Molecular Diagnosis & Therapy最新文献

Objectives: To investigate whether 18F-fluorodeoxyglucose positron emission tomography-computed tomography ([¹⁸F]F-FDG PET/CT) metabolic parameters were associated with histology and to assess their prognostic role in patients with thymic lesions.

Patients and methods: In total, 116 patients (49/67 M/F; mean age 59.5 years) who underwent preoperative [¹⁸F]F-FDG PET/CT and thymectomy from 2012 to 2022 were retrospectively analyzed. Associations between histology and metabolic parameters (maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), peak standardized uptake value (SUVpeak), total lesion glycolysis (TLG), metabolic tumor volume (MTV), ratio between target lesion and liver SUVmax (rPET), quotient of SUVpeak in the tumor residual and SUVmean in a 20-cm³ volume of interest (qPET), and tumor-to-mediastinum (T/M) were analyzed. Freedom from recurrence (FFR) was determined and compared using the Kaplan-Meier and the log-rank test. The median follow-up was 38 months (range 14-72 months).

Results: In total, 27 thymic hyperplasia, 41 low-risk thymomas (LRT) (types A, AB, and B1), and 48 high-risk thymomas (HRT) (B2, B3 thymoma, and carcinoma) were included. SUVmax, SUVmean, SUVpeak, rPET, qPET, and T/M were significantly higher in HRT than LRT and hyperplasia (p < 0.001). TLG and MTV were significantly higher in patients with LRT (p < 0.001). Only rPET, qPET, and T/M remained significantly higher in HRT than in LRT subgroups (p = 0.042, p = 0.049, and p = 0.028, respectively). SUVmax, SUVmean, and SUVpeak cutoffs of < 4.3, < 2.87, and 4.03, respectively, significantly distinguished patients with longer FFR (p = 0.009, p = 0.05, and p = 0.05).

Conclusions: Positron emission tomography (PET) metabolic parameters could help to differentiate thymic histotypes. Standardized uptake value (SUV)-based parameters appear promising to predict recurrent disease.

Hearing loss represents a highly prevalent and debilitating sensory disorder affecting roughly one in five people worldwide. In a majority of patients with congenital hearing loss, genetic mutations cause the disease. Up until recently, therapeutic options for individuals with hearing loss were limited to hearing aids and different types of auditory implants. However, after numerous years of intensive basic and translational research, gene therapy strategies are now being investigated in clinical trials. First results show significant hearing improvement in treated patients, highlighting gene therapy's role as a promising treatment for certain forms of genetic hearing loss. In this article, we provide an overview of genetic hearing loss and inner ear gene therapy research including relevant strategies that have been established in animal models and will likely be investigated in human patients soon. Furthermore, we summarize and contextualize the novel findings of recently completed and ongoing clinical trials, and discuss future hurdles needed to be overcome to allow for a broad and safe clinical application of inner ear gene therapy.

To better understand ovarian cancer lethality and treatment resistance, sophisticated computational approaches are required that address the complexity of the tumor microenvironment, genomic heterogeneity, and tumor evolution. The ovarian cancer tumor ecosystem consists of multiple tumors and cell types that support disease growth and progression. Over the last two decades, there has been a revolution in -omic methodologies to broadly define components and essential processes within the tumor microenvironment, including transcriptomics, metabolomics, proteomics, genome sequencing, and single-cell analyses. While most of these technologies comprehensively characterize a single biological process, there is a need to understand the biological and clinical impact of integrating multiple -omics platforms. Overall, multi-omics is an intriguing analytic framework that can better approximate biological complexity; however, data aggregation and integration pipelines are not yet sufficient to reliably glean insights that affect clinical outcomes.

Obecabtagene autoleucel (AUCATZYL^®) is a CD19-directed genetically modified autologous T cell immunotherapy which is being developed by Autolus for the treatment of hematological cancers and systemic lupus erythematosus. In comparison with other chimeric antigen receptor T (CAR T) therapies, obecabtagene autoleucel has a fast off-rate binder for CD19. Obecabtagene autoleucel received approval following positive results from the FELIX phase I/II trial in adults with relapsed or refractory B-cell precursor acute lymphoblastic leukemia (ALL), and it is the first CAR T therapy that does not have mandatory Risk Evaluation Mitigation Strategy monitoring requirements. This article summarizes the milestones in the development of obecabtagene autoleucel leading to this first approval for the treatment of adults with relapsed or refractory B-cell precursor ALL.

