transcript the epigenetics challenge dna methylation ......2 finally, thank you to new england...
TRANSCRIPT
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The Epigenetics Challenge: DNA Methylation Research from Basics to Biomarkers
[0:00:00] Sean Sanders: Hello and welcome to this Science/AAAS webinar. I’m Sean Sanders,
commercial editor and webinar editor at Science. The topic for today’s discussion is epigenetics. This rapidly growing area
of research examines how the covalent attachment of chemical groups to DNA and its associated histone proteins can influence phenotype without alteration of the DNA sequence. Such modifications often result in the alteration of gene expression levels that determine cell fate. Epigenetic marks are somatically inherited and therefore can be passed on as disease cells replicate.
In this webinar, viewers will gain insight into the current status of
epigenetic research with an emphasis on understanding the mechanism and effects of DNA methylation. Current methods associated with epigenetics research will be discussed as well as how these technologies are advancing the development of new diagnostics and biomarkers.
It gives me great pleasure to introduce our three panelists for today. To
my left we have Dr. Michael Teitell from the David Geffen School of Medicine at UCLA in Los Angeles, California; next we have Dr. Adam Karpf from the Roswell Park Cancer Institute in Buffalo, New York; and finally, Dr. Alex Meissner from the Broad Institute of MIT and Harvard in Cambridge, Massachusetts. Thank you all for being with us today. Good to have you here.
Each of our speakers is going to give a short presentation, after which we
will have a Q&A session during which the panel will address the questions submitted by you, the live audience. A reminder to the online viewers that you can see an enlarged version of the slides by clicking the enlarge slides button located underneath the slide window of your web console. You can also download a PDF copy of all of the slides by using the download slides button. As I mentioned, if you’re joining us live, you can submit a question to the panel at any time by typing it into the ask‐a‐question box on the bottom left of your viewing console below and clicking the submit button. Please remember to keep your questions short and to the point. That will give them the best chance of being put to our panel.
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Finally, thank you to New England Biolabs for the sponsorship of today’s webinar.
Now, I’d like to introduce our first speaker for this webinar, Dr. Michael
Teitell. Slide 2 Dr. Teitell received his M.D. and Ph.D. degrees emphasizing Molecular
Immunology in the Medical Scientist Training Program at UCLA before pursuing postdoctoral studies at UCLA, Harvard Medical School, and UCSF. He trained clinically in Anatomic Pathology at Brigham and Women’s Hospital, in Clinical Pathology at UCSF, and was a fellow in Pediatric Pathology at the Los Angeles Children’s Hospital.
Dr. Teitell is now a professor of Pathology and chief of the Division of
Pediatric and Neonatal Pathology in the UCLA School of Medicine. He is co‐director of the Jonsson Comprehensive Cancer Center Cell Biology Program Area and co‐director of the UCLA Center for Cell Control. The Teitell lab studies the immune system, developments in the immune system and cancer, focusing most strongly on DNA methylation and genetic regulation. His group uses genome‐wide and gene‐specific DNA methylation analysis to identify aberrantly silenced tumor suppressor genes in B cell leukemias and lymphomas.
Welcome, Dr. Michael Teitell. Dr. Michael Teitell: Thanks very much, Sean. It’s a pleasure to be here. Today, I’m going to
discuss studies related to DNA methylation in cancer. Slide 3 The outline for my talk will include the general topic of epigenetics, some
basics about DNA methylation, an overview of the DNA methylation in cancer, some of the methods used for analyzing DNA methylation, and the work that we’ve done in our lab on DNA methylation and TCL1‐driven B cell malignancies.
Slide 4 So, epigenetics is the heritable, reversible modification of DNA and
chromatin that doesn’t change the primary nucleotide sequence. In particular, there’s DNA methylation which can be a methyl group appended to the 5’ carbon of cytosine and another type of methylation
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that I will not discuss much in this discussion, which is the hydroxymethyl alteration of that same carbon in cytosine by the TET1 molecule.
There’s also histone modifications such as acetylation, methylation,
phosphorylation, ubiquitylation, and SUMOylation, which modify the chromatin structure and probably other modifications that alter the ability to express genes such as microRNAs, particularly in plants.
Slide 5 The human genome project actually sequence four or five nucleotides
because cytosine at the 5’ position that’s methylated within a CG dinucleotide sequence usually is not distinguishable from cytosine that’s unmethylated by the usual methods of DNA sequencing.
Slide 6 It’s been established that some of the roles for DNA methylation in
mammals include X chromosome inactivation, genomic imprinting, suppression of parasitic sequences and repetitive elements as you see here, and what I’ll focus on most, which is the regulation of gene expression.
Slide 7 DNA methylation can block transcription factor binding simply by
interference. Slide 8 And it can also cause the recruitment of methyl‐CpG binding proteins and
associated co‐repressors to drive the compaction of chromatin into heterochromatin and make unavailable genes for expression.
[0:05:00] Slide 9 Methylation can occur in a de novo fashion from regular cytosine in
which case the DNMT or DNA methyltransferase 3a and 3b molecules along with the cofactor S‐Adenosyl methionine will append a 5‐methylcytosine group onto cytosine. This occurs in pre‐implantation embryos, germ cells, and probably in somatic cells with aging.
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DNA replication also causes a methylated position, the CpG dinucleotide to become heavily methylated, in which case the maintenance methyltransferase DNMT 1, along with S‐Adenosyl methionine can remethylate that position and maintain methylation within an organism at that position, or if DNMT 1 doesn’t work, then passively the methylation at that position can be lost. In addition, there’s probably mechanisms of active DNA demethylation such as by activation‐induced cytidine deaminase or AID and also potentially the TET1 molecule.
Slide 10 Prokaryotes use DNA methylation on two distinct sequences in order to
protect their genome from invasion by parasitic elements such as bacteriophage, in which case their restriction enzymes that are methylation sensitive can cut the bacteriophage invading sequence but not their own sequence.
Vertebrates, on the other hand, have DNA methylation that’s mainly
found outside of promoter regions of genes that contain so‐called CpG or CpG‐rich islands, and these genes number about 50% to 60% in the human genome.
