Xiaowei Chen, PhD
Office Phone: 215-214-4288
Global DASE analysis to identify novel coding or no-coding genetic factors for breast tumorigenesis:
The significant mortality associated with breast cancer (BCa) suggests a clear need to improve current research strategies to identify new genes that predispose women to breast cancer. Therefore, we hypothesize that DASE is a functional index for cis-acting variants and pathogenic mutations and global profiling of DASE in BCa precursor tissues can be used to identify novel causative alleles for BCa susceptibility. Although other approaches have been examined for DASE profiling, SNP array-based technology is the most common approach for global DASE analysis. With the advance of array technology, new generation arrays carry much higher content of SNP probes (> 1 million). In our ongoing projects supported by Susan G. Komen, we have employed the Illumina® Omni1 array for genome-wide allele-specific expression (GWASE) measurements in a set of eight normal HMEC established from breast cancer patients. In order to use meaningful data, the raw results reported from Illumina were subjected to multiple filters, and only heterozygous SNPs that had significant intensity signals were left for DASE analysis. We have developed two statistical methods, SNP- and gene-based approaches, which allow us to identify 90 and 143 genes with significant DASE>2 (P ≤ 0.01, FDR ≤ 0.05), respectively. Importantly, 34 coding and 26 non-coding candidate loci are identified by both approaches. Ingenuity Pathway Analysis revealed two major interaction networks, which involve a variety of biological functions, including cell death and cell-to-cell signaling. One of the networks includes known cancer causative genes, ZNF331, USP6 and DMBT1. Our study demonstrated that global DASE profiling could be a powerful new approach to identify breast cancer risk alleles.
Differential Allele-specific Expression (DASE) as a Novel Functional Index for Risk Alleles:
Over the last decade, advances in array technologies have resulted in the ability to evaluate the expression of thousands of genes simultaneously. These platforms offer a powerful tool to test multiple markers for breast cancer diagnosis, prognosis and targeted therapy. However, gene expression as assessed by current techniques represents the total level of transcripts produced by both parental alleles. The absolute transcript level fails to account for potential imbalances in relative allelic contribution. This perspective is particularly important for the pathogenesis of breast cancer which is believed to occur through the accumulation of multiple genetic alterations, similar to the colon cancer model. Previously we reported that mutant BRCA1 transcripts containing premature stop codons were eliminated or destabilized by nonsense-mediated mRNA decay and could lead to a state of haploinsufficiency. As a result, the expression ratios of the mutant to corresponding wild-type alleles were significantly decreased, resulting in DASE. Differential ASE has been shown to contribute to phenotypic variability in humans and more recently to the pathogenesis of cancer. Recent studies have demonstrated that DASE in BRCA1 significantly increased in both familial and non-familial breast and ovarian cancer patients. These findings strongly suggest that differential ASE affecting BRCA1 contributes to the development of breast and ovarian cancer. Besides truncation mutations, multiple genetic factors can affect ASE. For example, genetic alterations in BRCA1 5’ promoter regions could mediate transcription factor binding thus disrupting mutant BRCA1 allele expression. As ASE can be affected by multiple genetic factors, we propose that DASE is a sensitive functional index for genetic variants, and can be used as a novel approach to identify risk alleles for breast tumor progression.
Intra-individual Heterogeneity in Ductal Carcinoma in Situ Lesions:
The widespread use of screening mammography has dramatically increased detection rates of early breast lesions, including DCIS. DCIS detection rates around the globe are expected to continuously climb as women’s life expectancies increase, and more developing countries begin BCa screening programs. As a neoplastic proliferation of mammary epithelial cells confined to the ductal-lobular structure without invasion through the basement membrane, DCIS is generally not immediately life threatening. However, 14-50% of women diagnosed with DCIS will develop IDC subsequently if left untreated. Cellular heterogeneity of IHC biomarker expression between patients has been well documented in invasive ductal carcinoma (IDC) and its precursor lesion, ductal carcinoma in situ (DCIS). However, few studies have quantified the variations in the expression of standard prognostic or therapeutic response-monitoring markers within an individual patient’s DCIS lesions. This intra-individual heterogeneity in DCIS likely hinders current personalized medicine strategies which largely rely on clinical results from single biopsy samples. More importantly, because current regimens are restricted to standardized IHC parameters, this bias could contribute to inadequate decision-making for risk assessment and therapeutic approaches in DCIS patients. Therefore, it is critical to quantitatively evaluate intra-individual heterogeneity of standard clinical markers in DCIS.