The University of North Carolina at Chapel Hill

University of Utah Research Foundation

Washington University

British Columbia Cancer Agency Branch

Lifeedit Therapeutics, Inc.

Genecentric Therapeutics, Inc.

Bioclassifier, LLC

Nanostring Technologies, Inc.

Joel S Parker

Charles M Perou

Matthew J Ellis

Tedd D Elich

Alexandra Briner Crawley

Philip Seth Bernard

Michael Coyle

Torsten O Nielsen

Gunjan H Arya

Philip S Bernard

Hawazin Faruki

Myla Lai-Goldman

Greg Mayhew

Sean M Ferree

Elaine R Mardis

Andrew Nobel

Eva Carrasco

Rosalia Caballero

James Stephen Marron

Maggie Cheang

Miguel Martin

James Justin Storhoff

Elaine Mardis

Matthew Ellis

James Marron

Torsten Nielsen

Compositions and methods for binding to a target sequence of interest are provided. The compositions find use in cleaving or modifying a target sequence of interest, visualization of a target sequence of interest, and modifying the expression of a sequence of interest. Compositions comprise RNA-guided nuclease (RGN) polypeptides, CRISPR RNAs, trans-activating CRISPR RNAs, guide RNAs, and nucleic acid molecules encoding the same. Vectors and host cells comprising the nucleic acid molecules are also provided. Further provided are RGN systems for binding a target sequence of interest, wherein the RGN system comprises an RNA-guided nuclease polypeptide and one or more guide RNAs.

RNA-guided nucleases and active fragments and variants thereof and methods of use

Methods and compositions are provided for determining a pan-cancer clustering of cluster assignment (COCA) subtype of a cancer in an individual by detecting the expression level of at least one classifier biomarker selected from a group of classifier biomarkers for COCA subtypes. Also provided herein are methods and compositions for determining the response of an individual with a COCA subtype to a therapy such as immunotherapy.

Detecting cancer cell of origin

Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer. Methods of the invention further include means for evaluating gene expression profiles, including microarrays and quantitative polymerase chain reaction assays, as well as kits comprising reagents for practicing the methods of the invention.

Method of classifying a breast cancer instrinsic subtype

The application describes methods for screening subjects with breast cancer to determine if the breast cancer will be responsive to a breast cancer therapy including a taxane or a taxane derivative. The application also describes methods for treating subjects with breast cancer by screening them for the likelihood of the effectiveness of treating the cancer with a therapy including a taxane or a taxane derivative and administering the therapy in subjects when it is found that a taxane or a taxane derivative is likely to be effective.

Methods of treating breast cancer with taxane therapy

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Apex, NC, United States of America

Joel S Parker