Introduction: Quiescin sulfhydryl oxidase 1 (QSOX1) oxidizes sulfhydryl groups to form disulfide bonds in proteins. Tumor specific expression of QSOX1 has been reported for numerous tumor types. In this study, we investigate QSOX1 as a marker of breast tumor progression and evaluate the role of QSOX1 as it relates to breast tumor growth and metastasis.

Methods: Correlation of QSOX1 expression with breast tumor grade, subtype and estrogen receptor (ER) status was gathered through informatic analysis using the "Gene expression based Outcome for Breast cancer Online" (GOBO) web-based tool. Expression of QSOX1 protein in breast tumors tissue microarray (TMA) and in a panel of breast cancer cell lines was used to confirm our informatics analysis. To investigate malignant cell mechanisms for which QSOX1 might play a key role, we suppressed QSOX1 protein expression using short hairpin (sh) RNA in ER+ Luminal A-like MCF7, ER+ Luminal B-like BT474 and ER- Basal-like BT549 breast cancer cell lines.

Results: GOBO analysis revealed high levels of QSOX1 RNA expression in ER+ subtypes of breast cancer. In addition, Kaplan Meyer analyses revealed QSOX1 RNA as a highly significant predictive marker for both relapse and poor overall survival in Luminal B tumors. We confirmed this finding by evaluation of QSOX1 protein expression in breast tumors and in a panel of breast cancer cell lines. Expression of QSOX1 in breast tumors correlates with increasing tumor grade and high Ki-67 expression. Suppression of QSOX1 protein slowed cell proliferation as well as dramatic inhibition of MCF7, BT474 and BT549 breast tumor cells from invading through Matrigel™ in a modified Boyden chamber assay. Inhibition of invasion could be rescued by the exogenous addition of recombinant QSOX1. Gelatin zymography indicated that QSOX1 plays an important role in the function of MMP-9, a key mediator of breast cancer invasive behavior.

Conclusions: Taken together, our results suggest that QSOX1 is a novel biomarker for risk of relapse and poor survival in Luminal B breast cancer, and has a pro-proliferative and pro-invasive role in malignant progression partly mediated through a decrease in MMP-9 functional activity.

Background: Recent advances in the treatment of cancer have focused on targeting genomic aberrations with selective therapeutic agents. In rare tumors, where large-scalec linical trials are daunting, this targeted genomic approach offers a new perspective and hope for improved treatments. Cancers of the ampulla of Vater are rare tumors that comprise only about 0.2% of gastrointestinal cancers. Consequently, they are often treated as either distal common bile duct or pancreatic cancers.

Methods: We analyzed DNA from a resected cancer of the ampulla of Vater and whole blood DNAfrom a 63 year-old man who underwent a pancreaticoduodenectomy by whole genomesequencing, achieving 37× and 40× coverage, respectively. We determined somatic mutations and structural alterations.

Results: We identified relevant aberrations, including deleterious mutations of KRAS and SMAD4 as well as a homozygous focal deletion of the PTEN tumor suppressor gene. These findings suggest that these tumors have a distinct oncogenesis from either common bile duct cancer or pancreatic cancer. Furthermore, this combination of genomic aberrations suggests a therapeutic context for dual mTOR/PI3K inhibition.

Conclusions: Whole genome sequencing can elucidate an oncogenic context and expose potential therapeutic vulnerabilities in rare cancers.

Background: The field of cancer genomics has rapidly adopted next-generation sequencing (NGS) in order to study and characterize malignant tumors with unprecedented resolution. In particular for cancer, one is often trying to identify somatic mutations--changes specific to a tumor and not within an individual's germline. However, false positive and false negative detections often result from lack of sufficient variant evidence, contamination of the biopsy by stromal tissue, sequencing errors, and the erroneous classification of germline variation as tumor-specific.

Results: We have developed a generalized Bayesian analysis framework for matched tumor/normal samples with the purpose of identifying tumor-specific alterations such as single nucleotide mutations, small insertions/deletions, and structural variation. We describe our methodology, and discuss its application to other types of paired-tissue analysis such as the detection of loss of heterozygosity as well as allelic imbalance. We also demonstrate the high level of sensitivity and specificity in discovering simulated somatic mutations, for various combinations of a) genomic coverage and b) emulated heterogeneity.

Conclusion: We present a Java-based implementation of our methods named Seurat, which is made available for free academic use. We have demonstrated and reported on the discovery of different types of somatic change by applying Seurat to an experimentally-derived cancer dataset using our methods; and have discussed considerations and practices regarding the accurate detection of somatic events in cancer genomes. Seurat is available at https://sites.google.com/site/seuratsomatic.