Clinical endpoints caused by hyperlipoproteinemia include atherosclerotic cardiovascular disease and acute pancreatitis. Emerging lipid-lowering therapies targeting proprotein convertase subtilisin/kexin 9 (PCSK9), lipoprotein(a), apolipoprotein C-III, and angiopoietin-like protein 3 represent promising advances in the management of patients with hyperlipoproteinemia. These therapies offer novel approaches for lowering pathogenic lipid and lipoprotein species, particularly in patients with serious perturbations who are not adequately controlled with conventional treatments or who are unable to tolerate them. Molecular targets for these novel therapeutic agents were identified and validated through genetic epidemiology studies. Proprotein convertase subtilisin/kexin 9 inhibitors (e.g., monoclonal antibodies and small interfering RNA) have revolutionized hypercholesterolemia management by significantly reducing both low-density lipoprotein cholesterol levels and major cardiovascular events. Genome editing of PCSK9 promises to provide a potential cure for patients with familial hypercholesterolemia. Several investigational lipoprotein(a)-targeting therapies aim to reduce the risk of atherosclerotic cardiovascular disease and aortic valve disease, although definitive clinical endpoint studies remain to be completed. Inhibition of APOC3 messenger RNA expression by olezarsen and plozasiran significantly lowers plasma triglyceride levels and markedly reduces pancreatitis risk in patients with familial chylomicronemia syndrome. Finally, angiopoietin-like protein 3 inhibition by the monoclonal antibody evinacumab has transformed management of patients with homozygous familial hypercholesterolemia. Together, these novel agents expand the therapeutic cache, offering personalized lipid-lowering strategies for high-risk patients with hyperlipoproteinemia, improving clinical outcomes and addressing previously unmet medical needs.

Introduction: Testing for homologous recombination deficiency (HRD) as a biomarker in relation to poly (ADP-ribose) polymerase inhibitor (PARPi) treatment in ovarian cancer is done by sequencing of the BRCA1/2 genes and/or by assessing a genomic instability signature. Here we present data obtained with two different methods for genomic instability testing: the Oncomine™ Comprehensive Assay Plus (OCA Plus) NGS panel and the OncoScan CNV assay.

Methods: The retrospective analytical study included 80 ovarian cancer samples of patients previously referred to clinical Myriad testing (reference cohort), and 50 ovarian cancer samples from patients collected as part of the Pelvic Mass study. OCA Plus NGS libraries were sequenced with the Ion S5™XL Sequencer and analyzed with the Ion Reporter™ Software v5.20 for calculation of the genomic instability metric (GIM). In addition, all samples were tested with the OncoScan CNV FFPE Assay and analyzed with a previously published R-algorithm for generation of an in-house genomic instability score (in-house GIS).

Results: The OCA Plus assay had a concordance to the reference of 89% on samples with a tumor fraction ≥ 30% (auto-calculated or via molecular estimation). A total of 15 samples in the reference cohort had a calculated tumor fraction < 30% in the OCA Plus assay. In these, the concordance to reference was only 60%. For the OncoScan CNV in-house GIS a local cutoff point of ≥ 50 was calculated. This gave a concordance to the reference of 85%, with 91% of the samples in the reference cohort passing quality control (QC) on tumor fraction. Both assays had a high sensitivity for the detection of genomic instability in samples with pathogenic or likely pathogenic BRCA1/2 mutations, with 12/13 being GIM positive (OCA Plus assay) and 13/13 being in-house GIS positive (OncoScan CNV assay).

Conclusions: The OCA Plus assay and the OncoScan CNV assay show a high but not complete concordance to reference standard homologous recombination deficiency (HRD) detection. The main reason for QC failure or non-concordance in our study was a low tumor fraction estimated in the assay, despite the selection of material by a pathologist with an inclusion criterion of > 30% tumor. QC steps should include careful tumor content evaluation, and results on samples with < 30% tumor should not be reported.

