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Abstract：
BACKGROUND: Risk stratification in multiple myeloma (MM) patients is crucial, and molecular genetic studies play a significant role in achieving this objective. Enrichment of plasma cells for next-generation sequencing (NGS) analysis has been employed to enhance detection sensitivity. However, these methods often come with limitations, such as high costs and low throughput. In this study, we explore the use of an error-corrected ultrasensitive NGS assay called positional indexing sequencing (PiSeq-MM). This assay can detect somatic mutations in MM patients without relying on plasma cell enrichment.
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.
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.
摘要：
背景：多发性骨髓瘤（MM）患者的危险分层至关重要，分子遗传学研究在实现这一目标方面发挥着重要作用。用于下一代测序(NGS)分析的浆细胞的富集已被用于增强检测灵敏度。然而,这些方法往往有局限性，如高成本和低吞吐量。在这项研究中,我们探索了一种错误校正的超灵敏NGS检测方法的使用,称为位置索引测序(PiSeq-MM).该测定可以检测MM患者的体细胞突变而不依赖于浆细胞富集。
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.
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.