Slide 11 In normal cells, the CpG islands are protected from methylation, and the
methylation in these slides is shown by those filled‐in circles that you can see in the slide. Methylation mainly occurs outside the CpG islands of the normal cells. But in cancer, there is a global demethylation because most methylation is outside of the CpG islands and CpG island hypermethylation that can affect as an example tumor suppressor genes that represses their transcription. There can also be CpG island demethylation of as an example imprint genes.
Slide 12 The process of deamination actually links genetics and epigenetics in the
sense that a position 5‐methylcytosine can be transversed into a thymine by the loss of an amine group, and that’s a spontaneous irreversible mechanism and occurs mainly in the CpG‐suppressed regions outside of islands to yield a very high content of TG sequences as opposed to the expected frequency of CG sequences.
Slide 13
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So going back to original biology related to Knudson’s “two‐hit” hypothesis in cancer for tumor suppressor genes, we’ve often of that as a genetic alteration of a tumor suppressor gene where there can be a mutation or a deletion, but now you have to add to that potential at least the process of methylation causing the loss of expression of a genome in both alleles.
Slide 14 There’s many methods for DNA methylation detection and all these
strategies really are based upon three approaches or their combinations. Digestion of DNA with methylation sensitive and insensitive enzymes, followed by some form of identification, is one method. Chemical modification of DNA by bisulfite and alkali, followed by identification, is a second method. And purification of methylated or unmethylated fractions of the genome using antibodies or methyl‐binding protein fragments, followed by identification, is a third method.
Slide 15 Some of these methods provide mainly sequence‐specific information
and in my talk at least I’ll focus a little bit on genomic bisulfite sequencing and there’s a large list of this here.
Slide 16 And there’s also methods of genome‐wide DNA methylation profiling.
Again, this is an incomplete list and I’m actually going to focus a little bit on an older method for this restriction landmark genome scanning.
Slide 17 So my lab studies very heavily tumors that originate from the germinal
center of lymphoid tissues, and what you see here in the histologic depiction is a lymph node germinal center that’s a very special place in which B cells actually proliferate a very high rate of speed and they have ongoing active DNA damage.
Slide 18 We asked a question a long time ago what are transforming genes that
are implicated in driving tumors that arise from that stage in development and identified too much TCL1 expression in many of the tumors that you see listed here from human samples. We also made a
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TCL1 transgenic mouse and you can see that in the bottom right two panels, where the spleen would become the size of the liver and the mouse would also succumb to disease related to too much TLC1 expression.
Slide 19 But too much TCL1 expression driving tumors from this stage in
development doesn’t happen all at once and there must be other alterations that actually drive the development of these tumors, not only genetic changes but also epigenetic changes. And so we ask the question, do epigenetic changes cooperate with TLC1 to transform B cells.
Slide 20 To address this question, we used restriction landmark genomic scanning
which is really a technique that uses a methylation‐sensitive enzyme Not1 to survey selected CpG islands within the genome and typically surveys about 2000 spots. What you get in a two‐dimensional gel electrophoresis that’s analyzed here is a representative and reproducible pattern of spots within the genome that are hypermethylated.
[0:10:00] Slide 21‐22 As an example, what you see here in the left panel is a normal TCL1
transgenic spleen where you have spots that are reproducible in the two tumors, a diffuse large B cell lymphoma and the Burkitt lymphoma, except for the spots 2E3 and 2E5 where the spots in the diffuse large cell lymphoma are missing and the spot 2E5 in the Burkitt lymphoma has actually lighter intensity. This indicates positions of hypermethylation potentially in these gene fragments.
Slide 23 We can go on and figure out whether or not this is a validated
hypermethylation by genomic bisulfite sequencing where a 5‐methylcytosine can’t be converted to uracil, but a cytosine can be converted to uracil by sodium bisulfite treatment.
Slide 24
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That conversion to uracil is then picked up by sequencing algorithms or by a genomic southern blot.
Slide 25 So what we’ve found was that one of the spots that I showed you in the
previous slide was actually the Sprouty 2 tumor suppressor gene that’s known to repress signaling through the MAP kinase‐ERK signaling pathway. As you can see in the top panel of clones, the spleen, there’s basically no methylation which is identified by filled‐in circles, but on the top bottom two tumors that arise from this animal model, a Burkitt‐like lymphoma and a diffuse large cell lymphoma, you can see hypermethylation. And in a work not from our lab shown on the right panel, what you can see is that methylated Sprouty 2 actually has a poor outcome for patients who have diffuse large cell lymphoma providing clinical relevance for this process.
Sprouty 2 RNA expression in many of the tumors in our mouse model is
repressed during development of tumors and the Sprouty 2 expression can be reactivated by treatments that block DNA methyltransferases such as 5‐azacytidine.
Slide 26 Sprouty 2 methylation is also found in human lymphomas as well as
silencing and the transformed cell lines and the epigenetic silencing process can be reactivated with methyltransferase inhibitors.
Slide 27 What makes us particularly interested, in the right panel, what you can
see is that TCL1 transgenic B cells actually hyperactivate upstream the MAP kinase‐ERK signaling pathway, but Sprouty 2 in the left panel as you can see blocks this pathway, indicating that usually, this would not be seen in these cells.
Slide 28 But if you silence Sprouty 2 by DNA methylation treatments, then you can
hyperactivate ERK pathway signaling, hyperproliferate the cells, and end up with a TCL1 B cell lymphoma, at least in some of our modeling.
Slide 29
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Finally, and this is my last slide, it turns out that if you have different models of TCL1 transgenic animals, you can actually find unique patterns of DNA methylation. For example, in this particular example of a B chronic lymphocytic leukemia, FOXD3 is hypermethylated by the dark blue circles that you see in the CLL patient samples or within a mouse model, whereas the Sprouty 2 allele is not methylated here in contrast to what we showed within diffuse large cell lymphoma and the Burkitt‐like lymphoma.
