Lim Emilia L, Trinh Diane L, Ries Rhonda E, Wang Jim, Gerbing Robert B, Ma Yussanne, Topham James, Hughes Maya, Pleasance Erin, Mungall Andrew J, Moore Richard, Zhao Yongjun, Aplenc Richard, Sung Lillian, Kolb E Anders, Gamis Alan, Smith Malcolm, Gerhard Daniela S, Alonzo Todd A, Meshinchi Soheil, Marra Marco A
Emilia L. Lim, Diane L. Trinh, Yussanne Ma, James Topham, Erin Pleasance, Andrew J. Mungall, Richard Moore, Yongjun Zhao, and Marco A. Marra, Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency; Marco A. Marra, University of British Columbia, Vancouver, British Columbia; Lillian Sung, The Hospital for Sick Children, Toronto, Ontario, Canada; Rhonda E. Ries, Maya Hughes, and Soheil Meshinchi, Fred Hutchinson Cancer Research Center; Rhonda E. Ries, Maya Hughes, and Soheil Meshinchi, University of Washington, Seattle, WA; Jim Wang, Robert B. Gerbing, E. Anders Kolb, Alan Gamis, and Todd A. Alonzo, Children's Oncology Group, Monrovia; Todd A. Alonzo, University of Southern California, Los Angeles, CA; Richard Aplenc, The Children's Hospital of Philadelphia, Philadelphia, PA; Malcolm Smith and Daniela S. Gerhard, Office of Cancer Genomics, National Cancer Institute, Bethesda, MD; and Robert J. Arceci, Phoenix Children's Hospital, Phoenix. AZ.
J Clin Oncol. 2017 Dec 10;35(35):3964-3977. doi: 10.1200/JCO.2017.74.7451. Epub 2017 Oct 25.
Purpose Children with acute myeloid leukemia (AML) whose disease is refractory to standard induction chemotherapy therapy or who experience relapse after initial response have dismal outcomes. We sought to comprehensively profile pediatric AML microRNA (miRNA) samples to identify dysregulated genes and assess the utility of miRNAs for improved outcome prediction. Patients and Methods To identify miRNA biomarkers that are associated with treatment failure, we performed a comprehensive sequence-based characterization of the pediatric AML miRNA landscape. miRNA sequencing was performed on 1,362 samples-1,303 primary, 22 refractory, and 37 relapse samples. One hundred sixty-four matched samples-127 primary and 37 relapse samples-were analyzed by using RNA sequencing. Results By using penalized lasso Cox proportional hazards regression, we identified 36 miRNAs the expression levels at diagnosis of which were highly associated with event-free survival. Combined expression of the 36 miRNAs was used to create a novel miRNA-based risk classification scheme (AMLmiR36). This new miRNA-based risk classifier identifies those patients who are at high risk (hazard ratio, 2.830; P ≤ .001) or low risk (hazard ratio, 0.323; P ≤ .001) of experiencing treatment failure, independent of conventional karyotype or mutation status. The performance of AMLmiR36 was independently assessed by using 878 patients from two different clinical trials (AAML0531 and AAML1031). Our analysis also revealed that miR-106a-363 was abundantly expressed in relapse and refractory samples, and several candidate targets of miR-106a-5p were involved in oxidative phosphorylation, a process that is suppressed in treatment-resistant leukemic cells. Conclusion To assess the utility of miRNAs for outcome prediction in patients with pediatric AML, we designed and validated a miRNA-based risk classification scheme. We also hypothesized that the abundant expression of miR-106a could increase treatment resistance via modulation of genes that are involved in oxidative phosphorylation.
目的 患有急性髓系白血病（AML）的儿童，若其疾病对标准诱导化疗难治或在初始缓解后复发，预后较差。我们试图全面分析儿科AML微小RNA（miRNA）样本，以识别失调基因并评估miRNA在改善预后预测方面的效用。
患者与方法 为了识别与治疗失败相关的miRNA生物标志物，我们对儿科AML的miRNA格局进行了基于序列的全面表征。对1362个样本进行了miRNA测序，其中包括1303个原发性样本、22个难治性样本和37个复发性样本。使用RNA测序分析了164个匹配样本，包括127个原发性样本和37个复发性样本。
结果 通过使用惩罚性套索Cox比例风险回归，我们鉴定出36个miRNA，其诊断时的表达水平与无事件生存期高度相关。这36个miRNA的联合表达被用于创建一种基于miRNA的新型风险分类方案（AMLmiR36）。这种基于miRNA的新风险分类器能够识别出那些经历治疗失败风险高（风险比，2.830；P≤0.001）或低（风险比，0.323；P≤0.001）的患者，与传统核型或突变状态无关。通过使用来自两项不同临床试验（AAML0531和AAML1031）的878名患者对AMLmiR36的性能进行了独立评估。我们的分析还表明，miR-10,6a-363在复发和难治性样本中大量表达，并且miR-106a-5p的几个候选靶点参与氧化磷酸化，这一过程在耐药白血病细胞中受到抑制。
结论 为了评估miRNA在儿科AML患者预后预测中的效用，我们设计并验证了一种基于miRNA的风险分类方案。我们还假设miR-106a的大量表达可能通过调节参与氧化磷酸化的基因来增加治疗耐药性。
