Systematic analysis of prognostic significance, functional enrichment and immune implication of STK10 in acute myeloid leukemia

Abstract

Background: Despite deeper understanding of the genetic landscape of acute myeloid leukemia (AML), the improvement of survival is still a great challenge. STK10 is overexpressed in several cancers with functions varying according to cancer types. But the functions of STK10 in AML has never been reported.

Methods: We analyzed the expression, prognosis and potential functions of STK10 utilizing public web servers. Metascape and the String database were used for functional and protein-protein interaction analyses.

Results: We found STK10 was enriched in blood & immune cells and overexpressed in AML. High STK10 expression was associated with poor overall survival, which was also identified in the subgroups of patients ≤ 60 years old and patients with non-high-risk cytogenetics. We demonstrated genes associated with STK10 were enriched in blood, spleen and bone marrow, influencing the immune function and biological process of AML. ITGB2 and ITGAM might directly interact with STK10 and were associated with poor prognosis. Besides, STK10 was associated with the infiltration of immune cells and immune checkpoints, like HLA-E, CD274 and GAL-9.

Conclusions: The present study was the original description of STK10 in AML and set the stage for developing STK10 as a new prognostic marker or therapeutic target for AML.

Keywords: AML; Functional analysis; Immune infiltration; Prognosis; STK10.

Fig. 1

STK10 expression in different cell types and tumors. a STK10 expression in different cell types, analyzed by HPA. b STK10 expression across various tumors and normal tissues, analyzed by GEPIA. c The expression of STK10 between normal tissues and AML based on data from TCGA and GETx. d ROC curve based on STK10 expression in distinguishing normal tissues and AML. e STK10 expression on AML and health donors in GSE9476

Fig. 2

Correlation between STK10 expression and clinical characteristics, based on data from TCGA. a STK10 expression in AML with different ages. b STK10 expression in AML with different cytogenetics risk stratifications. c ROC curve based on STK10 expression in predicting the favorable cytogenetic risk. d STK10 expression in AML with specific cytogenetics

Fig. 3

Prognostic values of STK10 in AML patients, based on TCGA datasets. a Survival curves of OS between the STK10^low and STK10^high groups. Prognostic values of STK10 had been shown in the subgroup of the patients ≤ 60 years (b), the patients > 60 years (c), the patients with favorable&intermediate cytogenetic risks (d) and the patients with poor cytogenetic risks (e)

Fig. 4

Genes associated with STK10 expression. a Volcano plot of different gene expression profiles between STK10^high and STK10^low groups. b Top ten co-expression genes positively and negatively associated with STK10 based on Spearman test’s value. c Overlapping genes that were significantly up-regulated and positively correlated with STK10. d Overlapping genes that were significantly down-regulated and negatively correlated with STK10

Fig. 5

Functional analysis of the overlapping genes in AML. a Enrichment of the overlapping genes in tissues and cells based on PaGenBase. b Analysis of GO and KEGG pathways associated with STK10. c The relevant regulatory genes of the overlapping genes based on the TRRUST

Fig. 6

PPI network of the overlapping genes. a Genes from (Additional file 4) interacted with STK10 directly. b, e The expression of ITGB2 and ITGAM between normal tissues and AML. c, f The co-expression of ITGB2 and ITGAM with STK10. d, g The prognostic value of ITGB2 and ITGAM in AML

Fig. 7

The relationship between STK10 and the immune cell infiltration. a Forrest plot showing the connection between STK10 and the immune cell infiltration levels. b, d, f, h, j, l The levels of various immune cells (|cor|≥ 0.3, p < 0.05) in STK10^low and STK10^high groups. c, e, g, i, k, m The correlation of STK10 expression with the specific immune cell infiltration levels. Cytotoxic cells: including CD8 T cells, Tgd, and NK cells

Fig. 8

The roles of specific immune checkpoints in AML. a, d, g The expression of HLA-E, CD274 and LGALS9 between normal tissue and AML. b, e, h The prognostic value of HLA-E, CD274 and LGALS9 in AML. c, f, i The co-expression of HLA-E, CD274, LGALS9 with STK10