Identification of novel SNPs in SYK gene of breast cancer patients: computational analysis of SNPs in the 5′UTR

microRNA-related single-nucleotide polymorphisms and breast cancer

Breast cancer, as the most common cancer in women which affects patients both mentally and physically, requires great attention in many areas and many levels as this cancer is known to be multifactorial. Single-stranded molecules called microRNAs with near 22 nucleotides are seen to act in central dogma of molecular biology by inhibiting the translation process; it is demonstrated that any alteration in their sequence especially single-nucleotide polymorphisms (SNPs) may lead into increasing the breast cancer risk. miR-SNPs are considered to be the potential biomarkers for early detection of breast cancer. As a result, this review documents the well-known miR-SNPs that are known to be associated with breast cancer. In this regard, two principals were discussed: (a) SNPs in the target genes of microRNAs and the alteration in gene expression due to this phenomenon; (b) changes based on the SNPs in the microRNA coding region and the impact on their interaction with target messenger RNA.

The Cancer Genomics Resource List 2014

CONTEXT

Genomic sequencing for cancer is offered by commercial for-profit laboratories, independent laboratory networks, and laboratories in academic medical centers and integrated health networks. The variability among the tests has created a complex, confusing environment.

OBJECTIVE

To address the complexity, the Personalized Health Care (PHC) Committee of the College of American Pathologists proposed the development of a cancer genomics resource list (CGRL). The goal of this resource was to assist the laboratory pathology and clinical oncology communities.

DESIGN

The PHC Committee established a working group in 2012 to address this goal. The group consisted of site-specific experts in cancer genetic sequencing. The group identified current next-generation sequencing (NGS)-based cancer tests and compiled them into a usable resource. The genes were annotated by the working group. The annotation process drew on published knowledge, including public databases and the medical literature.

RESULTS

The compiled list includes NGS panels offered by 19 laboratories or vendors, accompanied by annotations. The list has 611 different genes for which NGS-based mutation testing is offered. Surprisingly, of these 611 genes, 0 genes were listed in every panel, 43 genes were listed in 4 panels, and 54 genes were listed in 3 panels. In addition, tests for 393 genes were offered by only 1 or 2 institutions. Table 1 provides an example of gene mutations offered for breast cancer genomic testing with the annotation as it appears in the CGRL 2014.

CONCLUSIONS

The final product, referred to as the Cancer Genomics Resource List 2014, is available as supplemental digital content.

SYK Allelic Loss and the Role of Syk-Regulated Genes in Breast Cancer Survival

Heterozygotic loss of SYK, a non-receptor tyrosine kinase, gives rise to mouse mammary tumor formation where Syk protein levels are reduced by about half; loss of SYK mRNA is correlated with invasive cell behavior in in vitro models; and SYK loss has been correlated with distant metastases in patients. Here, allelic loss of the SYK gene was explored in breast ductal carcinoma in situ (DCIS) using fluorescence in situ hybridization and pyrosequencing, respectively, and in infiltrating ductal carcinoma (IDC) using genomic data from The Cancer Genome Atlas (TCGA). Allelic loss was present in a subset of DCIS cases where adjacent IDC was present. SYK copy number loss was found in about 26% of 1002 total breast cancer cases and 30% of IDC cases. Quantitative immunofluorescence revealed Syk protein to be six-fold higher in infiltrating immune cells compared with epithelial cells. This difference distorted tumor cell mRNA and protein levels in extracts. 20% of 1002 IDC cases contained elevated immune cell infiltration as estimated by elevated immune-specific mRNAs. In cases without immune cell infiltration, loss of SYK copy number was associated with a significant reduction of SYK mRNA. Here we define a 55 Gene Set consisting of Syk interacting, motility- and invasion-related genes. We found that overall survival was significantly reduced in IDC and Luminal A+B cases where copy number and mutations of these 55 genes were affected (Kaplan-Meier, Logrank test p-value 0.007141 and Logrank test p-value 0.001198, respectively). We conclude that reduction in Syk expression and contributions of genomic instability to copy number and mutations in the 55 Syk interacting genes significantly contribute to poorer overall patient survival. A closer examination of the role of Syk interacting motility and invasion genes and their prognostic and/or causative association with metastatic disease and patient outcome is warranted.

Expression of DNMTs and genomic DNA methylation in gastric signet ring cell carcinoma

The aim of the present study was to investigate the protein expression of DNA methyltransferases (DNMTs) and genomic DNA methylation status of genomes in gastric signet ring cell carcinoma (SRC). Immunohistochemistry was performed to analyze DNMT expression and methylated DNA immunoprecipitation microarray (MeDIP‑chip) and MeDIP quantitative real‑time PCR (MeDIP‑qPCR) were performed to analyze the genomic DNA methylation status in gastric SRC tissue. An increase in DNMT1 and decrease in DNMT3A expression in SRC tissue was observed compared with matched non‑cancerous tissue. However, expression of other DNMTs, DNMT2, DNMT3B and DNMT3L, was not found to differ significantly between carcinoma and control. The MeDIP‑chip assay revealed that methylation of gene promoters and CpG islands in SRC was higher than those in matched control tissue. However, MeDIP‑qPCR analysis demonstrated that specific tumor‑related genes, including ABL2, FGF18, TRAF2, EGFL7 and RAB33A were aberrantly hypomethylated in SRC tissue. Results of the current study indicate that gastric SRC may produce complex patterns of aberrant DNA methylation and DNMT expression.