Prostate specific antigen proteolytic activity for clinical use
AssigneeOHMX Corporation
InventorDimitra Georganopoulou
Life of this patent
Estimating the term…
Abstract
Methods for predicting the outcome of and monitoring prostate cancer patients using prostate specific antigen (PSA) proteolytic activity (PPA) in combination with other molecular biomarkers or other parameters are described. Methods of determining sets of parameters for use in predicting the outcome of and monitoring of prostate cancer patients are also described.
Claims29
A method for predicting outcome of prostate cancer in a subject diagnosed with prostate cancer, comprising:
- a) determining or obtaining a normalized level of prostate specific antigen (PSA) proteolytic activity (PPA) in a sample from the subject, wherein the normalized level is normalized with a normalization factor;
- b) determining or obtaining a gene expression level of one or more molecular biomarkers in the sample or another sample from the subject;
- c) performing a multi-variate analysis with the normalized level of PPA and gene expression level of one or more molecular biomarkers and, optionally, one or more additional parameters of the subject;
- and
- d) comparing result(s) of the multi-variate analysis to a cutoff value to predict the outcome of prostate cancer in the subject.
The method of any one of the preceding claims, wherein the sample and/or other sample is a/an expressed prostate secretion (EPS), prostatic fluid (PF), semen, urine, or post prostatic massage urine (PMU) sample.
The method of any one of the preceding claims, wherein the normalization factor is serum PSA (sPSA), log of the serum PSA (sPSA), EPS sample volume, log of the EPS sample volume, PSA RNA copy number, log of PSA RNA copy number, amount of RNA, or log of amount of RNA.
The method of any one of the preceding claims, wherein the one or more molecular biomarkers comprises any one or more of TXNRD2, TXNRD1, GAPDH, PSA, TMPRSS2:ERG, PCA3 and GAPDH.
The method of any one of the preceding claims, wherein the one or more additional parameters of the subject comprises one or more of age, Gleason score, and level of sPSA.
The method of any one of the preceding claims, wherein the method further comprises:
- i) creating a ROC curve based on one or more values from the multi-variate analysis;
- ii) identifying the point on the ROC curve closest to the coordinates (0,1);
- and
- iii) using the closest point to establish the cutoff value.
The method of any one of the preceding claims, wherein when the result of the multi-variate analysis is less than the cutoff value, poorer prognosis of prostate cancer is indicated, and when the result is greater than the cutoff value, better prognosis of prostate cancer is indicated.
The method of any one of the preceding claims, further comprising a step of treating the subject or providing information regarding a treatment to the subject based on information obtained from the comparison.
The method of any one of the preceding claims, wherein the treatment comprises further monitoring, or the method further comprises recommending further monitoring of the subject.
The method of any one of the preceding claims, wherein the method further comprises repeating steps a) through d) one or more additional times on one or more samples from the subject to monitor the prostate cancer in the subject.
A method of determining a set of parameters to predict the outcome of prostate cancer in a subject diagnosed with prostate cancer, comprising:
- a) determining or obtaining a normalized level of PPA in a sample from a subject, wherein the normalized level is normalized with a normalization factor;
- b) determining or obtaining a gene expression level of one or more molecular biomarkers in the sample or another sample from the subject;
- c) performing one or more multi-variate analyses with the normalized level of PPA and gene expression level of one or more molecular biomarkers and, optionally, one or more additional parameters of the subject;
- and
- d) determining the predictive power of the one or more multi-variate analyses.
Dependencies are inferred from the claim text.