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- Hi everyone. We're here with Janani.
Who's a first year graduate student.
And she recently completed a laboratory rotation
in the Miller-Jensen lab, where she used systems biology
approaches to study melanoma, which is a very,
or can be a very deadly form of skin cancer,
especially if not caught early.
So, Janani, can you tell us a bit about what you were
trying to figure out?
- Yeah. Thank you so much
for that wonderful introduction, Doro.
So, melanoma is one of the most deadly forms
of skin cancer.
Unlike most cancers, it's really difficult to treat
because if its ability to hide from our immune response,
which normally finds and destroys abnormal cancer cells.
And the most popular treatment option for this is a therapy
that targets this immune response called checkpoint
inhibitor therapy, which removes the cancer cells' ability
to hide from the immune cells.
And therefore our normal immune response against tumors
can effectively remove the cancer.
However, this option is only effective for 50% of patients,
and we want to understand why this treatment is not
effective at removing the cancer for some of these patients.
- Wow. That'd be great to make that an effective therapy
for 100% of the patients.
So how does systems biology actually help you figure out
and ensure that the immune system is able to find
and kill, destroy cancer cells?
- Yeah, so one way we can approach this question is
to investigate the sources of such complexity
in the immune system and tumors
and the immune response to tumors rely on a web
of cell to cell communication pathways.
And one example of cell to cell communication is
an immune cell that recognizes
and destroys an abnormal cancer cell.
Now, in reality, in the tumor,
there are actually several immune cells,
tumor cells and supporting stromal cells that are all
involved in the immune response against tumors.
And each of these cells has several different ways of
communicating with other cells. And this forms the complex
web of communication.
So as scientists,
we can use multiple technology platforms to learn more about
how these cells are communicating and determine important
interactions in the immune response that we can target
with the hope that what we've learned about melanoma can be
applicable to other types of cancer as well.
- So, how do you go about targeting one of these
cell to cell communication pathways or even know
which pathway to target given that it's this whole web of
cells that make up these communication pathways.
- Yeah, that's a great question.
So we can start by using mouse models of melanoma to look at
all of the cells involved in this complex tumor immune
response, without biasing, which cells or which
communication pathways we're looking for.
And then we can use computational tools to evaluate these
different cell communication networks that may be present in
the tumor immune response, and then generate hypotheses
about which pathways we can maybe target.
And so this is the stage that we are in trying to figure out
the pathways that we can target. And once we have
determined this, we can then test these hypotheses using
simple cell models with just a couple of immune cells
and tumor cells, and then expand this to more complex
mouse models to verify these hypotheses. And together,
the goal will be to establish different ways in which
we can target and enhance immunotherapies such as
checkpoint inhibitor therapy.
- Wow. You know, it's not the first research project
that we have heard about where you guys are employing
both wet lab experimental approaches and computational
approaches to really get at your question that
you're asking. Is this something that you enjoyed in this
particular research experience?
- Yeah, for sure.
This is an approach to science that I really liked.
And one thing in particular, was combining computational
and experimental approaches to solve a problem.
Like for example, as we get more data about the biology
of cancer, we can use computational analyses to then glean
important information about the patterns in these data.
These hypotheses can then be incredibly informative for
guiding experiments that may be most promising for solving
our initial questions. And my hope in my PhD is that
by combining the strengths of computational and wet lab
experimental approaches in biology, we can understand
the complexity of biology and then also propose simple
solutions for diseases such as cancer.
- All right. It'll be exciting to see which lab you end up
joining and what project you end up working on your PhD.
Thanks so much for telling us about your lab rotation.
- Thank you so much, Doro. I really enjoyed it.
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