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)