npj Genomic Medicine (May 2024)

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

  • Tom Venken,
  • Ian S. Miller,
  • Ingrid Arijs,
  • Valentina Thomas,
  • Ana Barat,
  • Johannes Betge,
  • Tianzuo Zhan,
  • Timo Gaiser,
  • Matthias P. Ebert,
  • Alice C. O’Farrell,
  • Jochen Prehn,
  • Rut Klinger,
  • Darran P. O’Connor,
  • Brian Moulton,
  • Verena Murphy,
  • Garazi Serna,
  • Paolo G. Nuciforo,
  • Ray McDermott,
  • Brian Bird,
  • Gregory Leonard,
  • Liam Grogan,
  • Anne Horgan,
  • Nadine Schulte,
  • Markus Moehler,
  • Diether Lambrechts,
  • Annette T. Byrne

DOI
https://doi.org/10.1038/s41525-024-00415-x
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 10

Abstract

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Abstract 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.