METHODS: Diagnostic bone marrow aspirates (BMAs) and blood samples from 14 MM patients were used for exploratory and validation sets.
RESULTS: PiSeq-MM successfully detected somatic mutations in all BMAs, outperforming conventional NGS using plasma cells. It also identified 38 low-frequency mutations that were missed by conventional NGS, enhancing detection sensitivity below the 5% analytical threshold. When tested in an actual clinical environment, plasma cell enrichment failed in most BMAs (14/16), but the PiSeq-MM enabled mutation detection in all BMAs. There was concordance between PiSeq-MM using BMAs and ctDNA analysis in paired blood samples.
CONCLUSIONS: This research provides valuable insights into the genetic landscape of MM and highlights the advantages of error-corrected NGS for detecting low-frequency mutations. Although the current standard method for mutation analysis is plasma cell-enriched BMAs, total BMA or ctDNA testing with error correction is a viable alternative when plasma cell enrichment is not feasible.
方法:将来自14例MM患者的诊断性骨髓抽吸物(BMAs)和血液样本用于探索和验证集。
结果:PiSeq-MM在所有BMA中成功检测到体细胞突变,优于使用浆细胞的常规NGS。它还确定了38个常规NGS错过的低频突变,提高检测灵敏度低于5%的分析阈值。当在实际临床环境中测试时,大多数BMAs(14/16)的浆细胞富集失败,但PiSeq-MM在所有BMA中都能检测到突变。在配对血液样品中使用BMA和ctDNA分析的PiSeq-MM之间存在一致性。
结论:这项研究为MM的遗传景观提供了有价值的见解,并突出了错误校正的NGS用于检测低频突变的优势。尽管目前用于突变分析的标准方法是富含浆细胞的BMA,当浆细胞富集不可行时,带误差校正的总BMA或ctDNA检测是可行的替代方法.