LncRNA-SNPs in a Brazilian Breast Cancer Cohort: A Case-Control Study.
Carolina MathiasAnelis Maria MarinAna Flávia KohlerHeloisa Bruna Soligo SanchukiNatalie SukowMarcia Holsbach BeltrameSuelen Cristina Soares BaalAna Paula Martins SebastiãoEnilze Maria de Souza Fonseca RibeiroDaniela Fiori GradiaMateus Nobrega AokiJaqueline Carvalho de OliveiraPublished in: Genes (2023)
Long noncoding RNAs (lncRNAs) are a class of non-coding RNAs that contain more than 200 nucleotides and exhibit a versatile regulatory capacity. Genomic alterations in lncRNAs have already been investigated in several complex diseases, including breast cancer (BC). BC is a highly heterogeneous disease and is the most prevalent cancer type among women worldwide. Single nucleotide polymorphisms (SNPs) in lncRNA regions appear to have an important role in BC susceptibility; however, little is known about lncRNA-SNPs in the Brazilian population. This study used Brazilian tumor samples to identify lncRNA-SNPs with a biological role in BC development. We applied a bioinformatic approach intersecting lncRNAs that are differentially expressed in BC tumor samples using The Cancer Genome Atlas (TCGA) cohort data and looked for lncRNAs with SNPs associated with BC in the Genome Wide Association Studies (GWAS) catalog. We highlight four lncRNA-SNPs-rs3803662, rs4415084, rs4784227, and rs7716600-which were genotyped in Brazilian BC samples in a case-control study. The SNPs rs4415084 and rs7716600 were associated with BC development at higher risk. These SNPs were also associated with progesterone status and lymph node status, respectively. The rs3803662/rs4784227 haplotype GT was associated with BC risk. These genomic alterations were also evaluated in light of the lncRNA's secondary structure and gain/loss of miRNA binding sites to better understand its biological functions. We emphasize that our bioinformatics approach could find lncRNA-SNPs with a potential biological role in BC development and that lncRNA-SNPs should be more deeply investigated in a highly heterogeneous disease population.
Keyphrases
- genome wide association
- genome wide
- long non coding rna
- long noncoding rna
- lymph node
- dna methylation
- copy number
- transcription factor
- adipose tissue
- papillary thyroid
- squamous cell carcinoma
- metabolic syndrome
- gene expression
- polycystic ovary syndrome
- artificial intelligence
- mass spectrometry
- case control
- radiation therapy
- machine learning
- young adults
- high resolution
- atomic force microscopy