Wey L. Leong

Proteomic Analyses Reveal High Expression of Decorin and Endoplasmin (HSP90B1) Are Associated with Breast Cancer Metastasis and Decreased Survival

Background Breast cancer is the most common malignancy among women worldwide in terms of incidence and mortality. About 10% of North American women will be diagnosed with breast cancer during their lifetime and 20% of those will die of the disease. Breast cancer is a heterogeneous disease and biomarkers able to correctly classify patients into prognostic groups are needed to better tailor treatment options and improve outcomes. One powerful method used for biomarker discovery is sample screening with mass spectrometry, as it allows direct comparison of protein expression between normal and pathological states. The purpose of this study was to use a systematic and objective method to identify biomarkers with possible prognostic value in breast cancer patients, particularly in identifying cases most likely to have lymph node metastasis and to validate their prognostic ability using breast cancer tissue microarrays. Methods and Findings Differential proteomic analyses were employed to identify candidate biomarkers in primary breast cancer patients. These analyses identified decorin (DCN) and endoplasmin (HSP90B1) which play important roles regulating the tumour microenvironment and in pathways related to tumorigenesis. This study indicates that high expression of Decorin is associated with lymph node metastasis (p<0.001), higher number of positive lymph nodes (p<0.0001) and worse overall survival (p = 0.01). High expression of HSP90B1 is associated with distant metastasis (p<0.0001) and decreased overall survival (p<0.0001) these patients also appear to benefit significantly from hormonal treatment. Conclusions Using quantitative proteomic profiling of primary breast cancers, two new promising prognostic and predictive markers were found to identify patients with worse survival. In addition HSP90B1 appears to identify a group of patients with distant metastasis with otherwise good prognostic features.

Clinical relevance of DNA microarray analyses using archival formalin-fixed paraffin-embedded breast cancer specimens

BackgroundThe ability of gene profiling to predict treatment response and prognosis in breast cancers has been demonstrated in many studies using DNA microarray analyses on RNA from fresh frozen tumor specimens. In certain clinical and research situations, performing such analyses on archival formalin fixed paraffin-embedded (FFPE) surgical specimens would be advantageous as large libraries of such specimens with long-term follow-up data are widely available. However, FFPE tissue processing can cause fragmentation and chemical modifications of the RNA. A number of recent technical advances have been reported to overcome these issues. Our current study evaluates whether or not the technology is ready for clinical applications.MethodsA modified RNA extraction method and a recent DNA microarray technique, cDNA-mediated annealing, selection, extension and ligation (DASL, Illumina Inc) were evaluated. The gene profiles generated from FFPE specimens were compared to those obtained from paired fresh fine needle aspiration biopsies (FNAB) of 25 breast cancers of different clinical subtypes (based on ER and Her2/neu status). Selected RNA levels were validated using RT-qPCR, and two public databases were used to demonstrate the prognostic significance of the gene profiles generated from FFPE specimens.ResultsCompared to FNAB, RNA isolated from FFPE samples was relatively more degraded, nonetheless, over 80% of the RNA samples were deemed suitable for subsequent DASL assay. Despite a higher noise level, a set of genes from FFPE specimens correlated very well with the gene profiles obtained from FNAB, and could differentiate breast cancer subtypes. Expression levels of these genes were validated using RT-qPCR. Finally, for the first time we correlated gene expression profiles from FFPE samples to survival using two independent microarray databases. Specifically, over-expression of ANLN and KIF2C, and under-expression of MAPT strongly correlated with poor outcomes in breast cancer patients.ConclusionWe demonstrated that FFPE specimens retained important prognostic information that could be identified using a recent gene profiling technology. Our study supports the use of FFPE specimens for the development and refinement of prognostic gene signatures for breast cancer. Clinical applications of such prognostic gene profiles await future large-scale validation studies.

Mapping genomic and transcriptomic alterations spatially in epithelial cells adjacent to human breast carcinoma.

