Search

Auf den zweijährig stattfindenden Konferenzen über „circulating nucleic acids in plasma and serum“ (CNAPS) treffen sich regelmäßig zahlreiche renommierte Forschende aus aller Welt, um die neuesten Erkenntnisse und Erfahrungen auf diesem jungen Forschungszweig auszutauschen. Diese umfassen grundlegende Fragen der Struktur und Biologie von zirkulierenden Nukleinsäuren (CNAs), technologische Neuerungen zum hochsensitiven und spezifischen Nachweis im Blut sowie deren Applikationen als diagnostische Biomarker für eine Vielzahl von klinischen Indikationen. In diesem Bericht sind Eindrücke vom 13th International Symposium on Circulating Nucleic Acids in Plasma and Serum (CNAPS) vom 04. bis 06.03.2024 in Graz, Österreich, zusammengefasst. [ABSTRACT FROM AUTHOR]

BACKGROUND: Despite successful response to first line therapy, patients with small-cell lung cancer (SCLC) often suffer from early relapses and disease progression. OBJECTIVE: To investigate the relevance of serum tumor markers for estimation of prognosis at several time points during the course of disease. METHODS: In a prospective, single-center study, serial assessments of progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), cytokeratin-19 fragments (CYFRA 21-1) and carcino-embryogenic antigen (CEA) were performed during and after chemotherapy in 232 SCLC patients, and correlated with therapy response and overall survival (OS). RESULTS: ProGRP, NSE and CYFRA 21-1 levels decreased quickly after the first chemotherapy cycle and correlated well with the radiological response. Either as single markers or in combination they provided valuable prognostic information regarding OS at all timepoints investigated: prior to first-line therapy, after two treatment cycles in patients with successful response to first-line therapy, and prior to the start of second-line therapy. Furthermore, they were useful for continuous monitoring during and after therapy and often indicated progressive disease several months ahead of radiological changes. CONCLUSIONS: The results indicate the great potential of ProGRP, NSE and CYFRA 21-1 for estimating prognosis and monitoring of SCLC patients throughout the course of the disease. [ABSTRACT FROM AUTHOR]

BACKGROUND: Lung cancer is a major burden to global health and is still among the most frequent and most lethal malignant diseases. Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine involved in a variety of processes including tumorigenesis, formation of a tumor microenvironment and metastasis. It is therefore a potential prognostic biomarker in malignant diseases. OBJECTIVE: In this study, we investigated the applicability of MIF in serum samples as a biomarker in lung cancer. METHODS: In a retrospective approach, we analyzed the sera of 79 patients with non-small-cell lung cancer (NSCLC) and 14 patients with small-cell lung cancer (SCLC) before the start of chemotherapy, as well as before the second and third chemotherapy cycle, respectively. Serum MIF levels were measured using a sandwich immunoassay with a sulfo-tag-labelled detection antibody, while pro-gastrin releasing peptide (proGRP) levels were determined with an enzyme-linked immunosorbent assay. RESULTS: No difference in serum MIF levels between responders and non-responders to chemotherapy was observed at all time points, while proGRP levels were significantly lower in responders before the second chemotherapy cycle (p = 0.012). No differences in biomarker levels depending on the histopathological classification of NSCLC patients was found. Moreover, in ROC curve analyses MIF was not able to distinguish between responders and non-responders to therapy. proGRP could differentiate between responders and non-responders before the second chemotherapy cycle (p = 0.015) with sensitivities of 43% at 90% and 95% specificity, respectively. Likewise, proGRP yielded significantly longer survival times of patients with low proGRP concentrations before the second chemotherapy cycle (p = 0.015) in Kaplan-Meier analyses, yet MIF showed no significant differences in survival times at all time points. Comparison with the biomarkers CEA and CYFRA 21-1 in the same cohort showed that these established biomarkers clearly performed superior to MIF and proGRP. CONCLUSIONS: From the present results, there is no indication that serum MIF may serve as a biomarker in prognosis and monitoring of response to therapy in lung cancer. Limitations of this study include its retrospective design, the inclusion of a larger NSCLC and a smaller SCLC subgroup, the classical chemotherapeutic treatment, the use of a non-diagnostic immunoassay (RUO-test) for MIF measurement and the lack of a validation cohort. Strengths of the study are its highly standardized procedures concerning sample collection, preanalytic treatment, measurements and quality control of the laboratory assays. [ABSTRACT FROM AUTHOR]

The cumulative pool of cell-free DNA (cfDNA) molecules within bodily fluids represents a highly dense and multidimensional information repository. This "biological mirror" provides real-time insights into the composition, function, and dynamics of the diverse genomes within the body, enabling significant advancements in personalized molecular medicine. However, effective use of this information necessitates meticulous classification of distinct cfDNA subtypes with exceptional precision. While cfDNA molecules originating from different sources exhibit numerous genetic, epigenetic, and physico-chemical variations, they also share common features that complicate analyses. Considerable progress has been achieved in mapping the landscape of cfDNA features, their clinical correlations, and optimizing extraction procedures, analytical approaches, bioinformatics pipelines, and machine learning algorithms. Nevertheless, preanalytical workflows, despite their profound impact on cfDNA measurements, have not progressed at a corresponding pace. In this perspective article, we emphasize the pivotal role of robust preanalytical procedures in the development and clinical integration of cfDNA assays, highlighting persistent obstacles and emerging challenges. [ABSTRACT FROM AUTHOR]

