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Köhler CU, Schork K, Turewicz M, Eisenacher M, Roghmann F, Noldus J, Marcus K, Brüning T, Käfferlein HU. Use of Multiple Machine Learning Approaches for Selecting Urothelial Cancer-Specific DNA Methylation Biomarkers in Urine. Int J Mol Sci 2024; 25:738. [PMID: 38255812 PMCID: PMC10815677 DOI: 10.3390/ijms25020738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 01/03/2024] [Accepted: 01/05/2024] [Indexed: 01/24/2024] Open
Abstract
Diagnosing urothelial cancer (UCa) via invasive cystoscopy is painful, specifically in men, and can cause infection and bleeding. Because the UCa risk is higher for male patients, urinary non-invasive UCa biomarkers are highly desired to stratify men for invasive cystoscopy. We previously identified multiple DNA methylation sites in urine samples that detect UCa with a high sensitivity and specificity in men. Here, we identified the most relevant markers by employing multiple statistical approaches and machine learning (random forest, boosted trees, LASSO) using a dataset of 251 male UCa patients and 111 controls. Three CpG sites located in ALOX5, TRPS1 and an intergenic region on chromosome 16 have been concordantly selected by all approaches, and their combination in a single decision matrix for clinical use was tested based on their respective thresholds of the individual CpGs. The combination of ALOX5 and TRPS1 yielded the best overall sensitivity (61%) at a pre-set specificity of 95%. This combination exceeded both the diagnostic performance of the most sensitive bioinformatic approach and that of the best single CpG. In summary, we showed that overlap analysis of multiple statistical approaches identifies the most reliable biomarkers for UCa in a male collective. The results may assist in stratifying men for cystoscopy.
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Affiliation(s)
- Christina U. Köhler
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Ruhr University Bochum (IPA), Bürkle-de-la-Camp Platz 1, 44789 Bochum, Germany; (C.U.K.)
| | - Karin Schork
- Medizinisches Proteom-Center, Medical Faculty, Ruhr-University Bochum and Medical Proteome Analysis, Center for Protein Diagnostics (PRODI), Gesundheitscampus 4, 44081 Bochum, Germany
| | - Michael Turewicz
- Medizinisches Proteom-Center, Medical Faculty, Ruhr-University Bochum and Medical Proteome Analysis, Center for Protein Diagnostics (PRODI), Gesundheitscampus 4, 44081 Bochum, Germany
| | - Martin Eisenacher
- Medizinisches Proteom-Center, Medical Faculty, Ruhr-University Bochum and Medical Proteome Analysis, Center for Protein Diagnostics (PRODI), Gesundheitscampus 4, 44081 Bochum, Germany
| | - Florian Roghmann
- Department of Urology, Marien Hospital Herne, University Hospital of the Ruhr University Bochum, Hölkeskampring 40, 44625 Herne, Germany
| | - Joachim Noldus
- Department of Urology, Marien Hospital Herne, University Hospital of the Ruhr University Bochum, Hölkeskampring 40, 44625 Herne, Germany
| | - Katrin Marcus
- Medizinisches Proteom-Center, Medical Faculty, Ruhr-University Bochum and Medical Proteome Analysis, Center for Protein Diagnostics (PRODI), Gesundheitscampus 4, 44081 Bochum, Germany
| | - Thomas Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Ruhr University Bochum (IPA), Bürkle-de-la-Camp Platz 1, 44789 Bochum, Germany; (C.U.K.)
| | - Heiko U. Käfferlein
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Ruhr University Bochum (IPA), Bürkle-de-la-Camp Platz 1, 44789 Bochum, Germany; (C.U.K.)
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2
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Moser T, Kühberger S, Lazzeri I, Vlachos G, Heitzer E. Bridging biological cfDNA features and machine learning approaches. Trends Genet 2023; 39:285-307. [PMID: 36792446 DOI: 10.1016/j.tig.2023.01.004] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 01/10/2023] [Accepted: 01/19/2023] [Indexed: 02/15/2023]
Abstract
Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to revolutionize precision oncology and blood-based cancer screening. Recent technological improvements, in combination with the ever-growing understanding of cell-free DNA (cfDNA) biology, are enabling the detection of tumor-specific changes with extremely high resolution and new analysis concepts beyond genetic alterations, including methylomics, fragmentomics, and nucleosomics. The interrogation of a large number of markers and the high complexity of data render traditional correlation methods insufficient. In this regard, machine learning (ML) algorithms are increasingly being used to decipher disease- and tissue-specific signals from cfDNA. Here, we review recent insights into biological ctDNA features and how these are incorporated into sophisticated ML applications.
