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.