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BackgroundProstate cancer is the most common cancer in men and represents a major public health problem. The current method for the diagnosis or screening of prostate cancer is invasive and costly. There have been renewed and innovative studies searching for urinary biomarkers to aid in the diagnosis of prostate cancer, especially with technologies based on urinary exosomes. However, technologies based on urine exosomes usually need expensive machines such as an ultracentrifuge and they are difficult to standardize, which hinder their application in clinical laboratories. We have optimized and standardized the isolation of urinary exosomes with the precipitation method. We have found that urinary exosomal prostate-specific antigen (PSA) can be quantified by automatic Elecsys total PSA technique. ObjectiveIn this study, our objective is to utilize urinary exosomes from prostate cancer for the development of a test to aid in its diagnosis. MethodsExosomes from the prostate cancer cell line LNCaP was used to set up the technique. To analyze urine samples from patients, the methods include the collection of first-void urine using the Colli-Pee device, the isolation of urine exosomes using the optimized precipitation method, and the quantification of exosomal PSA by Elecsys total PSA. ResultsThis will be a 2-year study. We will start including patients and controls in the last quarter of 2024. We expect the results to be published in the second quarter of 2027. ConclusionsThis is the first study to quantify urinary exosomal PSA using the Elecsys total PSA technique for the diagnosis of prostate cancer. This study emphasizes techniques that are suitable for implementation in clinical laboratories, which will facilitate the application of urinary exosomes to simplify and improve the diagnosis and screening of prostate cancer. International Registered Report Identifier (IRRID)PRR1-10.2196/63551

The objective of this study was to assess the clinical impact and financial costs of next-generation sequencing (NGS) in 5 categories of pediatric and adult hematological cancers. NGS prescriptions were prospectively collected from 26 laboratories, with varied technical and reporting practice (all or only significant targets). Impact was defined by the identification of (1) an actionable mutation, (2) a mutation with prognostic and/or theranostic value, and/or (3) a mutation allowing nosological refinement, reported by local investigators. A microcosting study was undertaken in 4 laboratories, identifying the types and volumes of resources required for each procedural step. Individual index prescriptions for 3961 patients were available for impact analysis on the management of myeloid disorders (two thirds) and, mainly mature B, lymphoid disorders (one third). NGS results were considered to impact the management for 73.4% of prescriptions: useful for evaluation of prognostic risk in 34.9% and necessary for treatment adaptation (actionable) in 19.6%, but having no immediate individual therapeutic impact in 18.9%. The average overall cost per sample was 191 € for the restricted mature lymphoid amplicon panel. Capture panel costs varied from 369 € to 513 €. Unit costs varied from 0.5 € to 5.7 € per kb sequenced, from 3.6 € to 11.3 € per target gene/hot-spot sequenced and from 4.3 € to 73.8 € per target gene/hot-spot reported. Comparable costs for the Amplicon panels were 5–8 € per kb and 10.5–14.7 € per target gene/hot-spot sequenced and reported, demonstrating comparable costs with greater informativity/flexibility for capture strategies. Sustainable funding of precision medicine requires a transparent discussion of its impact on care pathways and its financial aspects.

Background: We hypothesized that the fine needle aspiration (FNA) supernatant from tumor might contain tumor-derived exosomes. The objective of this pilot study was to test if tumor-derived exosomal RNA could be found in FNA supernatants for molecular diagnosis of cancer.Methods: 10 FNA samples from pancreatic tumor were included. After the routine recuperation of cellular material by centrifugation, the cell-free Cytolyt liquid was collected instead of being discarded. 10 ml Cytolyt was used to isolate the exosomes. Transmission electronic microscopy (TEM) was used to examine the presence of exosomes. The exosomal marker CD63 was analyzed by flow cytometry. The exosomal RNA was extracted. RT-qPCR was performed to detect the GAPDH and the tumor marker of glypican 1 gene expression.Results: TEM confirmed the presence of exosomes from FNA supernatants. Flow cytometry showed a strong positive expression of exosome marker CD63. The concentration of exosomal RNA ranged from 18.81 to 354.75 ng/μl with an average of 81.76 ng/μl. The average exosomal RNA quantity was 1390.01 ng (range from 319.77 to 6030.75 ng) with an average 260/280 ratio of 2.12. GAPDH was detectable in all samples. Exosomal glypican 1 was detected in all samples of pancreatic ductal adenorcarcinomas (3/3) and absent from benign cystic samples (3/3). Furthermore, exosomal glypican 1 was positive in one sample with a non-contributive cytology and in one sample in which no malignant cell was found.Conclusion: This is the first report that the supernatants from FNA biopsy may contain tumor-derived exosomal RNA. These tumor-derived exosomes from FNA may provide a new liquid biopsy for the molecular diagnosis of cancer.

Molecular tests have become an indispensable tool for the diagnosis and prognosis of hematological malignancies and are subject to accreditation according to the International Standard ISO 15189. National standardization of these techniques is essential to ensure that patients throughout France benefit from the same care. We report here on the experience of the GBMHM (Groupe des Biologistes Moléculaires des Hémopathies Malignes). By organizing External Evaluation of Quality (EEQ) programs and training meetings, the GBMHM has contributed to improvement and standardization of molecular tests in 64 French laboratories. A retrospective analysis of the quality-control results of 11 national campaigns spanning 10 years was performed for the 3 most frequently prescribed tests: BCR-ABL1, JAK2 V617F, and lymphoid clonality. For each test, particular attention was placed on comparing methodologies and their evolution throughout the period. The establishment of the BCR-ABL1, JAK2 V617F, and lymphoid clonality EEQ programs and the associated training meetings have initiated a process of collective standardization concerning the methods of implementation (JAK2 V617F) and the interpretation and formulation of results (lymphoid clonality). In addition, it resulted in objective improvement in technical performance (BCR-ABL1). Our evaluation of the impact of these EEQ programs demonstrates that it is possible to obtain reproducible values across different laboratories in France by applying national recommendations. To our knowledge, this is the first publication that evaluates the impact of a national quality assurance program on improving molecular results in hematology.

Acute myeloid leukemias (AMLs) are hematologic malignancies with varied molecular and immunophenotypic profiles, making them difficult to diagnose and classify. High-dimensional analysis algorithms might increase the utility of multicolor flow cytometry for AML diagnosis and follow-up. The objective of the present study was to assess whether a Compass database-guided analysis can be used to achieve rapid and accurate diagnoses. We conducted this study to determine whether this method could be employed to pilote the genetic and molecular tests and to objectively identify different-from-normal (DfN) patterns to improve measurable residual disease follow-up in AML. Three Compass databases were built using Infinicyt 2.0 software, including normal myeloid-committed hematopoietic precursors (n = 20) and AML blasts harboring the most frequent recurrent genetic abnormalities (n = 50). The diagnostic accuracy of the Compass database-guided analysis was evaluated in a prospective validation study (125 suspected AML patients). This method excluded AML associated with the following genetic abnormalities: t(8;21), t(15;17), inv(16), and KMT2A translocation, with 92% sensitivity [95% confidence interval (CI): 78.6%–98.3%] and a 98.5% negative predictive value (95% CI: 90.6%–99.8%). Our data showed that the Compass database-guided analysis could identify phenotypic differences between AML groups, representing a useful tool for the identification of DfN patterns.