CoChat
Sign Up
Cited by 133

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Bridging biological cfDNA features and machine learning approaches

Moser, Tina, Kühberger, Stefan, Lazzeri, Isaac, Vlachos, Georgios, Heitzer, Ellen·2023·Trends in Genetics
DOI 10.1016/j.tig.2023.01.004
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.tig.2023.01.004

Cites

12 of 12 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 12 references

Research works printed but not linked: 181

  1. Crowley, 2013, Liquid biopsy: monitoring cancer-genetics in the blood, Nat. Rev. Clin. Oncol., 10, 472, 10.1038/nrclinonc.2013.110 · DOI
  2. Alix-Panabieres, 2021, Liquid biopsy: from discovery to clinical application, Cancer Discov., 11, 858, 10.1158/2159-8290.CD-20-1311 · DOI
  3. Siravegna, 2017, Integrating liquid biopsies into the management of cancer, Nat. Rev. Clin. Oncol., 14, 531, 10.1038/nrclinonc.2017.14 · DOI
  4. Wan, 2017, Liquid biopsies come of age: towards implementation of circulating tumour DNA, Nat. Rev. Cancer, 17, 223, 10.1038/nrc.2017.7 · DOI · Paper page
  5. Turner, 2020, Circulating tumour DNA analysis to direct therapy in advanced breast cancer (plasmaMATCH): a multicentre, multicohort, phase 2a, platform trial, Lancet Oncol., 21, 1296, 10.1016/S1470-2045(20)30444-7 · DOI
  6. Riedl, 2021, Profiling of circulating tumor DNA and tumor tissue for treatment selection in patients with advanced and refractory carcinoma: a prospective, two-stage phase II Individualized Cancer Treatment trial, Ther. Adv. Med. Oncol., 13, 10.1177/1758835920987658 · DOI
  7. Zhang, 2021, Pan-cancer circulating tumor DNA detection in over 10,000 Chinese patients, Nat. Commun., 12, 11, 10.1038/s41467-020-20162-8 · DOI
  8. Horn, 2019, Monitoring therapeutic response and resistance: analysis of circulating tumor DNA in patients with ALK+ lung cancer, J. Thorac. Oncol., 14, 1901, 10.1016/j.jtho.2019.08.003 · DOI
  9. Jacob, 2021, The use of serial circulating tumor DNA to detect resistance alterations in progressive metastatic breast cancer, Clin. Cancer Res., 27, 1361, 10.1158/1078-0432.CCR-20-1566 · DOI
  10. Cao, 2020, Circulating tumor DNA is capable of monitoring the therapeutic response and resistance in advanced colorectal cancer patients undergoing combined target and chemotherapy, Front. Oncol., 10, 466, 10.3389/fonc.2020.00466 · DOI
  11. Fribbens, 2018, Tracking evolution of aromatase inhibitor resistance with circulating tumour DNA analysis in metastatic breast cancer, Ann. Oncol., 29, 145, 10.1093/annonc/mdx483 · DOI
  12. Hasenleithner, 2022, A clinician's handbook for using ctDNA throughout the patient journey, Mol. Cancer, 21, 81, 10.1186/s12943-022-01551-7 · DOI
  13. Heitzer, 2022, Recommendations for a practical implementation of circulating tumor DNA mutation testing in metastatic non-small-cell lung cancer, ESMO Open, 7, 10.1016/j.esmoop.2022.100399 · DOI
  14. Pascual, 2022, ESMO recommendations on the use of circulating tumour DNA assays for patients with cancer: a report from the ESMO Precision Medicine Working Group, Ann. Oncol., 33, 750, 10.1016/j.annonc.2022.05.520 · DOI · Paper page
  15. Weber, 2021, Dynamic changes of circulating tumor DNA predict clinical outcome in patients with advanced non-small-cell lung cancer treated with immune checkpoint inhibitors, JCO Precis. Oncol., 5, 1540, 10.1200/PO.21.00182 · DOI
  16. Zhou, 2022, Persistence of ctDNA in patients with breast cancer during neoadjuvant treatment is a significant predictor of poor tumor response, Clin. Cancer Res., 28, 697, 10.1158/1078-0432.CCR-21-3231 · DOI
  17. Moser, 2020, On-treatment measurements of circulating tumor DNA during FOLFOX therapy in patients with colorectal cancer, NPJ Precis. Oncol., 4, 30, 10.1038/s41698-020-00134-3 · DOI
  18. Pellini, 2021, ctDNA MRD detection and personalized oncogenomic analysis in oligometastatic colorectal cancer from plasma and urine, JCO Precis. Oncol., 5, 00276
