Fig 2: MAPK10 expression correlates with immune activity of the tumor microenvironment in HCC patients. As described in the Materials and Methods section, the immune landscape and immune profiles of HCC patients including immunoreactive intensity of IFN response, inflammation and cytolytic activity were obtained by using ssGSEA (single sample gene set enrichment analysis) in the GSVA (Gene Set Variation Analysis) R package. On the basis of the immune landscape and immune profiles and by using hierarchical clustering, HCC patients were divided into three groups that were corresponding to low, medium, and high immune activity. Then the heat map plotting was used to visualize immune activity of HCC patients and the abundance of immune cells, stromal cells and tumor cells in the liver cancer microenvironment (A). The relationship between immune activity and these parameters was demonstrated by statistical analysis by Wilcoxon Test for immune cells (B) (Wilcoxon Test, P < 0.001), for stromal cells (C) (Wilcoxon Test, P < 0.001), and for tumor cells (D) (Wilcoxon Test, P < 0.001). The predicted cellular compositions of specific immune cells in the HCC microenvironment were obtained by using transcriptome sequencing data of the TCGA database as an input into the CIBERSORTx software (https://cibersortx.stanford.edu/). The statistical analysis by Wilcoxon test uncovered that immune landscape of the TME in the HCC cohort demonstrated significant enrichment of expression signatures representative of CD8+ T cells, activated memory CD4+ T cells, resting dendritic cells, NK cells and the conversion of macrophages from M0 type to M1 type (E) (Wilcoxon test, P < 0.05). In order to analyze the link between MAPK10 expression and immune activity, HCC patients were ranked by MAPK10 expression in a descending order (F), and Wilcoxon test was used to correlate immune activity of HCC patients with the expression of MAPK10 (G) (Wilcoxon Test, P < 0.01). *P<0.05; **P<0.01; ***P<0.001; ns, not significant.

Fig 3: ICAM1 is a putative mediator of MAPK10 effects on immune activity in HCC. As described in the Materials and Methods section, our custom R script was used to measure the fold change of immunity-related genes to identify DIGs with average log2(Fold Change) of at least 0.585 and Q value (also known as adjusted P value) of less than 0.05. Subsequently, the R package of Pathview was used to visualize the KEGG pathway enrichment analysis of these MAPK10-linked DIGs, highlighting ICAM1 as a potential downstream effector of MAPK10 in the TME. The log2 fold changes of included DIGs are color-coded with green, gray, and red colors; the red-colored genes are up-regulated in low-MAPK10 patients compared to high-MAPK10 patients, while green-colored DIGs are down-regulated. (A) The Pearson correlation method was used to correlate MAPK10 expression with ICAM1 expression in HCC patients (B) (R2 = 0.26, P = 2.91 × 10-9). (C) The mRNA level of ICAM1 was compared between MAPK10-overexpressing HepG2-MAPK10 cell line and its corresponding control HepG2-puro cell line by use of the real time qPCR (Welch’s t test, P < 0.0001). (D) The mRNA level of ICAM1 was compared between MAPK10-deficient Huh7-shMAPK10 cell line and its corresponding control Huh7-pLKO cell line by use of the real time qPCR (Welch’s t test, P = 0.0401). In (C, D) one representative result of 3 independent experiments is shown, n=3 in each case. (E) Schematic diagram of the key conclusions of this study assembled in Pathway Builder 2.0 Software and Adobe illustrator demonstrates the putative role of MAPK10 in regulating ICAM1 expression in the TME, facilitating the recruitment of immune cells and suppressing cancer immune escape.

Fig 4: A working model of hyperglycemia in DCM.Hyperglycemia leads to the reduced expression of SIRT1, and the downregulated SIRT1 is responsible for the activation of ERS. Meanwhile, ERS activation stimulates the overexpression of MAPK10 at the mRNA and protein levels, which is a key event in hyperglycemia-induced cardiac remodeling.

Fig 5: The knockdown of MAPK10 alleviates apoptosis and cardiac dysfunction.A, B Expression of TUNEL-positive cardiomyocytes in heart sections (n = 4). Scale bar: 50 µm; C Relative protein levels of MAPK10, and apoptosis-associated protein expression inclusive of cleaved Caspase3 and Bax/Bcl2. ß-Tubulin was used as an internal control (n = 4); D Immunoblotting analysis of pERK12/ERK1/2 and TGF-ß1 protein levels in the hearts and quantification (n = 4).