Kadir Akdemir: Hello everyone. I'm sure many of you are hungry
now, but please bear with me for the next 10, 15 minutes. My name is Kadir Akdemir.
I'm a post doctorate fellow in Lynda Chin's lab. And first of all I would like to thank
the organizers to give me this opportunity to present our work about understanding the
evolution of the epigenome in melanoma progression.
So melanoma cells can exhibit plastic behavior, and in this study I'll also show that epigenome
immunotherapy, melanoma cells can go to reversible dedifferentiation process, which results in
the resistance to the therapy and the tumor growth. The fact that this cellular state
change is reversible suggests an underlying epigenetic component of this therapy resistance.
And recently, several groups have reemphasized the role of epigenomic changes in the human
[unintelligible], such as the case of loss of 5-Hydroxymethylcytosine in melanoma or
[unintelligible] signatures in human colon cancer. And AACR Cancer Epigenome Task Force
recommends establishment of an international cancer epigenome project to map and define
the number of cancer epigenomes that might help us to do a little bit better therapeutic
studies.
So the overarching question in this project is how does epigenome contribute to melanoma
progression? And we would like to understand what changes in Chromatin when the normal
melanocytes became primary melanoma and from primary melanoma to metastatic melanoma.
So first, we start with the cell line system. And this cell line system first initially
developed by David Fisher's lab, where they immortalized the primary human melanocytes
with TERT& Expression as well as p53 double negative, CDK4 mutation, and BRAF V600 mutation.
However, these alterations were not enough to produce the tumors in mouse. So we called
them non-tumorigenic. And when we add PTEN knockdown [spelled phonetically] in addition
to these alterations, as you can see, that there's a drastic formation of the tumor in
mouse. And, but we need to over express [unintelligible] to get the metastatic tumors in the mouse.
So we called this shPTEN level that's pro-tumorigenic, and shPTEN [unintelligible] over expression
as metastatic.
So initially we focused on the changes happening from non-tumorigenic to pro-tumorigenic cell
lines. And we are utilizing a method called High-Throughout ChIP-Sequencing, which is
initially developed [unintelligible] Institute, which helps you to paralyze the ChIPing [spelled
phonetically] protocol. And currently we can ChIP all [unintelligible] validated antibodies
for a given cell type.
So this is our initial results. When we compared the pro-tumorigenic epigenome to the non-tumorigenic
epigenome, what we observed a global loss of histone acetylations, as you can see four
different acetylation marks. And these changes are generally happening around the transcription
start site of the genes that are -- that can be associated with apoptosis DNA application
or cell cycle.
And more interesting then when we checked the de-acetylated enhancer images, the motif
that we found was putative tumor-suppressors such as FOXO3or RUNX1. And what we think is
going on is that pre-existing chromatin landscape is affecting the binding of this tumor-suppressors
and thereby affecting their regulatory functions. So if the chromatin is highly acetylated,
this transcription factors can bind and affect the gene regulation. However, the low is -- the
chromatin is low acetylated, then this transcription factors cannot bind effectively.
And there is supporting evidence coming from a recent publication [unintelligible] showed
that the initial enhancer marks the influential for the FOXO3 binding [unintelligible].
So next, we switch our focus from the cell line data, and we would like to learn -- know
what is happening from normal melanocyte to melanoma tumors. For this purpose, we acquired
10 melanoma tumor samples that is profiled by the TCJ project. And we had to optimize
our HD ChIPsing [spelled phonetically] matter to use a small number of cells, as the tissue
source was finite. So currently we can't ChIP the -- an antibody for a thousand to 10,000
cells. And so far we have profiled 36 histone marks, two forms of RNA polymerase, three
histone variance, and genomic insulator CTCF for eight tumor samples, and so generated
6 billion reads. And we think this is the biggest cancer histone modification data set.
But we are still in the data production stage, as you can see for certain -- certain marks
we are missing enough coverage for the certain tumors.
