Interplay of microRNAs to genetic, epigenetic, copy number variations of cervical cancer related genes

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.

Long Noncoding RNA LINC00899/miR-944/ESR1 Axis Regulates Cervical Cancer Cell Proliferation, Migration, and Invasion

Cervical cancer (CC) is a common malignancy in women. Long noncoding RNA LINC00899 plays a role in cancer, but its effects in CC are unknown. Our experiment aims to investigate the specific effects of LINC00899 in CC. LINC00899 was lowly expressed in CC tissues and cells, and overexpressed LINC0089 inhibited the viability, proliferation, migration, and invasion of CC cells, whereas silencing of LINC00899 had the opposite effect. There is a targeting relationship between LINC0089 and miR-944. It was found that miR-944 could competitively bind with LINC00899, and LINC00899 in turn, could downregulate expression of miR-944. Moreover, estrogen receptor 1 (ESR1) was the target gene of miR-944. Overexpressed miR-944 inhibited ESR1 expression, yet enhanced the migration and invasion of CC cells and promoted the expression levels of N-cadherin and Vimentin while inhibiting the expression of E-cadherin. However, overexpressed ESR1 reversed the effect of miR-944 overexpression on CC cells. LINC00899/miR-944/ESR1 axis regulates the proliferation, migration, and invasion of CC cells by regulating the expression levels of related proteins.