Lastly, in the bottom panel, what you can see is that mouse tumor
models actually replicate each other best for overall epigenetic alterations and they can actually be segregated by sequence and genome analysis.
So thank you very much, Sean. Slide 30 Sean Sanders: Great. Thanks very much, Dr. Teitell. Great introduction for us. We’re
going to move on to our second speaker now and that is Dr. Adam Karpf. Slide 31 Dr. Karpf completed his B.S. in Biology at the University of South Florida
in Tampa and his Ph.D. in Biology with a Virology specialization at the University of Texas in Austin. After completing postdoctoral training at the Huntsman Cancer Institute, University of Utah Medical Center in Salt Lake City, Dr. Karpf held a Research Assistant Professorship position in the Department of Oncological Sciences. He then moved to the State University of New York in Buffalo where he held an Assistant Professorship in the Department of Pharmacology and Therapeutics, and he served as the Director of Graduate Studies in the Molecular Pharmacology and Cancer Therapeutics Graduate Program.
Currently, Dr. Karpf is an Associate Professor of Oncology in the
Department of Pharmacology and Therapeutics at the Roswell Park Cancer Institute. His research interests focus on the role of altered DNA methylation in cancer and in designing rational interventions based on targeting these epigenetic changes. Dr. Karpf is also the Vice‐President of the Epigenetics Society and a standing member of the NIH Cancer Etiology Study Section.
Welcome, Dr. Karpf. Good to have you.
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Dr. Adam Karpf: Thank you, Sean. Slide 32 So today, I’d like to talk about DNA hypomethylation, cancer‐germline
antigens, and ovarian cancer which is of interest in my laboratory. So as Dr. Teitell went through, I’ll briefly go over again. In cancer, a very
well‐studied phenomenon is the hypermethylation of classical CpG islands which results in the transcriptional silencing of tumor suppressor genes. Another phenomenon which is actually discovered many years earlier was that CpG‐poor intergenic regions of the genome, which are normally methylated in normal somatic tissues, can become hypomethylated and those can lead to the activation of repetitive DNA elements in the genome.
A much less studied phenomenon is the fact that there’s a select region
of CpG‐rich gene promoters that correspond to genes on these cancer‐germline antigens, which are actually methylated in normal somatic tissues and can become hypomethylated both in germ cells and in tumors.
[0:15:10] Slide 33 So the causes and consequences of hypomethylation in cancer involves
one or more mechanisms that include loss of DNMT function, the activation of demethylases, and altered chromatin structure, all of which likely impact on the genomic DNA hypomethylation phenotype seen in cancer. And the consequences of this phenotype include the activation of certain oncogenes, the induction of genomic instability, and also the activation of cancer‐germline antigens.
Slide 34 The link between global DNA hypomethylation and genomic instability is
supported by some work from our laboratory in which we showed that a normal diploid human colorectal cancer cell line HCT116, when you knock out the function of DNMT1 or DNMT3b or both enzymes, you have a profound induction of aneuploidy and also the induction and persistence of chromosomal rearrangements which correspond to non‐reciprocal translocations.
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Slide 35 With regards to cancer‐germline antigens, their link with global
hypomethylation is indicated both by the fact that decitabine or 5‐aza‐2’‐deoxycytidine, which is a DNA methyltransferase inhibitor, robustly induces the expression of many members of the cancer‐germline antigen gene family in most tumor cells treated with this agent. In addition, these genes are activated by genetic disruption of DNA methylation in the HCT116 system that I described on the previous slide.
Slide 36 The cancer‐germline antigens are also known as cancer‐testis antigens,
and there’s about 150 members of this gene family of which about half of those genes are localized on the X chromosome and half are autosomal. They often exist in multi‐gene families. The MAGE genes are a prominent family of these. They show restricted expression to germ cells and cancers. Much of the interest in these genes is because they’re highly immunogenic. They promote both cell‐mediated and humoral responses in cancer patients, and there’s been a large translational interest in moving vaccines that target tumors that express these antigens into the clinic, and the two vaccines that are in the most advanced clinical trials are MAGE‐A3 and NY‐ESO‐1.
In the last few years, it’s been recognized that in addition to serving as ‐‐
existing as antigens in cancer, the proteins themselves may participate in oncogenesis. For instance, MAGE‐A genes are involved in negative regulation of p53 function, and a particular MAGE gene, MAGE‐A11, is involved as a co‐activator of androgen receptor in castration‐recurrent prostate cancer. Another example or one characteristic of these genes is that they show heterogeneous expression in tumors.
Slide 37 So my lab is focused on one particular CG antigen gene in some of our
studies called NY‐ESO‐1 in the context of epithelial ovarian cancer as our system, human epithelial ovarian cancer. So on the left side of this slide is shown the methylation pattern of the NY‐ESO‐1 promoter in normal ovary on the top and in ESO‐1 negative ovarian tumor in the middle, and then an ESO‐1 positive ovarian tumor on the bottom, and the data is shown as traditional sodium bisulfite sequencing which in this case is covering 41 CpG sites throughout the promoter CpG island. And so what you can see here is this unusual pattern of a gene with a CpG island promoter that is heavily methylated in the normal tissue and then
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becomes hypomethylated in some tumors, and that corresponds to the expression status.
On the right side of this slide is shown a more high throughput method
for analyzing DNA methylation, which is called bisulfite pyrosequencing, where we were able to determine the methylation pattern at 15 CpG sites throughout a larger panel of tumors versus normal ovary. And as you can see, there’s hypomethylation in many of those tumors.
Slide 38 Another interesting fact about these genes that I mentioned earlier was
their heterogeneous expression in tumor. So in these experiments, we microdissected tumors based on their NY‐ESO‐1 expression status as determined by immunohistochemistry and then took that DNA, which was taken from paraffin‐embedded tissues, and subjected it to bisulfite pyrosequencing. And as you can see on the top, the tumors on the right side of the panel are from NY‐ESO‐1 positive tumors, which show a lower methylation level of NY‐ESO‐1.