Almost all genomic studies of breast cancer have focused on well-established tumours because it is technically challenging to study the earliest mutational events occurring in human breast epithelial cells. To address this we created a unique dataset of epithelial samples ductoscopically obtained from ducts leading to breast carcinomas and matched samples from ducts on the opposite side of the nipple. Here, we demonstrate that perturbations in mRNA abundance, with increasing proximity to tumour, cannot be explained by copy number aberrations. Rather, we find a possibility of field cancerization surrounding the primary tumour by constructing a classifier that evaluates where epithelial samples were obtained relative to a tumour (cross-validated micro-averaged AUC = 0.74). We implement a spectral co-clustering algorithm to define biclusters. Relating to over-represented bicluster pathways, we further validate two genes with tissue microarrays and in vitro experiments. We highlight evidence suggesting that bicluster perturbation occurs early in tumour development.Studying the spatial mutational and gene expression alterations in breast cancer could impact our understanding of breast cancer development. Here, the authors analyse a unique dataset of epithelial samples that highlight potential field cancerisation surrounding the primary tumour.

Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations

IntroductionUsing genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts.MethodsAn independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147).ResultsThe original training cohort reached a statistically significant difference (p < 0.05) in disease-free survivals between the three CMTC groups after an additional two years of follow-up (median = 55 months). The prognostic value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups.ConclusionsBoth prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.

Regulatory T Cells in Ovarian Cancer Are Characterized by a Highly Activated Phenotype Distinct from that in Melanoma

Purpose: Regulatory T (Treg) cells expressing the transcription factor FOXP3 are essential for the maintenance of immunologic self-tolerance but play a detrimental role in most cancers due to their ability to suppress antitumor immunity. The phenotype of human circulating Treg cells has been extensively studied, but less is known about tumor-infiltrating Treg cells. We studied the phenotype and function of tumor-infiltrating Treg cells in ovarian cancer and melanoma to identify potential Treg cell–associated molecules that can be targeted by tumor immunotherapies. Experimental Design: The phenotype of intratumoral and circulating Treg cells was analyzed by multicolor flow cytometry, mass cytometry, RNA-seq, and functional assays. Results: Treg cells isolated from ovarian tumors displayed a distinct cell surface phenotype with increased expression of a number of receptors associated with TCR engagement, including PD-1, 4-1BB, and ICOS. Higher PD-1 and 4-1BB expression was associated with increased responsiveness to further TCR stimulation and increased suppressive capacity, respectively. Transcriptomic and mass cytometry analyses revealed the presence of Treg cell subpopulations and further supported a highly activated state specifically in ovarian tumors. In comparison, Treg cells infiltrating melanomas displayed lower FOXP3, PD-1, 4-1BB, and ICOS expression and were less potent suppressors of CD8 T-cell proliferation. Conclusions: The highly activated phenotype of ovarian tumor-infiltrating Treg cells may be a key component of an immunosuppressive tumor microenvironment. Receptors that are expressed by tumor-infiltrating Treg cells could be exploited for the design of novel combination tumor immunotherapies. Clin Cancer Res; 24(22); 5685–96. ©2018 AACR.

Preliminary experience of autofluorescence mammary ductoscopy

Mammary ductoscopy (MD) is a minimally invasive technique that uses a submillimeter endoscope inserted into breast ducts to directly visualize the ductal epithelium (lining) and to yield high-resolution white-light images of the tissue. Clinically, it has most commonly been used to manage pathological nipple discharge, as it allows therapeutic removal of intraductal papilloma and guides surgical excision during operations. MD has also been used as a diagnostic tool for ductal carcinoma, which is the most common form of cancer in the breast.1 However, to date, the approach was not deemed sufficiently advanced for detecting early-stage lesions. Here, we describe our efforts to enhance the diagnostic accuracy of MD through the addition of autofluorescence imaging2 and diffuse reflectance and fluorescence point spectroscopies.3, 4 Our goal was twofold: first, to assess the technical feasibility of of autofluorescence to produce acceptable image quality in the ducts; and second, to find distinct changes between malignant and benign tissues that potentially can facilitate visualization of lesions that are not seen under conventional white-light ductoscopy. For simplicity, we used an existing autofluorescenceimaging system that was developed and optimized for gastrointestinal endoscopy.5 A priori, this approach is not necessarily optimal for ductoscopy. Consequently, we included the point fluorescence and reflectance spectroscopies to gain further data to aid interpretation of the imaging results as well as to optimize the imaging parameters. Ten consenting mastectomy patients with a preoperative diagnosis of palpable invasive ductal carcinoma were recruited into the study between May 2005 and July 2008. This ex vivo pilot study was approved by the Research Ethics Board at the Figure 1. Normal region—(a) white light, (b) autofluorescence— compared to tumor region: (c) white light, (d) autofluorescence. The forward-looking field-of-view perspective is approximately 1mm. (Image adapted from a previous publication.3)