BACKGROUND: Therapeutic possibilities for non-small cell lung cancer (NSCLC) have considerably increased during recent decades. OBJECTIVE: To summarize the prognostic relevance of serum tumor markers (STM) for early and late-stage NSCLC patients treated with classical chemotherapies, novel targeted and immune therapies. METHODS: A PubMed database search was conducted for prognostic studies on carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA 21-1), neuron-specific enolase, squamous-cell carcinoma antigen, progastrin-releasing-peptide, CA125, CA 19-9 and CA 15-3 STMs in NSCLC patients published from 2008 until June 2022. RESULTS: Out of 1069 studies, 141 were identified as meeting the inclusion criteria. A considerable heterogeneity regarding design, patient number, analytical and statistical methods was observed. High pretherapeutic CYFRA 21-1 levels and insufficient decreases indicated unfavorable prognosis in many studies on NSCLC patients treated with chemo-, targeted and immunotherapies or their combinations in early and advanced stages. Similar results were seen for CEA in chemotherapy, however, high pretherapeutic levels were sometimes favorable in targeted therapies. CA125 is a promising prognostic marker in patients treated with immunotherapies. Combinations of STMs further increased the prognostic value over single markers. CONCLUSION: Protein STMs, especially CYFRA 21-1, have prognostic potential in early and advanced stage NSCLC. For future STM investigations, better adherence to comparable study designs, analytical methods, outcome measures and statistical evaluation standards is recommended. [ABSTRACT FROM AUTHOR]

BACKGROUND: The value of serum tumor markers (STMs) in the current therapeutic landscape of lung cancer is unclear. OBJECTIVE: This scoping review gathered evidence of the predictive, prognostic, and monitoring value of STMs for patients with advanced lung cancer receiving immunotherapy (IT) or targeted therapy (TT). METHODS: Literature searches were conducted (cut-off: May 2022) using PubMed and Cochrane CENTRAL databases. Medical professionals advised on the search strategies. RESULTS: Study heterogeneity limited the evidence and inferences from the 36 publications reviewed. While increased baseline levels of serum cytokeratin 19 fragment antigen (CYFRA21-1) and carcinoembryonic antigen (CEA) may predict IT response, results for TT were less clear. For monitoring IT-treated patients, STM panels (including CYFRA21-1, CEA, and neuron-specific enolase) may surpass the power of single analyses to predict non-response. CYFRA21-1 measurement could aid in monitoring TT-treated patients, but the value of CEA in this context requires further investigation. Overall, baseline and dynamic changes in individual or combined STM levels have potential utility to predict treatment outcome and for monitoring of patients with advanced lung cancer. CONCLUSIONS: In advanced lung cancer, STMs provide additional relevant clinical information by predicting treatment outcome, but further standardization and validation is warranted. [ABSTRACT FROM AUTHOR]

BACKGROUND: Patients with non-small cell lung cancer (NSCLC) and stable disease (SD) have an unmet clinical need to help guide early treatment adjustments. OBJECTIVE: To evaluate the potential of tumor biomarkers to inform on survival outcomes in NSCLC SD patients. METHODS: This post hoc analysis included 480 patients from the IMpower150 study with metastatic NSCLC, treated with chemotherapy, atezolizumab and bevacizumab combinations, who had SD at first CT scan (post-treatment initiation). Patients were stratified into high- and low-risk groups (overall survival [OS] and progression-free survival [PFS] outcomes) based on serum tumor biomarker levels. RESULTS: The CYFRA 21-1 and CA 125 biomarker combination predicted OS and PFS in patients with SD. Risk of death was ~4-fold higher for the biomarker-stratified high-risk versus low-risk SD patients (hazard ratio [HR] 3.80; 95% confidence interval [CI] 3.02–4.78; p < 0.0001). OS in patients with the low- and high-risk SD was comparable to that in patients with the CT-defined partial response (PR; HR 1.10; 95% CI 0.898–1.34) and progressive disease (PD) (HR 1.05; 95% CI 0.621–1.77), respectively. The findings were similar with PFS, and consistent across treatment arms. CONCLUSIONS: Biomarker testing shows potential for providing prognostic information to help direct treatment in NSCLC patients with SD. Prospective clinical studies are warranted. ClinicalTrials.gov: NCT02366143 [ABSTRACT FROM AUTHOR]