So the important question that we would like to know, answer is that which developmental
pathways are highjacked during melanoma genesis. And the idea came from a recent cell paper
from John Stanberg [spelled phonetically] at University of Washington when they studied
the DNA's hypersensitive sites at the tumor cells. DNA hypersensitivity assay is a way
to measure the regulatory regions in a given cell type. And these sites are generally in
good concordance with the active histone marks.
So the overall message from this paper is that, compared to the normal counterparts,
the cancer cells acquire a certain amount of regulatory regions, and many of these regions
are either overlapping with the sites that are active at embryonic stem cells, or they
are active in the different lineages.
So the take-home message is new oncogenic sites that the -- that are actually older
developmental pathways and cancer cells do not reinvent the wheel every time. They use
the already-existing arsenal of the regulatory sites.
So then we would like to compare the changes happening from normal melanocytes to melanoma
tumors. The one that in the normal human development from embryonic stem cells to Precursor cells
and the fetal or adult tissue. And for this purpose, we are using the data coming from
another NIH-funded project, Roadmap Epigenomics, that they profiled 127 different human body
cell types.
And here I am showing initial results for the H3K4 monomethylation site evolution. And
these results are overlapping with the models observed for the DNA's data. Once, when we
looked at the sites that are obtained in melanoma compared to the melanocytes, 24 percent of
these sites were active with the embryonic stem cells and 70 percent were active in the
different lineages. Only 6 percent are novel or unknown.
Here I am showing an example site that is gaining some K4 monomethylation for certain
tumors, melanoma tumors. And when you check the DNA signal, you can see these sites were
open in different cell types. And just to be sure this signal is not coming from the
[unintelligible] tissue with the different cell types; I profiled the DNA's hypersensitivity
coming from melanoma or melanoma-- melanocyte cell lines. And the sites gained H3K4 monomethylation
in melanoma tumors exhibit a very high DNA signal in melanoma, but not in melanocytes.
Another evidence is that when we look in other region that gained K4 monomethylation in melanoma
what we observed is that, in addition to the modest increase for DNAs, what we also observed
a binding site gaining of MITF, lineage-specific master regulator, in its specific master regulator
in melanoma; nothing in melanocytes. So that suggests these gain sites are somewhat functional
for the melanoma genesis.
And lastly, what we would like to also do is the -- to check -- to annotate the non-coding
variants in the cancer genome by integrating our epigenomic data sets. Given that the TERT
promoter mutations have been recently reported, I think we are just scratching the surface
for the non-coding mutation functionality.
And first, we focus on the GWAS locations. FTO GWAS has been identified for over 12,000
melanoma patients compared to the 55,000 controls. And first, I am showing you our cell line
data. As you can see in our pro-tumorigenic cell lines, we are losing the active histone
marks. And we also check these sites for our human tumor data, and you can see the similar
to that. In normal melanocytes we have a strong signal for H3K27 acetylation. In melanoma
cells this signal is gone, as well as you can see this DNA's hypersensitivity signal
is also going down in melanoma cells, and the cells are losing their MITF binding cells.
So as a summary, what we think is that understanding the epigenome in the human cancers, in this
case melanoma, could help us to understand where to target, or what the mutations to
prioritize and the-- can improve the therapeutic strategies.
With that, I would like to thank my mentor, Dr. Lynda Chin, and take a moment to thank
a close collaborator and a good friend, Kunal Rai, who has [unintelligible] all the ChIPs
in this project, as well as Emily Keung, with all the lab members , the computational group,
and [unintelligible], and the rest of the collaborators.
With that, I would like to thank all of you for your time and patience. I will answer
any questions.
[applause]
Male Speaker: So is this a TCGA-funded project or is this
outside the TCGA?
Kadir Akdemir: So this is outside.
Male Speaker: Okay, and where are you going to make the
sequencing results available?
Kadir Akdemir: So we are still in the data production stage,
and we are doing the QCs just to be sure that whatever we are producing is the real tumor
samples. But once we have the good, quality data, we were planning to do that.
Male Speaker: Okay, thank you very much. So this concludes
the morning session. Just housekeeping. It looks like we have lunch until 2:00, and then
the poster session starts, and then Session 5 starts at 3:00 in this room.
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