Cancer Working Group
Immunology Reading GroupÂ
Thursday, September 15
12:30-1:30 PM
Kresge 502
We’re going to try a slightly different format this year. Instead of having 1-2 people give a presentation, we ask that you all please read this paper (a review of cancer immunotherapy in NEJM by Finn in 2008) and come in ready to discuss the following questions:
(1) A major motivation for the identification of tumor-specific antigens is targeted treatment. How does this approach compare to other therapies (e.g. chemotherapy, radiation therapy, hormone depravation therapy) that we’ve discussed in the past or you’ve seen in other courses? What are some benefits and potential drawbacks to this type of targeted therapy?Â
(2) One of the hallmarks of cancer is the lack of regulation in the cell cycle. The role of cyclin B1 is to transition the cell from G2 to M phase but becomes unregulated in cancer cells where overexpression of cyclin B1 can lead to uncontrolled cell growth. Discuss how the peptides from cyclin B1 that have been identified as tumor antigens may inform cancer research and treatment.
(3) What evidence is there that therapeutic cancer vaccines can improve prognosis for individuals with a high cancer burden?
(4) Why might oncologists prefer therapeutic vaccines combined with chemotherapy to chemotherapy alone (or immune therapy alone)? What have some studies shown with respect to chemotherapy after immune therapy? Do we have any ideas as to why this might happen?Â
(5) What cancer prevention (primary and secondary) measures might immunology research offer us?Â
Please contact Ina Jazic or Sarah Peskoe with any questions or comments.
PQG SEMINAR
Tuesday, September 20
12:30pm to 1:30pm
FXB G12
Bogdan Pasaniuc
Assistant Professor, Pathology and Laboratory Medicine
David Geffen School of Medicine, UCLA
Emerging methods from summary GWAS data to understand genetics of complex traits
Many complex traits and diseases share a correlation at a phenotypic level. Such correlations can be attributed to shared environmental or genetic architectures. Quantifying the correlation in phenotypes that is due to genetics is of great interest in understanding the causal relationship between complex traits. Standard approaches to estimate either require individual-level genotype data, or make assumptions (e.g. random-effect) that renders them less suitable for local estimation. Here I present new methods for estimation of local genetic variance/covariance and discuss their relationship with the recently proposed methods for gene expression prediction as a tool to integrate eQTL and GWAS for a transcription-wide association scan (TWAS).
Neurostatistics Working Group
Wednesday, September 21
12:30pm to 1:30pm
FXB G11
Lidia Moura, M.D., M.P.H.
Instructor in Neurology, Harvard Medical School
Assistant in Neurology, MGH
Director, MGH NeuroValue Laboratory
Value-Based Healthcare Delivery in Neurology
Poor prescribing quality and increasing costs continue to affect the United States health care system despite numerous reforms. However, without a fundamental change to our approach, a majority of the population, including providers, employers, and most importantly, patients, will continue to suffer. Lidia Moura will provide an overview of the application of the Value-Based Health Care Delivery framework for restructuring neurology health care systems. She will discuss her research findings, which cover: performance metrics in chronic neurological conditions, large-scale assessment of patient-reported outcomes, and principles of measuring cost of care in geriatric neurology.
Biostat Student Research Talk
Tuesday, September 20
12:30pm to 1:30pm
Biostat Conference Room
pizza will be served
Ryan Sun
Set-based inference with the Generalized Berk-Jones statistic
