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HSPG2 overexpression independently predicts poor survival in patients with acute myeloid leukemia.

ABSTRACT: Heparan sulfate proteoglycan 2 (HSPG2), also known as perlecan, is a large multi-domain extracellular matrix proteoglycan, which contributes to the invasion, metastasis and angiogenesis of solid tumor. However, very little is known about the effect of HSPG2 on acute myeloid leukemia (AML). This study aims to investigate the prognostic value of the HSPG2 gene in terms of overall survival and leukemia-free survival in patients with AML. Bone marrow mononuclear cells (BMMCs) from 4 AML patients and 3 healthy controls were processed for RNA-Sequencing (RNA-seq). The mRNA expression level of HSPG2 in BMMCs and CD34⁺ hematopoietic stem/progenitor cells (HSPC) obtained from enrolled participants and human leukemic cell lines was detected by RT-qPCR. Then the correlations between the expression of HSPG2 and a variety of important clinical parameters, such as median white blood cell (WBC) count and bone marrow (BM) blasts, were further analyzed. The expression level of HSPG2 was significantly upregulated in AML patients at the time of diagnosis, downregulated after complete remission and then elevated again at relapse. Moreover, HSPG2 expression was associated with median WBC count (P?

SUBMITTER: Zhou X

PROVIDER: S-EPMC7327006 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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HSPG2 overexpression independently predicts poor survival in patients with acute myeloid leukemia.

Zhou Xiaojia X Liang Simin S Zhan Qian Q Yang Li L Chi Jianxiang J Wang Li L

Cell death & disease 20200630 6

Heparan sulfate proteoglycan 2 (HSPG2), also known as perlecan, is a large multi-domain extracellular matrix proteoglycan, which contributes to the invasion, metastasis and angiogenesis of solid tumor. However, very little is known about the effect of HSPG2 on acute myeloid leukemia (AML). This study aims to investigate the prognostic value of the HSPG2 gene in terms of overall survival and leukemia-free survival in patients with AML. Bone marrow mononuclear cells (BMMCs) from 4 AML patients and ...[more]

PMID: 32606327

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Project description:Background: Acute myeloid leukemia (AML) is a heterogeneous malignant disease. SLC25A1, the gene encoding mitochondrial carrier subfamily of solute carrier proteins, was reported to be overexpressed in certain solid tumors. However, its expression and value as prognostic marker has not been assessed in AML. Methods: We retrieved RNA profile and corresponding clinical data of AML patients from the Beat AML, TCGA, and TARGET databases (TARGET_AML). Patients in the TCGA cohort were well-grouped into two group based on SLC25A1 and differentially expressed genes were determined between the SLC25A1 high and low group. The expression of SLC25A1 was validated with clinical samples. The survival and apoptosis of two AML cell lines were analyzed with SLC25A1 inhibitor (CTPI-2) treatment. Cox and the least absolute shrinkage and selection operator (LASSO) regression analyses were applied to Beat AML database to identify SLC25A1-associated genes for the construction of a prognostic risk-scoring model. Survival analysis was performed by Kaplan-Meier and receiver operator characteristic curves. Results: Our analysis revealed that high expressed level of SLC25A1 in AML patients correlates with unfavorable prognosis. Moreover, SLC25A1 expression was positively associated with metabolism activity. We further demonstrated that the inhibition of SLC25A1 could inhibit the proliferation and increase the apoptosis of AML cells. In addition, a panel of SLC25A1-associated genes, was identified to construct a prognostic risk-scoring model. This SLC25A1-associated prognostic signature (SPS) is an independent risk factor with high area under curve (AUC) values of receiver operating characteristic (ROC) curves. A high SPS in leukemia patients is associated with poor survival. A Prognostic nomogram including the SPS and other clinical parameters, was constructed and its predictive efficiency was confirmed. Conclusion: We have successfully established a SPS prognostic model that predict outcome and risk stratification in AML. This risk model can be used as an independent biomarker to assess prognosis of AML.

Project description:PurposeOptimized strategies for risk classification are essential to tailor therapy for patients with biologically distinctive disease. Risk classification in pediatric acute myeloid leukemia (pAML) relies on detection of translocations and gene mutations. Long noncoding RNA (lncRNA) transcripts have been shown to associate with and mediate malignant phenotypes in acute myeloid leukemia (AML) but have not been comprehensively evaluated in pAML.MethodsTo identify lncRNA transcripts associated with outcomes, we evaluated the annotated lncRNA landscape by transcript sequencing of 1,298 pediatric and 96 adult AML specimens. Upregulated lncRNAs identified in the pAML training set were used to establish a regularized Cox regression model of event-free survival (EFS), yielding a 37 lncRNA signature (lncScore). Discretized lncScores were correlated with initial and postinduction treatment outcomes using Cox proportional hazards models in validation sets. Predictive model performance was compared with standard stratification methods by concordance analysis.ResultsTraining set cases with positive lncScores had 5-year EFS and overall survival rates of 26.7% and 42.7%, respectively, compared with 56.9% and 76.3% with negative lncScores (hazard ratio, 2.48 and 3.16; P < .001). Pediatric validation cohorts and an adult AML group yielded comparable results in magnitude and significance. lncScore remained independently prognostic in multivariable models, including key factors used in preinduction and postinduction risk stratification. Subgroup analysis suggested that lncScores provide additional outcome information in heterogeneous subgroups currently classified as indeterminate risk. Concordance analysis showed that lncScore adds to overall classification accuracy with at least comparable predictive performance to current stratification methods that rely on multiple assays.ConclusionInclusion of the lncScore enhances predictive power of traditional cytogenetic and mutation-defined stratification in pAML with potential, as a single assay, to replace these complex stratification schemes with comparable predictive accuracy.

Dataset Information

HSPG2 overexpression independently predicts poor survival in patients with acute myeloid leukemia.

Publications

HSPG2 overexpression independently predicts poor survival in patients with acute myeloid leukemia.

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