BTK Has Potential to Be a Prognostic Factor for Lung Adenocarcinoma and an Indicator for Tumor Microenvironment Remodeling: A Study Based on TCGA Data Mining

Abstract

Tumor microenvironment (TME) plays a crucial role in the initiation and progression of lung adenocarcinoma (LUAD); however, there is still a challenge in understanding the dynamic modulation of the immune and stromal components in TME. In the presented study, we applied CIBERSORT and ESTIMATE computational methods to calculate the proportion of tumor-infiltrating immune cell (TIC) and the amount of immune and stromal components in 551 LUAD cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were analyzed by COX regression analysis and protein-protein interaction (PPI) network construction. Then, Bruton tyrosine kinase (BTK) was determined as a predictive factor by the intersection analysis of univariate COX and PPI. Further analysis revealed that BTK expression was negatively correlated with the clinical pathologic characteristics (clinical stage, distant metastasis) and positively correlated with the survival of LUAD patients. Gene Set Enrichment Analysis (GSEA) showed that the genes in the high-expression BTK group were mainly enriched in immune-related activities. In the low-expression BTK group, the genes were enriched in metabolic pathways. CIBERSORT analysis for the proportion of TICs revealed that B-cell memory and CD8+ T cells were positively correlated with BTK expression, suggesting that BTK might be responsible for the preservation of immune-dominant status for TME. Thus, the levels of BTK might be useful for outlining the prognosis of LUAD patients and especially be a clue that the status of TME transition from immune-dominant to metabolic activity, which offered an extra insight for therapeutics of LUAD.

Identification of a Novel Tumor Microenvironment–Associated Eight-Gene Signature for Prognosis Prediction in Lung Adenocarcinoma

“…Considering that previous research has mainly focused on one or two types of immune cells and key genes, it may create a bias against the LUAD microenvironment. Finding multiple genes from the tumor microenvironment to build a gene signature can obtain a better accuracy of the prognostic potential ( Liu et al, 2019a ,b; Zhou et al, 2019 ; Bi et al, 2020 ; Guo et al, 2020 ).…”

Data mining of immune-related prognostic genes in metastatic melanoma microenvironment

“…ATP8B4, a participant in ATP biosynthesis and phospholipid transport via a variety of potential mechanisms, was found to be a risk factor for systemic sclerosis and pulmonary vascular complications [30]. BTK, located in the downstream of signal transduction of B-cell antigen receptor, might be a useful biomarker to predict the prognosis of lung cancer patients [31]. FCGR1B was overexpressed in renal cell carcinoma, predicting poor patient prognosis [32].…”

SPP1 Might Be a Novel Prognostic Biomarker for Patients With Malignancy: a Meta-analysis and Sequential Verification Based on Bioinformatic Analysis

“…The ESTIMATE algorithm in the estimate package of R software was used to estimate the ratio of the immune-stromal component in TIME, which was shown in the form of three kinds of scores: ImmuneScore, StromalScore and ESTIMATEScore. It's related to the ratio of immune, stromal, and the sum of both, which means the higher the respective score, the larger the ratio of the corresponding component in TIME [22] . We analysed the correlation between SPP1 expression and the three kinds of scores.…”