And more interestingly, on the bottom of the slide, when we
microdissected different regions of the same tumor that showed different NY‐ESO‐1 expression status, we were able to show that hypomethylation corresponded with those regions of the tumor that are expressed, providing some evidence that it’s involved in the regulation of the heterogeneity phenotype.
[0:20:02] Slide 39 So the global hypomethylation in cancer doesn’t only include CpG antigen
genes. It includes repetitive regions of the genome, and we wanted to test whether there was a simple association between these two phenomenons. So shown on this figure are pyrosequencing assays in which in panel A, we’re comparing two different CG antigen promoters and we see that the methylation level of those two promoters in these tumors is highly correlated. In panel B, we’re looking at two different repetitive elements, the Alu element and the line 1 element, and those are also highly correlated. And then most interestingly, in C we’re looking at one CG antigen promoter versus one of the global methylation measures as an example and they’re highly correlated. So this phenotype appears to be correlated and coordinated in epithelial ovarian cancer.
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Slide 40 The pathological significance of the hypomethylation phenotype is
suggested by the fact that hypomethylation of either the line 1 element or the BORIS promoter, which is an autosomal CG antigen, hypomethylation correlates with advanced disease stage in ovarian tumors, and this has been shown by other groups in other malignancies as well. As hypomethylation progresses, you have a more aggressive clinical phenotype.
Slide 41 So in the very last couple of slides, I want to mention that NY‐ESO‐1 is a
target for immunotherapy in ovarian cancer and vaccines targeting NY‐ESO‐1 are undergoing phase I and II trials at our institution and others, and what’s been seen in the clinic is that the vaccines against NY‐ESO‐1 are safe and they clearly promote immune responses. However, the clinical responses have been relatively sporadic, and it appears that at least one limitation of this is the lack of antigen expression in many tumors, the loss of antigen expression in the context of therapy, and also the heterogeneous expression which I mentioned.
In addition, all of these antigens have to be presented by Class I MHC at
the cell surface and MHC‐I’s expression loss is very common cancer, and so our group has been working under the guise that epigenetic modulation using drugs that target the DNA methylation machinery could overcome some of the limitations of NY‐ESO‐1 vaccine therapy in ovarian cancer.
Slide 42 And so we have a clinical trial ongoing at the institute which I won’t talk
about today, but I will show you on this slide preclinical data showing on the top that the RNA level of NY‐ESO‐1 is highly activatable by combination treatments between 5‐azacytidine and trichostatin A or other HDAC inhibitors, and also the protein is well induced. In addition, we are able to activate the recognition by cytotoxic T lymphocytes that recognize NY‐ESO‐1.
Slide 43 So this sets up a paradigm that our group and many others are pursuing
that you could use epigenetic therapy to modulate the immune response against cancers in combination with vaccines that target CG antigens or
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adopt a cell transfer therapy. That’s based on the fact that you can upregulate these genes and upregulate Class I MHC as well as co‐stimulatory molecules.
Slide 44 So to summarize, global DNA hypomethylation is common in cancer. It’s
associated with genomic instability and advanced disease stage. In ovarian cancer, the hypomethylation coordinately effects repetitive DNA elements and also the CpG‐rich promoters of the CG antigen genes. And tumors that show this phenotype may be amenable to targeting by CG antigen vaccines, either alone or in combination with epigenetic modulators.
Slide 45 I’d like to thank the folks in my lab and collaborators and funding
support. Thank you. Sean Sanders: Great. Thanks so much, Dr. Karpf. Slide 46 Our final speaker for today is Dr. Alex Meissner. Dr. Meissner undertook
both his graduate and postdoctoral training at the Whitehead Institute for Biomedical Research in Cambridge, Massachusetts.
Slide 47 He is currently an assistant professor in the Department of Stem Cell and
Regenerative Biology at Harvard University and a principal faculty member of the Harvard Stem Cell Institute. Research in the Meissner laboratory focuses on how stem cells achieve and maintain pluripotency and the role that epigenetic modifications play in this process. Dr. Meissner sits on the editorial board of the journal Stem Cell Research and was recently named a Pew Scholar in the Biomedical Sciences.
Welcome, Dr. Meissner. Dr. Alex Meissner: Thank you. All right. So you already heard in the two previous
presentations a lot about DNA methylation itself as well as some of the approaches to look at it, and so I just want to try to close with the last presentation to give you an overview of the technologies that we’ve
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recently used and studied and then just close on a final example of how to use these genome‐wide maps.
[0:24:54] Slide 48 As you already heard, there’s more than 20 different methods to look at
DNA methylation and I’m not going to go into the detail 'cause you already heard about the three different categories that are being used to analyze DNA methylation patterns. I just want to point out that a lot of them have been recently adapted to genome scale approaches by combining it with high throughput sequencing approaches.
Slide 49 And so depending on the application that you’re actually trying to use the
methylation detection for, there are different regions for example in the genome that you are particularly interested in. As you already heard for cancer, you’re particularly interested for example in the CpG islands and other regions of the genome. A lot of our studies are sort of focused around stem cell and developmental biology. Here again there might be different regions in the genome that you’re particularly interested in. And then finally, my lab is also part of the NIH Roadmap Reference Epigenome Mapping Centers, and as such you want to actually try to provide reference maps of the epigenome, and in these cases, you’re shooting for the most global and comprehensive mapping.
Slide 50 Now, if you think about these different approaches, what we are really
interested in is trying to detect DNA methylation differences. And so then obviously, the next questions to ask, which of the methods that are available currently are the most accurate, as well as the effective in identifying differentially methylated regions between any two different or many different samples?
And so the goal of one of the studies that we recently undertook was to
really try to identify and compare different approaches that are commonly available to different labs. And so it shows MeDIP‐seq using an antibody from methylcytosine, MethylCap‐seq using a recombinant methyl binding protein, RRBS which uses the high throughput bisulfite sequencing based approach, and then it’s not a sequencing‐based
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approach but we could use also the Illumina Infinium array which is because it’s a commonly available research tool.
And so then the goal was to try to ask between any two different sample
pairs. In this case, we selected a normal and colon tumor pair as well as two different embryonic stem cell lines and wanted to see how the different methods perform.
