Jennifer J. Hill

Glycoproteomic analysis of two mouse mammary cell lines during transforming growth factor (TGF)-β induced epithelial to mesenchymal transition

BackgroundTGF-β acts as an antiproliferative factor in normal epithelial cells and at early stages of oncogenesis. However, later in tumor development TGF-β can become tumor promoting through mechanisms including the induction of epithelial-to-mesenchymal transition (EMT), a process that is thought to contribute to tumor progression, invasion and metastasis. To identify EMT-related breast cancer therapeutic targets and biomarkers, we have used two proteomic approaches to find proteins that change in abundance upon the induction of EMT by TGF-β in two mouse mammary epithelial cell lines, NMuMG and BRI-JM01.ResultsPreliminary experiments based on two-dimensional electrophoresis of a hydrophobic cell fraction identified only 5 differentially expressed proteins from BRI-JM01 cells. Since 3 of these proteins were glycoproteins, we next used the lectin, wheat germ agglutinin (WGA), to enrich for glycoproteins, followed by relative quantification of tryptic peptides using a label-free LC-MS based method. Using these approaches, we identified several proteins that are modulated during the EMT process, including cell adhesion molecules (several members of the Integrin family, Fibronectin, Activated leukocyte cell adhesion molecule, and Neural cell adhesion molecule 1) and regulators of cellular signaling (Tumor-associated calcium signal transducer 2, Basigin).ConclusionInterestingly, despite the fact that TGF-β induces similar EMT phenotypes in NMuMG and BRI-JM01 cells, the proteomic results for the two cell lines showed only minimal overlap. These differences likely result in part from the conservative cut-off values used to define differentially-expressed proteins in these experiments. Alternatively, it is possible that the two cell lines may use different mechanisms to achieve an EMT transition.

Identification of Vascular Breast Tumor Markers by Laser Capture Microdissection and Label-Free LC−MS

Blood vessels in tumors frequently show abnormal characteristics, such as tortuous morphology or leakiness, but very little is known about protein expression in tumor vessels. In this study, we have used laser capture microdissection (LCM) to isolate microvessels from clinical samples of invasive ductal carcinoma (IDC), the most common form of malignant breast cancer, and from patient-matched adjacent nonmalignant tissue. This approach eliminates many of the problems associated with the heterogeneity of clinical tumor tissues by controlling for differences in protein expression between both individual patients and different cell types. Proteins from the microvessels were trypsinized and the resulting peptides were quantified by a label-free nanoLC-MS method. A total of 86 proteins were identified that are overexpressed in tumor vessels relative to vessels isolated from the adjacent nonmalignant tissue. These proteins include well-known breast tumor markers such as Periostin and Tenascin C but also proteins with lesser-known or emerging roles in breast cancer and tumor angiogenesis (i.e., Serpin H1, Clic-1, and Transgelin 2). We also identified 40 proteins that were relatively under-expressed in IDC tumor vessels, including several components of the basement membrane whose lower expression could be responsible for weakening tumor vessels. Lastly, we show that a subset of 29 proteins, derived from our list of differentially expressed proteins, is able to predict survival in three publicly available clinical breast cancer microarray data sets, which suggests that this subset of proteins likely plays a functional role in cancer progression and outcome.

Identification of secreted proteins regulated by cAMP in glioblastoma cells using glycopeptide capture and label-free quantification.

Exposure of glioblastoma U87MG cells to a cAMP analog leads to a decrease in proliferation, invasion, and angiogenic potential. Here, we apply a label‐free MS‐based approach to identify formerly N‐linked glycopeptides that change in abundance upon cAMP treatment. Over 150 unique glycopeptides in three biological repetitions were quantified, leading to the identification of 14 upregulated proteins and 21 downregulated proteins due to cAMP treatment. Of these, eight have been validated, either through comparison with microarray data or by Western blot. We estimate our ability to identify differentially expressed peptides at greater than 85% in a single biological repetition, while the analysis of multiple biological repetitions lowers the false positive rate to ∼2%. Many of the proteins identified in this study are involved in cell signaling and some, such as Tenascin C, Cathepsin L, Neuroblastoma suppressor of tumorigenicity, and AXL/UFO tyrosine–protein kinase receptor, have been previously shown to be involved in glioblastoma progression. We also identify several semitryptic peptides that increase in abundance upon cAMP treatment, suggesting that cAMP regulates protease activity in these cells. Overall, these results demonstrate the benefits of using a highly specific enrichment method for quantitative proteomic experiments.

Methods to study glycoproteins at the blood-brain barrier using mass spectrometry.

