Bioinformatics analysis of BTK expression in lung adenocarcinoma: implications for immune infiltration, prognostic biomarkers, and therapeutic targeting

Abstract

In recent years, as more and more lung-cancer patients have been treated with immunotherapeutic agents, their survival has been prolonged compared to before. It is well known that BTK (Bruton's tyrosine kinase) is predominantly found in cells of the hematopoietic system. However, there is a distinct lack of literature on BTK expression in lung adenocarcinoma (LUAD) patients and its effect on the immune microenvironment. Consequently, the main goal of this investigation was to analyze how BTK expression in lung adenocarcinoma affects its progression, along with its prognostic significance, through the utilization of bioinformatics online resources and publicly available databases. Data on the sequencing results and clinical records of lung adenocarcinoma patients were gathered from The Cancer Genome Atlas (TCGA) database. Based on the expression level of BKT, TCGA categorized lung adenocarcinoma patients into BTK high-expression and low-expression groups. We investigated the effects of BKT on clinicopathologic, genomic, and immunologic characteristics of lung adenocarcinoma patients. We analyzed BTK mRNA expression in tumors and normal tissues using two key resources: Tumor Immuno Estimation Resource 2.0 (TIMER 2.0) and Gene Expression Profiling Interactive Analysis 2 (GEPIA 2). We analyzed the prognosis of the patients using GEPIA2 and validated the results using univariate and multivariate analyses. In addition, we assessed BTK protein expression by Human Protein Atlas (HPA). We sought to elucidate the clinical prognostic significance of BTK in The TCGA using the online tool GEPIA 2. Furthermore, to clarify the biologic roles and pathways linked to BTK, we conducted a genomic enrichment analysis of the information. To predict the proportion of various immune cell infiltrations in the immune microenvironment of lung adenocarcinoma patients diagnosed in the TCGA database, we performed an analysis using the TIMER online tool. Using TIMER and CIBERSORT, the correlation between genes co-expressed with BTK and the corresponding tumor-infiltrating immune cells was explored; finally, the relationship between BTK expression and immune infiltration and immune checkpoints in the TMB group and the high and low groups was analyzed by R language analysis using the TCGA database. The expression of BTK provides some hints about the prognosis of the patients. The high expression of BTK is involved in immune response regulation signaling pathways, leukocyte-mediated immunity, leukocyte intercellular adhesion, graft rejection, and complement. Analysis of the GEPIA 2 database showed that BTK was co-expressed with the genes FGD2, SASH3, NCKAP1L, CD53, ARHGAP30 and LPXN. Increased expression of the above-mentioned genes resulted in increased proportions of CD8 + T cells, memory CD4 + T cells, B cells, macrophages, and dendritic cells, and decreased proportions of Treg cells and TH2 cells. In addition, our study revealed a strong positive correlation between various key immune checkpoints (e.g., PDCD1, CD274, PDCD1LG2, CTLA4, HAVCR2, LAG3, TIGIT, and SIGLEC15) and BTK expression. In conclusion, increased BTK expression in lung adenocarcinoma is closely associated with prolonged survival of lung-cancer patients. Moreover, the genes classified under the BTK high-expression group exhibit significant enrichment in immune-related pathways, suggesting a potential impact on the tumor microenvironment. We investigated the potential of BTK as a tumor suppressor gene in predicting prolonged patient survival. In addition, we further investigated the possibility that BTK further affects the immunotherapeutic response of patients by influencing the microenvironment of tumor immune infiltration, but the relevant mechanisms remain to be further studied.

Keywords: BTK expression; Bioinformatics; Immune microenvironment; Immunotherapy; Lung adenocarcinoma (LUAD); Prognostic marker.

Fig. 1

A The expression level of BTK in different tumor types from the TCGA database was detected by TIMER. B The expression difference between tumor tissue and normal tissue in the TCGA database was analyzed. C Paired differentiation analysis for expression of BTK in the tumor and normal tissue deriving from the same one patient. D GEPIA 2 database predicted the expression of BTK in lung adenocarcinoma tissues, with red representing tumor samples and gray representing normal samples

Fig. 2

The correlation of BTK expression with clinicopathological staging characteristics according to Table 1

Fig. 3

The relationship between BTK expression and prognosis of LUAD patients was studied using GEPIA 2

Fig. 4

Immunohistochemical staining results of BTK in lung adenocarcinoma tissues were retrieved using the HAP database. Neighboring cancerous tissues on the right and cancerous tissues on the left

Fig. 5

Univariate and multivariate analysis of LUAD patients was performed using the TCGA database

Fig. 6

LUAD TMB summary diagram

Fig. 7

The samples were categorized into two groups, high and low, based on the median expression of BTK, and plotted volcano

Fig. 8

Based on BTK, the differential genes were categorized into high and low groups for GO and KEGG analysis

Fig. 9

Differential genes were categorized into high and low groups based on BTK for GSEA analysis

Fig. 10

The correlation between BTK and co-expressed genes was analyzed using GEPIA2

Fig. 11

Using the TCGA database, the samples were categorized into high and low groups based on the median BTK and analyzed for ESTIMATEScore, ImmuneScore, and StromalScore

Fig. 12

Twenty-two immune cell types were analyzed using CIBERSORT

Fig. 13

Correlation analysis between BTK and co-expressed genes and immune cells was validated using the TIMER database (a)

Fig. 14

Correlation analysis between BTK and co-expressed genes and immune cells was validated using the TIMER database (b)

Fig. 15

Correlation analysis of BTK and co-expressed genes with 22 CIBERSORT immune cells

Fig. 16

Effect of BTK expression on immune checkpoint expression

Fig. 17

The oncoplot of TMB in LUAD