Extracellular vesicles (EVs) are found in all biological fluids, providing potential for the identification of disease biomarkers such as colorectal cancer (CRC). EVs are heavily glycosylated with specific glycoconjugates such as tetraspanins, integrins, and mucins, reflecting the characteristics of the original cell offering valuable targets for detection of CRC. We report here on europium-nanoparticle (EuNP)-based assay to detect and characterize different surface glycoconjugates of EVs without extensive purification steps from five different CRC and the HEK 293 cell lines. The promising EVs candidates from cell culture were clinically evaluated on small panel of serum samples including early-stage (n = 11) and late-stage (n = 11) CRC patients, benign condition (n = 11), and healthy control (n = 10). The majority of CRC cell lines expressed tetraspanin sub-population and glycovariants of integrins and conventional tumor markers. The subpopulation of CD151 having CD63 expression (CD151CD63) was significantly (p = 0.001) elevated in early-stage CRC (8 out of 11) without detecting any benign and late-stage samples, while conventional CEA detected mostly late-stage CRC (p = 0.045) and with only four early-stage cases. The other glycovariant assays such as CEACon-A, CA125WGA, CA 19.9Ma696, and CA 19.9Con-A further provided some complementation to the CD151CD63 assay. These results indicate the potential application of CD151CD63 assay for early detection of CRC patients in human serum.

To prospectively evaluate the performance of a pre-specified statistical model based on four kallikrein markers in blood (total prostate-specific antigen [PSA], free PSA, intact PSA, and human kallikrein-related peptidase 2), commercially available as the 4Kscore, in predicting Gleason Grade Group (GG) ≥2 prostate cancer at biopsy in an international multicentre study at three academic medical centres, and whether microseminoprotein-b (MSP) adds predictive value. Patients and MethodsA total of 984 men were prospectively enrolled at three academic centres. The primary outcome was GG ≥2 on prostate biopsy. Three pre-specified statistical models were used: a base model including PSA, age, digital rectal examination and prior negative biopsy; a model that added free PSA to the base model; and the 4Kscore. ResultsA total of 947 men were included in the final analysis and 273 (29%) had GG ≥2 on prostate biopsy. The base model area under the receiver operating characteristic curve of 0.775 increased to 0.802 with the addition of free PSA, and to 0.824 for the 4Kscore. Adding MSP to the 4Kscore model yielded an increase (0.014-0.019) in discrimination. In decision-curve analysis of clinical utility, the 4Kscore showed a benefit starting at a 7.5% threshold. ConclusionA prospective multicentre evaluation of a pre-specified model based on four kallikrein markers (4Kscore) with the addition of MSP improves the predictive discrimination for GG ≥2 prostate cancer on biopsy and could be used to inform biopsy decision-making.

Background Subforms of prostate-specific antigen (PSA) have been a subject of intensive research, and use of multikallikrein immunoassays can add clinical value to the early detection of prostate cancer, overcoming known limitations of PSA. In this study, we evaluated mutant 4D4 (L3-2) antibody-assisted assay constructs against reference wild-type (wt)-4D4-based assays for determination of intact PSA (iPSA) and nicked PSA (nPSA) in plasma samples. Methods Perioperative plasma samples obtained from 105 men who underwent biopsy (73 cancer, 32 noncancer) were analyzed with sandwich immunoassays for total PSA (tPSA), free PSA (fPSA), iPSA (3 constructs), and measured nPSA (2 constructs). Calculated nPSA (CN) was obtained from total fPSA − iPSA. Results Mutant-assisted iPSA assays measured lower concentrations than the reference in both patient groups. CN separated the 2 groups with the iPSA using the mutant for capture (I-MC) performing the best (P = 0.008). In prostate volume group > median, only measured nPSA provided significant discrimination [area under the curve (AUC), 0.71; P = 0.016] but equally using mutant and wt antibodies. In the whole cohort, all ratios to tPSA performed well (AUC, 0.819–0.870; P ≤ 0.0001) with CN based on I-MC scoring highest (AUC, 0.870). Importantly, in the ≤ median volume group, the I-MC/F and CN(I-MC)/T ratios stand out as the best performing parameters (AUC, 0.825 and 0.861; P = 0.001 and P = 0.0003, respectively). Conclusions The new assay construct using the mutant 4D4 (L3-2) as a capture provides clear improvement in separating cancer from noncancer in all subgroups analyzed but especially in patients with prostate volume ≤ median. Clinical Trial Registration: ClinicalTrials.gov Identifier NCT01864135.