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Simple Summary: Prostate cancer (PCa) accounts for the second-highest mortality rate in cancer-associated deaths. Liquid biopsy has great potential to tailor treatment choices in advanced PCa. In this study, we evaluated the utility and diagnostic potential of a custom-designed NGS cfDNA panel based on the AmpliSeq HD Technology in advanced PCa. cfDNA somatic mutations were detected in the majority (71%) of examined advanced PCa patients. The most frequently mutated genes in the PCa cohort of 68 patients (40 metastatic castration-resistant and 28 metastatic hormone-naive PCa) were: TP53, FOXA1, SPOP, PTEN, AR, CTNNB1, RB1, and PIK3CA. AR amplifications were detected in 31% of mCRPC patients. This approach appears to be a straightforward and cost-effective method for detecting clinically relevant somatic mutations in cfDNA to aid in clinical decision-making. Most men with prostate cancer (PCa), despite potentially curable localized disease at initial diagnosis, progress to metastatic disease. Despite numerous treatment options, choosing the optimal treatment for individual patients remains challenging. Biomarkers guiding treatment sequences in an advanced setting are lacking. To estimate the diagnostic potential of liquid biopsies in guiding personalized treatment of PCa, we evaluated the utility of a custom-targeted next-generation sequencing (NGS) panel based on the AmpliSeq HD Technology. Ultra-deep sequencing on plasma circulating free DNA (cfDNA) samples of 40 metastatic castration-resistant PCa (mCRPC) and 28 metastatic hormone-naive PCa (mCSPC) was performed. CfDNA somatic mutations were detected in 48/68 (71%) patients. Of those 68 patients, 42 had matched tumor and cfDNA samples. In 21/42 (50%) patients, mutations from the primary tumor tissue were detected in the plasma cfDNA. In 7/42 (17%) patients, mutations found in the primary tumor were not detected in the cfDNA. Mutations from primary tumors were detected in all tested mCRPC patients (17/17), but only in 4/11 with mCSPC. AR amplifications were detected in 12/39 (31%) mCRPC patients. These results indicate that our targeted NGS approach has high sensitivity and specificity for detecting clinically relevant mutations in PCa. [ABSTRACT FROM AUTHOR]

Purpose: The spatial variability and clinical relevance of the tumour immune microenvironment (TIME) are still poorly understood for hepatocellular carcinoma (HCC). Here we aim to develop a deep learning (DL)-based image analysis model for the spatial analysis of immune cell biomarkers, and microscopically evaluate the distribution of immune infiltration., Experimental Design: Ninety-two HCC surgical liver resections and 51 matched needle biopsies were histologically classified according to their immunophenotypes: inflamed, immune-excluded, and immune-desert. To characterise the TIME on immunohistochemistry (IHC)-stained slides, we designed a multi-stage DL algorithm, IHC-TIME, to automatically detect immune cells and their localisation in TIME in tumour-stromal, centre-border segments., Results: Two models were trained to detect and localise the immune cells on IHC-stained slides. The framework models, i.e. immune cell detection models and tumour-stroma segmentation, reached 98% and 91% accuracy, respectively. Patients with inflamed tumours showed better recurrence-free survival than those with immune-excluded or immune desert tumours. Needle biopsies were found to be 75% accurate in representing the immunophenotypes of the main tumour. Finally, we developed an algorithm that defines immunophenotypes automatically based on the IHC-TIME analysis, achieving an accuracy of 80%., Conclusions: Our DL-based tool can accurately analyse and quantify immune cells on IHC-stained slides of HCC. The microscopical classification of the TIME can stratify HCCs according to the patient prognosis. Needle biopsies can provide valuable insights for TIME-related prognostic prediction, albeit with specific constraints. The computational pathology tool provides a new way to study the HCC TIME.

Background/aim: Extracellular vesicle DNA (EV-DNA) has emerged as a novel biomarker for tumor mutation detection using liquid biopsies, exhibiting biological advantages compared to cell-free DNA (cfDNA). This study assessed the feasibility of EV-DNA and cfDNA extraction and sequencing in old serum samples of patients with breast cancer (BC)., Patients and Methods: A total of 28 serum samples of 27 patients with corresponding clinical information were collected between 1983 and 1991. EV-DNA was extracted using Exo-GAG kit (Nasabiotech) and cfDNA using QIAsymphony DSP Virus/Pathogen Midi Kit (Qiagen), respectively. Subsequently, 10 matched samples (EV-DNA n=5, cfDNA n=5) of five patients were subjected to sequencing using the Oncomine™ Breast cfDNA Research Assay v2 (Thermo Fisher Scientific)., Results: Samples were collected on median 1.9 years after primary diagnosis [interquartile range (IQR)=0.2-7.2]. Median follow-up was 9.5 years (IQR=5.2-14.2). Median age of serum samples was 36.1 years (IQR=34.5-37.3). EV-DNA and cfDNA were extracted from 100% (28/28) of the included samples. Both, DNA quantity and concentration were comparable between EV-DNA and cfDNA. Sequencing was successfully performed in 100% (10/10) of the included samples. Two matched analyses yielded equivalent results in EV-DNA and cfDNA (no mutations, n=1; PIK3CA mutation, n=1), whilst in two analyses, PIK3CA mutation was only found in cfDNA, and in one analysis, a TP53 mutation was only found in EV-DNA., Conclusion: EV-DNA extraction and sequencing in old serum samples of patients with BC is feasible and has the potential to address clinically relevant questions in longitudinal studies., (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)