-
Je něco špatně v tomto záznamu ?
Pan-Cancer Detection and Typing by Mining Patterns in Large Genome-Wide Cell-Free DNA Sequencing Datasets
H. Che, T. Jatsenko, L. Lenaerts, L. Dehaspe, L. Vancoillie, N. Brison, I. Parijs, K. Van Den Bogaert, D. Fischerova, R. Heremans, C. Landolfo, AC. Testa, A. Vanderstichele, L. Liekens, V. Pomella, A. Wozniak, C. Dooms, E. Wauters, S. Hatse, K....
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem
NLK
ProQuest Central
od 2002-12-01 do 2022-04-30
Open Access Digital Library
od 1955-02-01
Medline Complete (EBSCOhost)
od 2010-01-01 do Před 1 rokem
Nursing & Allied Health Database (ProQuest)
od 2002-12-01 do 2022-04-30
Health & Medicine (ProQuest)
od 2002-12-01 do 2022-04-30
Public Health Database (ProQuest)
od 2002-12-01 do 2022-04-30
PubMed
35769009
DOI
10.1093/clinchem/hvac095
Knihovny.cz E-zdroje
- MeSH
- lidé MeSH
- nádorové biomarkery genetika MeSH
- nádory * diagnóza genetika MeSH
- sekvenování celého genomu MeSH
- volné cirkulující nukleové kyseliny * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Cell-free DNA (cfDNA) analysis holds great promise for non-invasive cancer screening, diagnosis, and monitoring. We hypothesized that mining the patterns of cfDNA shallow whole-genome sequencing datasets from patients with cancer could improve cancer detection. METHODS: By applying unsupervised clustering and supervised machine learning on large cfDNA shallow whole-genome sequencing datasets from healthy individuals (n = 367) and patients with different hematological (n = 238) and solid malignancies (n = 320), we identified cfDNA signatures that enabled cancer detection and typing. RESULTS: Unsupervised clustering revealed cancer type-specific sub-grouping. Classification using a supervised machine learning model yielded accuracies of 96% and 65% in discriminating hematological and solid malignancies from healthy controls, respectively. The accuracy of disease type prediction was 85% and 70% for the hematological and solid cancers, respectively. The potential utility of managing a specific cancer was demonstrated by classifying benign from invasive and borderline adnexal masses with an area under the curve of 0.87 and 0.74, respectively. CONCLUSIONS: This approach provides a generic analytical strategy for non-invasive pan-cancer detection and cancer type prediction.
Centre for Human Genetics University Hospitals Leuven Leuven Belgium
Department of Development and Regeneration Woman and Child KU Leuven Leuven Belgium
Department of Gynecology and Obstetrics University Hospitals Leuven Leuven Belgium
Department of Hematology University Hospitals Leuven Leuven Belgium
Department of Human Genetics Laboratory of Genetics of Malignant Diseases KU Leuven Leuven Belgium
Department of Human Genetics Laboratory of Translational Genetics VIB KU Leuven Leuven Belgium
Department of Oncology Laboratory of Experimental Oncology KU Leuven Leuven Belgium
Department of Oncology Laboratory of Gynecological Oncology KU Leuven Leuven Belgium
Department of Oncology Molecular Digestive Oncology KU Leuven Leuven Belgium
Department of Pneumology University Hospitals Leuven Leuven Belgium
Multidisciplinary Breast Centre Leuven Cancer Institute University Hospitals Leuven Leuven Belgium
Citace poskytuje Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc22024531
- 003
- CZ-PrNML
- 005
- 20221031100109.0
- 007
- ta
- 008
- 221017s2022 enk f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1093/clinchem/hvac095 $2 doi
- 035 __
- $a (PubMed)35769009
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a enk
- 100 1_
- $a Che, Huiwen $u Department of Human Genetics, Laboratory for Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium $1 https://orcid.org/000000023651069X
- 245 10
- $a Pan-Cancer Detection and Typing by Mining Patterns in Large Genome-Wide Cell-Free DNA Sequencing Datasets / $c H. Che, T. Jatsenko, L. Lenaerts, L. Dehaspe, L. Vancoillie, N. Brison, I. Parijs, K. Van Den Bogaert, D. Fischerova, R. Heremans, C. Landolfo, AC. Testa, A. Vanderstichele, L. Liekens, V. Pomella, A. Wozniak, C. Dooms, E. Wauters, S. Hatse, K. Punie, P. Neven, H. Wildiers, S. Tejpar, D. Lambrechts, A. Coosemans, D. Timmerman, P. Vandenberghe, F. Amant, JR. Vermeesch
- 520 9_
- $a BACKGROUND: Cell-free DNA (cfDNA) analysis holds great promise for non-invasive cancer screening, diagnosis, and monitoring. We hypothesized that mining the patterns of cfDNA shallow whole-genome sequencing datasets from patients with cancer could improve cancer detection. METHODS: By applying unsupervised clustering and supervised machine learning on large cfDNA shallow whole-genome sequencing datasets from healthy individuals (n = 367) and patients with different hematological (n = 238) and solid malignancies (n = 320), we identified cfDNA signatures that enabled cancer detection and typing. RESULTS: Unsupervised clustering revealed cancer type-specific sub-grouping. Classification using a supervised machine learning model yielded accuracies of 96% and 65% in discriminating hematological and solid malignancies from healthy controls, respectively. The accuracy of disease type prediction was 85% and 70% for the hematological and solid cancers, respectively. The potential utility of managing a specific cancer was demonstrated by classifying benign from invasive and borderline adnexal masses with an area under the curve of 0.87 and 0.74, respectively. CONCLUSIONS: This approach provides a generic analytical strategy for non-invasive pan-cancer detection and cancer type prediction.
