INTRODUCTION: Prostate cancer (PC) is the most commonly diagnosed malignancy found in men. Conventional clinical predictors of PC severity—digital rectal examination (DRE), serum prostate specific antigen (PSA), trans-rectal ultrasound (TRUS), and TRUS-guided Gleason score (GS)—are readily obtained but have inherent limitations^1-2. Reports suggest that metabolic biomarkers may be strongly related to outcomes and morbidity in PC episodes^3-7. However, whether the serum metabolic biomarkers may be used for PC screening and prediction is still unknown. Hence, the following potential research queries are still waiting to be observed: (1) Are the filtered-serum-based metabolic biomarkers able to screen and predict BPH and PC? (2) Is a metabolic biomarkers-based model probing better than the PSA, DRE, and TRUS models? MATERIALS AND METHODS: Serum PSA levels, abnormal DRE and TRUS grades were used to evaluate all subjects. Histopathology-based GS were executed to determine low grade (LG) or high grade (HG) PC. A total of 210 blood samples from HC (n=65), BPH (n=70), and PC (n=75) subjects were collected and serum was separated according to standard protocol. Each serum samples were passed through 3kDa filters to remove copious proteins and lipoproteins, and NMR experiments were performed on collected filtrates. A Bruker Avance III 800 MHz spectrometer was used to execute NMR experiments using 400 μL filtered serum samples in 5-mm NMR tubes. Trimethylsilyl propionic acid sodium salt deuterated at CH2 groups was used for the deuterium lock, reference, and standard signal for the quantitation of metabolites. For all the specimens, 1D 1H NMR experiments were performed by suppression of water resonance by pre-saturation. The parameters used were as follows: spectral width, 16666 Hz; time domain points, 65k; relaxation delay, 10s; pulse angle, 90^o; number of scans, 128; and line broadening, 0.3 Hz. The statistical significance for the NMR derived quantified metabolites (n=52) and clinical variables (serum PSA levels, DRE and TRUS grades) were compared using separate linear multivariate discriminant function analysis (DFA) to define important variables for differentiation of disease group (BPH+PC) from controls, followed by discrimination between BPH and PC. DFA constructed four separate sets of classification model such as (1) HC vs BPH + PC, (2) HC vs BPH, (3) HC vs PC and (4) BPH vs PC. The relationship between serum PSA levels and metabolomics derived biomarkers were also analyzed with linear regression. RESULTS: DFA reveals that various combinations of glycine, sarcosine, alanine, creatine, xanthine, hypoxanthine, pyruvate, methylhistidine, creatinine and citrate were playing major role to discriminate all four sets of classifications. DFA between diseased prostate (BPH+PC) and HC reveals that NMR variables based classification (86.2%) is much better then clinical variables (68.1%). Likewise, DFA between BPH and HC discovers that NMR variables based classification (85.9%) is much better then clinical measures (68.1%). DFA between PC and HC reveals that NMR variables based classification (97.1%) is much better then clinical measures (76.4%). Similarly, DFA between BPH and PC reveals that NMR variables based classification (88.3%) is much better then clinical measures (75.2%).DISCUSSION: The results elucidate the gaps of the following thoughts: (i) the filtered-serum based metabolic biomarkers are able to screen and predict the BPH and PC and (ii) metabolic biomarkers based model probes better than clinical variables models. Alanine was found to be significantly higher in cell lines, serum, and biopsy tissues of PC^5,7,8 which is consistent to our observation. Probably it is precondition for uncontrolled cell propagation⁹. Augmented level of pyruvate in diseased prostate (BPH+PC) confirms the outcomes of an augmented level of transamination from pyruvate to alanine, which concurs with earlier 13C hyperpolarized and metabolomics studies^6,7. The augmented level of sarcosine in PC agrees with the finding that the rate of glycine methylation is much higher simultaneous dehydrogenation and that oxidation of sarcosine is relatively lesser in PC^4,3,7. Decrease in glycine level in diseased prostate endorses the lessening of the dehydrogenation and oxidation of sarcosine⁷. Citrate level reduction in PC concurs with the previous findings^10-13 and endorsing various possibly hypotheses^14-15. Serum creatinine and creatine levels were correlated to the GS of PC¹⁶ and cell proliferation in PC¹⁷, respectively, concurs with our observations. Carcinomatosis and muscle protein breakdown^18-19 causes an augmented level of 3-methylhistidine in BPH and PC. Higher levels of xanthine and hypoxanthine in BPH and PC validates that the xanthine as a diagnostic marker of PC^3,20 and hypoxanthine as a signature biomarker for non-Hodgkin’s lymphoma²¹. Regression analysis of these 10 metabolites with PSA revealed that only the PSA vs. pyruvate, PSA vs. citrate, PSA vs. glycine, and PSA vs. sarcosine presented significant correlation (Figure 1).