Abstract:
Disclosed is a gene expression panel that can be used to predict prostate cancer (PCa) progression. Some embodiments provide methods for predicting clinical recurrence of PCa. Some embodiments provide a method for predicting progression of prostate cancer in an individual, the method comprising: (a) receiving expression levels of a collection of signature genes from a biological sample taken from said individual, wherein said collection of signature genes comprises at least two genes selected from the group consisting of: NKX2-1, UPK1A, ADRA2C, ABCC11, MMP11, CPVL, ZYG11A, CLEC4F, OAS2, PGC, UPK3B, PCBP3, ABLIM1, EDARADD, GPR81, MYBPC1, F10, KCNA3, GLDC, KCNQ2, RAPGEF1, TUBB2B, MB, DUOXA1, C2orf43, DUOX1, PCA3 and NPR3; (b) applying the expression levels to a predictive model relating expression levels of said collection of signature genes with prostate cancer progression; and (c) evaluating an output of said predictive model to predict progression of prostate cancer in said individual. Systems are also provided for predicting progression and/or recurrence of PCa.
Abstract:
Disclosed is a gene expression panel that can be used to predict prostate cancer (PCa) progression. Some embodiments provide methods for predicting clinical recurrence of PCa. Some embodiments provide a method for predicting progression of prostate cancer in an individual, the method comprising: (a) receiving expression levels of a collection of signature genes from a biological sample taken from said individual, wherein said collection of signature genes comprises at least two genes selected from the group consisting of: NKX2-1, UPK1A, ADRA2C, ABCC11, MMP11, CPVL, ZYG11A, CLEC4F, OAS2, PGC, UPK3B, PCBP3, ABLIM1, EDARADD, GPR81, MYBPC1, F10, KCNA3, GLDC, KCNQ2, RAPGEF1, TUBB2B, MB, DUOXA1, C2orf43, DUOX1, PCA3 and NPR3; (b) applying the expression levels to a predictive model relating expression levels of said collection of signature genes with prostate cancer progression; and (c) evaluating an output of said predictive model to predict progression of prostate cancer in said individual. Systems are also provided for predicting progression and/or recurrence of PCa.
Abstract:
Disclosed is a gene expression panel that can be used to predict prostate cancer (PCa) progression. Some embodiments provide methods for predicting clinical recurrence of PCa. Some embodiments provide a method for treating a patient with prostate cancer, the method comprising: detecting expression levels of a collection of signature genes from a biological sample taken from said patient, wherein said collection of signature genes comprises at least NKX2-1; and correlating expression levels of said collection of signature genes with prostate cancer-related mortality to identify whether the patient is at risk of prostate cancer-related mortality.
Abstract:
Disclosed is a gene expression panel that can be used to predict prostate cancer (PCa) progression. Some embodiments provide methods for predicting clinical recurrence of PCa. Some embodiments provide a method for predicting progression of prostate cancer in an individual, the method comprising: (a) receiving expression levels of a collection of signature genes from a biological sample taken from said individual, wherein said collection of signature genes comprises at least two genes selected from the group consisting of: NKX2-1, UPK1A, ADRA2C, ABCC11, MMP11, CPVL, ZYG11A, CLEC4F, OAS2, PGC, UPK3B, PCBP3, ABLIM1, EDARADD, GPR81, MYBPC1, F10, KCNA3, GLDC, KCNQ2, RAPGEF1, TUBB2B, MB, DUOXA1, C2orf43, DUOX1, PCA3 and NPR3; (b) applying the expression levels to a predictive model relating expression levels of said collection of signature genes with prostate cancer progression; and (c) evaluating an output of said predictive model to predict progression of prostate cancer in said individual. Systems are also provided for predicting progression and/or recurrence of PCa.
Abstract:
Disclosed is a gene expression panel that can be used to predict prostate cancer (PCa) progression. Some embodiments provide methods for predicting clinical recurrence of PCa. Some embodiments provide a method for predicting progression of prostate cancer in an individual, the method comprising: (a) receiving expression levels of a collection of signature genes from a biological sample taken from said individual, wherein said collection of signature genes comprises at least two genes selected from the group consisting of: NKX2-1, UPK1A, ADRA2C, ABCC11, MMP11, CPVL, ZYG11A, CLEC4F, OAS2, PGC, UPK3B, PCBP3, ABLIM1, EDARADD, GPR81, MYBPC1, F10, KCNA3, GLDC, KCNQ2, RAPGEF1, TUBB2B, MB, DUOXA1, C2orf43, DUOX1, PCA3 and NPR3; (b) applying the expression levels to a predictive model relating expression levels of said collection of signature genes with prostate cancer progression; and (c) evaluating an output of said predictive model to predict progression of prostate cancer in said individual. Systems are also provided for predicting progression and/or recurrence of PCa.
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:
Presented herein are methods and compositions for multiplexed single cell gene expression analysis. Some methods and compositions include the use of droplets and/or beads bearing unique barcodes such as unique molecular barcodes (UMI).
Abstract:
Presented are methods and compositions for obtaining sequence information from one or more individual cells. The methods are useful for obtaining sequence information for a single nucleotide sequence, and for multiplex generation of sequence information from one or more individual cells.
Abstract:
Presented herein are methods and compositions for determining haplotypes in a sample. The methods are useful for obtaining sequence information regarding, for example, HLA type and haplotype. Also presented herein are methods of determining haplotypes in a sample based on a plurality sequence reads.
Abstract:
Presented are methods and compositions for obtaining sequence information from one or more individual cells. The methods are useful for obtaining sequence information for a single nucleotide sequence, and for multiplex generation of sequence information from one or more individual cells.