- 650 _2
- $a nádorové biomarkery $x genetika $7 D014408
- 650 12
- $a volné cirkulující nukleové kyseliny $7 D000073888
- 650 _2
- $a lidé $7 D006801
- 650 12
- $a nádory $x diagnóza $x genetika $7 D009369
- 650 _2
- $a sekvenování celého genomu $7 D000073336
- 655 _2
- $a časopisecké články $7 D016428
- 655 _2
- $a práce podpořená grantem $7 D013485
- 700 1_
- $a Jatsenko, Tatjana $u Department of Human Genetics, Laboratory for Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium
- 700 1_
- $a Lenaerts, Liesbeth $u Department of Oncology, Laboratory of Gynecological Oncology, KU Leuven, Leuven, Belgium
- 700 1_
- $a Dehaspe, Luc $u Centre for Human Genetics, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Vancoillie, Leen $u Centre for Human Genetics, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Brison, Nathalie $u Centre for Human Genetics, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Parijs, Ilse $u Centre for Human Genetics, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Van Den Bogaert, Kris $u Centre for Human Genetics, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Fischerova, Daniela $u Department of Obstetrics and Gynaecology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- 700 1_
- $a Heremans, Ruben $u Department of Development and Regeneration, Woman and Child, KU Leuven, Leuven, Belgium $1 https://orcid.org/0000000349458867
- 700 1_
- $a Landolfo, Chiara $u Department of Gynecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Testa, Antonia Carla $u Department of Woman and Child Health, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Università Cattolica del Sacro Cuore Roma, Rome, Italy
- 700 1_
- $a Vanderstichele, Adriaan $u Department of Gynecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Liekens, Lore $u Department of Oncology, Molecular Digestive Oncology, KU Leuven, Leuven, Belgium
- 700 1_
- $a Pomella, Valentina $u Department of Oncology, Molecular Digestive Oncology, KU Leuven, Leuven, Belgium
- 700 1_
- $a Wozniak, Agnieszka $u Department of Oncology, Laboratory of Experimental Oncology, KU Leuven, Leuven, Belgium $1 https://orcid.org/000000019726144X
- 700 1_
- $a Dooms, Christophe $u Department of Chronic Diseases and Metabolism, Laboratory of Respiratory Diseases and Thoracic Surgery (BREATHE), KU Leuven, Leuven, Belgium $u Department of Pneumology, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Wauters, Els $u Department of Chronic Diseases and Metabolism, Laboratory of Respiratory Diseases and Thoracic Surgery (BREATHE), KU Leuven, Leuven, Belgium $u Department of Pneumology, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Hatse, Sigrid $u Department of Oncology, Laboratory of Experimental Oncology, KU Leuven, Leuven, Belgium $u Multidisciplinary Breast Centre, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Punie, Kevin $u Multidisciplinary Breast Centre, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium $u Department of General Medical Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium $1 https://orcid.org/0000000211627963
- 700 1_
- $a Neven, Patrick $u Department of Gynecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium $u Multidisciplinary Breast Centre, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium
- 700 1_
- $a Wildiers, Hans $u Multidisciplinary Breast Centre, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium $u Department of General Medical Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium $1 https://orcid.org/0000000189907837
- 700 1_
- $a Tejpar, Sabine $u Department of Oncology, Molecular Digestive Oncology, KU Leuven, Leuven, Belgium
- 700 1_
- $a Lambrechts, Diether $u Department of Human Genetics, Laboratory of Translational Genetics, VIB-KU Leuven, Leuven, Belgium
- 700 1_
- $a Coosemans, An $u Department of Oncology, Laboratory of Tumor Immunology and Immunotherapy, Leuven Cancer Institute, KU Leuven, Leuven, Belgium $1 https://orcid.org/0000000273214339
- 700 1_
- $a Timmerman, Dirk $u Department of Development and Regeneration, Woman and Child, KU Leuven, Leuven, Belgium $u Department of Gynecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium $1 https://orcid.org/0000000237076645
- 700 1_
- $a Vandenberghe, Peter $u Department of Human Genetics, Laboratory of Genetics of Malignant Diseases, KU Leuven, Leuven, Belgium $u Department of Hematology, University Hospitals Leuven, Leuven, Belgium $1 https://orcid.org/0000000347191935
- 700 1_
- $a Amant, Frédéric $u Department of Oncology, Laboratory of Gynecological Oncology, KU Leuven, Leuven, Belgium $u Department of Gynecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium $u Department of Surgery, Center for Gynecological Oncology Amsterdam, Academic Medical Centre Amsterdam-University of Amsterdam and the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands $1 https://orcid.org/0000000160552569
- 700 1_
- $a Vermeesch, Joris Robert $u Department of Human Genetics, Laboratory for Cytogenetics and Genome Research, KU Leuven, Leuven, Belgium $u Centre for Human Genetics, University Hospitals Leuven, Leuven, Belgium $1 https://orcid.org/0000000230711191
- 773 0_
- $w MED00001129 $t Clinical chemistry $x 1530-8561 $g Roč. 68, č. 9 (2022), s. 1164-1176
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/35769009 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y p $z 0
- 990 __
- $a 20221017 $b ABA008
- 991 __
- $a 20221031100107 $b ABA008
- 999 __
- $a ok $b bmc $g 1854318 $s 1175821
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2022 $b 68 $c 9 $d 1164-1176 $e 20220901 $i 1530-8561 $m Clinical chemistry $n Clin Chem $x MED00001129
- LZP __
- $a Pubmed-20221017
