Non-invasive metastasis prognosis from plasma metabolites in stage II colorectal cancer patients: the DACHS study
Metastasis is the main cause of death from colorectal cancer (CRC). About 20% of stage II CRC patients develop metastasis during the course of disease. We performed metabolic profiling of plasma samples from non-metastasized and metachronously metastasized stage II CRC patients to assess the potenti...
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| Main Authors: | , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2019
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| In: |
International journal of cancer
Year: 2018, Volume: 145, Issue: 1, Pages: 221-231 |
| ISSN: | 1097-0215 |
| DOI: | 10.1002/ijc.32076 |
| Online Access: | Verlag, Pay-per-use, Volltext: https://doi.org/10.1002/ijc.32076 Verlag, Pay-per-use, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/ijc.32076 
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| Author Notes: | Inna Zaimenko, Carsten Jaeger, Hermann Brenner, Jenny Chang‐Claude, Michael Hoffmeister, Carsten Grötzinger, Katharina Detjen, Susen Burock, Clemens A. Schmitt, Ulrike Stein and Jan Lisec |
| Summary: | Metastasis is the main cause of death from colorectal cancer (CRC). About 20% of stage II CRC patients develop metastasis during the course of disease. We performed metabolic profiling of plasma samples from non-metastasized and metachronously metastasized stage II CRC patients to assess the potential of plasma metabolites to serve as biomarkers for stratification of stage II CRC patients according to metastasis risk. We compared the metabolic profiles of plasma samples prospectively obtained prior to metastasis formation from non-metastasized vs. metachronously metastasized stage II CRC patients of the German population-based case-control multicenter DACHS study retrospectively. Plasma samples were analyzed from stage II CRC patients for whom follow-up data including the information on metachronous metastasis were available. To identify metabolites distinguishing non-metastasized from metachronously metastasized stage II CRC patients robust supervised classifications using decision trees and support vector machines were performed and verified by 10-fold cross-validation, by nested cross-validation and by traditional validation using training and test sets. We found that metabolic profiles distinguish non-metastasized from metachronously metastasized stage II CRC patients. Classification models from decision trees and support vector machines with 10-fold cross-validation gave average accuracy of 0.75 (sensitivity 0.79, specificity 0.7) and 0.82 (sensitivity 0.85, specificity 0.77), respectively, correctly predicting metachronous metastasis in stage II CRC patients. Taken together, plasma metabolic profiles distinguished non-metastasized and metachronously metastasized stage II CRC patients. The classification models consisting of few metabolites stratify non-invasively stage II CRC patients according to their risk for metachronous metastasis. |
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| Item Description: | Gesehen am 31.05.2019 First published: 18 December 2018 |
| Physical Description: | Online Resource |
| ISSN: | 1097-0215 |
| DOI: | 10.1002/ijc.32076 |