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Hollanda CN, Gualberto ACM, Motoyama AB, Pittella-Silva F. Advancing Leukemia Management Through Liquid Biopsy: Insights into Biomarkers and Clinical Utility. Cancers (Basel) 2025; 17:1438. [PMID: 40361366 PMCID: PMC12070883 DOI: 10.3390/cancers17091438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2025] [Revised: 04/17/2025] [Accepted: 04/22/2025] [Indexed: 05/15/2025] Open
Abstract
Liquid biopsy is classically defined as the detection of biomarkers in bodily fluids. One of these biomarkers can be circulating cell-free DNA (cfDNA) released by healthy or cancer cells during apoptosis. These fragments can be quantified and molecularly characterized by techniques like digital droplet PCR (ddPCR) or next-generation sequencing (NGS). By identifying common genetic and epigenetic alterations associated with specific cancer types, cfDNA or circulating tumor DNA (ctDNA) can serve as robust biomarkers for monitoring tumor initiation and progression. Other biomarkers, such as circulating microRNAs (miRNAs), extracellular vesicles, or circulating tumor cells (CTCs) are also applied in this context. Liquid biopsy has gained attention as a versatile tool for cancer diagnostics, prognosis, therapeutic monitoring, and minimal residual disease (MRD) detection across various malignancies, including hematological cancers like myeloid and lymphoid leukemias. Herein, we present a comprehensive review of liquid biopsy usage in leukemia, with a specific focus on the clinical utility of ctDNA, miRNAs, and exosomes in monitoring treatment response, tracking clonal evolution, and detecting minimal residual disease. Our review emphasizes the translational implications of these tools for improving patient outcomes and outlines current challenges in their integration into clinical practice.
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Affiliation(s)
| | | | | | - Fabio Pittella-Silva
- Laboratory of Molecular Pathology of Cancer, Faculty of Health Sciences, University of Brasilia, Brasilia 70910-900, Brazil; (C.N.H.); (A.C.M.G.); (A.B.M.)
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Moldovan N, van der Pol Y, van den Ende T, Boers D, Verkuijlen S, Creemers A, Ramaker J, Vu T, Bootsma S, Lenos KJ, Vermeulen L, Fransen MF, Pegtel M, Bahce I, van Laarhoven H, Mouliere F. Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis. Cell Rep Med 2024; 5:101349. [PMID: 38128532 PMCID: PMC10829758 DOI: 10.1016/j.xcrm.2023.101349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 09/22/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023]
Abstract
The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.
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Affiliation(s)
- Norbert Moldovan
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Ymke van der Pol
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Tom van den Ende
- Amsterdam UMC, University of Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Dries Boers
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Sandra Verkuijlen
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Aafke Creemers
- Amsterdam UMC, University of Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Jip Ramaker
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Trang Vu
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Sanne Bootsma
- Amsterdam UMC, University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands; Oncode Institute, Amsterdam, the Netherlands
| | - Kristiaan J Lenos
- Amsterdam UMC, University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands; Oncode Institute, Amsterdam, the Netherlands
| | - Louis Vermeulen
- Amsterdam UMC, University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Amsterdam, the Netherlands; Cancer Center Amsterdam, Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands; Oncode Institute, Amsterdam, the Netherlands
| | - Marieke F Fransen
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pulmonology, Cancer Centre Amsterdam, Amsterdam, the Netherlands
| | - Michiel Pegtel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands
| | - Idris Bahce
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pulmonology, Cancer Centre Amsterdam, Amsterdam, the Netherlands
| | - Hanneke van Laarhoven
- Amsterdam UMC, University of Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands
| | - Florent Mouliere
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Centre Amsterdam, Amsterdam, the Netherlands; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands.
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Wang ZY, Li LL, Cao XL, Li P, Du J, Zou MJ, Wang LL. Clinical application of amplification-based versus amplification-free metagenomic next-generation sequencing test in infectious diseases. Front Cell Infect Microbiol 2023; 13:1138174. [PMID: 38094744 PMCID: PMC10716234 DOI: 10.3389/fcimb.2023.1138174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 11/07/2023] [Indexed: 12/18/2023] Open
Abstract
Background Recently, metagenomic next-generation sequencing (mNGS) has been used in the diagnosis of infectious diseases (IDs) as an emerging and powerful tool. However, whether the complicated methodological variation in mNGS detections makes a difference in their clinical performance is still unknown. Here we conducted a method study on the clinical application of mNGS tests in the DNA detection of IDs. Methods We analyzed the effect of several potential factors in the whole process of mNGS for DNA detection on microorganism identification in 98 samples of suspected ID patients by amplification-based mNGS. The amplification-based and amplification-free mNGS tests were successfully performed in 41 samples. Then we compared the clinical application of the two mNGS methods in the DNA detection of IDs. Results We found that a higher concentration of extracted nucleic acid was more conducive to detecting microorganisms. Other potential factors, such as read depth and proportion of human reads, might not be attributed to microorganism identification. The concordance rate of amplification-based and amplification-free mNGS results was 80.5% (33/41) in the patients with suspected IDs. Amplification-based mNGS showed approximately 16.7% higher sensitivity than amplification-free mNGS. However, 4 cases with causative pathogens only detected by amplification-based mNGS were finally proved false-positive. In addition, empirical antibiotic treatments were adjusted in 18 patients following mNGS testing with unexpected pathogens. Conclusions Amplification-based and amplification-free mNGS tests showed their specific advantages and disadvantages in the diagnosis of IDs. The clinical application of mNGS still needs more exploration from a methodological perspective. With advanced technology and standardized procedure, mNGS will play a promising role in the diagnosis of IDs and help guide the use of antibiotics.
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Affiliation(s)
- Zhe-Ying Wang
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, Jinan, Shandong, China
| | - Lu-Lu Li
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Xue-Lei Cao
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, Jinan, Shandong, China
| | - Ping Li
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, Jinan, Shandong, China
| | - Jian Du
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China
| | - Ming-Jin Zou
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Li-Li Wang
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, Jinan, Shandong, China
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Mendeville M, Roemer MGM, Los-de Vries GT, Chamuleau MED, de Jong D, Ylstra B. The path towards consensus genome classification of diffuse large B-cell lymphoma for use in clinical practice. Front Oncol 2022; 12:970063. [DOI: 10.3389/fonc.2022.970063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 10/17/2022] [Indexed: 11/13/2022] Open
Abstract
Diffuse large B-cell lymphoma (DLBCL) is a widely heterogeneous disease in presentation, treatment response and outcome that results from a broad biological heterogeneity. Various stratification approaches have been proposed over time but failed to sufficiently capture the heterogeneous biology and behavior of the disease in a clinically relevant manner. The most recent DNA-based genomic subtyping studies are a major step forward by offering a level of refinement that could serve as a basis for exploration of personalized and targeted treatment for the years to come. To enable consistent trial designs and allow meaningful comparisons between studies, harmonization of the currently available knowledge into a single genomic classification widely applicable in daily practice is pivotal. In this review, we investigate potential avenues for harmonization of the presently available genomic subtypes of DLBCL inspired by consensus molecular classifications achieved for other malignancies. Finally, suggestions for laboratory techniques and infrastructure required for successful clinical implementation are described.
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