3.1. The mRNA expression level of TPM4 in human cancers
To compare the expression of the tropomyosin family members including TPM1, TPM2, TPM3 and TPM4 in human cancers, we used the Oncomine database to analyze the mRNA levels in normal and tumor tissues. Specifically, this analysis indicated that TPM4 expression was higher in pancreatic cancer (Fig. 1a). Furthermore, we analyzed TPM4 expression in the 31 types of tissues through the GTEx dataset, which revealed TPM4 was generally lowly expressed in the pancreas tissues (Fig. S1a). Meanwhile, the expression of TPM4 was analyzed using the data of tumor cell lines downloaded from the CCLE database. The results indicated that TPM4 was expressed in various tumor cell lines (Fig. S1b). Next, we used the TCGA database to evaluate how TPM4 expression in multiple types of cancers (Fig. S1c). Considering pancreatic cancer with limited adjacent normal tissues in TCGA database, we compared the expression level of TPM4 gene in the integrated datasets combined TCGA with GTEx database. The analysis identified TPM4 was significantly upregulated in tumor tissues with the corresponding normal tissues as controls (Fig. 1b, c). Consistent with it, the upregulated TPM4 in PC tumor tissues was shown in the GSE15471, GSE16515, GSE23397 and GSE62165 cohorts (Fig. 2a-d).
We further evaluated the expression of TPM4 in different T-staging patients with PC, in which TPM4 was higher expressed in the T3/T4 than that of T1/T2 (Fig. 1d, P < 0.05). Besides, we found that TPM4 was also correlated with the pathological stages of patients with PC (Fig. 1e, P < 0.05). Sankey diagram could be used to show the distribution trend of the high and low expression of TPM4 gene in different ages, stages and other clinical features as well as the survival of patients with PC (Fig. 1f). In the end, we compared the protein level of TPM4 using the IHC staining by means of the THPA database. The protein expression level of TPM4 in PC tumor tissues was higher than that in normal tissues (Fig. 1g). These findings suggested that the upregulation of TPM4 may predict an advanced malignancy of PC.
3.2. Prognostic value of TPM4 in PC
To investigate the correlation of TPM4 expression with the prognosis of patients with pancreatic cancer, we assessed the distribution of TPM4 expression level and association with the survival for the patients using TCGA database. Notably, TPM4 expression was significantly correlated with patients’ OS in PC. The cancer cases were divided into high- and low-expression groups by the median value of TPM4 expression. Comprehensive considering the risk curve and the survival status, we found that the fatality rate in the TPM4 high-expression group was significantly higher than that in the low-expression group (Fig. 3a). Specifically, Kaplan-Meier survival analysis indicated that high TPM4 expression was significantly linked with poor prognosis of patients with PC (HR = 1.695, 95% CI = 1.114–2.581, P = 0.0138) (Fig. 3b). To observe the predictive value of TPM4 mRNA levels for prognosis, we evaluated the expression of TPM4 to distinguish TPM4high and TPM4low patients by the receiver operating characteristic (ROC) curve. Evaluating the area under the curve (AUC) under the ROC curve was applied to predict the 1, 3, 5-year risk of PC patients (1-year, AUC = 0.605; 3-year, AUC = 0.669; 5-year, AUC = 0.794) (Fig. 3c). In addition, we analyzed the relationship between TPM4 expression and patients’ DSS in PC. The results suggested that TPM4 expression impacted the survival status (Fig. 4a), DSS (HR = 1.801, 95% CI = 1.116–2.908, P = 0.0161) (Fig. 4b), and performed predictive effect on the risk of PC patients (1-year, AUC = 0.617; 3-year, AUC = 0.701; 5-year, AUC = 0.811) (Fig. 4c). Subsequently, the relationship between TPM4 expression and DFS (Fig. S2a-c) and PFS (Fig. S3a-c) were investigated, in which we found the same influence of TPM4 on poor prognosis. In conclusion, these consistent results from OS, DSS, DFS, and PFS analysis strongly revealed that TPM4 gene is significantly correlated with the prognosis of patients with PC.
3.3. Correlation of TPM4 expression with immune characteristics
TILs are an independent predictor in cancers [23, 24]. The association between TPM4 gene level and tumor-infiltrating immune cells across diverse cancer types based on the TIMER database, in which we found that TPM4 impacted tumor-infiltrating immune cells in PC. We first analyzed the percentage abundance of different types of tumor infiltrating immune cells in PAAD (Fig. 5a). Furthermore, we investigated the correlation of TPM4 expression with the tumor-infiltrating immune cells by establishing Immune cells score heatmap, which indicated that high TPM4 expression was significantly linked with immune infiltrates in PC (Fig. 5b). Specifically, as shown in Fig. 5c, TPM4 expression was negatively correlated with the purity of tumor (r = −0.174, P = 2.25e−02). In addition, TPM4 expression was appreciably positively correlated with the infiltration of several immune cell types, including CD8+ T cells (r = 0.411, P = 2.36e−08), B cells (r = 0.214, P = 5.00e−03), macrophages (r = 0.455, P = 4.10e−10), neutrophils (r = 0.469, P = 9.70e−11), and myeloid dendritic cells (r = 0.515, P = 6.08e−13), while there was no marked infiltration with CD4+ T cells (r = -0.064, P = 4.09e−01) in PAAD. The Immune Score, Stromal Score and ESTIMATE Score were used to identify and quantify the immune and matrix components in PAAD. Results indicated that TPM4 expression was positively correlated with the Immune Score (r = 0.188, P = 0.0122), Stromal Score (r = 0.46, P = 1.51e−10) and ESTIMATE Score (r = 0.33, P = 7.96e−06) in PAAD (Fig. 5d). Next, we examined the relations between TPM4 expression and abundance of 28 TILs using the TISIDB database. As shown in Fig. 6a, the relationship between TPM4 expression and TILs in different types of cancer was exhibited. Specifically, in PAAD, TPM4 expression was significantly correlated with multiple types of TILs (Fig. 6b–r).
