分析无细胞 DNA 以预测结直肠癌患者贝伐珠单抗治疗的结果。
Analysis of cell free DNA to predict outcome to bevacizumab therapy in colorectal cancer patients.
发表日期:2024 May 29
作者:
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
来源:
npj Genomic Medicine
摘要:
为了预测贝伐单抗 (BVZ) 联合治疗的结果,我们采用游离 DNA (cfDNA) 来确定转移性结直肠癌 (mCRC) 患者的染色体不稳定性 (CIN)、核小体足迹 (NF) 和甲基化谱。对从 AC-ANGIOPREDICT II 期试验 (NCT01822444) 的 74 名 mCRC 患者收集的匹配肿瘤和血浆样本进行低覆盖率全基因组测序 (LC-WGS),并分析 CIN 和 NF。来自曼海姆大学医学中心 (UMM) 的血浆样本验证队列也进行了类似的分析。选择 BVZ 治疗前后收集的 61 份 AC-ANGIOPREDICT 血浆样本进行靶向甲基化测序。使用 cfDNA CIN 图谱,AC-ANGIOPREDICT 样本以 92.3% 的准确度分为低 CIN 簇和高 CIN 簇,在匹配的血浆和肿瘤之间观察到良好的一致性。在 CIN 高的患者中观察到生存率提高。基于血浆的 CIN 聚类在 UMM 队列中得到了验证。甲基化分析确定了 CIN-low 与 CIN high 的差异 (AUC = 0.87)。此外,BVZ 后甲基化评分显着降低与结果改善相关 (p = 0.013)。对血浆样本中 cfDNA 的 CIN、NF 和甲基化谱进行分析有助于将 CIN 簇分层,从而告知患者对治疗的反应。© 2024。作者。
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.© 2024. The Author(s).