  19. Pellini, 2022, Circulating tumor DNA minimal residual disease detection of non-small-cell lung cancer treated with curative intent, J. Clin. Oncol., 40, 567, 10.1200/JCO.21.01929 · DOI
  20. Abbosh, 2017, Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution, Nature, 545, 446, 10.1038/nature22364 · DOI
  21. Karthikeyan, 2019, Circulating tumor DNA as a marker for disease relapse in early-stage breast cancer-bad blood, JAMA Oncol., 5, 1479, 10.1001/jamaoncol.2019.2047 · DOI
  22. Christensen, 2019, Early detection of metastatic relapse and monitoring of therapeutic efficacy by ultra-deep sequencing of plasma cell-free DNA in patients with urothelial bladder carcinoma, J. Clin. Oncol., 37, 1547, 10.1200/JCO.18.02052 · DOI
  23. Garcia-Murillas, 2019, Assessment of molecular relapse detection in early-stage breast cancer, JAMA Oncol., 5, 1473, 10.1001/jamaoncol.2019.1838 · DOI
  24. Wang, 2019, Prognostic potential of circulating tumor DNA measurement in postoperative surveillance of nonmetastatic colorectal cancer, JAMA Oncol., 5, 1118, 10.1001/jamaoncol.2019.0512 · DOI
  25. Azad, 2020, Circulating tumor DNA analysis for detection of minimal residual disease after chemoradiotherapy for localized esophageal cancer, Gastroenterology, 158, 494, 10.1053/j.gastro.2019.10.039 · DOI
  26. Cisneros-Villanueva, 2022, Cell-free DNA analysis in current cancer clinical trials: a review, Br. J. Cancer, 126, 391, 10.1038/s41416-021-01696-0 · DOI
  27. Ulz, 2019, Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection, Nat. Commun., 10, 4666, 10.1038/s41467-019-12714-4 · DOI
  28. Scherer, 2016, Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA, Sci. Transl. Med., 8, 364ra155, 10.1126/scitranslmed.aai8545 · DOI
  29. Cao, 2020, Integrated epigenetic biomarkers in circulating cell-free DNA as a robust classifier for pancreatic cancer, Clin. Epigenetics, 12, 112, 10.1186/s13148-020-00898-2 · DOI
  30. Chabon, 2020, Integrating genomic features for non-invasive early lung cancer detection, Nature, 580, 245, 10.1038/s41586-020-2140-0 · DOI
  31. Cristiano, 2019, Genome-wide cell-free DNA fragmentation in patients with cancer, Nature, 570, 385, 10.1038/s41586-019-1272-6 · DOI · Paper page
  32. Liang, 2019, Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA), Theranostics, 9, 2056, 10.7150/thno.28119 · DOI
  33. Luo, 2020, Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancer, Sci. Transl. Med., 12, 10.1126/scitranslmed.aax7533 · DOI
  34. Wan, 2019, Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA, BMC Cancer, 19, 832, 10.1186/s12885-019-6003-8 · DOI
  35. Liu, 2019, Comprehensive DNA methylation analysis of tissue of origin of plasma cell-free DNA by methylated CpG tandem amplification and sequencing (MCTA-Seq), Clin. Epigenetics, 11, 93, 10.1186/s13148-019-0689-y · DOI
  36. Heitzer, 2020, Cell-free DNA and apoptosis: how dead cells inform about the living, Trends Mol. Med., 26, 519, 10.1016/j.molmed.2020.01.012 · DOI
  37. Cherepanova, 2008, Deoxyribonuclease activity and circulating DNA concentration in blood plasma of patients with prostate tumors, Ann. N. Y. Acad. Sci., 1137, 218, 10.1196/annals.1448.016 · DOI
  38. Tamkovich, 2006, Circulating DNA and DNase activity in human blood, Ann. N. Y. Acad. Sci., 1075, 191, 10.1196/annals.1368.026 · DOI
  39. Yu, 2013, High-resolution profiling of fetal DNA clearance from maternal plasma by massively parallel sequencing, Clin. Chem., 59, 1228, 10.1373/clinchem.2013.203679 · DOI
  40. Khier, 2021, Hepatic clearance of cell-free DNA: possible impact on early metastasis diagnosis, Mol. Diagn. Ther., 25, 677, 10.1007/s40291-021-00554-2 · DOI
  41. Khier, 2018, Kinetics of circulating cell-free DNA for biomedical applications: critical appraisal of the literature, Future Sci. OA, 4, FSO295, 10.4155/fsoa-2017-0140 · DOI
  42. Lo, 1999, Rapid clearance of fetal DNA from maternal plasma, Am. J. Hum. Genet., 64, 218, 10.1086/302205 · DOI
  43. Diehl, 2008, Circulating mutant DNA to assess tumor dynamics, Nat. Med., 14, 985, 10.1038/nm.1789 · DOI
