Catching cancer at its earliest stages,
when it's most treatable, can save countless lives.
But the million-dollar question is:
in an otherwise healthy body made up of trillions of cells,
how can we zero in on a small group of rogue cancer cells?
The answer, I think,
may be rooted in something that, thanks to the pandemic,
we have all come to know quite well, and that is RNA.
I think these days, everyone has a basic understanding of how RNA works.
Again, thanks to the COVID vaccines.
But basically, RNA is transcribed from DNA in the cell,
and messenger RNA specifically serves as a template for protein synthesis.
So usually the more mRNA you have in the cell,
the more protein you get.
But our discovery is a little bit different.
We have found a new class of RNAs
that have changed how we think about cancer detection.
These are relatively small RNAs,
and they don't actually code for any protein.
So they're non-coding.
And since we found them, we got to name them.
And we have called them orphan non-coding RNAs
or oncRNAs for short.
These oncRNAs have not only changed
and transformed our approach to cancer detection
from blood non-invasively,
but they've also helped open a window into the tumor itself for us.
So leveraging these RNAs,
we are not only detecting cancer earlier,
we are actually peering into its biology.
So with that short introduction, let me break down the science for you.
As you may know, every cell in our body shares the same genetic code
as every other cell.
It's as if our cells have access to the same pantry,
but then they use different recipes
to mix the same ingredients into different dishes.
It's actually the diversity in genomic recipes
that gives us the more than 200 cell types we have in our bodies,
each with their own distinct role and function,
like skin cells, for example, or neurons.
And as you can imagine,
there is a complex machinery in place in the cell that governs this process
and tells the cell for each of its 20,000 genes
how much of them it needs to express
to be a healthy, well-functioning cell.
Now, cancer cells, being the resourceful survivalists that they are,
they actually hijack components of this machinery to their advantage.
And they do this to increase the expression of genes
that will help the tumor grow and spread throughout the body,
or silence or down-regulate genes whose job is to keep cancer in check.
Another way of putting this
is that cancer cells are basically hacking that original genomic recipe
that I told you about.
Now a few years ago, we made an interesting discovery
that is actually a consequence of this genomic reprogramming
that happens in cancer cells, is actually a hallmark of cancer.
Basically, parts of the genome that is normally silent
and inactive in healthy cells
becomes activated in cancer.
And a direct consequence of this activation
is the birth of a new kind of RNA.
That we only see these RNAs in cancer,
but not really in healthy cells.
Now over the past few years,
we have spent a lot of time basically mapping these cancer-emergent RNAs
across human cancers.
And as I told you earlier,
we have come to name them oncRNAs.
Now, what is even more interesting
is that which oncRNAs I see in a given sample is not random.
It's actually tied back to the type or subtype of cancer
that I'm looking at.
So collectively, oncRNAs actually provide a digital molecular barcode
that captures cancer cell identity.
And it's actually unique to the type or subtype of cancer.
But how are these molecular barcodes actually useful?
So it turns out oncRNAs are not actually confined to cancer cells.
Some of them are nicely packaged and released into the blood.
And this is something that healthy cells do as well with other small RNAs.
And with all of this introduction, I hope you know where I'm going with this.
Basically, if oncRNAs are only expressed in cancer cells,
and some of them do in fact find their way into the bloodstream,
doesn't it mean that we should be able to detect them
in blood samples from cancer patients?
The answer, turns out, is yes, but with an asterisk.
So the oncRNAs that we detect in blood samples from patients
actually form a partial barcode.
And it's only a partial barcode
because only a subset of oncRNAs
are actually secreted from cancer cells into the blood.
And even a smaller subset can be reliably detected
in a small volume of blood.
However, thanks to the magic of machine learning and AI,
we can actually use this partial information
to reconstruct the original barcode that resides in the tumor.
And we can match that deconstruction
against our catalog of oncRNA barcodes across cancers
to not only --
to not only detect the presence of the disease,
but also identify its type or subtype.
And actually, as we grow,
fundamentally increase the number of these oncRNA catalogs that we have built,
we can go deeper and deeper into the biology of the disease as well.
Now, with help from our clinical collaborators at UCSF,
we have come a step closer to actually bringing this platform to the clinic.
In a preliminary study across 200 breast cancer patients,
we have actually shown that we can use oncRNAs
to detect residual disease in patients
after they have received treatment,
and knowing which patients have remaining disease,
tells clinicians who needs additional treatment or monitoring
after the surgery.
And this way, patients receive more treatment
only when it's needed.
I truly believe that the next decade is the decade of cancer screening.
And as you can imagine, blood detection of cancers
is a major frontier in that war.
And I hope to have convinced you today that leveraging powerful AI
built on top of molecular barcodes of oncRNAs,
we can envision a future that’s precise and sensitive,
but more importantly,
very accessible.
Blood detection of cancers is not just the hope,
but it's actually a reality.
Thank you.
(Applause)