadjuvant AI treatment markedly improved surgical outcomes. Ki67 and PEPI data demonstrated that the three agents tested are biologically equivalent and therefore likely to have similar adjuvant activities. LumA tumors were more likely to have favorable biomarker characteristics after treatment; however, occasional paradoxical increases in Ki67 (12% of tumors with > 5% increase after therapy) suggest treatment-resistant cells, present in some LumA tumors, can be detected by post-treatment profiling.


Cancer Research | 2009

PIK3CA and PIK3CB Inhibition Produce Synthetic Lethality when Combined with Estrogen Deprivation in Estrogen Receptor-Positive Breast Cancer

Robert Crowder; Chanpheng Phommaly; Yu Tao; Jeremy Hoog; Jingqin Luo; Charles M. Perou; Joel S. Parker; Melinda A. Miller; David Huntsman; Li Lin; Jacqueline Snider; Sherri R. Davies; John A. Olson; Mark A. Watson; Anthony J. Saporita; Jason D. Weber; Matthew J. Ellis

Several phosphoinositide 3-kinase (PI3K) catalytic subunit inhibitors are currently in clinical trial. We therefore sought to examine relationships between pharmacologic inhibition and somatic mutations in PI3K catalytic subunits in estrogen receptor (ER)-positive breast cancer, in which these mutations are particularly common. RNA interference (RNAi) was used to determine the effect of selective inhibition of PI3K catalytic subunits, p110alpha and p110beta, in ER(+) breast cancer cells harboring either mutation (PIK3CA) or gene amplification (PIK3CB). p110alpha RNAi inhibited growth and promoted apoptosis in all tested ER(+) breast cancer cells under estrogen deprived-conditions, whereas p110beta RNAi only affected cells harboring PIK3CB amplification. Moreover, dual p110alpha/p110beta inhibition potentiated these effects. In addition, treatment with the clinical-grade PI3K catalytic subunit inhibitor BEZ235 also promoted apoptosis in ER(+) breast cancer cells. Importantly, estradiol suppressed apoptosis induced by both gene knockdowns and BEZ235 treatment. Our results suggest that PI3K inhibitors should target both p110alpha and p110beta catalytic subunits, whether wild-type or mutant, and be combined with endocrine therapy for maximal efficacy when treating ER(+) breast cancer.


Molecular & Cellular Proteomics | 2014

Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels

Philipp Mertins; Feng Yang; Tao Liu; D. R. Mani; Vladislav A. Petyuk; Michael A. Gillette; Karl R. Clauser; Jana W. Qiao; Marina A. Gritsenko; Ronald J. Moore; Douglas A. Levine; R. Reid Townsend; Petra Erdmann-Gilmore; Jacqueline Snider; Sherri R. Davies; Kelly V. Ruggles; David Fenyö; R. Thomas Kitchens; Shunqiang Li; Narcisco Olvera; Fanny Dao; Henry Rodriguez; Daniel W. Chan; Daniel C. Liebler; Forest M. White; Karin D. Rodland; Gordon B. Mills; Richard D. Smith; Amanda G. Paulovich; Matthew J. Ellis

Protein abundance and phosphorylation convey important information about pathway activity and molecular pathophysiology in diseases including cancer, providing biological insight, informing drug and diagnostic development, and guiding therapeutic intervention. Analyzed tissues are usually collected without tight regulation or documentation of ischemic time. To evaluate the impact of ischemia, we collected human ovarian tumor and breast cancer xenograft tissue without vascular interruption and performed quantitative proteomics and phosphoproteomics after defined ischemic intervals. Although the global expressed proteome and most of the >25,000 quantified phosphosites were unchanged after 60 min, rapid phosphorylation changes were observed in up to 24% of the phosphoproteome, representing activation of critical cancer pathways related to stress response, transcriptional regulation, and cell death. Both pan-tumor and tissue-specific changes were observed. The demonstrated impact of pre-analytical tissue ischemia on tumor biology mandates caution in interpreting stress-pathway activation in such samples and motivates reexamination of collection protocols for phosphoprotein analysis.


Proceedings of the National Academy of Sciences of the United States of America | 2009

Met induces diverse mammary carcinomas in mice and is associated with human basal breast cancer

Carrie R. Graveel; Jack D. DeGroot; Yanli Su; Julie Koeman; Karl Dykema; Samuel Leung; Jacqueline Snider; Sherri R. Davies; Pamela J. Swiatek; Sandra Cottingham; Mark A. Watson; Matthew J. Ellis; Robert E. Sigler; Kyle A. Furge; George F. Vande Woude

Understanding the signaling pathways that drive aggressive breast cancers is critical to the development of effective therapeutics. The oncogene MET is associated with decreased survival in breast cancer, yet the role that MET plays in the various breast cancer subtypes is unclear. We describe a knockin mouse with mutationally activated Met (Metmut) that develops a high incidence of diverse mammary tumors with basal characteristics, including metaplasia, absence of progesterone receptor and ERBB2 expression, and expression of cytokeratin 5. With gene expression and tissue microarray analysis, we show that high MET expression in human breast cancers significantly correlated with estrogen receptor negative/ERBB2 negative tumors and with basal breast cancers. Few treatment options exist for breast cancers of the basal or trastuzumab-resistant ERBB2 subtypes. We conclude from these studies that MET may play a critical role in the development of the most aggressive breast cancers and may be a rational therapeutic target.


BMC Medical Genomics | 2015

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay.

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.


Nature Communications | 2017

Proteogenomic integration reveals therapeutic targets in breast cancer xenografts.

Kuan-lin Huang; Shunqiang Li; Philipp Mertins; Song Cao; Harsha P. Gunawardena; Kelly V. Ruggles; D. R. Mani; Karl R. Clauser; Maki Tanioka; Jerry Usary; Shyam M. Kavuri; Ling Xie; Christopher Yoon; Jana W. Qiao; John A. Wrobel; Matthew A. Wyczalkowski; Petra Erdmann-Gilmore; Jacqueline Snider; Jeremy Hoog; Purba Singh; Beifang Niu; Zhanfang Guo; Sam Q. Sun; Souzan Sanati; Emily Kawaler; Xuya Wang; Adam Scott; Kai Ye; Michael D. McLellan; Michael C. Wendl

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities.

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Sherri R. Davies

Washington University in St. Louis

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Jeremy Hoog

Washington University in St. Louis

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Katherine DeSchryver

Washington University in St. Louis

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Elaine R. Mardis

Nationwide Children's Hospital

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Charles M. Perou

University of North Carolina at Chapel Hill

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Mark A. Watson

Washington University in St. Louis

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Jingqin Luo

University of Washington

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Tammi L. Vickery

Washington University in St. Louis

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Joel S. Parker

University of North Carolina at Chapel Hill

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