Association of genetic variants in the retinoblastoma binding protein 6 gene with the risk of glioma: a case-control study in a Chinese Han population

New progress in the study of germline susceptibility genes of myeloid neoplasms

In 2016, the World Health Organization incorporated ‘myeloid neoplasms with germline predisposition’ into its classification of tumors of hematopoietic and lymphoid tissues, revealing the important role of germline mutations in certain myeloid neoplasms, particularly myelodysplastic syndrome and acute myeloid leukemia. The awareness of germline susceptibility has increased, and some patients with myeloid neoplasms present with a preexisting disorder or organ dysfunction. In such cases, mutations in genes including CCAAT enhancer binding protein α (CEBPA), DEAD (Asp-Glu-Ala-Asp) box polypeptide 41 (DDX41), RUNX family transcription factor 1 (RUNX1), GATA binding protein 2 (GATA2), Janus kinase 2 (JAK2) and ETS variant transcription factor 6 (ETV6) have been recognized. Moreover, with the application of advanced technologies and reports of more cases, additional germline mutations associated with myeloid neoplasms have been identified and provide insights into the formation, prognosis and therapy of myeloid neoplasms. The present review discusses the well-known CEBPA, DDX41, RUNX1, GATA2, JAK2 and ETV6 germline mutations, and other mutations including those of lymphocyte adapter protein/SH2B adapter protein 3 and duplications of autophagy related 2B, GSK3B interacting protein αnd RB binding protein 6, ubiquitin ligase, that remain to be confirmed or explored. Recommendations for the management of diseases associated with germline mutations are also provided.

RBBP6 Is Abundantly Expressed in Human Cervical Carcinoma and May Be Implicated in Its Malignant Progression

RBBP6 is a novel gene encoding splicing-associated proteins. There are 3 protein isoforms (isoforms 1-3). RBBP6 isoforms 1 has been shown to interact with both p53 and Rb. It also plays a role in the induction of apoptosis and the regulation of the cell cycle. The expression of RBBP6 has been documented in several cancers but RBBP6 expression in cervical cancer has not been well studied. The aim of this study was to establish expression levels and tissue distribution of the RBBP6 gene products at both protein and messenger RNA (mRNA) levels in cervical cancer by immunocytochemistry and in situ hybridization (ISH). A link between RBBP6 expression, apoptosis, and cervical cancer progression was also investigated. RBBP6 mRNA was expressed in the nuclei and cytoplasm of normal and tumour cervical epithelium. In general, expression was high in the cytoplasm and nuclei of moderately differentiated and invasive carcinoma. Immunolabelling results were confirmed by image analysis and ISH experiments. Apoptosis assays using TUNEL correlated with the expression of the RBBP6 gene in all examined cases. This is the first report on the abundant expression of RBBP6 in cervical cancer and its involvement in the malignant progression of cervical cancer. Because of the high expression and corresponding pro-apoptotic activity observed in cervical cancer cells in this study, we suggest that RBBP6 is involved in the malignant progression of cervical cancer. RBBP6 proteins can therefore be targeted for therapeutic interventions against cervical cancer.

Development of risk prediction models for glioma based on genome-wide association study findings and comprehensive evaluation of predictive performances

Over 14 common single nucleotide polymorphisms (SNP) have been consistently identified from genome-wide association studies (GWAS) as associated with glioma risk in European background. The extent to which and how these genetic variants can improve the prediction of glioma risk has was not been investigated. In this study, we employed three independent case-control datasets in Chinese populations, tested GWAS signals in dataset1, validated association results in dataset2, developed prediction models in dataset2 for the consistently replicated SNPs, refined the consistently replicated SNPs in dataset3 and developed tailored models for Chinese populations. For model construction, we aggregated the contribution of multiple SNPs into genetic risk scores (count GRS and weighed GRS) or predicted risks from logistic regression analyses (PRFLR).

In dataset2, the area under receiver operating characteristic curves (AUC) of the 5 consistently replicated SNPs by PRFLR(SNPs) was 0.615, higher than those of all GRSs(ranging from 0.607 to 0.611, all P>0.05). The AUC of genetic profile significantly exceeded that of family history (fmc) alone (AUC=0.535, all P<0.001). The best model in our study comprised “PRURA +fmc” (AUC=0.646) in dataset3. Further model assessment analyses provided additional evidence.

This study indicates that genetic markers have potential value for risk prediction of glioma.