It turns out managing a blog is really hard during the assistant professor years. As in, I've posted on average once a year since I started this job...
So -- in hopes of doing better, we're going to start something new!
Each week in Theory Division we have lab meeting (which in itself is worthy of a post -- turns out no one teaches you how to run these, and how to best do it changes a LOT depending on the size of your lab), and we also have a one hour slot separately for either journal club, or for a long form research talk. Given the pandemic, these have been done via Zoom, and so have been recorded. So, what we are going to do is, for each long form research talk we will post the recording to our new youtube channel, along with a short textual abstract here on the blog with a link to the talk.
I'll start things off!
Just yesterday, my colleagues and I had a paper come out in the Journal of Thoracic Oncology:
This paper was the subject of my Peter Canham lecture in biophysics at Western University this year -- and we have ported this talk to be our first in the channel -- head over to the channel to watch/subscribe!
In this talk I discuss some of the frustration I feel as a radiation oncologist that our field has not yet entered the era of personalized medicine -- that is, each cancer patient doesn't have their radiation therapy (DOSE!) tailored to their tumor's genomic profile. Certainly, each prescription is physically personalized (geometrically), but biologically personalized dosing is not yet standard of care. Starting with the beautiful opening (to use a chess analogy) starting with a breakthrough creation of a Radiation Sensitivity Index (RSI) which linked canonical ideas of SF2 in radiation biology to genomics, by my friend and mentor Javier Torres-Roca, he and I and our colleagues have slowly and methodically moved through the middle game, setting the stage for a relationship to dose, which we outlined in our article: A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study.
We then (I hope) end the middle game with this paper from yesterday (see above), where we use information about what dose is needed to optimize a given patient's tumor control to then make inferences about OVER and UNDER treatment -- and using a novel combined model of TCP and NTCP, determine how much we could make radiation therapy better right now.
So - head on over to our youtube channel, watch the video, let me know what you think! And subscribe to see future talks in our lab!