  44. To, 2003, Rapid clearance of plasma Epstein-Barr virus DNA after surgical treatment of nasopharyngeal carcinoma, Clin. Cancer Res., 9, 3254
  45. Chen, 2019, Perioperative dynamic changes in circulating tumor DNA in patients with lung cancer (DYNAMIC), Clin. Cancer Res., 25, 7058, 10.1158/1078-0432.CCR-19-1213 · DOI
  46. Avanzini, 2020, A mathematical model of ctDNA shedding predicts tumor detection size, Sci. Adv., 6, 10.1126/sciadv.abc4308 · DOI
  47. Bettegowda, 2014, Detection of circulating tumor DNA in early- and late-stage human malignancies, Sci. Transl. Med., 6, 224ra24, 10.1126/scitranslmed.3007094 · DOI · Paper page
  48. Smith, 2020, Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors, Genome Med., 12, 23, 10.1186/s13073-020-00723-8 · DOI
  49. Mouliere, 2012, The importance of examining the proportion of circulating DNA originating from tumor, microenvironment and normal cells in colorectal cancer patients, Expert. Opin. Biol. Ther., 12, S209, 10.1517/14712598.2012.688023 · DOI
  50. Pereira, 2021, Cell-free DNA captures tumor heterogeneity and driver alterations in rapid autopsies with pre-treated metastatic cancer, Nat. Commun., 12, 3199, 10.1038/s41467-021-23394-4 · DOI
  51. McEvoy, 2018, Correlation between circulating tumour DNA and metabolic tumour burden in metastatic melanoma patients, BMC Cancer, 18, 726, 10.1186/s12885-018-4637-6 · DOI
  52. Winther-Larsen, 2017, Correlation between circulating mutant DNA and metabolic tumour burden in advanced non-small cell lung cancer patients, Br. J. Cancer, 117, 704, 10.1038/bjc.2017.215 · DOI
  53. Bredno, 2021, Clinical correlates of circulating cell-free DNA tumor fraction, PLoS One, 16, 10.1371/journal.pone.0256436 · DOI
  54. Liebs, 2021, Applicability of liquid biopsies to represent the mutational profile of tumor tissue from different cancer entities, Oncogene, 40, 5204, 10.1038/s41388-021-01928-w · DOI
  55. Suppan, 2019, Untargeted assessment of tumor fractions in plasma for monitoring and prognostication from metastatic breast cancer patients undergoing systemic treatment, Cancers (Basel), 11, 1171, 10.3390/cancers11081171 · DOI
  56. Rostami, 2020, Senescence, necrosis, and apoptosis govern circulating cell-free DNA release kinetics, Cell Rep., 31, 10.1016/j.celrep.2020.107830 · DOI
  57. Orntoft, 2021, Age-stratified reference intervals unlock the clinical potential of circulating cell-free DNA as a biomarker of poor outcome for healthy individuals and patients with colorectal cancer, Int. J. Cancer, 148, 1665, 10.1002/ijc.33434 · DOI
  58. Yuwono, 2021, The influence of biological and lifestyle factors on circulating cell-free DNA in blood plasma, eLife, 10, 10.7554/eLife.69679 · DOI
  59. Madsen, 2019, Day-to-day and within-day biological variation of cell-free DNA, EBioMedicine, 49, 284, 10.1016/j.ebiom.2019.10.008 · DOI
  60. Sun, 2015, Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments, Proc. Natl. Acad. Sci. U. S. A., 112, E5503, 10.1073/pnas.1508736112 · DOI
  61. Guo, 2017, Identification of methylation haplotype blocks aids in deconvolution of heterogeneous tissue samples and tumor tissue-of-origin mapping from plasma DNA, Nat. Genet., 49, 635, 10.1038/ng.3805 · DOI
  62. Kang, 2017, CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA, Genome Biol., 18, 53, 10.1186/s13059-017-1191-5 · DOI
  63. Snyder, 2016, Cell-free DNA comprises an in vivo nucleosome footprint that informs its tissues-of-origin, Cell, 164, 57, 10.1016/j.cell.2015.11.050 · DOI
  64. Sun, 2019, Orientation-aware plasma cell-free DNA fragmentation analysis in open chromatin regions informs tissue of origin, Genome Res., 29, 418, 10.1101/gr.242719.118 · DOI
  65. Sadeh, 2021, ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin, Nat. Biotechnol., 39, 586, 10.1038/s41587-020-00775-6 · DOI
  66. Vorperian, 2022, Cell types of origin of the cell-free transcriptome, Nat. Biotechnol., 40, 855, 10.1038/s41587-021-01188-9 · DOI · Paper page
  67. Teschendorff, 2017, A comparison of reference-based algorithms for correcting cell-type heterogeneity in epigenome-wide association studies, BMC Bioinformatics, 18, 105, 10.1186/s12859-017-1511-5 · DOI
  68. Lehmann-Werman, 2016, Identification of tissue-specific cell death using methylation patterns of circulating DNA, Proc. Natl. Acad. Sci. U. S. A., 113, E1826, 10.1073/pnas.1519286113 · DOI
  69. Moss, 2018, Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease, Nat. Commun., 9, 5068, 10.1038/s41467-018-07466-6 · DOI
  70. Lui, 2002, Predominant hematopoietic origin of cell-free DNA in plasma and serum after sex-mismatched bone marrow transplantation, Clin. Chem., 48, 421, 10.1093/clinchem/48.3.421 · DOI
  71. Caggiano, 2021, Comprehensive cell type decomposition of circulating cell-free DNA with CelFiE, Nat. Commun., 12, 2717, 10.1038/s41467-021-22901-x · DOI
  72. Wong, 2016, Cell-free DNA in maternal plasma and serum: A comparison of quantity, quality and tissue origin using genomic and epigenomic approaches, Clin. Biochem., 49, 1379, 10.1016/j.clinbiochem.2016.09.009 · DOI
  73. Lam, 2017, DNA of erythroid origin is present in human plasma and informs the types of anemia, Clin. Chem., 63, 1614, 10.1373/clinchem.2017.272401 · DOI
  74. de Miranda, 2021, Properties and application of cell-free DNA as a clinical biomarker, Int. J. Mol. Sci., 22, 9110, 10.3390/ijms22179110 · DOI
  75. Moss, 2022, Megakaryocyte and erythroblast DNA in plasma and platelets, bioRxiv
  76. Lubotzky, 2022, Liquid biopsy reveals collateral tissue damage in cancer, JCI Insight, 7, 10.1172/jci.insight.153559 · DOI
  77. Fox-Fisher, 2021, Remote immune processes revealed by immune-derived circulating cell-free DNA, eLife, 10, 10.7554/eLife.70520 · DOI
  78. Cheng, 2021, Cell-free DNA tissues of origin by methylation profiling reveals significant cell, tissue, and organ-specific injury related to COVID-19 severity, Med (N Y), 2, 411
  79. Stawski, 2022, Cell-free DNA: potential application in COVID-19 diagnostics and management, Viruses, 14, 321, 10.3390/v14020321 · DOI
  80. Andargie, 2021, Cell-free DNA maps COVID-19 tissue injury and risk of death and can cause tissue injury, JCI Insight, 6, 10.1172/jci.insight.147610 · DOI
  81. Jahr, 2001, DNA fragments in the blood plasma of cancer patients: quantitations and evidence for their origin from apoptotic and necrotic cells, Cancer Res., 61, 1659
  82. Schwarzenbach, 2011, Cell-free nucleic acids as biomarkers in cancer patients, Nat. Rev. Cancer, 11, 426, 10.1038/nrc3066 · DOI
  83. Stroun, 2001, About the possible origin and mechanism of circulating DNA apoptosis and active DNA release, Clin. Chim. Acta, 313, 139, 10.1016/S0009-8981(01)00665-9 · DOI
  84. van der Vaart, 2007, The origin of circulating free DNA, Clin. Chem., 53, 2215, 10.1373/clinchem.2007.092734 · DOI
  85. Han, 2021, The nexus of cfDNA and nuclease biology, Trends Genet., 37, 758, 10.1016/j.tig.2021.04.005 · DOI
  86. Ulz, 2016, Inferring expressed genes by whole-genome sequencing of plasma DNA, Nat. Genet., 48, 1273, 10.1038/ng.3648 · DOI
  87. Han, 2020, The biology of cell-free DNA fragmentation and the roles of DNASE1, DNASE1L3, and DFFB, Am. J. Hum. Genet., 106, 202, 10.1016/j.ajhg.2020.01.008 · DOI
  88. Lo, 2010, Maternal plasma DNA sequencing reveals the genome-wide genetic and mutational profile of the fetus, Sci. Transl. Med., 2, 61ra91, 10.1126/scitranslmed.3001720 · DOI
  89. Ramachandran, 2015, Replicating nucleosomes. Science, Advances, 1
  90. Sanchez, 2021, Circulating nuclear DNA structural features, origins, and complete size profile revealed by fragmentomics, JCI Insight, 6, 10.1172/jci.insight.144561 · DOI
  91. Mouliere, 2018, Enhanced detection of circulating tumor DNA by fragment size analysis, Sci. Transl. Med., 10, eaat4921, 10.1126/scitranslmed.aat4921 · DOI
  92. Esfahani, 2022, Inferring gene expression from cell-free DNA fragmentation profiles, Nat. Biotechnol., 40, 585, 10.1038/s41587-022-01222-4 · DOI
  93. Markus, 2022, Refined characterization of circulating tumor DNA through biological feature integration, Sci. Rep., 12, 1928, 10.1038/s41598-022-05606-z · DOI
  94. Yu, 2021, Single-molecule sequencing reveals a large population of long cell-free DNA molecules in maternal plasma, Proc. Natl. Acad. Sci. U. S. A., 118, 10.1073/pnas.2114937118 · DOI
  95. Hudecova, 2022, Characteristics, origin, and potential for cancer diagnostics of ultrashort plasma cell-free DNA, Genome Res., 32, 215, 10.1101/gr.275691.121 · DOI
  96. Jiang, 2015, Lengthening and shortening of plasma DNA in hepatocellular carcinoma patients, Proc. Natl. Acad. Sci. U. S. A., 112, E1317, 10.1073/pnas.1500076112 · DOI
  97. Mouliere, 2011, High fragmentation characterizes tumour-derived circulating DNA, PLoS One, 6, 10.1371/journal.pone.0023418 · DOI
  98. Underhill, 2016, Fragment length of circulating tumor DNA, PLoS Genet., 12, 10.1371/journal.pgen.1006162 · DOI
  99. Katsman, 2022, Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing, Genome Biol., 23, 158, 10.1186/s13059-022-02710-1 · DOI
  100. Jiang, 2018, Preferred end coordinates and somatic variants as signatures of circulating tumor DNA associated with hepatocellular carcinoma, Proc. Natl. Acad. Sci. U. S. A., 115, E10925, 10.1073/pnas.1814616115 · DOI
  101. Jiang, 2020, Detection and characterization of jagged ends of double-stranded DNA in plasma, Genome Res., 30, 1144, 10.1101/gr.261396.120 · DOI
  102. Lo, 2021, Epigenetics, fragmentomics, and topology of cell-free DNA in liquid biopsies, Science, 372, eaaw3616, 10.1126/science.aaw3616 · DOI
  103. Chiu, 2020, Cell-free DNA fragmentomics: the new ‘omics’ on the block, Clin. Chem., 66, 1480, 10.1093/clinchem/hvaa258 · DOI
  104. Jensen, 2015, Whole genome bisulfite sequencing of cell-free DNA and its cellular contributors uncovers placenta hypomethylated domains, Genome Biol., 16, 78, 10.1186/s13059-015-0645-x · DOI
  105. Jones, 2019, Epigenetic therapy in immune-oncology, Nat. Rev. Cancer, 19, 151, 10.1038/s41568-019-0109-9 · DOI
  106. Zhou, 2022, Epigenetic analysis of cell-free DNA by fragmentomic profiling, Proc. Natl. Acad. Sci. U. S. A., 119, 10.1073/pnas.2209852119 · DOI
  107. Weerts, 2018, Tumor-specific mitochondrial DNA variants are rarely detected in cell-free DNA, Neoplasia, 20, 687, 10.1016/j.neo.2018.05.003 · DOI
  108. Hu, 2018, False-positive plasma genotyping due to clonal hematopoiesis, Clin. Cancer Res., 24, 4437, 10.1158/1078-0432.CCR-18-0143 · DOI
  109. Marass, 2020, Fragment size analysis may distinguish clonal hematopoiesis from tumor-derived mutations in cell-free DNA, Clin. Chem., 66, 616, 10.1093/clinchem/hvaa026 · DOI
  110. Im, 2021, Next-generation liquid biopsies: embracing data science in oncology, Trends Cancer, 7, 283, 10.1016/j.trecan.2020.11.001 · DOI
  111. Forshew, 2012, Noninvasive identification and monitoring of cancer mutations by targeted deep sequencing of plasma DNA, Sci. Transl. Med., 4, 136ra68, 10.1126/scitranslmed.3003726 · DOI
  112. Kinde, 2011, Detection and quantification of rare mutations with massively parallel sequencing, Proc. Natl. Acad. Sci. U. S. A., 108, 9530, 10.1073/pnas.1105422108 · DOI · Paper page
  113. Schmitt, 2012, Detection of ultra-rare mutations by next-generation sequencing, Proc. Natl. Acad. Sci. U. S. A., 109, 14508, 10.1073/pnas.1208715109 · DOI · Paper page
  114. Newman, 2016, Integrated digital error suppression for improved detection of circulating tumor DNA, Nat. Biotechnol., 34, 547, 10.1038/nbt.3520 · DOI
  115. Phallen, 2017, Direct detection of early-stage cancers using circulating tumor DNA, Sci. Transl. Med., 9, eaan2415, 10.1126/scitranslmed.aan2415 · DOI
  116. Smith, 2017, UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy, Genome Res., 27, 491, 10.1101/gr.209601.116 · DOI
  117. Wan, 2020, ctDNA monitoring using patient-specific sequencing and integration of variant reads, Sci. Transl. Med., 12, eaaz8084, 10.1126/scitranslmed.aaz8084 · DOI
  118. McDonald, 2019, Personalized circulating tumor DNA analysis to detect residual disease after neoadjuvant therapy in breast cancer, Sci. Transl. Med., 11, eaax7392, 10.1126/scitranslmed.aax7392 · DOI
  119. Zviran, 2020, Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring, Nat. Med., 26, 1114, 10.1038/s41591-020-0915-3 · DOI
  120. Widman, A.J.S. et al. Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring. bioRxiv. Published online January 20, 2022. https://doi.org/10.1101/2022.01.17.476508 · DOI
  121. Gydush, 2022, Massively parallel enrichment of low-frequency alleles enables duplex sequencing at low depth, Nat. Biomed. Eng., 6, 257, 10.1038/s41551-022-00855-9 · DOI
  122. Luo, 2021, Liquid biopsy of methylation biomarkers in cell-free DNA, Trends Mol. Med., 27, 482, 10.1016/j.molmed.2020.12.011 · DOI
  123. Angeles, 2021, Liquid biopsies beyond mutation calling: genomic and epigenomic features of cell-free DNA in cancer, Cancers (Basel), 13, 5615, 10.3390/cancers13225615 · DOI
  124. Liu, 2022, At the dawn: cell-free DNA fragmentomics and gene regulation, Br. J. Cancer, 126, 379, 10.1038/s41416-021-01635-z · DOI
  125. Ding, 2022, Cell-free DNA fragmentomics in liquid biopsy, Diagnostics (Basel), 12, 978, 10.3390/diagnostics12040978 · DOI
  126. Zhu, 2021, Tissue-specific cell-free DNA degradation quantifies circulating tumor DNA burden, Nat. Commun., 12, 2229, 10.1038/s41467-021-22463-y · DOI
  127. Li, 2021, DISMIR: Deep learning-based noninvasive cancer detection by integrating DNA sequence and methylation information of individual cell-free DNA reads, Brief. Bioinform., 22, bbab250, 10.1093/bib/bbab250 · DOI
  128. Sprang, 2020, CpG-islands as markers for liquid biopsies of cancer patients, Cells, 9, 1820, 10.3390/cells9081820 · DOI
  129. Zhang, 2022, Genome-wide analysis of cell-free DNA methylation profiling with MeDIP-seq identified potential biomarkers for colorectal cancer, World J. Surg. Oncol., 20, 21, 10.1186/s12957-022-02487-4 · DOI
  130. Shen, 2019, Preparation of cfMeDIP-seq libraries for methylome profiling of plasma cell-free DNA, Nat. Protoc., 14, 2749, 10.1038/s41596-019-0202-2 · DOI
  131. Li, 2020, Genome-wide analysis of cell-free DNA methylation profiling for the early diagnosis of pancreatic cancer, Front. Genet., 11, 10.3389/fgene.2020.596078 · DOI
  132. Han, 2021, A deep-learning pipeline for TSS coverage imputation from shallow cell-free DNA sequencing, Front. Med. (Lausanne), 8
  133. Jiang, 2020, Plasma DNA end-motif profiling as a fragmentomic marker in cancer, pregnancy, and transplantation, Cancer Discov., 10, 664, 10.1158/2159-8290.CD-19-0622 · DOI
  134. Li, 2018, CancerDetector: ultrasensitive and non-invasive cancer detection at the resolution of individual reads using cell-free DNA methylation sequencing data, Nucleic Acids Res., 46, 10.1093/nar/gky423 · DOI
  135. Silva, 2021, Longitudinal analysis of individual cfDNA methylome patterns in metastatic prostate cancer, Clin. Epigenetics, 13, 168, 10.1186/s13148-021-01155-w · DOI
  136. Wu, 2020, Genome-wide plasma DNA methylation features of metastatic prostate cancer, J. Clin. Invest., 130, 1991, 10.1172/JCI130887 · DOI
  137. Beltran, 2020, Circulating tumor DNA profile recognizes transformation to castration-resistant neuroendocrine prostate cancer, J. Clin. Invest., 130, 1653, 10.1172/JCI131041 · DOI
  138. Mathios, 2021, Detection and characterization of lung cancer using cell-free DNA fragmentomes, Nat. Commun., 12, 5060, 10.1038/s41467-021-24994-w · DOI
  139. Zhang, 2021, Ultrasensitive and affordable assay for early detection of primary liver cancer using plasma cell-free DNA fragmentomics, Hepatology, 76, 317, 10.1002/hep.32308 · DOI
  140. Jin, 2021, Characterization of fragment sizes, copy number aberrations and 4-mer end motifs in cell-free DNA of hepatocellular carcinoma for enhanced liquid biopsy-based cancer detection, Mol. Oncol., 15, 2377, 10.1002/1878-0261.13041 · DOI
