Development and evaluation of the MiCheck® Prostate test for clinically significant prostate cancer.

BACKGROUND: There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously reported the development of the MiCheck® Test for clinically significant prostate cancer. Here, we report MiCheck's further development and incorporation of the Roche Cobas standard clinical chemistry analyzer. OBJECTIVES: To further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample set. DESIGN, SETTINGS, AND PARTICIPANTS: About 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP. METHODS: Serum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry analyzers were examined for their ability to contribute to an algorithm with high sensitivity for the detection of clinically significant prostate cancer. Samples were then re-measured using a Roche Cobas analyzer for development of the final algorithm. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Logistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensitivity. A final model was developed using analyte measurements from the Cobas analzyer. RESULTS: The MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant cancer with AUC of 0.85, sensitivity of 95%, and specificity of 50%. Applying the MiCheck® test to all evaluable 358 patients from the MiCheck-01 study demonstrated that up to 50% of unnecessary biopsies could be avoided while delaying diagnosis of only 5.3% of Gleason Score (GS) ≥3+4 cancers, 1.8% of GS≥4+3 cancers and no cancers of GS 8 to 10. CONCLUSIONS: The MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas clinical chemistry analyzer. The MiCheck® Prostate test could assist in reducing unnecessary prostate biopsies with a marginal number of patients experiencing a delayed diagnosis.

Detection of rare prostate cancer cells in human urine offers prospect of non-invasive diagnosis.

Two molecular cytology approaches, (i) time-gated immunoluminescence assay (TGiA) and (ii) Raman-active immunolabeling assay (RiA), have been developed to detect prostate cancer (PCa) cells in urine from five prostate cancer patients. For TGiA, PCa cells stained by a biocompatible europium chelate antibody-conjugated probe were quantitated by automated time-gated microscopy (OSAM). For RiA, PCa cells labeled by antibody-conjugated Raman probe were detected by Raman spectrometer. TGiA and RiA were first optimized by the detection of PCa cultured cells (DU145) spiked into control urine, with TGiA-OSAM showing single-cell PCa detection sensitivity, while RiA had a limit of detection of 4-10 cells/mL. Blinded analysis of each patient urine sample, using MIL-38 antibody specific for PCa cells, was performed using both assays in parallel with control urine. Both assays detected very low abundance PCa cells in patient urine (3-20 PCa cells per mL by TGiA, 4-13 cells/mL by RiA). The normalized mean of the detected PCa cells per 1 ml of urine was plotted against the clinical data including prostate specific antigen (PSA) level and Clinical Risk Assessment for each patient. Both cell detection assays showed correlation with PSA in the high risk patients but aligned with the Clinical Assessment rather than with PSA levels of the low/intermediate risk patients. Despite the limited available urine samples of PCa patients, the data presented in this proof-of-principle work is promising for the development of highly sensitive diagnostic urine tests for PCa.

Glypican-1 as a target for fluorescence molecular imaging of bladder cancer.

OBJECTIVES: To investigate whether anti-glypican-1 antibody Miltuximab conjugated with near-infrared dye IRDye800CW can be used for in vivo fluorescence imaging of urothelial carcinoma. METHODS: The conjugate, Miltuximab-IRDye800CW, was produced and characterized by size exclusion chromatography and flow cytometry with glypican-1-expressing cells. Balb/c nude mice bearing subcutaneous urothelial carcinoma xenografts were intravenously injected with Miltuximab-IRDye800CW or control IgG-IRDye800CW and imaged daily by fluorescence imaging. After 10 days, tumors and major organs were collected for ex vivo study of the conjugate biodistribution, including its accumulation in the tumor. RESULTS: The intravenous injection of Miltuximab-IRDye800CW to tumor-bearing mice showed its specific accumulation in the tumors with the tumor-to-background ratio of 12.7 ± 2.4, which was significantly higher than that in the control group (4.6 ± 0.9, P < 0.005). The ex vivo imaging was consistent with the in vivo findings, with tumors from the mice injected with Miltuximab-IRDye800CW being significantly brighter than the organs or the control tumors. CONCLUSIONS: The highly specific accumulation and retention of Miltuximab-IRDye800CW in glypican-1-expressing tumors in vivo shows its high potential for fluorescence imaging of urothelial carcinoma and warrants its further investigation toward clinical translation.

The feasibility of Miltuximab®-IRDye700DX-mediated photoimmunotherapy of solid tumors.

