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. 2022 Feb 28;15(1):38.
doi: 10.1186/s12920-022-01193-0.

Comprehensive analysis of SPAG1 expression as a prognostic and predictive biomarker in acute myeloid leukemia by integrative bioinformatics and clinical validation

Affiliations

Comprehensive analysis of SPAG1 expression as a prognostic and predictive biomarker in acute myeloid leukemia by integrative bioinformatics and clinical validation

Yu Gu et al. BMC Med Genomics. .

Abstract

Background: Recently, an increasing number of studies have reported that sperm-associated antigen (SPAG) proteins play crucial roles in solid tumorigenesis, and may serve as potentially helpful biomarkers for cancer diagnosis and prognosis. However, very few studies systematically investigated the expression of SPAG family members and their clinical significance in acute myeloid leukemia (AML).

Methods: The expression of SPAGs and their prognostic significance in AML were determined by a systematic analysis on data gathered from public databases, and the results were validated in clinical samples.

Results: Using public data, we identified only increased SPAG1 expression negatively associated with survival in AML by Cox regression (P < 0.001) and Kaplan-Meier analysis (P < 0.001). The prognostic value of SPAG1 expression was further confirmed in other independent cohorts. Clinically, higher SPAG1 expression was significantly correlated with white blood cell counts (P = 0.014) and French-American-British (FAB) subtypes (P = 0.024). Moreover, higher SPAG1 expression was more common in + 8 patients (P = 0.034), rarely found with t(8;21) (P = 0.014), and correlated with FLT3 (P < 0.001) and DNMT3A mutations (P = 0.001). Despite these associations, multivariate analysis confirmed the independent prognostic value of SPAG1 expression in AML (P < 0.001). Notably, AML patients with higher SPAG1 expression may benefit from hematopoietic stem cell transplantation (HSCT), whereas patients with lower SPAG1 expression appeared less likely to benefit. Finally, we further validated that SPAG1 expression was significantly increased in newly diagnosed AML patients compared with normal controls (P < 0.001) and with AML patients who achieved complete remission (P < 0.001). Additionally, SPAG1 expression could act as a potentially helpful biomarker for the diagnosis and prognosis of AML (P < 0.001 and = 0.034, respectively).

Conclusions: Our findings demonstrated that SPAG1 overexpression may serve as an independent prognostic biomarker and may guide the choice between HSCT and chemotherapy in patients with AML.

Keywords: AML; Bioinformatics; Expression; Prognosis; SPAG1.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The impact of SPAG1 expression on survival of AML patients. a The effect of SPAG1 expression on overall survival in whole-cohort AML, non-M3 AML, and CN-AML from TCGA dataset. b The effect of SPAG1 expression on disease/leukemia free survival in in whole-cohort AML, non-M3 AML, and CN-AML from TCGA dataset. c SPAG1 expression in AML from TCGA dataset. d The effect of SPAG1 expression on overall survival in 78 and 162 CN-AML from the GEO dataset (GSE12417) analyzed by the online web tool Genomicscape (http://genomicscape.com/microarray/survival.php). e The effect of SPAG1 expression on event-free survival and overall survival in AML from GEO datasets (GSE6891 and GSE37642)
Fig. 2
Fig. 2
The associations of SPAG1 expression with genetic abnormalities in AML. a SPAG1 expression in AML patients with and without chromosome 8 abnormalities from TCGA datasets. b SPAG1 expression in AML patients with and without FLT3 mutations from TCGA datasets. c SPAG1 expression in AML patients with and without DNMT3A mutations from TCGA datasets. d SPAG1 expression in AML patients with and without WT1 mutations from TCGA datasets
Fig. 3
Fig. 3
The impact of SPAG1 expression on survival of AML patients with specific subtypes. a Kaplan–Meier survival curves of overall survival and disease/leukemia free survival in whole-cohort AML and CN-AML without FLT3 mutation from TCGA datasets. b Kaplan–Meier survival curves of overall survival and disease/leukemia free survival in whole-cohort AML and CN-AML without DNMT3A mutation from TCGA datasets. c Kaplan–Meier survival curves of overall survival and disease/leukemia free survival in whole-cohort AML and CN-AML without WT1 mutation from TCGA datasets. d Kaplan–Meier survival curves of overall survival and disease/leukemia free survival in whole-cohort AML and CN-AML without FLT3/DNMT3A/WT1 mutation from TCGA datasets
Fig. 4
Fig. 4
The effect of HSCT on survival of AML patients among different SPAG1 expression groups. Kaplan–Meier survival curves of overall survival and disease/leukemia free survival among whole-cohort AML in both lower and higher SPAG1 expression group from TCGA datasets
Fig. 5
Fig. 5
Molecular signatures associated with SPAG1 in AML. a Expression heatmap of differentially expressed genes between AML patients with lower and higher SPAG1 expression groups among TCGA datasets (FDR < 0.05, P < 0.05 and |log2 FC|> 1.5). b Volcano plot of differentially expressed genes between AML patients with lower and higher SPAG1 expression (FDR < 0.05, P < 0.05, and |log2 FC|> 1.5). c Expression heatmap of differentially expressed microRNAs between AML patients with lower and higher SPAG1 expression (FDR < 0.05, P < 0.05, and |log2 FC|> 1.5). d GSEA analysis of SPAG1 expression associated with HOXA9 dysregulation oin AML (NOM P < 0.05 and FDR Q < 0.05)
Fig. 6
Fig. 6
Validation of SPAG1 expression and its clinical significance in AML. a SPAG1 expression in 15 controls, 86 AML patients at diagnosis time, and 45 AML patients who achieved complete remission. b ROC curve analysis of SPAG1 expression in distinguishing AML from controls. c SPAG1 expression at diagnosis time in AML patients who did and did not achieve CR after 1–2 course induction therapy. d Kaplan–Meier survival curves of overall survival regarding SPAG1 expression in whole-cohort AML from our hospital

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