  141. Zhitnyuk, 2022, Deep cfDNA fragment end profiling enables cancer detection, Mol. Cancer, 21, 26, 10.1186/s12943-021-01491-8 · DOI
  142. Ko, 2018, Machine learning to detect signatures of disease in liquid biopsies - a user's guide, Lab Chip, 18, 395, 10.1039/C7LC00955K · DOI
  143. Ge, 2020, Urothelial carcinoma detection based on copy number profiles of urinary cell-free DNA by shallow whole-genome sequencing, Clin. Chem., 66, 188, 10.1373/clinchem.2019.309633 · DOI
  144. Mouliere, 2018, Detection of cell-free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients, EMBO Mol. Med., 10, 10.15252/emmm.201809323 · DOI
  145. Mouliere, 2021, Fragmentation patterns and personalized sequencing of cell-free DNA in urine and plasma of glioma patients, EMBO Mol. Med., 13, 10.15252/emmm.202012881 · DOI
  146. Saeys, 2008, Robust feature selection using ensemble feature selection techniques, Lect. Notes Comput. Sci, 5212, 313, 10.1007/978-3-540-87481-2_21 · DOI
  147. Liu, 2021, Machine learning protocols in early cancer detection based on liquid biopsy: a survey, Life (Basel), 11, 638
  148. Yang, 2021, Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer, NPJ Breast Cancer, 7, 35, 10.1038/s41523-021-00237-5 · DOI
  149. Panagopoulou, 2019, Circulating cell-free DNA in breast cancer: size profiling, levels, and methylation patterns lead to prognostic and predictive classifiers, Oncogene, 38, 3387, 10.1038/s41388-018-0660-y · DOI
  150. Raman, 2020, Shallow whole-genome sequencing of plasma cell-free DNA accurately differentiates small from non-small cell lung carcinoma, Genome Med., 12, 35, 10.1186/s13073-020-00735-4 · DOI
  151. Liang, 2021, Ultrasensitive detection of circulating tumour DNA via deep methylation sequencing aided by machine learning, Nat. Biomed. Eng., 5, 586, 10.1038/s41551-021-00746-5 · DOI
  152. Han, 2021, Enhanced detection of genitourinary cancers using fragmentation and copy number profiles obtained from urinary cell-free DNA, Clin. Chem., 67, 394, 10.1093/clinchem/hvaa283 · DOI
  153. Constantin, 2022, Opportunities for early cancer detection: the rise of ctDNA methylation-based pan-cancer screening technologies, Epigenomes, 6, 6, 10.3390/epigenomes6010006 · DOI
  154. Liu, 2021, Early cancer detection from genome-wide cell-free DNA fragmentation via shuffled frog leaping algorithm and support vector machine, Bioinformatics, 37, 3099, 10.1093/bioinformatics/btab236 · DOI
  155. Qiao, 2021, Discovery and validation of methylation signatures in circulating cell-free DNA for early detection of esophageal cancer: a case-control study, BMC Med., 19, 243, 10.1186/s12916-021-02109-y · DOI
  156. Zhou, 2022, Next-generation sequencing-based analysis of urine cell-free mtDNA reveals aberrant fragmentation and mutation profile in cancer patients, Clin. Chem., 68, 561, 10.1093/clinchem/hvab268 · DOI
  157. Nassiri, 2020, Detection and discrimination of intracranial tumors using plasma cell-free DNA methylomes, Nat. Med., 26, 1044, 10.1038/s41591-020-0932-2 · DOI
  158. Panagopoulou, 2021, Circulating cell-free DNA in breast cancer: searching for hidden information towards precision medicine, Cancers (Basel), 13, 728, 10.3390/cancers13040728 · DOI
  159. Shen, 2020, A web-based automated machine learning platform to analyze liquid biopsy data, Lab Chip, 20, 2166, 10.1039/D0LC00096E · DOI
  160. Markus, 2018, Evaluation of pre-analytical factors affecting plasma DNA analysis, Sci. Rep., 8, 7375, 10.1038/s41598-018-25810-0 · DOI
  161. Greytak, 2020, Harmonizing cell-free DNA collection and processing practices through evidence-based guidance, Clin. Cancer Res., 26, 3104, 10.1158/1078-0432.CCR-19-3015 · DOI · Paper page
  162. van der Leest, 2022, Dutch national round robin trial on plasma-derived circulating cell-free DNA extraction methods routinely used in clinical pathology for molecular tumor profiling, Clin. Chem., 68, 963, 10.1093/clinchem/hvac069 · DOI