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Affiliation(s)
- Tina Moser
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Stefan Kühberger
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Isaac Lazzeri
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Georgios Vlachos
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Ellen Heitzer
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria.
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3
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Liu Z, Georgakopoulos-Soares I, Ahituv N, Wong KC. Risk scoring based on DNA methylation-driven related DEGs for colorectal cancer prognosis with systematic insights. Life Sci 2023; 316:121413. [PMID: 36682524 DOI: 10.1016/j.lfs.2023.121413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/13/2023] [Accepted: 01/16/2023] [Indexed: 01/22/2023]
Abstract
Colorectal cancer is a common malignant tumor of the digestive tract. Despite advances in diagnostic techniques and medications. Its prognosis remains challenging. DNA methylation-driven related circulating tumor cells have attracted enormous interest in diagnosing owing to their non-invasive nature and early recognition properties. However, the mechanism through which risk biomarkers act remains elusive. Here, we designed a risk model based on differentially expressed genes, DNA methylation, robust, and survival-related factors in the framework of Cox regression. The model has satisfactory performance and is independently verified by an external and isolated dataset in terms of C-index value, ROC, and tROC. The model was applied to Colorectal cancer patients who were subsequently divided into high- and low-risk groups. Functional annotations, genomic alterations, tumor immune environment, and drug sensitivity were analyzed. We observed that up-regulated genes are associated with epithelial cell differentiation and MAPK signaling pathways. The down-regulated genes are related to IL-7 signaling and apoptosis-induced DNA fragmentation. Interestingly, the immune system was inhibited in high-risk groups. High-frequency mutation genes tend to co-occur. High-risk score patients are related to copy number amplification events. To address the challenges, we suggested eleven and twenty-one drugs that are sensitive to low- and high-risk patients. Finally, an artificial neural network was provided to evaluate the immunotherapeutic efficiency. Taken together, the findings demonstrated that our risk score model is robust and reliable for evaluating the prognosis with novel diagnostic and treatment targets. It also yields benefits for the treatment and provides unique insights into developing therapeutic strategies.
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Affiliation(s)
- Zhe Liu
- Department of Computer Science, City University of Hong Kong, Hong Kong, China
| | - Ilias Georgakopoulos-Soares
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Ka-Chun Wong
- Department of Computer Science, City University of Hong Kong, Hong Kong, China.
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4
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Blood-based DNA methylation signatures in cancer: A systematic review. Biochim Biophys Acta Mol Basis Dis 2023; 1869:166583. [PMID: 36270476 DOI: 10.1016/j.bbadis.2022.166583] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 09/30/2022] [Accepted: 10/11/2022] [Indexed: 11/07/2022]
Abstract
DNA methylation profiles are in dynamic equilibrium via the initiation of methylation, maintenance of methylation and demethylation, which control gene expression and chromosome stability. Changes in DNA methylation patterns play important roles in carcinogenesis and primarily manifests as hypomethylation of the entire genome and the hypermethylation of individual loci. These changes may be reflected in blood-based DNA, which provides a non-invasive means for cancer monitoring. Previous blood-based DNA detection objects primarily included circulating tumor DNA/cell-free DNA (ctDNA/cfDNA), circulating tumor cells (CTCs) and exosomes. Researchers gradually found that methylation changes in peripheral blood mononuclear cells (PBMCs) also reflected the presence of tumors. Blood-based DNA methylation is widely used in early diagnosis, prognosis prediction, dynamic monitoring after treatment and other fields of clinical research on cancer. The reversible methylation of genes also makes them important therapeutic targets. The present paper summarizes the changes in DNA methylation in cancer based on existing research and focuses on the characteristics of the detection objects of blood-based DNA, including ctDNA/cfDNA, CTCs, exosomes and PBMCs, and their application in clinical research.
