Mount Sinai Hospital Scientist Wins World’s Largest Prize for Diabetes Research

Dr. Daniel Drucker, Senior Investigator at Mount Sinai Hospital’s Lunenfeld-Tanenbaum Research Institute, is the recipient of the world’s most valuable award for diabetes research, the 2014 Manpei Suzuki International Prize. The award, which was announced today by the Manpei Suzuki Diabetes Foundation in Tokyo, recognizes Dr. Drucker’s research in the area of gut hormones and how they control glucose and body weight, which have led to the development of two new classes of therapies for the treatment of type 2 diabetes.

“The 2014 Manpei Suzuki International Prize brings tremendous international recognition to the work that we have done for over 25 years, with my trainees and fellow scientists, both at the Lunenfeld-Tanenbaum Research Institute and at the University of Toronto,” says Dr. Drucker, who is also Professor of Medicine in the Division of Endocrinology at the University of Toronto.“We are honoured that our science has helped in the development of new medications for patients with diabetes, and delighted to have our research achievements recognized by our esteemed colleagues in Japan.”

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New Advances in Next Generation RNA Sequencing

Genetic sequencing determines the precise order of the molecules that make up our DNA and RNA, which in turn are the molecular “fingerprint” of tumour cells that allow for personalized medicine for individual patients. Now, a new way of analyzing genomic data from tumours may one day allow clinicians to treat each person’s cancer as its own unique disease.

In a recent paper published by Mount Sinai researchers led by Drs. Alex Zlotta and Jeff Wrana, the team used leading-edge molecular analysis to decode the genetic makeup of a bladder cancer patient’s tumour, with will be vital to the medical decisions that are being tailored for the individual patient.

The research team established the methods to sequence all of a tumour’s RNA (whole transcriptome RNA-Sequencing) from tumours preserved in formalin. Formalin is an organic compound useful for preserving samples. Tumours are then embedded in paraffin (FFPE), which allows for samples to be solidified so that analysis can be done. When the results were compared between matched, freshly frozen tumour samples and FFPE tumour samples, the team observed similar results between the two sample types.

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Over 40 genetic links to rheumatoid arthritis discovered

One of Canada’s pre-eminent researchers, Dr. Kathy Siminovitch, played a leading role in a study that identifies over 40 new genetic links to rheumatoid arthritis, published in Nature on December 25, 2103. The discovery opens the door to a personalized approach to treating the autoimmune disorder, allowing medications to target a person’s individual genetic make up.

Rheumatoid arthritis is a leading cause of disability world-wide, afflicting up to one in a hundred individuals, according to World Health Organization estimates. About half of adults with the autoimmune disease are unable to work full time within 10 years of diagnosis. The findings of this study by an international consortium of researchers, including Dr. Siminovitch, offer new potential targets for therapy. She is the Director of the Office of Personalized Genomics and Innovative Medicine at Mount Sinai Hospital and a Senior Investigator at the hospital’s Lunenfeld-Tanenbaum Research Institute in Toronto, Canada.

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Free software for purifying mass spectrometry data

Researchers at the Samuel Lunenfeld Research Institute of Mount Sinai Hospital and the University of Toronto, as well as colleagues in Michigan and Scotland, have developed an innovative computational approach—the first of its kind worldwide—designed to analyze mass spectrometry data. The software, called SAINT (Significance Analysis of INTeractome), will allow researchers globally to quickly assess the reliability and accuracy of protein binding data helping to further their studies of cancer and other illnesses.

SAINT is described online in the leading international journal Nature Methods.

Dr. Anne-Claude Gingras

The tool was developed by Lunenfeld Principal Investigator Dr. Anne-Claude Gingras (Lea Reichmann Research Chair in Cancer Proteomics and Assistant Professor in the Department of Molecular Genetics at the University of Toronto), and Dr. Alexey Nesvizhskii (Assistant Professor in the Department of Pathology and in the Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor) to meet a key challenge in the field of protein mass spectrometry (a technology that helps researchers separate, identify, and quantify specific proteins): namely, to identify and quantify ‘true’ protein interactions gleaned from mass spectrometry data, and filter them from protein-based contaminants in the sample data. Previously, other approaches to analyze mass spectrometry data have not allowed for a probability-based model to measure and account for errors in a data set.

