Methods for predicting cancer outcome and gene signatures for use therein

Inactive Publication Date: 2006-08-31
YEATMAN TIMOTHY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0015] The present invention provides systems and methods for predicting outcomes in patients diagnosed with cancer. Specifically, the subject invention utilizes molecular staging with gene expression prof

Problems solved by technology

The available data, however, does not provide explanations regarding which aspects of human biology affect which genes.
Unfortunately, no research has yet been conducted on identifying specific genes associated with colorectal cancer and specific outcomes to provide an accurate prediction of prognosis.
The Dukes' staging system, however, has only been found useful in predicting the behaviour of a population of patients, rather than an individual.
Unfortunately, application of th

Method used

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  • Methods for predicting cancer outcome and gene signatures for use therein
  • Methods for predicting cancer outcome and gene signatures for use therein
  • Methods for predicting cancer outcome and gene signatures for use therein

Examples

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example 1

Human Colon Cancer Survival Classifier

Training Set Tumor Samples

[0065] In one embodiment of the subject invention, a colon cancer survival classifier was developed using 78 tumor samples, including 3 adenomas and 75 cancers. Informative frozen colorectal cancer samples were selected from the Moffitt Cancer Center Tumor Bank (Tampa, Fla.) based on evidence for good (survival >36 mo) or poor prognosis (survival <36 mo) from the Tumor Registry. Dukes' stages can include B, C, and D. In this particular embodiment, survival was measured as last contact minus collection date for living patients, or date of death minus collection date for patients who have died.

[0066] In this embodiment, the number of samples per Dukes' stage was as follows: 23 patients with stage B, 22 patients with stage C and 30 patients with stage D disease. Just as adenomas can be included to help train the classifier to recognize good prognosis patients, Dukes D patients with synchronous metastatic disease can be...

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Abstract

The present invention pertains to specific gene signatures for cancer that are used to predict survival and novel processes for identifying such gene signatures. In one embodiment, gene signatures for human colorectal cancer are identified and outcomes are linked to the specific gene signatures using significance analysis of microarrays (SAM) and support vector machines (SVM) to provide a prognosis/survival classifier.

Description

CROSS-REFERENCE TO A RELATED APPLICATION [0001] This application claims the benefit of U.S. Provisional Application Ser. No. 60 / 547,871, filed Feb. 25, 2004, which is hereby incorporated by reference in its entirety.BACKGROUND OF THE INVENTION [0002] In the last decade, scientists have labored to complete a high-quality, comprehensive sequence of the human genome. With its recent completion, a large number of genomic data sets have been made available in public databases. The available data, however, does not provide explanations regarding which aspects of human biology affect which genes. Researchers are just beginning to explore genomic function. [0003] Several technological advances have made it possible to accurately measure cellular constituents and therefore derive profiles. For example, new techniques provide the ability to monitor the expression level of a large number of transcripts at any one time (see, for example, Schena et al., “Quantitative monitoring of gene expressio...

Claims

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Application Information

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IPC IPC(8): G06F19/00G16B25/10G16B40/10G16B40/20
CPCC12Q1/6886C12Q2600/106C12Q2600/118G06F19/20G06F19/24G16B25/00G16B40/00G16B40/10G16B25/10G16B40/20
Inventor YEATMAN, TIMOTHY
Owner YEATMAN TIMOTHY
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