CD1a and CD1d genes polymorphisms in breast, colorectal and lung cancers

CD1a- and CD83-positive dendritic cells as prognostic markers of metastasis development in early breast cancer patients

PURPOSE

Dendritic cells (DCs) are the most potent antigen-presenting cells that play a major role in initiating the antitumor immune response in different types of cancer. However, the prognostic significance of the accumulation of these cells in human early breast tumors is not totally clear. The aim of this study is to evaluate the prognostic relevance of CD1a( +) and CD83( +) dendritic cells in early breast cancer patients.

METHODS

We conducted immunohistochemical assays to determine the number of stromal CD1a( +) and CD83( +) DCs in primary tumors from early invasive ductal breast cancer patients, and analyzed their association with clinico-pathological characteristics.

RESULTS

Patients with high CD1a( +) DC number had lower risk of bone metastatic occurrence, as well as, longer disease-free survival (DFS), bone metastasis-free survival (BMFS) and overall survival (OS). Moreover, CD1a( +) DC number was an independent prognostic factor for BMFS and OS. In contrast, we found that patients with high number of CD83( +) DCs had lower risk of mix (bone and visceral)-metastatic occurrence. Likewise, these patients presented better prognosis with longer DFS, mix-MFS and OS. Furthermore, CD83( +) DC number was an independent prognostic factor for DFS and OS.

CONCLUSION

The quantification of the stromal infiltration of DCs expressing CD1a or CD83 in early invasive breast cancer patients serves to indicate the prognostic risk of developing metastasis in a specific site.

Association between genetic variants in CD1A and CD1D genes and pulmonary tuberculosis in an Iranian population

Cluster of differentiation (CD)1 molecules are a highly conserved family of MCH-like transmembrane glycoproteins that bind lipid and glycolipid antigens and present a diverse range of microbial and self-glycolipids to antigen-specific T cells. The current study aimed to find out the impact of CD1A and CD1D polymorphisms on pulmonary tuberculosis (PTB). This case-control study encompassed 172 PTB patients and 180 healthy subjects. Genotyping of CD1A and CD1D variants was achieved using the polymerase chain reaction restriction fragment length polymorphism method. The results revealed that CD1A rs411089 variant significantly increased the risk of PTB in recessive model [odds ratio (OR)=2.71, 95% confidence interval (CI)=1.38-5.57, CC vs. TT+TC, P=0.005]. CD1D rs859009 polymorphism significantly reduced the risk of PTB in heterozygous codominant (OR=0.50, 95% CI=0.29-0.86, P=0.011, GC vs. GG) and dominant (OR=0.53, 95% CI=0.31-0.88, P=0.019, GC+CC vs. GG) inheritance model. The CD1A rs366316, CD1D rs973742 and CD1D rs859010 were not associated with the risk/protection from PTB (P>0.05). The results of the present study suggest that CD1A rs411089 and CD1D rs859009 but not CD1A rs366316, CD1D rs973742 and CD1D rs859010 polymorphisms are associated with PTB in a sample of the Iranian population. Further investigation with different ethnicities and larger sample sizes are necessary to certify the findings of the present study.

DNA co-methylation analysis suggests novel functional associations between gene pairs in breast cancer samples

Localized promoter hypermethylation and overall DNA hypomethylation have been associated with the presence of tumor in humans. Yet, despite the large amount of recently produced epigenetic data, there is still a lack of understanding on how several genes behave in tumor cells with respect to their epigenetic alterations such as DNA methylation. Here we performed a novel type of analysis that measures the correlation of DNA methylation levels between two genes across many samples. We linked this so-called co-methylation to the genomic distance of these genes, their functional similarity and their expression levels. Co-methylation analysis of more than 300 breast cancer samples from the TCGA portal yielded 187 pairs of genes showing Pearson correlation coefficients |r| ≥ 0.75. These pairs were formed by 133 genes. Less than half of these pairs are located on the same chromosome. For these, we found that the level of co-methylation is weakly anti-correlated with genomic distance (r = -0.29). Linking co-methylation with the functional similarity of genes showed that genes with r ≥ 0.8 tend to have similar molecular function and to be involved in the same biological process as described in the Gene Ontology project. Clustering of highly co-methylated genes identified four enriched KEGG pathways. Hence we have introduced co-methylation as a new indicator to discover functional associations between gene pairs in breast cancer and furthermore to discover new candidate genes that should be inspected more closely in the context of the studied disease.