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Challenges in promoter methylation analysis in the new era of translational oncology: a focus on liquid biopsy. Biochim Biophys Acta Mol Basis Dis 2022; 1868:166390. [PMID: 35296416 DOI: 10.1016/j.bbadis.2022.166390] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 02/01/2022] [Accepted: 03/08/2022] [Indexed: 12/20/2022]
Abstract
Toward the discovery of novel reliable biomarkers, epigenetic alterations have been repeatedly proposed for the diagnosis and the development of therapeutic strategies against cancer. Indeed, for promoter methylation to actively become a tumor marker for clinical use, it must be combined with a highly informative technology evaluated in an appropriate biospecimen. Methodological standardization related to epigenetic research is, in fact, one of the most challenging tasks. Moreover, tissue-based biopsy is being complemented and, in some cases, replaced by liquid biopsy. This review will highlight the advancements made for both pre-analytical and analytical implementation for the prospective use of methylation biomarkers in clinical settings, with particular emphasis on liquid biopsy.
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Huang J, Soupir AC, Schlick BD, Teng M, Sahin IH, Permuth JB, Siegel EM, Manley BJ, Pellini B, Wang L. Cancer Detection and Classification by CpG Island Hypermethylation Signatures in Plasma Cell-Free DNA. Cancers (Basel) 2021; 13:cancers13225611. [PMID: 34830765 PMCID: PMC8616264 DOI: 10.3390/cancers13225611] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 11/01/2021] [Accepted: 11/06/2021] [Indexed: 01/12/2023] Open
Abstract
Simple Summary The detection of DNA methylation changes in blood has emerged as a promising approach for cancer diagnosis and management. Our group has previously optimized a blood DNA methylation profiling technology that is based on affinity capture of methylated DNA, termed cfMBD-seq. The aim of this study was to assess the potential clinical feasibility of cfMBD-seq. We applied cfMBD-seq to the blood samples of cancer patients and identified methylation signatures that can not only discriminate cancer patients from cancer-free individuals but can also enable accurate multi-cancer classification. Our findings will help to expand on existing blood-based molecular diagnostic tests and identify novel methylation biomarkers for early cancer detection and classification. Abstract Cell-free DNA (cfDNA) methylation has emerged as a promising biomarker for early cancer detection, tumor type classification, and treatment response monitoring. Enrichment-based cfDNA methylation profiling methods such as cfMeDIP-seq have shown high accuracy in the classification of multiple cancer types. We have previously optimized another enrichment-based approach for ultra-low input cfDNA methylome profiling, termed cfMBD-seq. We reported that cfMBD-seq outperforms cfMeDIP-seq in the enrichment of high-CpG-density regions, such as CpG islands. However, the clinical feasibility of cfMBD-seq is unknown. In this study, we applied cfMBD-seq to profiling the cfDNA methylome using plasma samples from cancer patients and non-cancer controls. We identified 1759, 1783, and 1548 differentially hypermethylated CpG islands (DMCGIs) in lung, colorectal, and pancreatic cancer patients, respectively. Interestingly, the vast majority of DMCGIs were overlapped with aberrant methylation changes in corresponding tumor tissues, indicating that DMCGIs detected by cfMBD-seq were mainly driven by tumor-specific DNA methylation patterns. From the overlapping DMCGIs, we carried out machine learning analyses and identified a set of discriminating methylation signatures that had robust performance in cancer detection and classification. Overall, our study demonstrates that cfMBD-seq is a powerful tool for sensitive detection of tumor-derived epigenomic signals in cfDNA.
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Affiliation(s)
- Jinyong Huang
- Department of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA; (J.H.); (A.C.S.)
| | - Alex C. Soupir
- Department of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA; (J.H.); (A.C.S.)
| | - Brian D. Schlick
- Department of Thoracic Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA;
- Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
| | - Mingxiang Teng
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA;
| | - Ibrahim H. Sahin
- Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA;
| | - Jennifer B. Permuth
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA; (J.B.P.); (E.M.S.)
| | - Erin M. Siegel
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA; (J.B.P.); (E.M.S.)
| | - Brandon J. Manley
- Department of Genitourinary Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA;
| | - Bruna Pellini
- Department of Thoracic Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA;
- Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
- Correspondence: (B.P.); (L.W.)
| | - Liang Wang
- Department of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA; (J.H.); (A.C.S.)
- Correspondence: (B.P.); (L.W.)
