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Stefanie S. Jeffrey

Researcher at Stanford University

Publications -  152
Citations -  43958

Stefanie S. Jeffrey is an academic researcher from Stanford University. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 54, co-authored 147 publications receiving 40347 citations. Previous affiliations of Stefanie S. Jeffrey include University of California, San Francisco.

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Molecular portraits of human breast tumours

TL;DR: Variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals were characterized using complementary DNA microarrays representing 8,102 human genes, providing a distinctive molecular portrait of each tumour.
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Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications

TL;DR: Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
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Systematic variation in gene expression patterns in human cancer cell lines.

TL;DR: Using cDNA microarrays to explore the variation in expression of approximately 8,000 unique genes among the 60 cell lines used in the National Cancer Institute's screen for anti-cancer drugs provided a novel molecular characterization of this important group of human cell lines and their relationships to tumours in vivo.
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Genome-wide analysis of DNA copy-number changes using cDNA microarrays.

TL;DR: This work describes a cDNA microarray-based CGH method, and its application to DNA copy-number variation analysis in breast cancer cell lines and tumours, and identifies gene amplifications and deletions genome-wide and with high resolution.
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Distinctive gene expression patterns in human mammary epithelial cells and breast cancers

TL;DR: The results support the feasibility and usefulness of this systematic approach to studying variation in gene expression patterns in human cancers as a means to dissect and classify solid tumors.