“SAINT allows researchers to identify the real protein interactions in their sample, and to exclude the false positives generated through contaminants,” said Dr. Gingras. “In effect, the software applies a much needed filter to purify the data and remove ‘noise.’”

SAINT was introduced earlier this year by Drs. Gingras, Nesvizhskii and Mike Tyers, when their teams generated a comprehensive road map of the signaling proteins that control many aspects of cellular behaviour in yeast cells (www.yeastkinome.org)—a discovery reported in a May issue of Science. However, the updated approach can be applied to a wider variety of datasets of various sizes and levels of protein network density.

“The first version of SAINT was intended to help us analyze very large-scale datasets, which is something that only a few laboratories worldwide are generating,” said Dr. Nesvizhskii. “We then realized that, with some modifications, the same approach could be extended to researchers specifically interested in knowing what a few proteins interact with inside the cell. This makes our approach very useful to most cancer biologists using mass spectrometry, as it enables them to quantify their interaction data.”

Drs. Gingras and Nesvizhskii are former research associates and have collaborated on various research projects over the past eight years, and bring together their expertise in biology and computational modeling, respectively.

“We come from completely different directions but have focused on this problem together,” said Dr. Gingras.

Dr. Gingras has encouraged many other scientists to use SAINT, and the software is being implemented at research institutes internationally. Drs. Gingras and Nesvizhskii, with study first author Dr. Hyungwon Choi (a post-doctoral Research Fellow in the Nesvizhskii lab), recently held a workshop at the Lunenfeld, at which almost 100 Toronto-based scientists and industry representatives learned of the advantages offered by SAINT.

“SAINT is a new and important software tool that—for the first time—allows us to assign a confidence value to every protein-protein interaction that we identify in our mass spectrometry studies,” said Dr. Brian Raught, Canada Research Chair in Proteomics and Molecular Medicine, and a scientist at the Ontario Cancer Institute. Dr. Raught attended Dr. Gingras’ workshop and uses the tool in his research.

“It has been truly instrumental in our work on deciphering the protein-protein interactions within complex intracellular regulatory networks, and thus represents a major advance in our field.”

The software is available for downloading at http://sourceforge.net/projects/saint-apms

The development of SAINT was supported by several agencies, including the Canadian Institutes of Health Research and the National Institutes of Health, as well as the Mount Sinai Hospital Foundation.

About the Samuel Lunenfeld Research Institute of Mount Sinai Hospital

The Samuel Lunenfeld Research Institute of Mount Sinai Hospital, a University of Toronto affiliated research centre established in 1985, is one of the world’s premier centres in biomedical research. Thirty-four principal investigators lead research in diabetes, cancer biology, epidemiology, stem cell research, women’s and infants’ health, neurobiology and systems biology. For more information on the Samuel Lunenfeld Research Institute, please visit www.lunenfeld.ca.

Identification of potential biomarker shows promise for the development of personalized thyroid cancer treatment

Toronto, ON ― November 15, 2010 ― Researchers at Mount Sinai Hospital and the University of Toronto have utilized proteomic technologies to discover proteins secreted by thyroid cancer cell lines to identify and characterize potential biomarkers for the future management of thyroid carcinomas.

The study recently published in the Journal of Proteome Research is of particular importance because these biomarkers have the potential to aid oncologists in determining the aggressiveness of the cancer so appropriate treatment plans can be developed for patients. Thyroid cancer represents 90% of all endocrine malignancies with an estimated annual incidence of 122,800 cases worldwide and approximately 33,000 newly diagnosed cases in North America.

