Jianjiong Gao: The Cancer Genome Atlas as the name suggested
has been focusing on genomic -- identifying genomic events and did not include larger
scale proteomics profiling.
And the -- Gordon Mills [spelled phonetically] and Yiling Lu [spelled phonetically] from
MD Anderson they just started to measuring protein levels [spelled phonetically] and
phosphoprotein levels in TCGA sample, and we kind of [unintelligible] this data and
we're playing around with it and we try to correlate those proteomics data in -- where
those genomics alterations.
And I should point out that this presentation is not about working in progress and we're
just started to scratch the surface of this interesting data.
And this one, so RPPA, it stands for Reverse Phase Protein Array and it's high-throughput
proteomics technique to measure protein level and the phosphoprotein level in relatively
-- relatively inexpensive way and each slides [spelled phonetically] is developed with a
single antibody and can contain up to 1,000 samples which can choose and there are currently
about 300 [unintelligible] antibodies available.
The -- Yiling Lu and Gordon Mills from MD Anderson, they have generated those RPPA data
so far in six cancer types for more than 2,000 samples and including like about 200 antibodies
among which 50 antibodies are phosphorylation antibodies.
Here I list a few for protein antibodies that including like P10 [spelled phonetically],
TP53, ER, AR, and AKT, et cetera.
For phosphoprotein antibodies including AKT, EGFR, or B2 [spelled phonetically], MAPK,
et cetera, and we should note that several of the genes have both protein level and the
phosphoprotein level for example the ErbB2/ErbB3, AKT, and MK [spelled phonetically].
And this is a pathway overview of the antibodies.
The pink and orange dot indicate that the particular gene have phospho-antibodies [spelled
phonetically] -- phospho-antibody and protein antibody respectively.
And from this view it's clear that the antibodies actually covers a lot of members in those
interesting, important signaling pathways in cancer.
And one might thought that if this technique RPPA, if it is working for TCGA examples and
in the next few slides I will just briefly give some examples that can confirm our expectation
from the data.
And here the ErbB2 [unintelligible] the correlation between ErbB2 mRNA protein level and the phosphorylation
level, and from this slide we can see that the ErbB2 phosphorylation level is highly
correlated with ErbB2 [unintelligible] expression and ErbB2 phosphorylation level is also correlated
with the ErbB2 protein level.
And we also study -- compared the ER and GATA3 protein level in breast cancer subtypes and
expected the protein level of basal-like and HER2 as significantly lower than the Luminal
impulse [spelled phonetically] and the same with the GATA3 protein level.
And as Giovanni have mentioned and the P10 deletion and under-expression are highly correlated
with AKT phosphorylation, actually it's across multiple cancers.
And so I hope that at this point I -- we -- I kind of -- we have more knowledge about this
RPPA.
We have some confidence in the RPPA technology and we want to dig into this AKT phosphorylation
in breast cancer.
So the AKT activation phosphorylation has been found in many cancer types and phospho-AKT
[spelled phonetically] has diverse targets regulating a lot of important process in cancer
and phospho-AKT contributes to breast cancer progression and confers [spelled phonetically]
resistance to conventional therapies inhibiting phosphor-AKT could be beneficial to some patients.
Sorry.
Male Speaker: You [inaudible]?
Jianjiong Gao: Okay, this is a box plot and histogram for
two important phosphorylation site levels in AKT and clearly we can see that there is
a long tail for both of the phosphorylation site that has higher phosphorylation level.
The question is what genomic event causes AKT activation in breast tumors?
From our pathway overview, we have some usual suspects including like P10, KRAS [spelled
phonetically], ErbB2, and PGFR1 [spelled phonetically], and PIK3CA [spelled phonetically]; and as
expected -- as I have shown and the P10 deletion loss of expression is highly associated with
phosphor-AKT but not P10 mutation.
And for those KRAS, ErbB2, FGFR1, and PIK3CA, actually they are not highly associated with
high AKT phosphorylation level.
So we wanted to know what other genomic events can explain AKT phosphorylation in breast
cancer?
To approach that we separated the samples into AKT high phosphorylation and AKT low
phosphorylation and performed enrichment tests of all GISTIC [spelled phonetically] reaching
of inches [spelled phonetically] and frequently mutated genes and we found a couple of interesting
carbon number change.
These two and a few mutations that are significant frequently [spelled phonetically] altered
in AKT high with examples with higher phosphorylation of AKT and we actually test all these genomic
events and find that CAMK1D amplification and AKT1 E17K mutation may be related to higher
AKT phosphorylation level.
Again, I should mention -- again this is just a surface, we just scratching the surface
of those great data and we think that the data is very interesting and definitely worthwhile
to gain more.
And we found that it's -- we have all observed very good correlation between genomics and
proteomics data on the level of individual genes and proteins.
And -- but the downstream effects of protein level and phospho-protein level is harder
to link to genomic events for in the case of AKT phosphorylation we can explain some
but not all.
We're in the progress to systematically investigate those genomic events combinations and of -- for
all antibodies.
And we think that correlations between phosphorylation data may have elucidated [spelled phonetically]
activate signaling pathways.
This RPPA data has been integrated in the cBio GDAC [spelled phonetically] Portal and
with that I would like to thank Nikki [spelled phonetically], Giovanni, Ethan, Ben, and Chris
from MSKCC and Gordon Mills, Yiling Lu, and the RPPA team from MD Anderson.
And thanks for your attention.
[applause]
Male Speaker: Thank you, Jianjiong.
Male Speaker: Thanks.
Jianjiong Gao: Thank you.