Over-Expression of RNA Processing, Heat Shock, and DNA Repair Proteins in Breast Tumor Compared to Normal Tissue.

This study identifies the main changes in protein expression in human breast tumors compared to normal breast tissue. Malignant tumors (32) and normal breast tissue samples (23), from formaldehyde-fixed, paraffin-embedded specimens are subjected to discovery proteomics using liquid chromatography/tandem mass spectrometry, with spectral counts for quantitation. The dataset contains 1406 proteins.

Collectively Improving Our Teaching: Attempting Biology Department-wide Professional Development in Scientific Teaching.

Many efforts to improve science teaching in higher education focus on a few faculty members at an institution at a time, with limited published evidence on attempts to engage faculty across entire departments. We created a long-term, department-wide collaborative professional development program, Biology Faculty Explorations in Scientific Teaching (Biology FEST). Across 3 years of Biology FEST, 89% of the department's faculty completed a weeklong scientific teaching institute, and 83% of eligible instructors participated in additional semester-long follow-up programs.

Glycoproteins in Claudin-Low Breast Cancer Cell Lines Have a Unique Expression Profile.

Claudin proteins are components of epithelial tight junctions; a subtype of breast cancer has been defined by the reduced expression of mRNA for claudins and other genes. Here, we characterize the expression of glycoproteins in breast cell lines for the claudin-low subtype using liquid chromatography/tandem mass spectrometry. Unsupervised clustering techniques reveal a group of claudin-low cell lines that is distinct from nonmalignant, basal, and luminal lines.

Mining the Breast Cancer Proteome for Predictors of Drug Sensitivity.

Approximately 20 drugs have been approved by the FDA for breast cancer treatment, yet predictive biomarkers are known for only a few of these. The identification of additional biomarkers would be useful both for drugs currently approved for breast cancer treatment and for new drug development. Using glycoprotein expression data collected via mass spectrometry, in conjunction with statistical models constructed by elastic net or lasso regression, we modeled quantitatively the responses of breast cancer cell lines to ~90 drugs.

Overcoming challenges and opening new opportunities in glycoproteomics.

Glycoproteomics has emerged as a prime area of interest within the field of proteomics because glycoproteins have been shown to function as biomarkers for disease and as promising therapeutic targets. A significant challenge in the study of glycoproteins is the fact that they are expressed in relatively low abundance in cells. In response, various enrichment methods have been developed to improve the detection of glycoproteins.

Using a cell line breast cancer progression system to identify biomarker candidates.

Unlabelled: Secreted and plasma membrane glycoproteins are considered excellent candidates for disease biomarkers. Herein we describe the identification of secreted and plasma membrane glycoproteins that are differentially expressed among a family of three breast cancer cell lines that models the progression of breast cancer. Using two-dimensional liquid chromatography-tandem mass spectrometry we identified more than 40 glycoproteins that were differentially expressed in either the premalignant (MCF10AT) or the fully malignant (MCF10CA1a) cell lines of this model system.

Systemic alteration of cell-surface and secreted glycoprotein expression in malignant breast cancer cell lines.

Breast cancer cell lines express fewer transmembrane and secreted glycoproteins than nonmalignant ones. The objective of these experiments was to characterize the changes in the expression of several hundred glycoproteins quantitatively. Secreted and cell-surface glycoproteins were isolated using a glycoprotein capture protocol and then identified by tandem mass spectrometry.

Glycoprotein profiles of human breast cells demonstrate a clear clustering of normal/benign versus malignant cell lines and basal versus luminal cell lines.

Gene expression profiling has defined molecular subtypes of breast cancer including those identified as luminal and basal. To determine if glycoproteins distinguish various subtypes of breast cancer, we obtained glycoprotein profiles from 14 breast cell lines. Unsupervised hierarchical cluster analysis demonstrated that the glycoprotein profiles obtained can serve as molecular signatures to classify subtypes of breast cancer, as well as to distinguish normal and benign breast cells from breast cancer cells.