Slide 51 And so in order to actually try to compare them fairly, we did about an
equal number of sequencing reads for the three sequencing‐based approaches and as you can see in this table, they range between 30 and 40 million aligned reads for the three methods, and obviously the Infinium array focuses on the limited number of CpG dinucleotides featured on the array.
Slide 52 And so this shows you a screenshot of how the different methods
compare to each other for a particular region or on the HOX cluster. You can see on top two sequencing lanes for MeDIP‐seq, below that three lanes of the MethylCap‐seq. then below that you can see tracks for two RRBS samples, as well as below that the Infinium reads.
And just to zoom in so you can ‐‐ so the first thing you can see
immediately on the zoomed‐out view is this very large agreement between the different approaches, so you can see the MeDIP as well as the MethylCap, both enriched in the same regions. And then the RRBS, it’s a little bit harder to see, but basically, the color coding indicates the levels of methylation and so darker bars indicate high levels of DNA methylation.
Slide 53 And just to zoom in a little bit and show you this so there’s peaks for the
MeDIP capture seq and below that you can see a lane for the RRBS. We can see very accurately whether MeDIP capture enriches for methylated fragments. You can also see confirmed methylation using the bisulfite sequencing‐based approach.
Slide 54
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And so zooming out further, it’s showing you now for example one arm of the chromosome 21. You can see that again overall there’s very good agreement. You can also see that MeDIP‐seq has a little bit higher background compared to the MethylCap‐seq, but again, overall the agreement is quite high. What you will also notice when you look at the Infinium data on the bottom, you can see that the coverage obviously genome‐wide is fairly limited compared to the other three approaches.
Slide 55 Now, a different way to look at the coverage of the approaches is to look
at these pie charts, and what you can see here now is from left to right the MeDIP, MethylCap, RRBS, and Infinium, and then three different genomic features where we looked at promoter regions on the top and CpG islands in the middle and then using a whole genome sliding window approach to compare the coverage.
And so what you can see if you start with the whole genome approach,
obviously you can see that the bisulfite sequencing‐based approach because we’re enriching for particular regions of the genome only has less genome‐wide coverage compared to the other two methods, the MeDIP and the MethylCap. However, if you look for example at particular regions that are obviously important for gene regulation such as promoters and CpG islands, you can see that for example, RRBS very nicely enriches to a high degree for this particular genomic features, giving you very good coverage and very in‐depth reads for these particular regions of the genome.
[0:29:57] Slide 56 And so as I said initially, we are interested in trying the differentially
methylated regions between the methods. And so if you now just focus on the Venn diagram on the bottom right, this is now comparing for example between two different samples, trying to ‐‐ between the three different approaches, trying to find how many differentially methylated CpG islands do we find using the different approaches. And if you look at the numbers, you can see first of all that there’s quite some overlap of all three methods to take the fair number of the same differentially methylated regions in the genome, but overall, MethylCap let in the first largest number of these regions compared to the other two approaches.
Slide 57
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So just to summarize some of the results that I just showed you, overall
we find that MethylCap‐seq seems to be less prone to the global bias than MeDIP so it has less background than MeDIP. RRBS and MethylCap are surprisingly similar in their power to detect differentially methylated regions, but then there are sort of individual considerations for using the different methods. For example, one advantage of the RRBS approach is that it actually works on formalin‐fixed and paraffin‐embedded tissues, which is very relevant for cancer studies. It’s also, compared to the other methods, it’s much more sensitive so it works on nanogram quantities of DNA versus the other ones are still in the microgram range.
On the other hand, MethylCap and MeDIP provide genome‐wide
coverage, whereas RRBS does provide only focused coverage or more focused coverage. RRBS, however, provides single base pair resolution, which is another advantage. Compared to that, MethylCap and MeDIP protocols are a bit simpler in terms of their experimental execution than RRBS, but RRBS, because it’s bisulfite sequencing based, has the potential to be continuously scaled until whole methylome sequencing becomes feasible.
Slide 58 And so with this, I just want to close with the last two slides. I’m showing
you one example if you would now actually apply this in a bigger scale to particular samples. And so in this case we’re interested now in stem cells and trying to understand a bit more about the variation that you observe among human embryonic stem cell lines and also induced pluripotent stem cell lines.
And so what we chose here to do is establish a reference and so we took
19 high‐quality human embryonic stem cell lines and performed the genome‐wide bisulfite sequencing for them, as well as a test set of 11 iPS cell lines.
Slide 59 And so showing you now here is an example from a number of different
genes, and calculating the average methylation variation that you can see for individual genes across the 19 different human ‐‐ just the human embryonic stem cell lines. And so if you look at the left, you see for example a number of genes that show very little variation and all of the cell lines across the 19 lines show very little evidence of DNA methylation.
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There’s other regions in the genome, however, that show a lot more
variation if you look at the different cell lines. And if you go to the right, you can see fairly widespread distribution of methylation found at these individual genes.
And so what we sort of considered this is sort of as a reference map or
you could also reference ‐‐ use it as a reference corridor that now defines DNA methylation values for any particular feature in the genome throughout the genome, and so having this established as a reference allows you now obviously to compare it to any particular question. In our case, we wanted to compare it to induced pluripotent stem cells, but again, you could also use this similar approach for looking at normal versus cancer.
Slide 60 And so this slightly more busy slide just shows you the exact same
corridor that I showed you just before, but now plotting on the left of this numbered x/+ ES cell lines, on the right plotting iPS cell lines. And so what you can immediately see is that on the left genes that show little variation and very tight DNA methylation patterns are very similar between the ES cells as well as the iPS cell lines. But if you then move further to the right and look at genes that are highly variable among embryonic stem cell lines, you also find that the same genes are very variable among the iPS cell lines suggesting rather then there is some sort of systematic differences between ES cells and iPS cells that they’re sort of more of the same variation among pluripotent cell lines in general. And so having this reference corridor allows you obviously now to immediately search for outlier genes among the different individual lines.
