Development and validation of a quantitative polymerase chain reaction assay to evaluate minimal residual disease for T-cell acute lymphoblastic leukemia and follicular lymphoma.
Development and validation of a quantitative polymerase chain reaction assay to evaluate minimal residual disease for T-cell acute lymphoblastic leukemia and follicular lymphoma.
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开发和验证定量聚合酶链反应测定法，以评估 T 细胞急性淋巴细胞白血病和滤泡性淋巴瘤的微小残留病。
DOI：
10.1016/s0002-9440(10)65355-2
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
Scheuermann,RH
中科院分区：
文献类型：
--
作者：
Hosler,GA;Bash,RO;Bai,X;Jain,V;Scheuermann,RH
The presence of occult disease in cancer patients after therapy is one of the major problems faced by oncologists. For example, although 95% of pediatric T-cell acute lymphoblastic leukemia (T-ALL) patients have a complete therapeutic response to multiagent chemotherapy, half will relapse, indicating that they must have harbored low levels of residual cancer cells at the end of therapy. Sensitive detection assays promise to help identify those patients that carry this minimal residual disease (MRD) and are at risk of relapse. We have developed and validated a quantitative polymerase chain reaction (PCR) assay targeting tumor-specific chromosomal rearrangements, including del(1) involving the tal-1 locus in pediatric T-ALL and t(14;18) involving the bcl-2 locus in follicular lymphoma. This quantitative PCR assay utilizes a synthetic internal calibration standard (ICS) that contains priming sequences identical to those found flanking the chromosomal rearrangement breakpoints. Using this ICS-PCR method, the limits of detection were 5 tumor cells at ratios of 1 tumor cell in 105normal cells and a linear range up to 100% tumor cells. This ICS-PCR method has also performed well in terms of precision and accuracy as indicated by low coefficients of variation, minimal random, proportional, and constant errors, and good clinical sensitivity and specificity characteristics. This technique will allow for the evaluation of parameters such as the rate of therapeutic response and the levels of MRD as predictors of patient outcome.
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