Abstract:
A method for detecting nucleic acids by (a) providing a sample having target nucleic acids, each nucleic acid having contiguous first, second, and third domains; (b) contacting the sample with probe sets to form hybridization complexes, wherein each probe set includes (i) a first probe having a sequence that is complementary to the first domain; and (ii) a second probe having a sequence substantially complementary to the third domain; (c) extending the first probes along the second domains of the complexes while the complexes are immobilized on a solid support; (d) ligating the extended first probes to the second probes to form templates; (e) amplifying the templates with primers that are complementary to the first and second priming sequences to produce amplicons; and (f) detecting the amplicons on the surface of a nucleic acid array.
Abstract:
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.
Abstract:
A method for determining the presence of multiple nucleotide sequences of interest in multiple samples while preserving the identity of each sample, by contacting the samples with a plurality of probe sets. The probes are designed to indicate the presence of the sequences of interest and the identity of the sample containing the sequence of interest in complex mixtures. Applications of the method include genotyping, expression analysis, and identification of individual species in complex samples. Kits of probe sets for use in the methods are also provided.
Abstract:
The present invention relates to parallel genotyping (or other sample analysis) of multiple patients by direct sample immobilization onto microspheres of an array. The patient beads can then be used in a variety of target analyte analyses.
Abstract:
The present invention relates to parallel genotyping (or other sample analysis) of multiple patients by direct sample immobilization onto microspheres of an array. The patient beads can then be used in a variety of target analyte analyses.
Abstract:
The present invention provides a method for identification of differentially methylated genomic CpG dinucleotide sequences within genomic target sequences that are associated with cancer in an individual by obtaining a biological sample comprising genomic DNA from the individual measuring the level or pattern of methylated genomic CpG dinucleotide sequences for two or more of the genomic targets in the sample, and comparing the level of methylated genomic CpG dinucleotide sequences in the sample to a reference level of methylated genomic CpG dinucleotide sequences, wherein a difference in the level or pattern of methylation of the genomic CpG dinucleotide sequences in the sample compared to the reference level identifies differentially methylated genomic CpG dinucleotide sequences associated with cancer. As disclosed herein, the methods of the invention have numerous diagnostic and prognostic applications. The methods of the invention can be combined with a miniaturized array platform that allows for a high level of assay multiplexing and scalable automation for sample handling and data processing. Also provided by the invention are genomic targets and corresponding nucleic acid probes that are useful in the methods of the invention as they enable detection of differentially methylated genomic CpG dinucleotide sequences associated with adenocarcinomas of the lung.
Abstract:
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.