Digital PCR (dPCR) has been used in the field of virology since its inception. Technological innovations in microfluidics more than a decade ago caused a sharp increase in its use. There is an emerging consensus that dPCR now outperforms quantitative PCR (qPCR) in the basic parameters such as precision, sensitivity, accuracy, repeatability and resistance to inhibitors. These strengths have led to several current applications in quantification, mutation detection and environmental DNA and RNA samples. In high throughput scenarios, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the cost and throughput still significantly hampered the adaption of dPCR. There is much unexplored potential within the multiplexing capabilities of dPCR. This will allow simultaneous multi-target quantification and can also partially alleviate the throughput and cost drawback. In this review, we discuss the strengths and weaknesses of dPCR with a focus on virology applications and we discuss future applications. Finally, we discuss recent evolutions of the technology in the form of real-time dPCR and digital high-resolution melting.

Compromising between accuracy and rapidity is an important issue in analytics and diagnostics, often preventing timely and appropriate reactions to disease. This issue is particularly critical for infectious diseases, where reliable and rapid diagnosis is crucial for effective treatment and easier containment, thereby reducing economic and societal impacts. Diagnostic technologies are vital in disease modeling, tracking, treatment decision making, and epidemic containment. At the point-of-care level in modern healthcare, accurate diagnostics, especially those involving genetic-level analysis and nucleic acid amplification techniques, are still needed. However, implementing these techniques in remote or non-laboratory settings poses challenges because of the need for trained personnel and specialized equipment, as all nucleic acid-based diagnostic techniques, such as polymerase chain reaction and isothermal nucleic acid amplification, require temperature cycling or elevated and stabilized temperatures. However, in smart food packaging, there are approved and commercially available methods that use temperature regulation to enable autonomous heat generation without external sources, such as chemical heaters with phase change materials. These approaches could be applied in diagnostics, facilitating point-of-care, electricity-free molecular diagnostics, especially with nucleic acid-based detection methods such as isothermal nucleic acid amplification. In this review, we explore the potential interplay between self-heating elements, isothermal nucleic acid amplification techniques, and phase change materials. This paves the way for the development of truly portable, electricity-free, point-of-care diagnostic tools, particularly advantageous for on-site detection in resource-limited remote settings and for home use.

Background: The widespread use of next-generation sequencing in clinical practice has contributed to the accumulation of a large number of genomic findings associated with targeted therapy; therefore, the problem of ranking the detected findings has become acute. The European Society for Medical Oncology Scale of Clinical Actionability of molecular Targets (ESCAT) system was designed by the European Society for Medical Oncology to rank biomarkers into levels of evidence that reflect their potency and clinical significance based on published clinical data. However, the ESCAT system remains imperfect, as it is based on a subjective assessment of the levels of evidence.

Objective: The objective of this study was to determine whether the ranking of LOE for biomarker-drug pairs based on the ESCAT system is dependent on the human factor, and to uncover potential issues associated with the use of the framework.

Methods: To evaluate the inter-rater agreement, we created a dataset of a total of 154 biomarker-drug pairs for 18 unique tumor types. We aimed to include biomarker-drug pairs that could be considered standard of care as well as less common and under investigated pairs. Fourteen precision oncology experts were invited to assign an ESCAT level of evidence for biomarker-drug pairs. Statistical analysis was carried out using Cohen's kappa and the Kolmogorov-Smirnov test.

Results: The inter-rater agreement was low with some exceptions, and significant deviations from the consensus level of evidence were observed. For biomarker-drug associations, the deviations from the consensus were observed for more than 50% of the contributors' rankings. The most agreement between the contributors was observed for lung adenocarcinoma (p < 0.005), while the most disagreement was observed for esophageal cancer (p < 0.01) biomarker-drug pairs in our dataset.

Conclusions: This study demonstrates noteworthy discordances between the precision oncology experts and may provide the directions for future developments in modifying the ESCAT framework and the overall applicability of the results of genomic profiling into clinical practice.