mRNA-lncRNA gene expression signature in HPV-associated neoplasia and cervical cancer.

Cervical cancer is one of the most frequent cancers in women and is associated with human papillomavirus (HPV) in 70 % of cases. Cervical cancer occurs because of progression of low-differentiated cervical intraepithelial neoplasia through grade 2 and 3 lesions. Along with the protein-coding genes, long noncoding RNAs (lncRNAs) play an important role in the development of malignant cell transformation. Although human papillomavirus is widespread, there is currently no well-characterized transcriptomic signature to predict whether this tumor will develop in the presence of HPV-associated neoplastic changes in the cervical epithelium. Changes in gene activity in tumors reflect the biological diversity of cellular phenotype and physiological functions and can be an important diagnostic marker. We performed comparative transcriptome analysis using open RNA sequencing data to assess differentially expressed genes between normal tissue, neoplastic epithelium, and cervical cancer. Raw data were preprocessed using the Galaxy platform. Batch effect correction, identification of differentially expressed genes, and gene set enrichment analysis (GSEA) were performed using R programming language packages. Subcellular localization of lncRNA was analyzed using Locate-R and iLoc-LncRNA 2.0 web services. 1,572 differentially expressed genes (DEGs) were recorded in the "cancer vs. control" comparison, and 1,260 DEGs were recorded in the "cancer vs. neoplasia" comparison. Only two genes were observed to be differentially expressed in the "neoplasia vs. control" comparison. The search for common genes among the most strongly differentially expressed genes among all comparison groups resulted in the identification of an expression signature consisting of the CCL20, CDKN2A, CTCFL, piR-55219, TRH, SLC27A6 and EPHA5 genes. The transcription level of the CCL20 and CDKN2A genes becomes increased at the stage of neoplastic epithelial changes and stays so in cervical cancer. Validation on an independent microarray dataset showed that the differential expression patterns of the CDKN2A and SLC27A6 genes were conserved in the respective gene expression comparisons between groups.

mRNA-lncRNA gene expression signature for predicting pediatric AML relapse.

Children with acute myeloid leukemia (AML) face a relapse of the disease in 30% of all cases. AML relapse is difficult to predict, and existing risk scales are often ineffective. Using data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET-AML) project, we defined an expression signature based on matrix RNAs (mRNAs) and long non-coding RNAs (lncRNAs) that could predict relapse in pediatric AML patients. We used a comprehensive bioinformatics analysis that included the identification of functionally significant differentially expressed genes in AML relapse, several rounds of association with relapse-free survival (RFS) mRNAs and lncRNAs selection, and evaluation of the obtained expression signatures to predict recurrence at the primary tumor level. Two mRNAs (ENSG00000149289.11 (ZC3H12C) and ENSG00000075213.11 (SEMA3A)) and one lncRNA (ENSG00000287569.1) were associated with a decreased RFS. Models including changes in the expression of ZC3H12C and ENSG00000287569.1, as well as all three markers, demonstrated very good quality and could predict the recurrence of pediatric AML.

Prognostic value of ASXL1 mutations in acute myeloid leukemia: A meta-analysis.

OBJECTIVES: Mutations in ASXL1 are being investigated for prognostic value in AML, but the relationship between these mutations and prognosis for patients with AML remains unclear. Therefore, we are conducting a meta-analysis to estimate the effect of mutations in ASXL1 to determine their prognostic significance. METHODS: Eight studies were selected by searching PubMed, Embase, Web of Science, ClinicalTrials, and the Cochrane Library databases. Hazard ratios (HRs) and their 95% confidence intervals (CIs) for overall survival (OS) and event-free survival (EFS) were pooled to assess the effect of ASXL1 mutations on the prognosis in AML patients. RESULTS: A total of 8 studies with 4143 patients were included in this meta-analysis. The pooled HRs for OS and EFS revealed that AML patients with ASXL1 mutations had a significantly poor prognosis as compared with those without mutations (OS: HR = 1.59, 95% CI = 1.34-1.88, p < 0.00001; EFS: HR = 1.63, 95% CI = 1.27-2.08, p < 0.0001). Mutations in ASXL1 showed no strong relationship with other AML-specific mutations and FAB subtypes. DISCUSSION: This meta-analysis showed that AML patients with ASXL1 mutations had a poor prognosis, which may be a reason to include the diagnostics of this mutation in the prognostic scales for assessing risk in patients with AML.