  163. Godsey, 2020, Generic protocols for the analytical validation of next-generation sequencing-based ctDNA Assays: a Joint Consensus Recommendation of the BloodPAC's Analytical Variables Working Group, Clin. Chem., 66, 1156, 10.1093/clinchem/hvaa164 · DOI · Paper page
  164. Williams, 2021, Validation of ctDNA quality control materials through a precompetitive collaboration of the Foundation for the National Institutes of Health. JCO Precis, Oncol, 5
  165. Lampignano, 2020, Multicenter evaluation of circulating cell-free DNA extraction and downstream analyses for the development of standardized (pre)analytical work flows, Clin. Chem., 66, 149, 10.1373/clinchem.2019.306837 · DOI
  166. Sorber, 2017, A comparison of cell-free DNA isolation kits: isolation and quantification of cell-free DNA in plasma, J. Mol. Diagn., 19, 162, 10.1016/j.jmoldx.2016.09.009 · DOI
  167. Worm Orntoft, 2017, Comparative analysis of 12 different kits for bisulfite conversion of circulating cell-free DNA, Epigenetics, 12, 626, 10.1080/15592294.2017.1334024 · DOI
  168. Moser, 2017, Single-stranded DNA library preparation does not preferentially enrich circulating tumor DNA, Clin. Chem., 63, 1656, 10.1373/clinchem.2017.277988 · DOI
  169. Tan, 2019, Long fragments achieve lower base quality in Illumina paired-end sequencing, Sci. Rep., 9, 2856, 10.1038/s41598-019-39076-7 · DOI
  170. van der Pol, 2022, The effect of preanalytical and physiological variables on cell-free DNA fragmentation, Clin. Chem., 68, 803, 10.1093/clinchem/hvac029 · DOI
  171. Sharma, 2022, Computational challenges in detection of cancer using cell-free DNA methylation, Comput. Struct. Biotechnol. J., 20, 26, 10.1016/j.csbj.2021.12.001 · DOI
  172. Barefoot, 2021, Detection of cell types contributing to cancer from circulating, cell-free methylated DNA, Front. Genet., 12, 10.3389/fgene.2021.671057 · DOI
  173. Wong, 2019, Early cancer detection from multianalyte blood test results, iScience, 15, 332, 10.1016/j.isci.2019.04.035 · DOI
  174. Lennon, 2020, Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention, Science, 369, eabb9601, 10.1126/science.abb9601 · DOI
  175. Corcoran, 2018, Application of cell-free DNA analysis to cancer treatment, N. Engl. J. Med., 379, 1754, 10.1056/NEJMra1706174 · DOI
  176. Ivanov, 2015, Non-random fragmentation patterns in circulating cell-free DNA reflect epigenetic regulation, BMC Genomics, 16, S1, 10.1186/1471-2164-16-S13-S1 · DOI
  177. Bro, 2008, Cross-validation of component models: a critical look at current methods, Anal. Bioanal. Chem., 390, 1241, 10.1007/s00216-007-1790-1 · DOI
  178. Liu, 2020, Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning, Comput. Struct. Biotechnol. J., 18, 1891, 10.1016/j.csbj.2020.06.042 · DOI
  179. Tao, 2020, Machine learning-based genome-wide interrogation of somatic copy number aberrations in circulating tumor DNA for early detection of hepatocellular carcinoma, EBioMedicine, 56, 10.1016/j.ebiom.2020.102811 · DOI
  180. Doebley, 2022, A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA, Nat. Commun., 3, 7475, 10.1038/s41467-022-35076-w · DOI
  181. Danyi, 2021, Cancer Type Classification in Liquid Biopsies Based on Sparse Mutational Profiles Enabled through Data Augmentation and Integration, Life, 12, 10.3390/life12010001 · DOI

Cited by

Sorted by citations

See all 133

Metadata

Authors
Moser, T., Kühberger, S., Lazzeri, I., Vlachos, G., & Heitzer, E.
Venue
Trends in Genetics
Publisher
Elsevier BV
Published
2023-04
Volume
39
Issue
4
Pages
285-307
ISSN
0168-9525
DOI
10.1016/j.tig.2023.01.004
Cited by
133
References
12
Language
en
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Bridging biological cfDNA features and machine learning approaches. https://app.cochat.ai/papers/10.1016/j.tig.2023.01.004
The paper
Moser, T., Kühberger, S., Lazzeri, I., Vlachos, G., & Heitzer, E. (2023). Bridging biological cfDNA features and machine learning approaches. Trends in Genetics. https://doi.org/10.1016/j.tig.2023.01.004