Slide 61 And so this is I just like to thank all the people in my laboratory as well as
collaborators and the funding agencies, and thank you for your attention. Sean Sanders: Great. Thank you very much, Dr. Meissner, and many thanks to all of our
speakers for the superb presentations. Slide 62 And we’ve received a lot of questions so we’re going to move right onto
our Q&A session so that we can answer some of the questions submitted by you, the viewers.
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A quick reminder to those watching us live that you can still submit your
questions by typing them into the ask‐a‐question box and clicking the submit button.
[0:35:00] So the first question I have for our panel, and I’ll address it to you Dr.
Teitell to start off with, is you talked about a lot of different methods that are available, but do you see a need anywhere for new methods to study DNA methylation?
Dr. Michael Teitell: Thanks, Sean. That’s a great question. I can partially address that I think.
So there’s regions I believe that have been relatively overlooked and there’s also new types of methylation, as an example hydroxymethylcytosine positions that at least as yet we haven’t developed really great techniques to address it at least quantitatively. So that along with perhaps some continuing needs I guess in the bioinformatics realm suggest that yes, absolutely, that there’s needs to develop techniques, but I think as you’ve heard from the others as well, it maybe depend on the actual application that’s involved.
Sean Sanders: Uh‐hum. Dr. Karpf? Dr. Adam Karpf: Yeah. I mean, I agree with Mike and we do have an evolution of
techniques going on, but I do think that we do have a lot of good methods now to study DNA methylation and it’s just a matter of what questions are being addressed. With regards to 5‐hydroxymethylcytosine, that’s a very exciting area and I think the methodology development for that is going to be something in the next couple of years that is going to really take off.
Sean Sanders: Uh‐hum. Dr. Meissner? Dr. Alex Meissner: Yes. I would just resonate that this is mostly application driven and going
to be dictating what kind of method is the method of choice. And again, there’s obviously the natural evolution that we want for example for certain studies to have more high throughput. So we want to look at thousands, tens of thousands of cancer samples so their cost is certainly a factor. Other projects will look more at discovery‐based directions and those obviously will be more comprehensive and perilous throughput. So…
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Sean Sanders: Great. Now, a couple of you mentioned hydroxymethylation and then a question was sent in by a live viewer asking you to talk a little bit more about that. I know it’s failing you. Maybe you could address sort of where we stand at the moment as far as research is concerned. I know there’s maybe a little bit of discussion still as to how real this phenomenon is. So, Dr. Teitell?
Dr. Michael Teitell: There’s a few papers on hydroxymethylation and it’s at least in my
reading not clear yet whether or not this is an intermediate stage between the demethylation of a methylcytosine position and the conversion to a cytosine, but whether or not hydroxymethylcytosine actually has a physiological. One consideration of course is that there’s a lot of hydroxymethylcytosine present in the central nervous system apparently, and so if it’s related to simply a DNA repair effect or some phase of DNA repair, then you would imagine that that would be repaired early on. And so it’s curious that we find a lot of that there.
Sean Sanders: Uh‐hum. Dr. Karpf? Dr. Adam Karpf: Yeah. I mean, we don’t work on this in my laboratory, but there do
appear to be antibodies now available to 5‐hydroxymethylcytosine that I think are going to enable analysis of that question as well as some other techniques that are based on the differential chemistry of the two bases between 5‐methylcytosine and 5‐hydroxymethylcytosine, and I think it’s a really unknown area right now, the physiological significance of this mark as Dr. Teitell said.
Sean Sanders: Great. Dr. Alex Meissner: All right. So it is mostly unknown because people have mostly overlooked
it in the past and obviously our laboratory is very focused on bisulfite sequencing, which does not unfortunately discriminate between the methylcytosine and the hydroxymethylcytosine. But as such, as Adam also just mentioned, so there’s no antibodies available. Enzymes become available so that one in the very near future should probably get a bunch of better feeling or where this mark sits and how it’s distributed throughout the genome and that usually helps at least as the first step to inform about its function. So…
Sean Sanders: Okay. I’m going to stay with you Dr. Meissner. The question: You
mentioned high throughput technology so the viewer asked if there’s any that are currently available, and if not, are there any current obstacles preventing high throughput epigenetic screens and where do you see this in the near future.
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Dr. Alex Meissner: Yeah. Well, this is an area that has very much evolved over the last few
years with high throughput sequencing per se becoming more available to individual labs that used to be only big sequencing centers, but now most departments have sequencing course available or it can pay as a fee for service different places to do the sequencing for you.
So sequencing probably becomes more available. At the same rate, a lot
of companies have developed for example kits for antibodies as well as bisulfite sequencing kits, and a lot of the tools that basically are required for this have become much more user‐friendly. And so I think there has been a great, great advance in terms of making it much more accessible to the end user.
[0:40:00] A more problematic part that Mike was referring to is sort of the
bioinformatics entity end because the more sequencing data you produce, the more data you have to analyze. And so at some point, you run into this challenge that you have to actually deal with the data. But so far, it’s been certainly helped by a lot of developments on these technical funds.
Sean Sanders: Great. So maybe I’ll come to you Dr. Karpf for this question. They’re
asking sort of essentially, what is the critical mass of methylation that you need in order to get activation or deactivation? So is it a single nucleotide? Is it, you know, a number? Is there a cutoff?
Dr. Adam Karpf: I think in the cancer realm, we generally see a pretty robust conversion of
unmethylated CpG islands and many contiguous CpG sites becoming hypermethylated concordantly, and that relates to and results in silencing. There are a few papers out there where you can have single or very limited CpG sites at key regions that for instance are bound by methylation‐sensitive transcription factors that occlude the binding of those factors that can lead to silencing as well. But I think that at least in the cancer realm, we generally see large scale conversion of larger regions of a CpG island from unmethylated to methylated.
Sean Sanders: Uh‐hum. Okay. Dr. Teitell, a question for you. This is asking about
studying the methylation status of specific genes using blood. Is this a good proxy for tissue, easier to obtain? And in this case, they’re asking specifically about breast tissue but, you know, more generally.