BACKGROUND: Photoimmunotherapy (PIT) is an emerging method of cancer treatment based on the use of a photosensitizer near-infrared dye IRDye700DX (IR700) conjugated to a monoclonal antibody. The antibody selectively delivers IR700 to cancer cells, which can then be killed after photoexcitation. Glypican-1 (GPC-1) is a novel target expressed specifically in malignant tumors. We aimed to investigate whether anti-GPC-1 antibody Miltuximab® (Glytherix Ltd., Sydney, Australia) can be conjugated with IR700 for PIT of solid tumors. METHODS: The dye IR700 was conjugated with Miltuximab® and characterized by spectrophotometry and flow cytometry. Miltuximab®-IR700-mediated PIT was tested in prostate (DU-145), bladder (C3 and T-24), brain (U-87 and U-251) and ovarian (SKOV-3) cancer cell lines. After 1 h incubation with Miltuximab®-IR700, the cells were washed by PBS and illuminated using a 690-nm light-emitting diode. The viability of the cells was assessed by a CCK-8 viability kit 24 h later. RESULTS: Miltuximab®-IR700-mediated PIT caused 67.3-92.3% reduction in viability of cells with medium-high GPC-1 expression and did not affect the viability of GPC-1-low cells. Cytotoxicity was attributed to the targeted binding of the conjugate with subsequent photoactivation, as the conjugate or light exposure alone had no effect on the cell viability. Miltuximab®-IR700 did not induce cytotoxicity in cells blocked by unconjugated Miltuximab®. CONCLUSIONS: PIT with Miltuximab®-IR700 appears to be highly specific and effective against GPC-1-expressing cancer cells, indicating that it holds promise for an effective and safe treatment of early stage solid tumors or as adjuvant therapy following surgical resection. These findings necessitate further investigation of PIT with Miltuximab®-IR700 in other GPC-1-expressing cancer cell lines in vitro and in vivo in xenograft tumor models.

Near-Infrared Molecular Imaging of Glioblastoma by Miltuximab®-IRDye800CW as a Potential Tool for Fluorescence-Guided Surgery.

Glioblastoma (GBM) is one of the most aggressive tumors and its 5-year survival is approximately 5%. Fluorescence-guided surgery (FGS) improves the extent of resection and leads to better prognosis. Molecular near-infrared (NIR) imaging appears to outperform conventional FGS, however, novel molecular targets need to be identified in GBM. Proteoglycan glypican-1 (GPC-1) is believed to be such a target as it is highly expressed in GBM and is associated with poor prognosis. We hypothesize that an anti-GPC-1 antibody, Miltuximab®, conjugated with the NIR dye, IRDye800CW (IR800), can specifically accumulate in a GBM xenograft and provide high-contrast in vivo fluorescent imaging in rodents following systemic administration. Miltuximab® was conjugated with IR800 and intravenously administered to BALB/c nude mice bearing a subcutaneous U-87 GBM hind leg xenograft. Specific accumulation of Miltuximab®-IR800 in subcutaneous xenograft tumor was detected 24 h later using an in vivo fluorescence imager. The conjugate did not cause any adverse events in mice and caused strong fluorescence of the tumor with tumor-to-background ratio (TBR) reaching 10.1 ± 2.8. The average TBR over the 10-day period was 5.8 ± 0.6 in mice injected with Miltuximab®-IR800 versus 2.4 ± 0.1 for the control group injected with IgG-IR800 (p = 0.001). Ex vivo assessment of Miltuximab®-IR800 biodistribution confirmed its highly specific accumulation in the tumor. The results of this study confirm that Miltuximab®-IR800 holds promise for intraoperative fluorescence molecular imaging of GBM and warrants further studies.

Computer-assisted cystoscopy diagnosis of bladder cancer.

OBJECTIVES: One of the most reliable methods for diagnosing bladder cancer is cystoscopy. Depending on the findings, this may be followed by a referral to a more experienced urologist or a biopsy and histological analysis of suspicious lesion. In this work, we explore whether computer-assisted triage of cystoscopy findings can identify low-risk lesions and reduce the number of referrals or biopsies, associated complications, and costs, although reducing subjectivity of the procedure and indicating when the risk of a lesion being malignant is minimal. MATERIALS AND METHODS: Cystoscopy images taken during routine clinical patient evaluation and supported by biopsy were interpreted by an expert clinician. They were further subjected to an automated image analysis developed to best capture cancer characteristics. The images were transformed and divided into segments, using a specialised color segmentation system. After the selection of a set of highly informative features, the segments were separated into 4 classes: healthy, veins, inflammation, and cancerous. The images were then classified as healthy and diseased, using a linear discriminant, the naïve Bayes, and the quadratic linear classifiers. Performance of the classifiers was measured by using receiver operation characteristic curves. RESULTS: The classification system developed here, with the quadratic classifier, yielded 50% false-positive rate and zero false-negative rate, which means, that no malignant lesions would be missed by this classifier. CONCLUSIONS: Based on criteria used for assessment of cystoscopy images by medical specialists and features that human visual system is less sensitive to, we developed a computer program that carries out automated analysis of cystoscopy images. Our program could be used as a triage to identify patients who do not require referral or further testing.