Analysis of cell free DNA to predict outcome to bevacizumab therapy in colorectal cancer patients.
Journal
NPJ genomic medicine
ISSN: 2056-7944
Titre abrégé: NPJ Genom Med
Pays: England
ID NLM: 101685193
Informations de publication
Date de publication:
29 May 2024
29 May 2024
Historique:
received:
22
09
2023
accepted:
02
05
2024
medline:
30
5
2024
pubmed:
30
5
2024
entrez:
29
5
2024
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 38811554
doi: 10.1038/s41525-024-00415-x
pii: 10.1038/s41525-024-00415-x
doi:
Types de publication
Journal Article
Langues
eng
Pagination
33Subventions
Organisme : EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)
ID : 278981
Informations de copyright
© 2024. The Author(s).
Références
Siegel, R. L. et al. Colorectal cancer statistics, 2020. CA Cancer J. Clin. 70, 145–164 (2020).
doi: 10.3322/caac.21601
pubmed: 32133645
Kafatos, G. et al. RAS mutation prevalence among patients with metastatic colorectal cancer: a meta-analysis of real-world data. Biomark. Med. 11, 751–760 (2017).
doi: 10.2217/bmm-2016-0358
pubmed: 28747067
pmcid: 6367778
Hurwitz, H. et al. Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer. N. Engl. J. Med. 350, 2335–2342 (2004).
doi: 10.1056/NEJMoa032691
pubmed: 15175435
Saltz, L. B. et al. Randomized phase II trial of cetuximab, bevacizumab, and irinotecan compared with cetuximab and bevacizumab alone in irinotecan-refractory colorectal cancer: the BOND-2 study. J. Clin. Oncol. 25, 4557–4561 (2007).
doi: 10.1200/JCO.2007.12.0949
pubmed: 17876013
Yamazaki, K. et al. Randomized phase III study of bevacizumab plus FOLFIRI and bevacizumab plus mFOLFOX6 as first-line treatment for patients with metastatic colorectal cancer (WJOG4407G). Ann. Oncol. 27, 1539–1546 (2016).
doi: 10.1093/annonc/mdw206
pubmed: 27177863
Lambrechts, D., Lenz, H. J., de Haas, S., Carmeliet, P. & Scherer, S. J. Markers of response for the antiangiogenic agent bevacizumab. J. Clin. Oncol. 31, 1219–1230 (2013).
doi: 10.1200/JCO.2012.46.2762
pubmed: 23401453
de Haas, S. et al. Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy. Angiogenesis 17, 909–920 (2014).
doi: 10.1007/s10456-014-9438-1
pubmed: 25012543
Van Cutsem, E. et al. Bevacizumab in combination with chemotherapy as first-line therapy in advanced gastric cancer: a biomarker evaluation from the AVAGAST randomized phase III trial. J. Clin. Oncol. 30, 2119–2127 (2012).
doi: 10.1200/JCO.2011.39.9824
pubmed: 22565005
Schneider, B. P. et al. Association of vascular endothelial growth factor and vascular endothelial growth factor receptor-2 genetic polymorphisms with outcome in a trial of paclitaxel compared with paclitaxel plus bevacizumab in advanced breast cancer: ECOG 2100. J. Clin. Oncol. 26, 4672–4678 (2008).
doi: 10.1200/JCO.2008.16.1612
pubmed: 18824714
pmcid: 2653128
Lambrechts, D. et al. VEGF pathway genetic variants as biomarkers of treatment outcome with bevacizumab: an analysis of data from the AViTA and AVOREN randomised trials. Lancet Oncol. 13, 724–733 (2012).
doi: 10.1016/S1470-2045(12)70231-0
pubmed: 22608783
van Dijk, E. et al. Loss of chromosome 18q11.2-q12.1 is predictive for survival in patients with metastatic colorectal cancer treated with bevacizumab. J. Clin. Oncol. 36, 2052–2060 (2018).
doi: 10.1200/JCO.2017.77.1782
pubmed: 29792754
Smeets, D. et al. Copy number load predicts outcome of metastatic colorectal cancer patients receiving bevacizumab combination therapy. Nat. Commun. 9, 4112 (2018).
doi: 10.1038/s41467-018-06567-6
pubmed: 30291241
pmcid: 6173768
Alese, O. B. et al. Circulating tumor DNA: an emerging tool in gastrointestinal cancers. Am. Soc. Clin. Oncol. Educ. Book 42, 1–20 (2022).
pubmed: 35471832
Cristiano, S. et al. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature 570, 385–389 (2019).
doi: 10.1038/s41586-019-1272-6
pubmed: 31142840
pmcid: 6774252
Hallermayr, A. et al. Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients. J. Hematol. Oncol. 15, 125 (2022).
doi: 10.1186/s13045-022-01342-z
pubmed: 36056434
pmcid: 9438339
Kilgour, E., Rothwell, D. G., Brady, G. & Dive, C. Liquid biopsy-based biomarkers of treatment response and resistance. Cancer Cell 37, 485–495 (2020).
doi: 10.1016/j.ccell.2020.03.012
pubmed: 32289272
Mouliere, F. et al. Detection of cell-free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients. EMBO Mol. Med. https://doi.org/10.15252/emmm.201809323 (2018).
