A method and an apparatus for determining a presence or an amount of a polyamine or its derivative in a sample, the method including: applying the sample on an electrochemical detector having a substance selection structure, wherein the substance selection structure is sensitive to the polyamine or its derivative; applying at least one voltage bias to the electrochemical detector; and detecting a change of electrical characteristics of the electrochemical detector so as to determine the presence or the amount of the polyamine or its derivative in the sample.

Methods for differentiating between benign prostatic hyperplasia (BPH) and prostate cancer, in a subject, are provided, such methods including the detection of levels of one or more biomarker diagnostic of BPH. The invention also provides a kit for the diagnosis of BPH, without the need for a biopsy.

The disclosure is directed to a method of diagnosing a prostate condition in a subject by determining, in a sample obtained from a subject, levels of a plurality of constituents selected from the group consisting of Ca, K, Mg, Zn, Ag, AI, Au, B, Ba, Bi, Br, Cd, Ce, Co, Cr, Cs, Cu, Dy, Er, Fe, Gd, Hg, Ho, La, Li, Mn, Na, Nd, Ni, P, Pb, Pr, Rb, S, Sb, Sc, Se, Si, Sm, Sr, Tb, Th, Tl, U, Y, and Zr. A combination of the levels of the plurality of constituents in the sample is compared with a combination of control levels of the same plurality of constituents. A difference between the combinations is indicative of the prostate condition.

A method of analyzing diagnostic information for estimating which of a benign prostate disease and prostate cancer is affecting a subject to be diagnosed combines two methods of analyzing diagnostic information. The first method includes measuring a concentration of a mucin-1 (Tn-MUC1), reactive with a lectin that recognizes and binds to an N-acetyl-D-galactosamine->serine(threonine) residue, in a subject blood sample, comparing the measured value with a threshold value, and estimating that a disease affecting the subject is benign prostate disease when the measured value is greater than the threshold value. The second method includes measuring a concentration of a prostate-specific antigen (LacdiNAc-PSA), reactive with a lectin that recognizes and binds to an N-acetyl-D-galactosamine B1-4 N-acetylglucosamine residue in the blood sample, comparing the measured value with a threshold value, and estimating that the disease affecting the subject is prostate cancer when the measured value of LacdiNAc-PSA is greater than the threshold value.

A method that provides a graphical indication of whether a patient will have cancer recurrence uses univariate and bivariate prognostic features that were generated as part of a minimal spanning tree (MST). The method determines the values of first and second features. A first value is measured by detecting objects in an image of tissue from the cancer patient stained with a protein-specific IHC biomarker. A second value is measured using objects marked with an mRNA-specific probe biomarker detected in the tissue. The first feature is the univariate prognostic feature for cancer recurrence in a cohort of cancer patients. A combination of the first and second features is the bivariate prognostic feature for cancer recurrence in the cohort. The first and second features are elements of the MST. Nodes of the MST represent the univariate features, edges represent the bivariate features, and edge weights represent prognostic significance of bivariate features.

An analysis and display system generates and displays a score indicative of whether cancer will recur in a patient. In a learning phase, a phenomic feature of tumor tissue is measured. A corresponding phenomic feature is defined. The phenomic feature may be measured through image analysis of digital images taken of tissue slices stained with IHC-based stains. A genomic feature of the tissue is also measured. This may entail obtaining a probe count indicative of a degree of expression of a particular gene. A bivariate feature is calculated using both the phenomic and genomic information. A network including the bivariate feature is displayed. In a diagnostic phase, raw phenomic and genomic data is obtained from a tissue sample taken from the patient. From the data, a score for the bivariate feature, and scores for the other features, are calculated. The score is a function of the underlying feature scores.

A method of analyzing diagnostic information, the method including: measuring a concentration of a mucin-1 (Tn-MUC1), which is reactive with a lectin that recognizes and binds to an N-acetyl-D-galactosamine.fwdarw.serine (threonine) residue, in a blood sample originated from a subject to be diagnosed; comparing the measured value with a threshold value; and estimating that a disease affecting the subject to be diagnosed is not prostate cancer but a benign prostate disease when the measured value of the concentration of Tn-MUC1 is greater than the threshold value.

A detection system for determining alpha-methylacyl-CoA (AMACR) levels in a bodily sample includes at least one reaction solution for generating H.sub.2O.sub.2 upon combination with AMACR in the bodily sample and a biosensor for determining a level of generated H.sub.2O.sub.2. The reaction solution includes a (2R)-2-methylacyl-CoA epimer that can be chirally inverted by AMACR to a (2S)-2-methylacyl-CoA epimer and an enzyme that carries out beta oxidation with the (2S)-2-methylacyl-CoA epimer to generate hydrogen peroxide (H.sub.2O.sub.2).

Provided herein and methods and systems for diagnosis of chronic prostatitis (CP) and/or chronic pelvic pain syndrome (CPPS). In particular, methods and systems are provided for monitoring levels of bio-markers of mast cell activity (e.g., mast cell tryptase, carboxypeptidase A3 (CPA3), etc.) in a sample from a subject (e.g., urine, expressed prostatic secretions (EPS), etc.), diagnosing the subject as suffering from CP/CPPS based thereon, and/or treating a subject for CP/CPPS based thereon.

A method of analyzing diagnostic information, the method including: measuring the concentration of all mucin-1s (total MUC1) in a blood sample originated from a subject to be diagnosed; comparing the measured value with a threshold value; and estimating that a disease affecting the subject to be diagnosed is not prostate cancer but a benign prostate disease when the measured value of the concentration of total MUC1 is greater than the threshold value.