Clinicopathological and Prognostic Significance of Expression of B-Cell-Specific Moloney Murine Leukemia Virus Insertion Site 1 (BMI-1) Gene and Protein in Gastrointestinal Stromal Tumors

MicroRNA-128 acts as a suppressor in the progression of gastrointestinal stromal tumor by targeting B-lymphoma Mo-MLV insertion region 1

INTRODUCTION

The critical role of microRNA-128 (miR-128) in gastrointestinal-related diseases has been documented. In the current study, we tried to clarify the specific role miR-128 in gastrointestinal stromal tumor (GIST) and the underlying mechanism.

METHODS

Differentially expressed genes in GIST were identified following bioinformatics analysis. Then, expression patterns of miR-128 and B-lymphoma Mo-MLV insertion region 1 (BMI-1) in clinical tissue samples and cell lines were characterized, followed by validation of their correlation. GIST-T1 cells were selected and transfected with different mimic, inhibitor, or siRNA plasmids, after which the biological functions were assayed.

RESULTS

We identified low miR-128 and high BMI-1 expression in GIST tissues of 78 patients and 4 GIST cell lines. Ectopic expression of miR-128 or silencing of BMI-1 suppressed the malignant potentials of GIST-T1 cells. As a target of miR-128, BMI-1 re-expression could partly counteract the suppressive effect of miR-128 on the malignancy of GIST-T1 cells.

CONCLUSION

Our study provided evidence that miR-128-mediated silencing of BMI-1 could prevent malignant progression of GIST, highlighting a promising anti-tumor target for combating GIST.

Construction and validation of a prognostic model for gastrointestinal stromal tumors based on copy number alterations and clinicopathological characteristics

Background

The increasing incidence of gastrointestinal stromal tumors (GISTs) has led to the discovery of more novel prognostic markers. We aim to establish an unsupervised prognostic model for the early prediction of the prognosis of future patients with GISTs and to guide clinical treatment.

Methods

We downloaded the GISTs dataset through the cBioPortal website. We extracted clinical information and pathological information, including the microsatellite instability (MSI) score, fraction genome altered (FGA) score, tumor mutational burden (TMB), and copy number alteration burden (CNAB), of patients with GISTs. For survival analysis, we used univariate Cox regression to analyze the contribution of each factor to prognosis and calculated a hazard ratio (HR) and 95% confidence interval (95% CI). For clustering groupings, we used the t-distributed stochastic neighbor embedding (t-SNE) method for data dimensionality reduction. Subsequently, the k-means method was used for clustering analysis.

Results

A total of 395 individuals were included in the study. After dimensionality reduction with t-SNE, all patients were divided into two subgroups. Cluster 1 had worse OS than cluster 2 (HR=3.45, 95% CI, 2.22-5.56, P<0.001). The median MSI score of cluster 1 was 1.09, and the median MSI score of cluster 2 was 0.24, which were significantly different (P<0.001). The FGA score of cluster 1 was 0.28, which was higher than that of cluster 2 (P<0.001). In addition, both the TMB and CNAB of cluster 1 were higher than those of cluster 2, and the P values were less than 0.001.

Conclusion

Based on the CNA of GISTs, patients can be divided into high-risk and low-risk groups. The high-risk group had a higher MSI score, FGA score, TMB and CNAB than the low-risk group. In addition, we established a prognostic nomogram based on the CNA and clinicopathological characteristics of patients with GISTs.