Glycosylation is the most common posttranslational modification of proteins in mammalian cells and is limited mainly to membrane and secreted proteins. Glycoproteins play several key roles in the physiology and pathophysiology of the blood-brain barrier (BBB) and are attractive as diagnostic markers and therapeutic targets for many neurological diseases. However, large-scale glycoproteomic studies of the BBB have been lacking, largely due to the complexity of analyzing glycoproteins and a lack of available tools for this analysis. Recent development of the hydrazide capture method and significant advances in mass spectrometry (MS)-based proteomics over the last few years have enabled selective enrichment of glycoproteins from complex biological samples and their quantitative comparisons in multiple conditions. In this chapter, we describe methods for: (1) isolating membrane and secreted proteins from BEC and other cells of the neurovascular unit, (2) enriching glycoproteins using hydrazide capture, and (3) performing label-free quantitative proteomics to identify differential glycoprotein expression in various biological conditions. Hydrazide capture, when coupled with label-free quantitative proteomics, is a reproducible and sensitive method that allows for quantitative profiling of a large number of glycoproteins from biological samples for the purposes of differential expression measurements and biomarker discovery.

Computational selection of antibody-drug conjugate targets for breast cancer

The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell membrane targets were identified, including one target for which an antibody-drug conjugate is in clinical use, and six targets for which antibody-drug conjugates are in clinical trials for the treatment of breast cancer and other solid tumors. In addition, 50 extracellular proteins were identified as potential targets for non-internalizing strategies and alternative modalities. Candidate targets linked with the epithelial-to-mesenchymal transition were identified by analyzing differential gene expression in epithelial and mesenchymal tumor-derived cell lines. Overall, these results show that mining human gene expression data has the power to select and prioritize breast cancer antibody-drug conjugate targets, and the potential to lead to new and more effective cancer therapeutics.

Glycoproteomic Comparison of Clinical Triple-Negative and Luminal Breast Tumors

Triple-negative (TN) breast cancer accounts for ∼ 15% of breast cancers and is characterized by a high likelihood of relapse and a lack of targeted therapies. In contrast, luminal-type tumors that express the estrogen and progesterone receptors (ER+/PR+) and lack expression of human epidermal growth factor receptor 2 (Her2-) are treated with targeted hormonal therapy and carry a better prognosis. To identify potential targets for the development of future therapeutics aimed specifically at TN breast cancers, we have used a hydrazide-based glycoproteomic workflow to compare protein expression in clinical tumors from nine TN (Her2-/ER-/PR-) and nine luminal (Her2-/ER+/PR+) patients. Using a label-free LC-MS based approach, we identified and quantified 2264 proteins. Of these, 90 proteins were more highly expressed and 86 proteins were underexpressed in the TN tumors relative to the luminal tumors. The expression level of four of these potential targets was verified in the original set of tumors by Western blot and correlated well with our mass-spectrometry-based quantification. Furthermore, 30% of the proteins differentially expressed between luminal and TN tumors were validated in a larger cohort of 406 TN and 469 luminal tumors through corresponding differences in their mRNA expression in publically available microarray data. A group of 29 of these differentially expressed proteins was shown to correctly classify 88% of TN and luminal tumors using microarray data of their associated mRNA levels. Interestingly, even within a group of TN breast cancer patients, the expression levels of these same mRNAs were able to significantly predict patient survival, suggesting that these proteins play a role in the aggressiveness seen in TN tumors. This study provides a comprehensive list of potential targets for the development of diagnostic and therapeutic agents specifically aimed at treating TN breast cancer and demonstrates the utility of using publicly available microarray data to further prioritize potential targets.

Proteomic Identification and Functional Validation of Activins and Bone Morphogenetic Protein 11 as Candidate Novel Muscle Mass Regulators

