Illumina Corporation

Microsoft Technology Licensing, LLC

Eugene Chudin

Marina Bibikova

Jian-Bing Fan

Jean Lozach

Michelle Elena Keslin

Daniel Robert Snyder

Arunkumar Gururajan

Si-Qing Chen

Semyon Kruglyak

Tony Y Tzeng

John Hoegger

Jin Hee Lim

Theodor J Scott

Kamal Choudhary

Mihai Aldea

Jeff D Jarrard

Sanjeev Bagaria

Cynthia Guo

Automatic generation of document templates based on recognized composition element patterns in a group of clustered documents is provided. Composition elements used in documents are typically unique to a particular user or to a group of users. An automated template generation system detects composition element patterns in documents associated with a given user. Sequences of composition elements from one document are aligned with sequences of composition elements of one or more other documents. The aligned sequences are scored to generate a document distance matrix. The documents are clustered together based on the alignment scores and a document template is generated for each corresponding cluster of documents. In one or more aspects, selecting a document template and updating it results in a modified document template or, in certain cases, a new document template. The generated document templates are displayed in a user interface for selection by a user.

Generating templates from user's past documents

The present disclosure provides a method for cancer relapse prediction that provides higher resolution grading than Gleason score alone. In particular, the method provides for prediction of prostate cancer relapse that correlates gene expression of each individual signature gene and deriving a prostate cancer gene expression (GEX) score in the plurality of prostate cancer tissue samples; and correlating said GEX score with the clinical outcome for each prostate carcinoma tissue sample. A set of signature genes is provided that encompasses all or a sub-combination of GI_2094528, KIP2, NRG1, NBL1, Prostein, CCNE2, CDC6, FBP1, HOXC6, MKI67, MYBL2, PTTG1, RAMP, UBE2C, Wnt5A, MEMD, AZGP1, CCK, MLCK, PPAP2B, and PROK1.

Gene expression profiles to predict relapse of prostate cancer

The present invention provides a method for preparing a reference model for cancer relapse prediction that provides higher resolution grading than Gleason score alone. The method encompasses obtaining from different individuals a plurality of prostate carcinoma tissue samples of known clinical outcome representing different Gleason scores; selecting a set of signature genes having an expression pattern that correlates positively or negatively in a statistically significant manner with the Gleason scores; independently deriving a prediction score that correlates gene expression of each individual signature gene with Gleason score for each signature gene in said plurality of prostate carcinoma tissue samples; deriving a prostate cancer gene expression (GEX) score that correlates gene expression of said set of signature genes with the Gleason score based on the combination of independently derived prediction scores in the plurality of prostate cancer tissue samples; and correlating said GEX score with the clinical outcome for each prostate carcinoma tissue sample. A set of signature genes is provided that encompasses all or a sub-combination of GI_2094528, KIP2, NRG1, NBL1, Prostein, CCNE2, CDC6, FBP1, HOXC6, MKI67, MYBL2, PTTG1, RAMP, UBE2C, Wnt5A, MEMD, AZGP1, CCK, MLCK, PPAP2B, and PROK1. Also provided a methods for predicting the probability of relapse of cancer in an individual and methods for deriving a prostate cancer gene expression (GEX) score for a prostate carcinoma tissue sample obtained from an individual.

Expression profiles to predict relapse of prostate cancer

The present embodiments relate to a system and method of measuring the methylation level of DNA. Some embodiments relate to a system and method of measuring methylation level of DNA with a gene array.

System and method of measuring methylation of nucleic acids

Growing community of inventors

Kirkland, WA, United States of America

Eugene Chudin