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Krasic J, Abramovic I, Vrtaric A, Nikolac Gabaj N, Kralik-Oguic S, Katusic Bojanac A, Jezek D, Sincic N. Impact of Preanalytical and Analytical Methods on Cell-Free DNA Diagnostics. Front Cell Dev Biol 2021; 9:686149. [PMID: 34552921 PMCID: PMC8451956 DOI: 10.3389/fcell.2021.686149] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 08/13/2021] [Indexed: 01/18/2023] Open
Abstract
While tissue biopsy has for the longest time been the gold-standard in biomedicine, precision/personalized medicine is making the shift toward liquid biopsies. Cell-free DNA (cfDNA) based genetic and epigenetic biomarkers reflect the molecular status of its tissue-of-origin allowing for early and non-invasive diagnostics of different pathologies. However, selection of preanalytical procedures (including cfDNA isolation) as well as analytical methods are known to impact the downstream results. Calls for greater standardization are made continuously, yet comprehensive assessments of the impact on diagnostic parameters are lacking. This study aims to evaluate the preanalytic and analytic factors that influence cfDNA diagnostic parameters in blood and semen. Text mining analysis has been performed to assess cfDNA research trends, and identify studies on isolation methods, preanalytical and analytical impact. Seminal and blood plasma were tested as liquid biopsy sources. Traditional methods of cfDNA isolation, commercial kits (CKs), and an in-house developed protocol were tested, as well as the impact of dithiothreitol (DTT) on cfDNA isolation performance. Fluorimetry, qPCR, digital droplet PCR (ddPCR), and bioanalyzer were compared as cfDNA quantification methods. Fragment analysis was performed by qPCR and bioanalyzer while the downstream application (cfDNA methylation) was analyzed by pyrosequencing. In contrast to blood, semen as a liquid biopsy source has only recently begun to be reported as a liquid biopsy source, with almost half of all publications on it being review articles. Experimental data revealed that cfDNA isolation protocols give a wide range of cfDNA yields, both from blood and seminal plasma. The addition of DTT to CKs has improved yields in seminal plasma and had a neutral/negative impact in blood plasma. Capillary electrophoresis and fluorometry reported much higher yields than PCR methods. While cfDNA yield and integrity were highly impacted, cfDNA methylation was not affected by isolation methodology or DTT. In conclusion, NucleoSnap was recognized as the kit with the best overall performance. DTT improved CK yields in seminal plasma. The in-house developed protocol has shown near-kit isolation performance. ddPCR LINE-1 assay for absolute detection of minute amounts of cfDNA was established and allowed for quantification of samples inhibited in qPCR. cfDNA methylation was recognized as a stable biomarker unimpacted by cfDNA isolation method. Finally, semen was found to be an abundant source of cfDNA offering potential research opportunities and benefits for cfDNA based biomarkers development related to male reproductive health.
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Affiliation(s)
- Jure Krasic
- Department of Medical Biology, School of Medicine, University of Zagreb, Zagreb, Croatia
- Scientific Group for Research on Epigenetic Biomarkers, School of Medicine, University of Zagreb, Zagreb, Croatia
- Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Irena Abramovic
- Department of Medical Biology, School of Medicine, University of Zagreb, Zagreb, Croatia
- Scientific Group for Research on Epigenetic Biomarkers, School of Medicine, University of Zagreb, Zagreb, Croatia
- Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Alen Vrtaric
- Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Clinical Chemistry, Sestre Milosrdnice University Hospital Center, Zagreb, Croatia
| | - Nora Nikolac Gabaj
- Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Clinical Chemistry, Sestre Milosrdnice University Hospital Center, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Sasa Kralik-Oguic
- Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
- Clinical Institute of Laboratory Diagnostics, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Ana Katusic Bojanac
- Department of Medical Biology, School of Medicine, University of Zagreb, Zagreb, Croatia
- Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Davor Jezek
- Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Histology and Embryology, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Nino Sincic
- Department of Medical Biology, School of Medicine, University of Zagreb, Zagreb, Croatia
- Scientific Group for Research on Epigenetic Biomarkers, School of Medicine, University of Zagreb, Zagreb, Croatia
- Centre of Excellence for Reproductive and Regenerative Medicine, School of Medicine, University of Zagreb, Zagreb, Croatia
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Liu L, Chen X, Petinrin OO, Zhang W, Rahaman S, Tang ZR, Wong KC. Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey. Life (Basel) 2021; 11:638. [PMID: 34209249 PMCID: PMC8308091 DOI: 10.3390/life11070638] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 06/23/2021] [Accepted: 06/24/2021] [Indexed: 12/24/2022] Open
Abstract
With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.
