Analysis of cell free DNA to predict outcome to bevacizumab therapy in colorectal cancer patients

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Institut Català de la Salut

[Venken T, Arijs I] Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium. VIB Center for Cancer Biology, Leuven, Belgium. [Miller IS, Thomas V] Precision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland. [Barat A] Centre for Systems Medicine, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland. [Betge J] Department of Medicine II, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. Junior Clinical Cooperation Unit Translational Gastrointestinal Oncology and Preclinical Models, German Cancer Research Center (DKFZ), Heidelberg, Germany. DKFZ-Hector Cancer Institute at University Medical Center Mannheim, Mannheim, Germany. German Cancer Consortium (DKTK), Heidelberg, Germany. [Serna G, Nuciforo PG] Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain

Vall d'Hebron Barcelona Hospital Campus

Fecha de publicación

2024-06-03T11:04:41Z

2024-06-03T11:04:41Z

2024-05-29



Resumen

Cell free DNA; Bevacizumab; Colorectal cancer


ADN lliure de cèl·lules; Bevacizumab; Càncer colorectal


ADN libre de células; Bevacizumab; Cáncer colorrectal


To predict outcome to combination bevacizumab (BVZ) therapy, we employed cell-free DNA (cfDNA) to determine chromosomal instability (CIN), nucleosome footprints (NF) and methylation profiles in metastatic colorectal cancer (mCRC) patients. Low-coverage whole-genome sequencing (LC-WGS) was performed on matched tumor and plasma samples, collected from 74 mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444), and analysed for CIN and NFs. A validation cohort of plasma samples from the University Medical Center Mannheim (UMM) was similarly profiled. 61 AC-ANGIOPREDICT plasma samples collected before and following BVZ treatment were selected for targeted methylation sequencing. Using cfDNA CIN profiles, AC-ANGIOPREDICT samples were subtyped with 92.3% accuracy into low and high CIN clusters, with good concordance observed between matched plasma and tumor. Improved survival was observed in CIN-high patients. Plasma-based CIN clustering was validated in the UMM cohort. Methylation profiling identified differences in CIN-low vs. CIN high (AUC = 0.87). Moreover, significant methylation score decreases following BVZ was associated with improved outcome (p = 0.013). Analysis of CIN, NFs and methylation profiles from cfDNA in plasma samples facilitates stratification into CIN clusters which inform patient response to treatment.


The authors would like to acknowledge the assistance of Evy Vanderheyden, Thomas Van Brussel and Rogier Schepers with plasma and tumor sample processing and library preparation. The authors would also like to acknowledge the assistance of Dr. Nicole Prasnikar, Dr. Judith Franz-Werner and Dr. Hans-Peter Feustely with tumor tissue collection. This research was supported by a Health Research Board (HRB) Investigator Led Project (ILP) grant agreement number: ILPPOR-2019-066 to A.T.B. and D.L. who are further supported by the European Union’s Horizon 2020 Health Research and Innovation award “COLOSSUS” (grant agreement number: 754923). The ANGIOPREDICT Phase II trial was funded by the European Commission Framework Programme Seven (FP7) initiative under contract No. 278981 ‘ANGIOPREDICT’ (www.ANGIOPREDICT.com). This publication has also been supported in part by grants awarded to A.T.B. from Science Foundation Ireland under Grant number 20/FFP-P/8884 and the Higher Education Authority North-South Research Programme 2021 'RadCOL'. This research was further supported by a European Research Council (ERC) Proof of Concept Award to D.L. (Grant Agreement number 899947). Funding was further provided by Kom Op Tegen Kanker (Stand up to Cancer, the Flemish Cancer Society) and FWO (SBO MICADO: Multiomic Integration of cell-free DNA profiles to Advance Disease Outcome, S003422N).

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Nature Portfolio

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Attribution 4.0 International

http://creativecommons.org/licenses/by/4.0/

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