Dr. Paul Walfish

“We know that about 10 to 15 per cent of thyroid cancers are aggressive. Our hope is that out of this research a diagnostic test can be developed that will allow us to detect aggressive forms of the cancer early so we create rigorous treatment plans that will help improve outcomes for patients,” said endocrinologist Dr. Paul Walfish, Alex and Simona Shnaider Research Chair in Thyroid Oncology at Mount Sinai Hospital, Professor Emeritus at the University of Toronto, and the senior author of the study. “On the other side of the equation, if we determine a patient’s cancer is a non-aggressive form the treatment plan can be less intensive, making it easier for patients to tolerate, and have a lesser impact on their quality of life.”

Dr. Walfish and his team employed liquid chromatography-mass spectrometry for identification of proteins secreted by aggressive and non-aggressive thyroid cancer cell lines. Among the majority of the 46 high confidence secretory proteins identified, 31 have not yet been reported in thyroid cancer demonstrating the ability of secretome analysis to identify potential biomarker candidates for correlation with clinical management of thyroid cancer.

“Six proteins secreted by thyroid cancer cells could be independently verified in cell lines, tumor xenografts in immunocompromised mice, as well as tumor tissues and blood samples of thyroid cancer patients,” said Dr. Ranju Ralhan, Co-Director of the Alex and Simona Shnaider Research Laboratory in Molecular Oncology at Mount Sinai Hospital. “This underscores their potential as candidate thyroid cancer biomarkers. Clinical trials will still need to be undertaken to validate our research, but we are very hopeful that this will lead to a diagnostic test.”

The studies also revealed that it’s the nuclear and/or cytoplasmic localization of these proteins in human thyroid cancer tissues that might have clinical relevance. Notably, similar subcellular localization of these proteins could be observed in xenografts of thyroid cancer cells in NOD/SCID/gamma mice as well. Importantly, prothymosin alpha (PTMA) was particularly elevated in aggressive anaplastic thyroid carcinomas compared to the more differentiated papillary thyroid cancer indicating it may serve as a marker for aggressive carcinomas upon validation in a larger study.

“To our knowledge this study is the first report on the identification of biotinidase and nucleolin in thyroid cancer,” added Dr. Walfish. “Further, in depth studies showed a protein called PTMA, a heterochromatin remodeling protein, is significantly elevated in well differentiated thyroid carcinomas compared to adenomas and non-toxic goitres.”

Large scale analysis of these proteins in sera of thyroid cancer patients and characterization of their expression in cancer tissues may serve as the next step towards evaluating their suitability as candidate cancer markers. Thus, these researchers have successfully demonstrated the application of proteomic technologies for discovery and verification of proteins secreted by cultured thyroid cancer cells and large scale validation will pave the way for development of minimally invasive biomarkers for future clinical applications in thyroid cancer as well as other epithelial cancers.

Dr. Walfish and his team including co-director Dr. Ranju Ralhan, Dr. Christina MacMillan and laboratory co-workers Lawrence Kashat, Anthony So and X. Meng of the Shnaider Laboratory of Molecular Oncology in the Department of Pathology and Laboratory Medicine, in collaboration with Dr. K.W. Michael Siu’s team in the Department of Chemistry and Centre for Research and Mass Spectrometry at York University, and Dr. Laurie E. Ailles in the Ontario Cancer Institute, University Hospital Network, developed a strategy to identify thyroid cancer biomarkers.

The research was made possible by support from the Mount Sinai Hospital Foundation Da Vinci Fundraiser, Alex and Simona Shnaider Chair in Thyroid Oncology, Temmy Latner Foundation and the Mount Sinai Hospital Department of Medicine Research Fund.

An abstract of the study entitled Secretome-Based Identification and Characterization of Potential Biomarkers in Thyroid Cancer can be found online at http://www.ncbi.nlm.nih.gov/pubmed/20873772.

source: University of Toronto Press Release