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Affiliation(s)
- Linjing Liu
- Department of Computer Science, City University of Hong Kong, Hong Kong, China; (L.L.); (X.C.); (O.O.P.); (W.Z.); (S.R.); (Z.-R.T.)
| | - Xingjian Chen
- Department of Computer Science, City University of Hong Kong, Hong Kong, China; (L.L.); (X.C.); (O.O.P.); (W.Z.); (S.R.); (Z.-R.T.)
| | - Olutomilayo Olayemi Petinrin
- Department of Computer Science, City University of Hong Kong, Hong Kong, China; (L.L.); (X.C.); (O.O.P.); (W.Z.); (S.R.); (Z.-R.T.)
| | - Weitong Zhang
- Department of Computer Science, City University of Hong Kong, Hong Kong, China; (L.L.); (X.C.); (O.O.P.); (W.Z.); (S.R.); (Z.-R.T.)
| | - Saifur Rahaman
- Department of Computer Science, City University of Hong Kong, Hong Kong, China; (L.L.); (X.C.); (O.O.P.); (W.Z.); (S.R.); (Z.-R.T.)
| | - Zhi-Ri Tang
- Department of Computer Science, City University of Hong Kong, Hong Kong, China; (L.L.); (X.C.); (O.O.P.); (W.Z.); (S.R.); (Z.-R.T.)
| | - Ka-Chun Wong
- Department of Computer Science, City University of Hong Kong, Hong Kong, China; (L.L.); (X.C.); (O.O.P.); (W.Z.); (S.R.); (Z.-R.T.)
- Hong Kong Institute for Data Science, City University of Hong Kong, Hong Kong, China
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Huang J, Soupir AC, Wang L. Cell-free DNA methylome profiling by MBD-seq with ultra-low input. Epigenetics 2021; 17:239-252. [PMID: 33724157 DOI: 10.1080/15592294.2021.1896984] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Methylation signatures in cell-free DNA (cfDNA) have shown great sensitivity and specificity in the characterization of tumour status and classification of tumour types, as well as the response to therapy and recurrence. Currently, most cfDNA methylation studies are based on bisulphite conversion, especially targeted bisulphite sequencing, while enrichment-based methods such as cfMeDIP-seq are beginning to show potential. Here, we report an enrichment-based ultra-low input cfDNA methylation profiling method using methyl-CpG binding proteins capture, termed cfMBD-seq. We optimized the conditions for cfMBD capture by adjusting the amount of MethylCap protein along with using methylated filler DNA. Our data show high correlation between low input cfMBD-seq and standard MBD-seq (>1000 ng input). When compared to cfMEDIP-seq, cfMBD-seq demonstrates higher sequencing data quality with more sequenced reads passed filter and less duplicate rate. cfMBD-seq also outperforms cfMeDIP-seq in the enrichment of CpG islands. This new bisulphite-free ultra-low input methylation profiling technology has great potential in non-invasive and cost-effective cancer detection and classification.
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Affiliation(s)
- Jinyong Huang
- Department of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL, USA
| | - Alex C Soupir
- Department of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL, USA
| | - Liang Wang
- Department of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL, USA
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10
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Hernández-Barranco A, Nogués L, Peinado H. Could Extracellular Vesicles Contribute to Generation or Awakening of "Sleepy" Metastatic Niches? Front Cell Dev Biol 2021; 9:625221. [PMID: 33738282 PMCID: PMC7960773 DOI: 10.3389/fcell.2021.625221] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/25/2021] [Indexed: 12/12/2022] Open
Abstract
Pre-metastatic niches provide favorable conditions for tumor cells to disseminate, home to and grow in otherwise unfamiliar and distal microenvironments. Tumor-derived extracellular vesicles are now recognized as carriers of key messengers secreted by primary tumors, signals that induce the formation of pre-metastatic niches. Recent evidence suggests that tumor cells can disseminate from the very earliest stages of primary tumor development. However, once they reach distal sites, tumor cells can persist in a dormant state for long periods of time until their growth is reactivated and they produce metastatic lesions. In this new scenario, the question arises as to whether extracellular vesicles could influence the formation of these metastatic niches with dormant tumor cells? (here defined as "sleepy niches"). If so, what are the molecular mechanisms involved? In this perspective-review article, we discuss the possible influence of extracellular vesicles in early metastatic dissemination and whether they might play a role in tumor cell dormancy. In addition, we comment whether extracellular vesicle-mediated signals may be involved in tumor cell awakening, considering the possibility that extracellular vesicles might serve as biomarkers to detect early metastasis and/or minimal residual disease (MRD) monitoring.