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Dr. Michael Teitell: Sure. That’s a great question. I think it has been pretty reasonably established that different tissues and different states of tissues have unique DNA methylation and chromatin modification patterns. And so blood as a surrogate for breast tissue or for any other type of tissues such as colon or brain or what have you might not be the most accurately appropriate surrogate. There also may be a variation within the tissues of course and the technique that you use, whether it’s a sequencing‐based technique or a more blending technique if you will such as array techniques could also obscure that. So I think as surrogates go, probably there’s tissue‐specific factors that have to be considered.
Sean Sanders: Uh‐hum. Dr. Karpf? Dr. Adam Karpf: Yeah. And I’d also point out that even in the context of blood, you’re
talking about many different cell lineages and cell types and it hasn’t been well established that the methylation patterns of those different cell types are highly conserved or not. So you’re introducing another heterogeneity into the issue as well.
Sean Sanders: Great. So this I thought was an interesting question which does relate to
what we’ve just been talking about, asking about obtaining personalized epigenome maps. Do you think this is something that is possible and would it be useful? So I’m going to start with Dr. Meissner.
Dr. Alex Meissner: It certainly becomes more and more feasible. So we’ve seen sort of last
year the first whole methylome maps. There have already been dozens, hundreds of chromatin modification maps genome‐wide. So it’s certainly doable. Whether it’s just like a personalized genome, it’s going to be a while before everybody has their own epigenome sequenced. It’s certainly going to be useful to see a lot more epigenomes just to get a better understanding 'cause there’s a lot of variables that are not well understood. So while there are certain very clear cut cases where genes were silenced, overall we don’t have a very good understanding of variation for example between individuals, between again different age groups, different sex, and so there’s a lot of environmental influence that may change these. And so I think having a large number of these available will certainly help.
Sean Sanders: Great. Dr. Michael Teitell: I mean to add to that, Alex, with your study, it was very interesting
actually with embryonic stem cells and iPS cells that there were genes that seem to have specific amounts of methylation that was quite invariant and then you had genes that had very wide ranges of
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methylation. So on top of tissue heterogeneity, you might have gene to gene variability as you’re seeing in the pluripotent state even in the tissue of interest.
Dr. Alex Meissner: Right. Dr. Michael Teitell: And that could be complicating. Dr. Alex Meissner: But in this case, part of the reason that we could actually detect it was
looking at large numbers in this case, and so I think the more we get, the better we can actually understand both, so of constant versus variable regions, and that will again feedback into your development of assays of how you want to actually look at certain parts. Because once you know where to look for most variations, you probably can narrow it down to fewer CpG sites in the genome.
Sean Sanders: Uh‐hum, uh‐hum. Dr. Adam Karpf: There may not be really an equivalent of the personal genome and the
personal epigenome due to the fact that you have different tissues, different cell types. And so it might be that you can evolve down to key markers to follow rather than sequencing genome.
[0:45:11] Dr. Alex Meissner: Well, it’s actually yes. That’s a very good point. So I mean, obviously,
every single tissue might be different, and again, just like your genome might take quite a few mutations, your epigenome is certainly going to change probably over time. And so even though when you’re 20 you got your epigenome sequenced, when you’re 80 it might look quite differently. So…
Sean Sanders: Right, right. Is it possible to look at a single cell, the epigenome of a single
cell currently or to analyze a single cell, or is it just, you know, beyond what we can do right now?
Dr. Adam Karpf: I have to defer to Dr. Meissner. Dr. Alex Meissner: It’s in theory possible. So obviously, it’s a big challenge. The high
throughput sequences help a lot because they use very small amounts in the molecule range. But for example, the technology that we use is bisulfite sequencing based which is very DNA degrading, so that certainly creates some challenge. So going back to the very first question, having new methods available that do not use bisulfite will probably help that a
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little bit. But in theory, DNA methylation, I would say yes, it’s possible; chromatin, much harder because again, you need to enrich using antibodies and capture enough fragments to actually get to your sequencing libraries. So it’s I think for methylation possible; for ChIPs or chromatin, most likely not.
Sean Sanders: Uh‐hum. Now, I assume when you’re doing these studies you’re looking
at nuclear DNA. Has anyone studied mitochondrial DNA and are there differences in methylation, the way it’s methylated, the genes, the proteins involved?
Dr. Adam Karpf: Yeah. So mitochondrial DNA doesn’t have ‐‐ mitochondria doesn’t have
histones. To my knowledge it doesn’t have DNA methylation and the DNA methyltransferase enzymes are not present in the mitochondria. There is at least one interesting paper showing that the presence or absence of the mitochondrial genome can impact epigenetic DNA methylation changes in the nucleus, but in terms of the mitochondrial genome, I’m not aware of studies that have shown any epigenetic regulation of it.
Dr. Michael Teitell: I mean, linking back to immunity for a second which is very interesting
you bring that up, non‐methylated CpG sequences in bacteria for example are very stimulatory to the innate immune system, and I really, you know, I’ve wondered whether or not if you had mitochondrial DNA that actually leaked out of a cell that was either undergoing apoptosis and not completely fragmented or necrotic, if that would actually stimulate the innate immune system as well.
Dr. Adam Karpf: Yeah, that’s interesting. Sean Sanders: Uh‐hum. So the next question is for you, Dr. Karpf. You concluded that
global hypomethylation is a hallmark of cancer. Is this based on ovarian cancer and do you think the conclusion is more generally applicable to other genotypes?
Dr. Adam Karpf: Yeah. It’s not confined to ovarian cancer. There’s really quite a bit of
literature for the last 25 years showing global hypomethylation in various malignancies. Prostate cancer for instance is one of the early studies. Colon cancer is another. So it’s pretty well established in many different systems. I would say that it probably hasn’t been as well established as hypermethylation has been just because there’s probably a hundred to a thousandfold more studies that have been published on hypermethylation in cancer.