Immune checkpoint inhibitors (ICIs), a significantly novel strategy for tumor immunotherapy, has already gradually improved the outcomes of patients with many types of cancers [25, 26]. Subsequently, the correlation between the expression of TPM4 and that of over 40 common immune control genes was analyzed. Interestingly, in PAAD, TPM4 expression was associated with nearly 18 immune checkpoint markers, including CD274, CD276, CD44, CD80 and so on (Fig. 7a). It is important to emphasize that CD274 (PD-L1), a biomarker of response to immune-checkpoint inhibitors , performed significantly correlated with TPM4 expression in PAAD. Accordingly, these results strongly demonstrated that TPM4 gene may play a crucial role in tumor immunity. To further elucidate the association between TPM4 expression and immune cell migration, we comprehensively analyzed the connection with chemokines and chemokine receptors (Fig. 7b-f). The results have proven that TPM4 expression was positively correlated with immune cells-associated chemokines and chemokine receptors, such as CCL7 (r = 0.348, P = 2.11e−06), CCL13 (r = 0.312, P = 2.32e−05), CCL18 (r = 0.312, P = 2.31e−05), CXCL5 (r = 0.336, P = 4.78e−06), and CXCL8 (r = 0.398, P = 4.57e−08). Since those chemokines and chemokine receptors appeared to be upregulated with TPM4 expression level increased, high TPM4 expression may involve in the migration of immune cells to tumor microenvironment.
3.4. Functional inference of TPM4 in PAAD
Differentially expressed genes (DEGs), a popular method to explore the potential biological role by enrichment analysis, are applied for the study in disease. To further confirm the underlying biological function of TPM4 gene in PAAD, the transcriptome data from TCGA was analyzed by functional enrichment. According to the expression level of TPM4, the samples of pancreatic cancer were divided into two groups, including TPM4high and TPM4low. Next, we compared DEGs analysis between TPM4high group and TPM4low group with the criteria set of |log2FC|>1, adjusted P <0.05. As shown in the volcano plot, 381 genes were differentially expressed including 367 upregulated genes and 14 downregulated genes (Fig. 8a). Corresponding hierarchical clustering analysis of these DEGs was displayed by the heatmap (Fig. 8b). To further determine the potential function of TPM4, we attempted to perform a series of enrichment analyses, including KEGG and GO. The results of KEGG pathway enrichment analysis of upregulated DEGs were mainly involved in small cell lung cancer, proteoglycans in cancer, protein digestion and absorption, PI3K−Akt signaling pathway, hypertrophic cardiomyopathy (HCM), human papillomavirus infection, focal adhesion, and ECM−receptor interaction (Fig. 8c). Moreover, we performed GO enrichment analysis of upregulated DEGs, which indicated that most of these genes were linked to the events such as regulation of cell−substrate adhesion, extracellular structure organization, extracellular matrix organization, connective tissue development, collagen metabolic process, collagen fibril organization, cell−substrate adhesion, and cell−matrix adhesion (Fig. 8d). Owing to a few number of downregulated genes, there seemed very little point in continuing with the enrichment analysis of those downregulated DEGs. The GO and KEGG analysis demonstrated that TPM4 might regulate the process of cell adhesion and metabolic process, which could provide a novel direction to the research on tumor cell migration.
To further investigate the internal mechanism of the TPM4 gene in tumorigenesis, the PPI network analysis was performed by utilizing the STRING database. Fig. 9a showed the visualizing interaction network of 50 TPM4-binding proteins with the experimental evidence identification. In addition, through comparing TPM4 expression-correlated DEGs with TPM4-interacted genes, we screened out the common members such as ACTA2, ACTG2, and TNNT1 (Fig. 9b). The detailed gene information mentioned has been provided in the Supporting Information materials. Moreover, the TPM4 expression level was remarkably positively correlated with that of ACTA2 (r = 0.692, P = 7.13e−27), ACTG2 (r = 0.487, P = 4.71e−12), and TNNT1 (r = 0.335, P = 4.63e−06) (Fig. 9c).
3.5. Correlation of TPM4 expression with MMR gene mutation levels in human Pan-Cancer.
MMRs is involve in the DNA damage repair. To investigate the potential role of TPM4 in tumorigenesis, the correlation between TPM4 expression and MMR gene mutation levels was analyzed. The landscape of correlation between TPM4 expression and 5 MMR genes, including MLH1, MSH2, MSH6, PMS2, and EPCAM in human cancers was obtained (Fig. S4). Notably, results indicated a positive correlation between TPM4 expression and these MMR genes in PAAD.