Elevated Expression of Squamous Cell Carcinoma Antigen (SCCA) Is Associated with Human Breast Carcinoma

Squamous cell carcinoma antigen (SCCA) belongs to the serine protease inhibitor (Serpin) family of proteins. Elevated expression of SCCA has been used as a biomarker for aggressive squamous cell carcinoma (SCC) in cancers of the cervix, lung, head and neck, and liver. However, SCCA expression in breast cancer has not been investigated. Immunohistochemical analysis of SCCA expression was performed on tissue microarrays containing breast tumor tissues (n = 1,360) and normal breast epithelium (n = 124). SCCA expression was scored on a tiered scale (0-3) independently by two evaluators blind to the patient's clinical status. SCCA expression was observed in Grade I (0.3%), Grade II (2.5%), and Grade III (9.4%) breast cancers (p<0.0001). Comparing tissues categorized into the three non-metastatic TNM stages, I-III, SCCA positivity was seen in 2.4% of Stage I cancers, 3.1% of Stage II cancers, and 8.6% of Stage III breast cancers (p = 0.0005). No positive staining was observed in normal/non-neoplastic breast tissue (0 out of 124). SCCA expression also correlated to estrogen receptor/progesterone receptor (ER/PR) double-negative tumors (p = 0.0009). Compared to SCCA-negative patients, SCCA-positive patients had both a worse overall survival and recurrence-free survival (p<0.0001 and p<0.0001, respectively). This study shows that SCCA is associated with both advanced stage and high grade human breast carcinoma, and suggests the necessity to further explore the role of SCCA in breast cancer development and treatment

Systematic Inference of Copy-Number Genotypes from Personal Genome Sequencing Data Reveals Extensive Olfactory Receptor Gene Content Diversity

Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. We benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95–99% concordance). We further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ∼15% and ∼20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, we found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing