Underexpression of in -Positive Cases Is Associated With Poor Prognosis in Children With B-Cell Precursor Acute Lymphoblastic Leukemia
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Background: B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is the most frequent pediatric cancer worldwide. Despite improvements in treatment regimens, approximately 20% of the cases cannot be cured, highlighting the necessity for identifying new biomarkers to improve the current clinical and molecular risk stratification schemes. We aimed to investigate whether is a biomarker in ALL and to explore its expression level in other human cancer types.
Methods: A nested case-control study including Mexican children with BCP-ALL was conducted. expression was evaluated by qRT-PCR using hydrolysis probes. To validate our findings, RNA-seq expression data from BCP-ALL and normal tissues were retrieved from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) repositories, respectively. expression was also evaluated in solid tumors by downloading available data from The Cancer Genome Atlas (TCGA).
Results: A lower expression of in BCP-ALL cases compared to normal subjects was observed ( < 0.05). ALL patients who carry the fusion gene displayed lower expression of in contrast to other BCP-ALL molecular subtypes ( < 0.04). underexpression was associated with a high risk to relapse (HR = 1.946, 95% CI = 1.213-3.120) and die (HR = 2.073, 95% CI = 1.211-3.547). Patients with and underexpression of had the worst prognosis (DFS: HR = 12.24, 95% CI = 5.04-29.71; OS: HR = 11.19, 95% CI = 26-32). TCGA data analysis revealed that underexpression of is also associated with poor clinical outcomes in six new reported tumor types.
Conclusion: Our findings suggest that is a biomarker of poor prognosis in BCP-ALL and other types of cancer. We observed an association between the expression of and and the risk to relapse and die in BCP-ALL, which is worse in positive cases displaying underexpression of Experimental studies are needed to provide insight into the and relationship.
L-RAPiT: A Cloud-Based Computing Pipeline for the Analysis of Long-Read RNA Sequencing Data.
Nelson T, Ghosh S, Postler T Int J Mol Sci. 2022; 23(24).
PMID: 36555493 PMC: 9781625. DOI: 10.3390/ijms232415851.