Novel cancer gene discovery using a forward genetic screen in RCAS-PDGFB-driven gliomas

Common and novel haplotype structures between different types of cancer

BACKGROUND

Background: Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with cancer risk. GWAS data are important for cancer prevention and understanding the underlying mechanisms of cancer.

AIMS

This study aimed to investigate the genetic association between different types of cancer using GWAS data and a bioinformatics approach.

METHODS AND RESULTS

The significant GWAS variants associated with more than one cancer type were identified. Common linkage disequilibrium (LD) variants between different types of cancer were identified by 1000 genomes phase 3 LD data. Haplotype blocks were identified by analyzing 1000 Genomes phase 3 genotyping data in the GWAS populations. Subsequent analyses included functional SNP analyses and TCGA gene expression. The results associated with significant GWAS variants (P<5E-8) showed the following haplotype associations in European population: GT rs4808075-rs8170 haplotype on BABAM1 with breast and ovarian cancers, GC rs16857609-rs11693806 haplotype on DIRC3 with breast and thyroid cancers, GCG rs380286-rs401681-rs31487 haplotype on CLPTM1L with skin and lung cancers, GGG rs4430796-rs11651052-rs11263763 haplotype on HNF1B with prostate and endometrial cancers, and GT rs10505477-rs6983267 haplotype on CASC8 associated with colorectal and prostate cancers. All these genes had significantly different expressions in tumor tissues (P<1E-3). In addition, the rs11693806 variant is located in the hsa-miR-873-5p binding site and has an enhancing effect on the hsa-miR-873-5p:DIRC3 interaction.

CONCLUSION

These novel haplotype structures and miRNA:lncRNA interactions are important for understanding the common genetic link between cancers. These results can potentially be used in genetic panels.

The TGF-β Family in Glioblastoma

Members of the transforming growth factor β (TGF-β) family have been implicated in the biology of several cancers. In this review, we focus on the role of TGFβ and bone morphogenetic protein (BMP) signaling in glioblastoma. Glioblastoma (GBM) is the most common malignant brain tumor in adults; it presents at a median age of 64 years, but can occur at any age, including childhood. Unfortunately, there is no cure, and even patients undergoing current treatments (surgical resection, radiotherapy, and chemotherapy) have a median survival of 15 months. There is a great need to identify new therapeutic targets to improve the treatment of GBM patients. TGF-βs signaling promotes tumorigenesis in glioblastoma, while BMPs suppress tumorigenic potential by inducing tumor cell differentiation. In this review, we discuss the actions of TGF-βs and BMPs on cancer cells as well as in the tumor microenvironment, and their use in potential therapeutic intervention.

Multiparametric Longitudinal Profiling of RCAS-tva-Induced PDGFB-Driven Experimental Glioma

Glioblastomas are incurable primary brain tumors harboring a heterogeneous landscape of genetic and metabolic alterations. Longitudinal imaging by MRI and [18F]FET-PET measurements enable us to visualize the features of evolving tumors in a dynamic manner. Yet, close-meshed longitudinal imaging time points for characterizing temporal and spatial metabolic alterations during tumor evolution in patients is not feasible because patients usually present with already established tumors. The replication-competent avian sarcoma-leukosis virus (RCAS)/tumor virus receptor-A (tva) system is a powerful preclinical glioma model offering a high grade of spatial and temporal control of somatic gene delivery in vivo. Consequently, here, we aimed at using MRI and [18F]FET-PET to identify typical neuroimaging characteristics of the platelet-derived growth factor B (PDGFB)-driven glioma model using the RCAS-tva system. Our study showed that this preclinical glioma model displays MRI and [18F]FET-PET features that highly resemble the corresponding established human disease, emphasizing the high translational relevance of this experimental model. Furthermore, our investigations unravel exponential growth dynamics and a model-specific tumor microenvironment, as assessed by histology and immunochemistry. Taken together, our study provides further insights into this preclinical model and advocates for the imaging-stratified design of preclinical therapeutic interventions.