CAMTA1, a novel antitumor gene, regulates proliferation and the cell cycle in glioma by inhibiting AKT phosphorylation

Highlights

• CAMTA1 expression is downregulated within glioma.

• CAMTA1 expression is negatively correlated with ITGA5/ITGB1.

• CAMTA1 regulates glioma cell proliferation, migration, invasion and cell cycle via ITGA5/ITGB1 and AKT signaling.

Abstract

Identifying biomarkers for the early diagnosis of glioma and elucidating the molecular mechanisms underlying the development of this cancer are of considerable clinical importance. Recently, studies performing microarray profiling of genes to identify distinct gene signatures reported specific subtypes with predictive and prognostic relevance. Thus, we performed deep sequencing on a total of 26 glioma tissue samples to identify the frequently mutated of oncogenes and tumor suppressors in gliomas. A total of 2306 single-nucleotide polymorphisms (SNPs) and 2010 insertion and deletion sites (indels) were found by aligning sequencing information from 26 glioma samples with sequences from the normal human gene database (GRCh37/hg19). GSEA results suggest that an underexpressed gene, calmodulin binding transcription activator 1 (CAMTA1), participates in the cell proliferation and cell cycle regulation of glioma cells. Moreover, overexpression of CAMTA1 in glioma cells notably inhibited cell growth, migration, invasion and cell cycle and enhanced temozolomide (TMZ)-induced cell apoptosis in glioma cells, while CAMTA1 overexpression decreased the ITGA5, ITGB1, p-AKT, p-FAK, and Myc protein levels, suggesting that the signaling pathways of these proteins might be involved in the cellular functions of CAMTA1 in glioma. Moreover, overexpression of CAMTA1 attenuated the growth and tumorigenesis of glioma in vivo. In summary, we identified high-frequency mutant genes in glioma and provided an experimental basis for a novel mechanism by which CAMTA1 may serve as a tumor suppressor in glioma.

Introduction

Gliomas are brain tumors generated by glial cells and are the most commonly diagnosed primary tumors of the central nervous system (accounting for approximately 30% of these tumors). Gliomas have a high mortality rate, which is close to 80% within one year after diagnosis. Although the metastatic potential of gliomas is limited, one of their features is a higher death rate, which is primarily attributable to high rates of local infiltration and angiogenesis with immunosuppression. In addition, delayed diagnosis of gliomas leads to advanced/graded tumors and poor prognosis, while high-grade gliomas are often associated with extensive blood vessel invasion, massive loss of oxygen and neck inflammation [1]. Histologically, gliomas can be divided into glioblastomas, astrocytomas, and oligodendrogliomas. Moreover, the World Health Organization (WHO) introduced a four-tiered grading system in 2002 that identified four classes of malignancies: low-grade (WHO grade I–II), anaplastic (grade III) and glioblastoma multiform (grade IV) [2]. The most recent WHO Classification of Tumors of the Central Nervous System was proposed in 2016; this classification not only integrated the morphological characteristics, growing patterns and molecular features of tumor cells [3] but also defined the degree of malignancy with sufficient prognosis to play a critical role in determining the clinical settings and treatment programs [4]. Recently, studies performing on gene expression profiling to identify distinct gene signatures reported specific subtypes with predictive and prognostic relevance [[5], [6], [7], [8]]. However, due to the risks of radiation therapy and the limited effectiveness of surgery, there is an urgent need for new options for the treatment of glioma. Identifying early diagnostic biomarkers of glioma and elucidating the molecular mechanisms underlying the development of this cancer are of considerable clinical importance.

To explore the mechanisms underlying tumor initiation, progression and metastasis and to identify novel diagnostic biomarkers and new targeted therapies for glioma, in the past several years, studies have focused on gene alterations related to glioma and the signaling pathway deregulation. Recently, The Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov) analyses of gliomas have utilized a variety of technology platforms, such as mutation arrays, copy number arrays, expression arrays and methylation arrays [5,6,9]. Expression array date have revealed that molecular subtypes are related to grade and outcome, suggesting that expression profiles are more predictive of outcome, than are histological subtypes [5,6,9]. For example, CD44 is overexpressed in glioma and is involved in many important cell functions that contribute to tumorigenesis [10,11]. Cyclin dependent kinase 1 (CDK1) and cadherin 1 (CDH1) play important roles in the protein-protein interaction (PPI) network according to Gene Ontology functional and KEGG pathway enrichment analyses based on the GSE31262 dataset [12]. Many other glioma-related genes such as FN1 [13], TGF-β [14], SPP1 and EGFR [15] have also been studied and their potential applications as targets for the diagnosis and therapy of glioma have also been evaluated.

There is increasing evidence that the risk and prognosis of gliomas may be influenced by the genetic backgrounds of patients. As single nucleotide polymorphisms (SNPs) are the most commonly seen genetic variation, they may be useful alternative biomarkers of patients' genetic backgrounds and may be employed to predict treatment response and prognosis. Barbashina et al. reported that the loss of combined 1p/19q was strongly correlated with the histology of typical oligodendroglioma and determined that a small segment of 1p36 in calmodulin binding transcription activator 1 (CAMTA1) was deleted within all oligodendroglial tumors with loss of heterozygosity of 1p, which could overlap with the minimal deleted region of the neuroblastoma 1p36 [16]. More importantly, CAMTA1 is a novel tumor suppressor in glioblastoma, and colony formation is significantly decreased by the overexpression of CAMTA1. Consistent with the finding, CAMTA1 expression correlates with glioblastoma patient survival [17]. Nevertheless, the biological function CAMTA1 in glioma still unclear and need further clarification.

In the present study, we performed deep sequencing on a total of 26 glioma tissue samples to identify the frequently occurring mutation of oncogenes and tumor suppressors in gliomas. The SNPs and indels that were detected were analyzed and compared to the normal human genetic database (hg19) to identify the high-frequency mutant genes. Based on the essential role played by CAMTA1 in glioma, we subsequently analyzed the correlation between the gene polymorphism and the expression of CAMTA1. The expression of CAMTA1 in glioma was analyzed based on the Chinese Glioma Genome Atlas (CGGA) and TCGA and examined in tissue samples using real-time PCR and immunoblotting. Next, gene set enrichment analysis (GSEA) was performed to identify signaling pathways related to CAMTA1. The correlation between the expression of CAMTA1 and related factors and the cellular function of CAMTA1 in glioma cells and relevant pathways were examined. In summary, we identified frequently occurring mutant genes in glioma and provided an experimental basis for a novel mechanism by which CAMTA1 may serve as a tumor suppressor in glioma.