Unique CD44 intronic SNP is associated with tumor grade in breast cancer: a case control study and in silico analysis

Cancer Cell Int. 2018 Feb 23;18:28. doi: 10.1186/s12935-018-0522-2. eCollection 2018.


Background: CD44 encoded by a single gene is a cell surface transmembrane glycoprotein. Exon 2 is one of the important exons to bind CD44 protein to hyaluronan. Experimental evidences show that hyaluronan-CD44 interaction intensifies the proliferation, migration, and invasion of breast cancer cells. Therefore, the current study aimed at investigating the association between specific polymorphisms in exon 2 and its flanking region of CD44 with predisposition to breast cancer.

Methods: In the current study, 175 Iranian female patients with breast cancer and 175 age-matched healthy controls were recruited in biobank, Breast Cancer Research Center, Tehran, Iran. Single nucleotide polymorphisms of CD44 exon 2 and its flanking were analyzed via polymerase chain reaction and gene sequencing techniques. Association between the observed variation with breast cancer risk and clinico-pathological characteristics were studied. Subsequently, bioinformatics analysis was conducted to predict potential exonic splicing enhancer (ESE) motifs changed as the result of a mutation.

Results: A unique polymorphism of the gene encoding CD44 was identified at position 14 nucleotide upstream of exon 2 (A37692→G) by the sequencing method. The A > G polymorphism exhibited a significant association with higher-grades of breast cancer, although no significant relation was found between this polymorphism and breast cancer risk. Finally, computational analysis revealed that the intronic mutation generated a new consensus-binding motif for the splicing factor, SC35, within intron 1.

Conclusions: The current study results indicated that A > G polymorphism was associated with breast cancer development; in addition, in silico analysis with ESE finder prediction software showed that the change created a new SC35 binding site.

Keywords: CD44; In silico analysis; Mutation; SR proteins; Single nucleotide polymorphism; Splice variants.