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MicroRNA Signatures in Blood or Bone Marrow Distinguish Subtypes of Pediatric Acute Lymphoblastic Leukemia.

ABSTRACT: OncomiRs are microRNAs that are associated with early onset of specific cancers. To identify microRNAs involved in pediatric acute lymphoblastic leukemia (ALL) subtypes T-ALL and B-ALL, peripheral blood and bone marrow samples were independently subjected to microarray analysis using two different high-fidelity array platforms. The unique and common gene signatures from both arrays were validated by TaqMan individual assays in 100 pediatric ALL samples. Survival studies were carried out in the test set and validation set with 50 randomly selected samples in each set. MicroRNA expression profile revealed characteristic signatures for distinguishing T and B lineages and identified 51 novel microRNAs in pediatric ALL. Interestingly, the present study also revealed endogenous similarities and differences between blood and bone marrow within each ALL subtype. When Cox regression analysis was carried out with these identified microRNAs, 11 of them exhibited expression levels significantly correlated with survival. Validation of some of the common and relevant microRNAs from both arrays showed that their targets are involved in key oncogenic signaling pathways. Thus, this study suggests that microRNAs have the potential to become important diagnostic tools for identification and monitoring clinical outcomes in ALL patients.

SUBMITTER: Nair RA

PROVIDER: S-EPMC7292917 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Pediatric acute lymphoblastic leukemia (ALL) contains cytogenetically distinct subtypes that respond differently to cytotoxic drugs. Subtype classification can be also achieved through gene expression profiling. However, how to apply such classifiers to a single patient and correctly diagnose the disease subtype in an independent patient group has not been addressed. Furthermore, the underlying regulatory mechanisms responsible for the subtype-specific gene expression patterns are still largely unknown. Here, by combining three published microarray datasets (PMIDs: 12086872, 12730115, 17002788) on 535 Caucasian samples and generating a new dataset on 100 Chinese children ALL samples, we were able to 1) identify a 62-gene classifier with 97.6% accuracy from the Caucasian samples and validated it on the completely independent set of 100 Chinese samples, 2) to uncover potential regulatory networks of ALL subtypes. The classifier we identified was so far the only one that could be applied directly to a single sample and sustained validation in a large independent patient group. Our results also suggest that the etiology of ALL is largely the same among different ethnic groups, and that the transcription factor hubs in the predicted regulatory network might play important roles in regulating gene expression and development of ALL. A total of 100 Chinese pediatric acute lymphoblastic leukemia bone marrow (BM) samples were analyzed, together with five non-ALL BM samples as negative control (the five samples were combined to generate one control, see details in Li et al. Blood, 2009). The diagnosis of ALL was based on morphology, immunology, cytogenetic and molecular (MICM) classification. Cytogenetic ALL subtypes were identified experimentally by G-banding karyotype and multiplex nested RT-PCR. Among the 100 ALL patients, eleven relapsed within five years. All the samples, including those relapsed afterward, were from patients treated on BCH-2003 protocol and were extracted at their initial diagnosis. The five non-ALL BM samples were taken from the removed bones of patients who had plastic surgery for their bone deformity in Beijing Children’s Hospital. And the informed consent was obtained from parents, guardians, or patients (as appropriate). More details are available in Li et al. Gene expression-based classification and regulatory networks of pediatric acute lymphoblastic leukemia, Blood, 2009. We have generated these ALL and control samples to validate that a high accuracy subtype classifier that we identified could be applied directly to a single sample and sustained validation in a large independent patient group.

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MicroRNA Signatures in Blood or Bone Marrow Distinguish Subtypes of Pediatric Acute Lymphoblastic Leukemia.

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