- T-Cell Repertoires and Structural Relatedness: A New Approach to T-Cell Repertoire Analysis
T-Cell Repertoires and Structural Relatedness: A New Approach to T-Cell Repertoire Analysis
As part of our prep for AACR, we spoke with John-William Sidhom, an MD/PhD candidate working in Drew Pardoll’s lab at the Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins. Following are excerpts from our conversation:
Before we jump into your presentation topic, tell us about your background. It’s unusual, but seems especially well-suited to your area of research.
In college, one of my professors said that the most successful people don’t focus only on the things at which they excel; they jump into an exciting field and then figure it out once they land. That’s entrepreneurial thinking, for sure. I majored in bio-mechanical engineering, and minored in math and business – it involved a lot of computational work. After college, I headed into the world of medical device design and was thrilled to gain admission to Hopkins. Once there, I matriculated into the medical school because I saw how important physicians’ contributions are in the medical device design process. Another happy coincidence: coming to Hopkins meant that I was now at the most exciting clinical research center in the world.
From there, the leap to immunology was straightforward. Immunology is THE hot topic in medical school, and immuno-oncology is the most exciting area of all. I had never done this type of work previously, and in my first year of graduate school, I was terrible! I couldn’t culture cells, my projects weren’t working, but I overcame my early deficits and ultimately found an exciting niche where my skills and interests have found their best fit.
So what IS your current area of focus? How does that relate to immunoSEQ?
At present, I am 100% focused on bioinformatics, but when I first started, I didn’t even know about high-throughput sequencing! I remember meeting someone from Adaptive, and I just had no clue that we would ever need this kind of technology. I didn’t understand TCR sequencing; I thought in terms of “single antigen, single clone” because I didn’t understand the implications of clonality. But then I kept reading papers, and seeing others citing large numbers of sequences in their research. Lucky for me, the Adaptive team has been helpful and collaborative at every step of my own evolution. I believe their platform is the highest quality and the most reliable, bar none. But just as important, the people at Adaptive are amazing. I just recently met (Adaptive co-founder and Scientific Head) Harlan Robins at the SITC (Society for Immunotherapy of Cancer) conference last November. Harlan is inspiring; listening to him made me realize that intellectual power and creativity are at the heart of Adaptive Biotechnologies. I thought, “I need to figure out how to be like this guy. Don’t just take a hammer to this nail, but bring in a different skill set and apply it in a novel way.”
And so how has this “think different” mentality served you in your current work?
Well, that’s the topic of my presentation. I started to wonder if there were better or different ways to quantify the diversity of the T-cell repertoire? The idea is this: perhaps TCR structure is tied to function, in terms of to which antigen it binds. I call this analysis the ImmunoMap – a means to holistically quantify the relatedness of the T-cell response in the repertoire, or in comparisons of repertoires.
What do you mean by “relatedness”?
Sure. The classic example I give is this: you can have two files of sequences, each of which contains 10,000 sequences, each with the same distribution of clones. In the first file, all are identical except that they’re one amino acid off. In the second file, there are totally different sequences. Our ImmunoMap analytics look at the relatedness of the sequences, rather than the distribution of clones. Make sense?
Kind of. Tell us more.
In my AACR presentation, entitled ImmunoMap: a novel bioinformatics tool for immune cell repertoire analysis, I will go through two examples of the value of this analytic approach. What we explored analytically was the differences in antigen responses – foreign or self antigens – and how the TCR sequence structures shifted, pre and post tumor effect. It’s a somewhat complex analysis, so I’ll save the details for our presentation, but we had a hunch – just a hunch, mind you – that neo-antigen responses might have the potential for a more diverse T-cell repertoire, which in turn might make them more effective in tumor response.
We’ll be eager to learn more, at your presentation. Can you share the ultimate implications of this kind of analysis?
Sure thing. Many scientists are focused on developing biomarkers in response to checkpoint inhibitors. So an important question in that effort is – can we predict who will respond?
If we can figure out who responds to what, then perhaps we can combine therapies to triage people more effectively and get to higher overall response. Assessing the structural relatedness of T-cell repertoires – understanding repertoire diversity in response to tumor effect - may be one step that contributes to these goals.
Thank you for our discussion. One other thing: do you have any hobbies?
Yes! I love making music – I play the guitar and piano, and I sing. I also am hoping to qualify to compete in the American Open Series in Miami this July in Olympic weight lifting. Weight lifting is a big time sink: two- to three-hour sessions, five times per week. But that’s the beauty of computational work: once you code it, it can be working while you’re doing other things!
Join John-William Sidhom at AACR Session MS.BSB01.01 - Computational Cancer Biology
976 - ImmunoMap: a novel bioinformatics tool for immune cell repertoire analysis
Sunday, April 2, 4:20 pm, Level 1, Room 151 at the Washington Convention Center