2011 Finding Biomedical Markers in Lung and Cervix Cancer
February 10, 2011
Supervisor: Melania Pintilie
Location: Princess Margaret Hospital, Toronto
PMH/OCI has a leading role in cancer research with more than $100 million in external grant funding for the year of 2010. In the medical research world a large effort is directed towards personalized medicine and translational research. During this process, of great importance is the finding of genetic signatures and/or target genes which could be used for clinical decision making or finding new treatments. Once a target is found, whether a signature, individual gene or a probe-set, this needs to be tested in the laboratory in vitro and in vivo to validate the conclusion. A predictive signature may initiate clinical trials in which the patients are stratified based on the signature classification. A new treatment will initiate the series of clinical trials phase I-III to test its efficacy. For a statistician it is fulfilling to be part of an interdisciplinary team and to be able to observe and participate in these different aspects of the discovery process. At every ste p of the way the challenges are both biological and statistical. To give only several examples the finding of a signature from a set of 20000 (or more) features is daunting. LASSO is one methodology which could be used but it is not infallible. When treatments are tested in vivo (most of the time mice are used) the effect on tumour growth may not be linear even after making the necessary transformations. It is known that radiation produces an initial regression in tumour, but which is not subsequently sustained. This produces a wavy curve which needs to be modelled and the model’s coefficients need to be interpreted. One of the active groups working towards finding signatures to explain outcome is in non-small lung cancer. The group in PMH is led by world renowned scientists: Dr. Frances Shepherd and Dr. Ming Tsao. Dr. Shepherd is an international leader in molecular targeted treatments. She is the Chair of the National Cancer Institute of Canada Clinical Trials Group Lung Cancer Site and the President of the International Association for the Study of Lung Cancer. Dr. Shepherd received the 2008 Premier’s Summit Award for Medical Research, the IASLC (International Association for the Study of Lung Cancer) Scientific Award and is a Member of the Order of Ontario. Last year, Dr. Tsao and Dr. Shepherd received the Inventor of the year award, Dr. Tsao is Director of the Lung Cancer Translational Research Laboratory in PMH and Chair of the M. Qasim Choksi in Lung Cancer Translational Research. Another group working towards personalized medicine is led by Drs. Brad Wouters and Rob Bristow. The program is investigating the tumour microenvironment in cervix, pancreas and prostate cancer. The microenvironment of human tumors is, unlike that of any normal tissue, characterized by extreme heterogeneities in nutrient supply, pH, and oxygenation. These features develop as a consequence of alterations in the metabolic and proliferative status of tumor cells together with a highly irregular vascular supply. The program is investigating the tumor microenvironment with a primary interest in understanding the cellular and molecular responses to deficiencies in oxygenation (hypoxia) and their influence on the biological behavior of tumors. Besides being the co-director for the Hypoxia program, Dr. Wouters is also a senior scientist in the Selective Therapies Program, OICR. Dr. Bristow is the Head of CFCRI-PMH Prostate Cancer Research Program, Vice-Chair for the Strategic Partne rships and Networks for Prostate Cancer and Chair for the Translational Biology Group for Canadian Association of Radiation Oncologists. Dr. Bristow was twice awarded the Canadian Foundation for Innovation Award. Shortly after graduating from the University of Toronto with an MSc, Statistics, I started working at PMH. Besides performing statistical analysis I am involved in the teaching of several courses in University of Toronto. Within this activity I supervise students (one/academic year) for their practical section of their degree. I am also asked to review papers for a variety of journals. I have over 150 published papers. My main accomplishment is the publishing of the book on competing risks with Wiley. Currently I am working with the two groups introduced earlier. Two large arrayCGH microarray(aCGH) datasets are already available: one for lung cancer and one for prostate cancer. The goal for each is to find a signature which explains the outcome. Besides the size of the data and the fact that there are more features to analyze than patients, there are several extra challenges: extracting the useful information from the aCGH is not standard, the clones (which are the features in the aCGH) are usually scored as amplified or deleted, losing the continuous aspect of the expression data. We also have the opportunity to analyze a dataset obtained from the NanoString chip on xenograft data. Since this a completely new technology it is unclear what is up/down regulated. This analysis might prove to be an application to EM algorithms. A good part of my practice involves testing the effects of different markers for their association with outcome. From the basic research area the most frequent analysis is on the growth of tumours in mice under di fferent conditions, involving mixed effects modeling. The intern will be an integral part of the two research teams. S/he will participate in the regular meetings and have exposure to the multitudes of problems which the scientists are faced with. These meetings are informal and the intern will have the opportunity to ask questions and give ideas of how to approach an analysis. I will also arrange to have periodic meetings with the intern, although the intern will be able to approach me at any time when s/he will have questions or concerns. The intern will have the opportunity to analyze the data and present it to the lung group. It will be beneficial if the intern has good knowledge of modeling and some knowledge of survival analysis. Most of the work will be done in R software and working knowledge of this software is an asset.
The University of Waterloo is a well known hub for mathematical and statistical work. We are honored to be considered as part of the process of forming new statisticians. We believe that the intern will benefit from the exposure to international leading scientists, real world data and the analysis of data coming from cutting edge biomedical technology.