Myostatin is a secreted TGF- family member that controls skeletal muscle growth. Humans, cattle, and dogs carrying natural loss-of-function mutations in the myostatin gene and myostatin knockout mice exhibit significant increases in skeletal muscle mass. Treatment of adult mice with antimyostatin antibodies also resulted in significant muscle mass increases. However, myostatinknockout mice that were treated with a soluble form of the activin type II receptor (ActRII) B increased their muscle mass by an additional 15– 25%, indicating that there is at least one additional ligand, in addition to myostatin, that functions to limit muscle growth. Here, both soluble ActRII and -IIB fragment-crystallizable proteins were used to affinity purify their native ligands from human and mouse sera. Using mass spectrometry-based proteomics and in vitro binding assays we have identified and confirmed that a number of TGF- family members, including myostatin, activins-A, -B, and -AB, bone morphogenetic proteins (BMPs) -9, -10, and -11, bind to both ActRIIs. Many of these factors, such as BMPs-11, -9, and -10 were discovered in systemic circulation for the first time, indicating that these ligands may also act in an endocrine fashion. Using a promoter-specific gene reporter assay, we demonstrated that soluble ActRIIB fragment-crystallizable proteins can inhibit the canonical signaling induced by these ligands. In addition, like myostatin, these factors were able to block the differentiation of myoblast cells into myotubes. However, in addition to myostatin, only BMP11, and activins-A, -B, and -AB could be blocked from inhibiting the myoblast-to-myotube differentiation with both soluble ActRIIs, thus implicating them as potential novel regulators of muscle growth. (Molecular Endocrinology 22: 2689–2702, 2008)

Biotin-transfer from a trifunctional crosslinker for identification of cell surface receptors of soluble protein ligands

Here we describe a novel crosslinker and its application as a biotin-transfer reagent to identify cell surface receptors of soluble protein ligands on live cells. This crosslinker contains three functional groups: an aldehyde-reactive aminooxy group, a sulfhydryl, and a biotin (ASB). It is readily synthesized via a 3-step addition reaction using standard solid-phase peptide synthesis methods and commercially available intermediates, allowing access to laboratories without specialized synthetic chemistry capabilities. For the biotin-transfer method, ASB is linked to a protein ligand through the sulfhydryl group in a two-step process that allows the introduction of a disulfide bond between the ligand and the crosslinker. Incubation of the labelled ligand with oxidized live cells leads to the formation of crosslinks with aldehyde-containing glycans on the cell surface receptor. Subsequent reduction of the disulfide bond results in biotin transfer from the ligand to the cell surface receptor. Protein biotinylation that is mediated by ligand binding to its receptor is differentiated from background biotinylation events by comparison with a similarly labelled control protein using comparative proteomic mass spectrometry to quantify streptavidin-bound proteins. Using this method, we successfully identified the cell surface receptors of a peptide hormone, a monoclonal antibody, and a single-domain antibody-Fc fusion construct.

Abstract 3669: Screening platform for development of antibody-drug conjugates against novel targets at the National Research Council of Canada

One of the most promising of the next generation of biologic-based cancer therapeutics builds on the molecular targeting abilities of antibodies by combining them with drugs to generate highly specific antibody-drug conjugates (ADCs). However, the development of ADCs requires time-consuming selection of the antibody for every target and cancer type. High-throughput screening technologies based on the use of conjugated secondary antibodies provide a fast and efficient surrogate assay from which to identify which antibodies are best internalized and suitable for immunoconjugate development into ADCs. As part of its integrated antibody development initiative, NRC has isolated and characterized anti- mouse Fc and anti-human Fc monoclonal antibodies to serve as very selective detective reagents for various IgG isotypes. We have shown that these secondary antibodies are species specific, selective and of high affinity. When conjugated to pH sensitive fluorophores, we have used them to specifically identify internalizing antibodies against tumor targets, which were later validated as ADCs. Furthermore, these secondary conjugates exhibit high specific potency and low background toxicity once conjugated to linkered drugs. This approach allow us to optimize the selection of an antibody for a particular target, tumor type, linker and drug for ADC development. NRC will present results of a screen of 285 mouse antibodies against 20 different targets in 7 different cancer cell lines, using either MCC-DM1 or vc-MMAE-conjugated secondary antibodies. The NRC ADC discovery platform is combining this methodology with our proprietary mRNA and DNA expression database for the selection of appropriate ADC targets. NRC Biologics and Biomanufacturing program is in the process of screening thousands of NRC antibodies generated against a variety of cancer-associated cell surface targets to deliver a steady pipeline of ADCS as part of its drug discovery efforts. This functional screening platform further promotes the integration and advancement of NRC’s capabilities and strengths in the area of biologic-based therapeutics lead candidate selection, including quality attributes and characterization and biomanufacturing. The combined expertise in cell biology, high throughput screening, antibody generation and selection, bioinformatics and expression analysis forms the foundation by which NRC can establish strategic collaborations with other Canadian or international partners to develop antibodies into novel ADC biologics. Citation Format: Maria Luz Jaramillo, Luc Meury, Patrice Bouchard, Allan Matte, Anne Marcil, Mauro Acchione, Jennifer Hill, Francois Fauteux. Screening platform for development of antibody-drug conjugates against novel targets at the National Research Council of Canada [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3669. doi:10.1158/1538-7445.AM2017-3669