Abstract
Background: Precursor B-cell acute lymphoblastic leukemia (B-ALL) is one of the most common types of leukemias in children. The majority of B-ALL patients are distinguished by chromosomal rearrangements; however, alternative splicing and epigenetic deregulations can also change the expression level of transcripts correlated with B-ALL. Therefore, the identification of prognostic and predictive biomarkers as well as the use of individualized treatments can help in B-ALL therapy. In this study, we performed an RNA-seq analysis to determine differentially expressed RNA transcripts in B-ALL.
Methods: The RNA-seq data of 79 B-ALL and 14 non-malignant ITP (immune thrombocytopenic purpura) samples were obtained from the Gene Expression Omnibus (GEO) database. Moreover, RNA-seq was performed for Iranian patients with B-ALL to identify differentially expressed genes (DEGs). In order to experimentally validate the findings, the mRNA expression of SPRING1 (or C12orf49) was evaluated in bone marrow aspiration samples of B-ALL patients using quantitative reverse transcription-PCR.
Results: Differential expression analysis revealed 920 downregulated and 1216 upregulated genes in B-ALL compared to ITP samples. Quantitative RT-PCR revealed the significant upregulation ofSPRING1 (80%) in B-ALL patients. Functional enrichment analysis exhibited that SPRING1 was principally associated with lipopolysaccharide-mediated signaling pathways.
Conclusion: Our results provided evidence for the involvement of SPRING1 in the B-ALL pathogenesis. However, further functional and clinical research is needed to understand its role in dysregulation of lipopolysaccharide-mediated signaling pathways in B-ALL.
Keywords: B-cell acute lymphoblastic leukemia, B-ALL, Biomarker, RNA-seq, SPRING1Introduction
Acute lymphoblastic leukemia (ALL) is the most common cancer in children under five years of age, with an annual incidence rate of nearly 60% (36.2 per million person-year) and a 5-year survival rate of 90% worldwide . Moreover, it accounts for nearly 25% of all acute leukemias in adults with a 5-year survival rate of 75-85% . Accumulating evidence suggests that excessive proliferation of B (B-ALL) and T (T-ALL) lineage lymphoid progenitors in the bone marrow, blood, and extramedullary sites leads to the formation of ALL . Many genetic alterations are associated with the onset of ALL, such as chromosomal translocations, mutations, and aneuploidies that occur in genes responsible for controlling cell cycle regulation and lymphoid cell development . B cell precursor ALL (B-ALL) is associated with an infectious and in hereditary etiology distinguished by chromosomal changes, resulting in protein dysregulation via the formation of chimeric genes . B-ALL patients carry a chromosomal translocation and acquire secondary genetic alterations, which lead to the differentiation and proliferation of B cells . The genetic heterogeneity in B-ALL is a promising source of biomarkers used for early detection, monitoring tools, and new chemotherapy targets . Despite the advances in the treatment of B-ALL, this disease still plays a key role in the mortality rate of patients . Consequently, the identification of specific biomarkers, pathways, and gene networks related to B-ALL is crucial for developing new strategies to improve prognostic capabilities, accelerate early diagnosis, and provide therapeutic strategies at early stages of the disease . A comprehensive understanding of the possible causes of B-ALL can be based on integrated bioinformatic analysis of high-throughput sequencing, identification of differential expression profiles, and prediction of possible biomarker function . Next-generation sequencing (NGS) methods, such as transcriptome sequencing have revealed the enormous genetic diversity of B-ALL and could be a promising diagnostic platform .
In this study, we aimed to identify a novel B-ALL-related marker that could serve as a diagnostic, prognostic, and therapeutic target as well as provide new insights into the underlying molecular mechanisms of this disease. To facilitate this, we have performed transcriptome analysis to identify a genetic biomarker for B-ALL. Moreover, we conducted differentially expressed genes (DEGs) analysis, weighted gene co-expression network analysis (WGCNA), and gene ontology (GO) enrichment analysis on a B-ALL clinical cohort, in parallel with other samples from the GEO data bank, to identify genes and pathways associated with B-ALL. Here, we identified SPRING1 (or C12orf49) as a novel marker in B-ALL using RNA-seq analysis and validated its mRNA expression level with quantitative real-time PCR.