Pietrasz, D. et al. Circulating tumour DNA: a challenging innovation to develop “precision onco-surgery” in pancreatic adenocarcinoma. Br. J. Cancer 126, 1676–1683 (2022).
doi: 10.1038/s41416-022-01745-2
pubmed: 35197581
pmcid: 9174156
Rodriguez-Casanova, A. et al. Epigenetic landscape of liquid biopsy in colorectal cancer. Front. Cell Dev. Biol. 9, 622459 (2021).
doi: 10.3389/fcell.2021.622459
pubmed: 33614651
pmcid: 7892964
Vanderstichele, A. et al. Chromosomal Instability in cell-free DNA as a highly specific biomarker for detection of ovarian cancer in women with adnexal masses. Clin. Cancer Res. 23, 2223–2231 (2017).
doi: 10.1158/1078-0432.CCR-16-1078
pubmed: 27852697
Vanderstichele, A. et al. Nucleosome footprinting in plasma cell-free DNA for the pre-surgical diagnosis of ovarian cancer. NPJ Genom. Med 7, 30 (2022).
doi: 10.1038/s41525-022-00300-5
pubmed: 35484288
pmcid: 9050708
Mouliere, F. et al. Enhanced detection of circulating tumor DNA by fragment size analysis. Sci. Transl. Med. https://doi.org/10.1126/scitranslmed.aat4921 (2018).
Xu, R. H. et al. Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma. Nat. Mater. 16, 1155–1161 (2017).
doi: 10.1038/nmat4997
pubmed: 29035356
Thienpont, B. et al. Tumour hypoxia causes DNA hypermethylation by reducing TET activity. Nature 537, 63–68 (2016).
doi: 10.1038/nature19081
pubmed: 27533040
pmcid: 5133388
Van Loo, P. et al. Allele-specific copy number analysis of tumors. Proc. Natl Acad. Sci. USA 107, 16910–16915 (2010).
doi: 10.1073/pnas.1009843107
pubmed: 20837533
pmcid: 2947907
Adalsteinsson, V. A. et al. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. Nat. Commun. 8, 1324 (2017).
doi: 10.1038/s41467-017-00965-y
pubmed: 29109393
pmcid: 5673918
Raman, L., Dheedene, A., De Smet, M., Van Dorpe, J. & Menten, B. WisecondorX: improved copy number detection for routine shallow whole-genome sequencing. Nucleic Acids Res. 47, 1605–1614 (2019).
doi: 10.1093/nar/gky1263
pubmed: 30566647
Snyder, M. W., Kircher, M., Hill, A. J., Daza, R. M. & Shendure, J. Cell-free DNA comprises an in vivo nucleosome footprint that informs its tissues-of-origin. Cell 164, 57–68 (2016).
doi: 10.1016/j.cell.2015.11.050
pubmed: 26771485
pmcid: 4715266
Shirley, M. Epi proColon((R)) for colorectal cancer screening: a profile of its use in the USA. Mol. Diagn. Ther. 24, 497–503 (2020).
doi: 10.1007/s40291-020-00473-8
pubmed: 32557236
Paracchini, L. et al. Genome-wide copy-number alterations in circulating tumor DNA as a novel biomarker for patients with high-grade serous ovarian cancer. Clin. Cancer Res. 27, 2549–2559 (2021).
doi: 10.1158/1078-0432.CCR-20-3345
pubmed: 33323403
Tie, J. et al. Circulating tumor DNA analysis guiding adjuvant therapy in stage II colon cancer. N. Engl. J. Med. 386, 2261–2272 (2022).
doi: 10.1056/NEJMoa2200075
pubmed: 35657320
pmcid: 9701133
Weiss, G. J. et al. Changes in tumor cell-free DNA copy number instability (CNI) predict therapeutic response in metastatic cancers. Cancer Res. 76, 3138 (2016).
doi: 10.1158/1538-7445.AM2016-3138
Wan, J. C. M. et al. ctDNA monitoring using patient-specific sequencing and integration of variant reads. Sci. Transl. Med. https://doi.org/10.1126/scitranslmed.aaz8084 (2020).
Papageorgis, P. et al. Smad4 inactivation promotes malignancy and drug resistance of colon cancer. Cancer Res. 71, 998–1008 (2011).
doi: 10.1158/0008-5472.CAN-09-3269
pubmed: 21245094
pmcid: 3075468
Horgan, D. et al. Accelerating the development and validation of liquid biopsy for early cancer screening and treatment tailoring. Healthcare 10, 1714 (2022).
doi: 10.3390/healthcare10091714
pubmed: 36141326
pmcid: 9498805
Pataky, R. E. et al. Real-world cost-effectiveness of bevacizumab with first-line combination chemotherapy in patients with metastatic colorectal cancer: population-based retrospective cohort studies in three Canadian provinces. MDM Policy Pract. 6, 23814683211021060 (2021).
pubmed: 34212111
pmcid: 8216386
Betge, J. et al. Outcome of colorectal cancer patients treated with combination bevacizumab therapy: a pooled retrospective analysis of three European cohorts from the angiopredict initiative. Digestion 94, 129–137 (2016).
doi: 10.1159/000449412
pubmed: 27756074
Hadley, W. Ggplot2. (Springer Science+Business Media, LLC, 2016).
R: A language and environment for statistical computing (2020).