BACKGROUND: Serum tumor markers (STM) may complement imaging and provide additional clinical information for patients with non-small cell lung cancer (NSCLC). OBJECTIVE: To determine whether STMs can predict outcomes in patients with stable disease (SD) after initial treatment. METHODS: This single-center, prospective, observational trial enrolled 395 patients with stage III/IV treatment-naïve NSCLC; of which 263 patients were included in this analysis. Computed Tomography (CT) scans were performed and STMs measured before and after initial treatment (two cycles of chemotherapy and/or an immune checkpoint inhibitor or tyrosine kinase inhibitor); analyses were based on CT and STM measurements obtained at first CT performed after cycle 2 only PFS and OS were analyzed by Kaplan-Meier curves and Cox-proportional hazard models. RESULTS: When patients with SD (n = 100) were split into high- and low-risk groups based on CYFRA 21-1, CEA and CA 125 measurements using an optimized cut-off, a 4-fold increase risk of progression or death was estimated for high- vs low-risk SD patients (PFS, HR 4.17; OS, 3.99; both p < 0.0001). Outcomes were similar between patients with high-risk SD or progressive disease (n = 35) (OS, HR 1.17) and between patients with low-risk SD or partial response (n = 128) (PFS, HR 0.98; OS, 1.14). CONCLUSIONS: STMs can provide further guidance in patients with indeterminate CT responses by separating them into high- and low-risk groups for future PFS and OS events. [ABSTRACT FROM AUTHOR]

Paclitaxel/platinum chemotherapy, the backbone of standard first‐line treatment of advanced non‐small cell lung cancer (NSCLC), exhibits high interpatient variability in treatment response and high toxicity burden. Baseline blood biomarker concentrations and tumor size (sum of diameters) at week 8 relative to baseline (RS8) are widely investigated prognostic factors. However, joint analysis of data on demographic/clinical characteristics, blood biomarker levels, and chemotherapy exposure‐driven early tumor response for improved prediction of overall survival (OS) is clinically not established. We developed a Weibull time‐to‐event model to predict OS, leveraging data from 365 patients receiving paclitaxel/platinum combination chemotherapy once every three weeks for ≤six cycles. A developed tumor growth inhibition model, combining linear tumor growth and first‐order paclitaxel area under the concentration‐time curve‐induced tumor decay, was used to derive individual RS8. The median model‐derived RS8 in all patients was a 20.0% tumor size reduction (range from −78% to +15%). Whereas baseline carcinoembryonic antigen, cytokeratin fragments, and thyroid stimulating hormone levels were not significantly associated with OS in a subset of 221 patients, and lactate dehydrogenase, interleukin‐6 and neutrophil‐to‐lymphocyte ratio levels were significant only in univariate analyses (p value < 0.05); C‐reactive protein (CRP) in combination with RS8 most significantly affected OS (p value < 0.01). Compared to the median population OS of 11.3 months, OS was 128% longer at the 5th percentile levels of both covariates and 60% shorter at their 95th percentiles levels. The combined paclitaxel exposure‐driven RS8 and baseline blood CRP concentrations enables early individual prognostic predictions for different paclitaxel dosing regimens, forming the basis for treatment decision and optimizing paclitaxel/platinum‐based advanced NSCLC chemotherapy. [ABSTRACT FROM AUTHOR]

Copyright of Trillium-Diagnostik is the property of Trillium GmbH Medizinischer Fachverlag and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Epigenetic Features of cfDNA Progress in cfDNA research has been driven forward rapidly by systematic characterizations of specific DNA mutations across basic and clinical research settings. This momentum has promise to not only accelerate the advent of personalized cancer care based on cfDNA assays but to also unlock the potential of cfDNA as a biomarker for various other diseases and clinical conditions. Oberhofer et al. also discuss cfDNA fragmentomics, but they also explore exciting and rapidly expanding research showing that various other epigenetic and physico-chemical features of cfDNA, such as various types of DNA methylation patterns, post-translational histone modifications, and nucleosome compaction patterns, are often cell- and disease-specific, which can be leveraged to trace the origins of cfDNA molecules. They found a high concordance in the mutational profiles between cfDNA and tissue analysis, indicating that cfDNA may be an ideal biomarker and potentially an alternative method to tissue analysis for the management of PMBL cases [[20]]. [Extracted from the article]

Laboratory information systems typically contain hundreds or even thousands of reference limits stratified by sex and age. Since under these conditions a manual plausibility check is hardly feasible, we have developed a simple algorithm that facilitates this check. An open-source R tool is available as a Shiny application at github.com/SandraKla/Zlog_AdRI. Based on the zlog standardization, we can possibly detect critical jumps at the transitions between age groups, regardless of the analytical method or the measuring unit. Its advantage compared to the standard z-value is that means and standard deviations are calculated from the reference limits rather than from the underlying data itself. The purpose of the tool is illustrated by the example of reference intervals of children and adolescents from the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER). The Shiny application identifies the zlog values, lists them in a colored table format and plots them additionally with the specified reference intervals. The algorithm detected several strong and rapid changes in reference intervals from the neonatal period to puberty. Remarkable jumps with absolute zlog values of more than five were seen for 29 out of 192 reference limits (15.1%). This might be attenuated by introducing shorter time periods or mathematical functions of reference limits over age. Age-partitioned reference intervals will remain the standard in laboratory routine for the foreseeable future, and as such, algorithmic approaches like our zlog approach in the presented Shiny application will remain valuable tools for testing their plausibility on a wide scale. [ABSTRACT FROM AUTHOR]