Institution
Windber Research Institute
Nonprofit•Windber, Pennsylvania, United States•
About: Windber Research Institute is a nonprofit organization based out in Windber, Pennsylvania, United States. It is known for research contribution in the topics: Breast cancer & Cancer. The organization has 118 authors who have published 150 publications receiving 12833 citations.
Topics: Breast cancer, Cancer, Metastasis, Breast disease, CA15-3
Papers published on a yearly basis
Papers
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Daniel C. Koboldt1, Robert S. Fulton1, Michael D. McLellan1, Heather Schmidt1 +352 more•Institutions (35)
TL;DR: The ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity.
Abstract: We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.
9,355 citations
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Van Andel Institute1, Johns Hopkins University2, Henry M. Jackson Foundation for the Advancement of Military Medicine3, University of Michigan4, International Agency for Research on Cancer5, United States Department of Health and Human Services6, Erasmus University Rotterdam7, National Institutes of Health8, Windber Research Institute9, Lawrence Berkeley National Laboratory10
TL;DR: The Biospecimen Reporting for Improved Study Quality (BRISQ) recommendations outlined herein are intended to apply to any study in which human biospecimens are used and supply others, from researchers to regulators, with more consistent and standardized information to better evaluate, interpret, compare, and reproduce the experimental results.
Abstract: Human biospecimens are subjected to collection, processing, and storage that can significantly alter their molecular composition and consistency. These biospecimen preanalytical factors, in turn, influence experimental outcomes and the ability to reproduce scientific results. Currently, the extent and type of information specific to the biospecimen preanalytical conditions reported in scientific publications and regulatory submissions varies widely. To improve the quality of research that uses human tissues, it is crucial that information on the handling of biospecimens be reported in a thorough, accurate, and standardized manner. The Biospecimen Reporting for Improved Study Quality (BRISQ) recommendations outlined herein are intended to apply to any study in which human biospecimens are used. The purpose of reporting these details is to supply others, from researchers to regulators, with more consistent and standardized information to better evaluate, interpret, compare, and reproduce the experimental results. The BRISQ guidelines are proposed as an important and timely resource tool to strengthen communication and publications on biospecimen-related research and to help reassure patient contributors and the advocacy community that their contributions are valued and respected.
290 citations
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TL;DR: This study quantitatively assess the application of Gene Ontology (GO)-derived similarity measures for the characterization of direct and indirect interactions within human regulatory pathways and demonstrates that the functional similarity of proteins within known regulatory pathways decays rapidly as the path length between two proteins increases.
Abstract: Motivation: Pathway modeling requires the integration of multiple data including prior knowledge. In this study, we quantitatively assess the application of Gene Ontology (GO)-derived similarity measures for the characterization of direct and indirect interactions within human regulatory pathways. The characterization would help the integration of prior pathway knowledge for the modeling.
Results: Our analysis indicates information content-based measures outperform graph structure-based measures for stratifying protein interactions. Measures in terms of GO biological process and molecular function annotations can be used alone or together for the validation of protein interactions involved in the pathways. However, GO cellular component-derived measures may not have the ability to separate true positives from noise. Furthermore, we demonstrate that the functional similarity of proteins within known regulatory pathways decays rapidly as the path length between two proteins increases. Several logistic regression models are built to estimate the confidence of both direct and indirect interactions within a pathway, which may be used to score putative pathways inferred from a scaffold of molecular interactions.
Contact: s.guo@wriwindber.org
203 citations
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TL;DR: The first high‐throughput proteomic analysis of human breast infiltrating ductal carcinoma (IDCA) using OCT (optimal cutting temperature) embedded biopsies, two‐dimensional difference gel electrophoresis (2‐D DIGE) technology and a fully automated spot handling workstation is described.
Abstract: Large-scale proteomics will play a critical role in the rapid display, identification and validation of new protein targets, and elucidation of the underlying molecular events that are associated with disease development, progression and severity. However, because the proteome of most organisms are significantly more complex than the genome, the comprehensive analysis of protein expression changes will require an analytical effort beyond the capacity of standard laboratory equipment. We describe the first high-throughput proteomic analysis of human breast infiltrating ductal carcinoma (IDCA) using OCT (optimal cutting temperature) embedded biopsies, two-dimensional difference gel electrophoresis (2-D DIGE) technology and a fully automated spot handling workstation. Total proteins from four breast IDCAs (Stage I, IIA, IIB and IIIA) were individually compared to protein from non-neoplastic tissue obtained from a female donor with no personal or family history of breast cancer. We detected differences in protein abundance that ranged from 14.8% in stage I IDCA versus normal, to 30.6% in stage IIB IDCA versus normal. A total of 524 proteins that showed ≥ three-fold difference in abundance between IDCA and normal tissue were picked, processed and identified by mass spectrometry. Out of the proteins picked, ∼ 80% were unambiguously assigned identities by matrix-assisted laser desorbtion/ionization-time of flight mass spectrometry or liquid chromatography-tandem mass spectrometry in the first pass. Bioinformatics tools were also used to mine databases to determine if the identified proteins are involved in important pathways and/or interact with other proteins. Gelsolin, vinculin, lumican, alpha-1-antitrypsin, heat shock protein-60, cytokeratin-18, transferrin, enolase-1 and β-actin, showed differential abundance between IDCA and normal tissue, but the trend was not consistent in all samples. Out of the proteins with database hits, only heat shock protein-70 (more abundant) and peroxiredoxin-2 (less abundant) displayed the same trend in all the IDCAs examined. This preliminary study demonstrates quantitative and qualitative differences in protein abundance between breast IDCAs and reveals 2-D DIGE portraits that may be a reflection of the histological and pathological status of breast IDCA.
180 citations
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TL;DR: Through comparison of two human assemblies, genome assembly comparison is shown to be a robust approach for identification of all classes of genetic variation, highlighting the need for comprehensive annotation strategies to fully interpret genome scanning and personalized sequencing projects.
Abstract: Numerous types of DNA variation exist, ranging from SNPs to larger structural alterations such as copy number variants (CNVs) and inversions. Alignment of DNA sequence from different sources has been used to identify SNPs1,2 and intermediate-sized variants (ISVs)3. However, only a small proportion of total heterogeneity is characterized, and little is known of the characteristics of most smaller-sized ( 1.5 million SNPs. Some differences were simple insertions and deletions, but in regions containing CNVs, segmental duplication and repetitive DNA, they were more complex. Our results uncover substantial undescribed variation in humans, highlighting the need for comprehensive annotation strategies to fully interpret genome scanning and personalized sequencing projects.
173 citations
Authors
Showing all 121 results
Name | H-index | Papers | Citations |
---|---|---|---|
Dan Theodorescu | 74 | 303 | 20119 |
Craig D. Shriver | 35 | 190 | 4109 |
Hai Hu | 28 | 76 | 16007 |
Michael N. Liebman | 26 | 68 | 2359 |
Stella Somiari | 25 | 42 | 11797 |
Darrell L. Ellsworth | 25 | 57 | 1430 |
Brad Love | 22 | 62 | 1449 |
Rachel E. Ellsworth | 21 | 48 | 1292 |
Brenda Deyarmin | 19 | 35 | 10473 |
Richard I. Somiari | 17 | 35 | 887 |
Rick Jordan | 15 | 24 | 1763 |
Yuanbin Ru | 14 | 22 | 1006 |
Xiang Guo | 14 | 29 | 1592 |
Rachel E. Ellsworth | 12 | 19 | 463 |
Leonid Kvecher | 11 | 23 | 10070 |