Georg Emons, Noam Auslander, Peter Jo, Julia Kitz, Azadeh Azizian, Yue Hu, Clemens F. Hess, Claus Rödel, Ulrich Sax, Gabriela Salinas-Riester, Philipp Ströbel, Frank Kramer, Tim Beissbarth, Michael Ghadimi, Eytan Ruppin, Thomas Ried, Jochen Werner Christian Gaedcke, Marian Grade
- Purpose: Preoperative (neoadjuvant) chemoradiotherapy (CRT) and total mesorectal excision is the standard treatment for rectal cancer patients (UICC stage II/III). Up to one-third of patients treated with CRT achieve a pathological complete response (pCR). These patients could be spared from surgery and its associated morbidity and mortality, and assigned to a “watch and wait” strategy. However, reliably identifying pCR based on clinical or imaging parameters remains challenging.
Experimental design: We generated gene-expression profiles of 175 patients with locally advanced rectal cancer enrolled in the CAO/ARO/AIO-94 and -04 trials. One hundred and sixty-one samples were used for building, training and validating a predictor of pCR using a machine learning algorithm. The performance of the classifier was validated in three independent cohorts, comprising 76 patients from (i) the CAO/ARO/AIO-94 and -04 trials (n = 14), (ii) a publicly available dataset (n = 38) and (iii) in 24 prospectively collected samples from the TransValid A trial.
Results: A 21-transcript signature yielded the best classification of pCR in 161 patients (Sensitivity: 0.31; AUC: 0.81), when not allowing misclassification of non-complete-responders (False-positive rate = 0). The classifier remained robust when applied to three independent datasets (n = 76).
Conclusion: The classifier can identify >1/3 of rectal cancer patients with a pCR while never classifying patients with an incomplete response as having pCR. Importantly, we could validate this finding in three independent datasets, including a prospectively collected cohort. Therefore, this classifier could help select rectal cancer patients for a “watch and wait” strategy.
Translational relevance: Forgoing surgery with its associated side effects could be an option for rectal cancer patients if the prediction of a pathological complete response (pCR) after preoperative chemoradiotherapy would be possible. Based on gene-expression profiles of 161 patients a classifier was developed and validated in three independent datasets (n = 76), identifying over 1/3 of patients with pCR, while never misclassifying a non-complete-responder. Therefore, the classifier can identify patients suited for “watch and wait”.
MetadatenAuthor: | Georg EmonsORCiD, Noam Auslander, Peter Jo, Julia KitzGND, Azadeh AzizianORCiD, Yue HuORCiD, Clemens F. HessGND, Claus RödelORCiDGND, Ulrich SaxORCiDGND, Gabriela Salinas-RiesterGND, Philipp StröbelORCiDGND, Frank Kramer, Tim BeissbarthORCiDGND, Michael GhadimiORCiDGND, Eytan RuppinORCiD, Thomas RiedORCiD, Jochen Werner Christian GaedckeORCiDGND, Marian GradeGND |
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URN: | urn:nbn:de:hebis:30:3-632598 |
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DOI: | https://doi.org/10.1038/s41416-022-01842-2 |
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ISSN: | 1532-1827 |
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Parent Title (English): | British journal of cancer |
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Publisher: | Nature Publ. Group |
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Place of publication: | Edinburgh |
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Document Type: | Article |
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Language: | English |
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Date of Publication (online): | 2022/05/21 |
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Date of first Publication: | 2022/05/21 |
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Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
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Release Date: | 2023/01/17 |
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Tag: | Genetics research; Predictive markers; Radiotherapy; Surgical oncology |
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Volume: | 127 |
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Issue: | 4 |
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Page Number: | 10 |
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First Page: | 766 |
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Last Page: | 775 |
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Note: | Gene-expression data were deposited to Gene Expression Omnibus (GSE87211). |
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Note: | This work was supported by the Deutsche Forschungsgemeinschaft (Klinische Forschergruppe 179) and the Intramural Research Program of the National Institutes of Health, National Cancer Institute. Open Access funding enabled and organized by Projekt DEAL. |
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HeBIS-PPN: | 507024478 |
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Institutes: | Medizin |
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Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
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Sammlungen: | Universitätspublikationen |
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Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |
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