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Affiliation(s)
- Alberto Hernández-Barranco
- Microenvironment and Metastasis Laboratory, Molecular Oncology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain
| | - Laura Nogués
- Microenvironment and Metastasis Laboratory, Molecular Oncology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain
| | - Héctor Peinado
- Microenvironment and Metastasis Laboratory, Molecular Oncology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain
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11
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García-Silva S, Gallardo M, Peinado H. DNA-Loaded Extracellular Vesicles in Liquid Biopsy: Tiny Players With Big Potential? Front Cell Dev Biol 2021; 8:622579. [PMID: 33575258 PMCID: PMC7872099 DOI: 10.3389/fcell.2020.622579] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022] Open
Affiliation(s)
- Susana García-Silva
- Microenvironment and Metastasis Laboratory, Molecular Oncology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain
| | - Miguel Gallardo
- H12O - CNIO Hematological Malignancies Clinical Research Unit, Clinical Research Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain
| | - Héctor Peinado
- Microenvironment and Metastasis Laboratory, Molecular Oncology Programme, Spanish National Cancer Research Center (CNIO), Madrid, Spain
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12
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Qian Y, Wang H, Zhang Y, Wang JW, Fan YC, Gao S, Wang K. Hypermethylation of Cyclin D2 Predicts Poor Prognosis of Hepatitis B Virus-Associated Hepatocellular Carcinoma after Hepatectomy. TOHOKU J EXP MED 2021; 254:233-243. [PMID: 34334537 DOI: 10.1620/tjem.254.233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Prognosis of patients with hepatocellular carcinoma remains poor because of progression of hepatocellular carcinoma and high recurrence rates. Cyclin D2 (CCND2) plays a vital role in regulating the cell cycle; indeed, aberrant methylation of CCND2 is involved in the development of hepatocellular carcinoma. Therefore, we aimed to investigate levels of CCND2 methylation in patients with hepatitis B virus (HBV)-associated hepatocellular carcinoma and to evaluate its prognostic significance after hepatectomy. In total, 257 subjects were enrolled (166 hepatocellular carcinoma patients undergoing surgical resection, 61 chronic hepatitis B (CHB) patients, and 30 healthy controls). CCND2 methylation in peripheral blood mononuclear cells was measured quantitatively using MethyLight. We found that CCND2 methylation levels in patients with HBV-associated hepatocellular carcinoma were significantly higher than in CHB patients (P < 0.001) or healthy controls (P < 0.001). Within the hepatocellular carcinoma group, CCND2 methylation levels were higher in patients with portal vein invasion, early tumor recurrence, TNM III/IV stage, and tumor size ≥ 5 cm (P < 0.05). Furthermore, higher levels of CCND2 methylation were associated with worse overall survival and disease-free survival (P = 0.005 and P < 0.001, respectively). Multivariate analysis identified CCND2 methylation as an independent prognostic factor for early tumor recurrence (P = 0.021), overall survival (P = 0.022), and disease-free survival (P < 0.001) in hepatocellular carcinoma patients after resection. In conclusion, hypermethylation of CCND2 may have clinical utility for predicting a high risk of poor prognosis and early tumor recurrence in patients with HBV-associated hepatocellular carcinoma after hepatectomy.
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Affiliation(s)
- Yu Qian
- Department of Hepatology, Qilu Hospital, Cheeloo College of Medicine, Shandong University
| | - He Wang
- Department of Hepatopathy, Qingdao Sixth People's Hospital
| | - Ying Zhang
- Department of Hepatology, Qilu Hospital, Cheeloo College of Medicine, Shandong University
| | - Jing-Wen Wang
- Department of Hepatology, Qilu Hospital, Cheeloo College of Medicine, Shandong University
| | - Yu-Chen Fan
- Department of Hepatology, Qilu Hospital, Cheeloo College of Medicine, Shandong University.,Institute of Hepatology, Shandong University
| | - Shuai Gao
- Department of Hepatology, Qilu Hospital, Cheeloo College of Medicine, Shandong University.,Institute of Hepatology, Shandong University
| | - Kai Wang
- Department of Hepatology, Qilu Hospital, Cheeloo College of Medicine, Shandong University.,Institute of Hepatology, Shandong University
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