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So it’s kind of really ran the gamut of every tumor type you can think of. There’s evidence for silencing by DNA hypermethylation, but in general, it does appear to be very common in malignancy and somewhat unrelated to the hypermethylation phenotype. So studies that have tried to determine whether hypermethylation and hypomethylation are associated have generally shown no association between those two phenomenon even though sometimes they do occur in the same tumor. So at this point, it’s a little bit paradoxical what’s going on.
Sean Sanders: Great. So coming back to you Dr. Meissner, here’s a question back about
asking how dynamic DNA methylation patterns are and can they be altered during the course of an infection? Or I mean, we know disease definitely, but do you have any idea of infection?
Dr. Alex Meissner: So we have not studied any infections in terms of their dynamics. So
obviously, during normal development, the patterns of DNA methylation are fairly dynamic at different phases. Once you established a cell type, in principle they are fairly stable, but then again, that may be influenced by diseases or again acquiring for example changes in the epigenetic patterns of particular sites, and so we don’t have any data to sort of support or comment on that. Yeah, I don’t know if there’s any other comments.
[0:50:07] Dr. Michael Teitell: Yeah. I think Adam discussed this earlier. I think that perhaps there’s at
least a smattering of evidence in the case of Helicobacter pylori and infection of the GI tract in which case the epithelial cells of the GI tract and the lymphocytes in the GI tract seemed to have some changes of methylation, although how that will pan out, I’m not 100% sure. And Helicobacter has been associated with the development of multiple lymphoma in the GI tract, so it’s possible at least but I don’t know from personal experience.
Sean Sanders: Okay. So I’m going to move on to a little bit more on the clinical side since
we’re talking about infection, and this viewer asks if there are any complications when using therapies that target the methylation machinery since it’s needed for regulatory function of normal cells. So Dr. Teitell, would you like to start us off with that?
Dr. Michael Teitell: Well, I think that’s a complicated question. There are two or three drugs I
believe in trials and actually use these for underlying therapies particularly in the disease myelodysplastic syndrome, which seem to be if you will epigenetic static in that they can as an example demethylate
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methylated tumor suppressor genes as an example, but when you take the patients off of those drugs, then they can revert to the prior phenotype.
But those drugs also are very nonspecific. They’re not targeted. And so,
you know, one would have to always question and I’m sure that there’s literature that is out there of alterations in genes that are unintended in those cells and the treatments and also in the bystander cells that are not, you know, related to the tumor that you might have under therapy. So there is promise obviously with treatment in myelodysplastic syndrome with some of these nonspecific agents such as 5‐azacytidine derivatives and histone‐deacetyl‐lysine derivatives, but it probably does affect much more than just simply the genes that have gone array to drive this dysplasia.
Sean Sanders: Uh‐hum. Dr. Karpf? Dr. Adam Karpf: Yeah. So the drugs that we have now, 5‐azacytidine and 5‐aza‐2’‐
deoxycytidine which are cytidine analogs and essentially antimetabolite driven mechanism of action, the specificity of those drugs is really driven by the same specificity that other antimetabolites are driven by, which is the proliferative index of the target tissue. So it is quite interesting though that in the case of MDS, the proliferation rate might not be really the issue in that malignancy. But more generally, I think in these drugs and in other contexts it’s thought that the specificity for tumor tissue as opposed to normal tissue is really derived from the proliferation index of those tissues.
Sean Sanders: Uh‐hum. Great. Dr. Meissner, anything to add? Dr. Alex Meissner: I think they just summarized it. Sean Sanders: Great. So the discovery of 5‐hydroxymethylcytosine, do you think we
know yet whether it plays into any therapeutic or diagnostic areas, or is it too early to tell?
Dr. Adam Karpf: Well, it appears to have a function in the brain. I think the best
established literature is the detection of that mark in the brain. So I guess one could envision neurodegenerative disorders might have altered levels of that base and certainly it’s distinct from 5‐methylcytosine in terms of its ability to be recognized by certain elements of methylated DNA binding protein family that can repress gene expression which are unable to bind 5‐hydroxymethylcytosine. So I think it’s an intriguing molecule, it exists, but the jury is out.
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Sean Sanders: Uh‐hum. So talking about the brain, a question came in asking ‐‐ saying
that DNA methylation has been welcomed by researchers in psychiatry to form a basis for looking at how gene and environment interact and result in different behavior. Do you have any opinions on this type of research? Dr. Karpf?
Dr. Adam Karpf: It’s kind of outside of my area. From what I surmise from the literature
though, I mean, it’s clear that some of these disorders do have an epigenetic component, but exactly what epigenetic marks constitute that component or whether we’re even studying the right ones at this point I’m not sure about, but I don’t know of the other panelists.
Dr. Alex Meissner: I mean, we had engaged in some of these kinds of environment
epigenetic studies, and I think the one thing where we don’t really have a solid answer for you right now is because you really need to build a much stronger baseline of what normal would constitute because a lot of these environmental influences made much more subtle effects than for example the particular CpG island like in cancer is fully methylated.
[0:55:11] So you might change to a mild degree of the methylation levels, which
again was one of the questions earlier, may actually have a mild effect on the expression of the gene and in that case could also have some translation into some mild phenotype. But in order to really distinguish sort of normal variation versus sort of really environmentally induced stable changes and whether these could be passed on through the germline, I think we still need to study a lot more details, but it’s certainly an interesting area. So…
Sean Sanders: Uh‐hum. Do we have any idea of the incidence of hypomethylation and
oncogene activation in cancers? Do you think this is something that occurs in all cancers or is it going to be a subset? Dr. Teitell?
Dr. Michael Teitell: Sure. So hypomethylation, as Dr. Karpf alluded to, there are genes that
are imprinted such as the insulin‐like growth factor II which can become activated by DNA hypomethylation. There are the major genes which can be activated by DNA hypomethylation. There’s probably isn’t a restricted phenomenon to any particular cancer. For DNA hypermethylation, we know that as Dr. Karpf alluded to as well and as Dr. Meissner alluded to, there’s a large literature that says that the propensity in the frequency of DNA hypermethylation in a whole variety of tumors is quite high. Again, there’s going to be variability in the tissue, the variability in the cells that
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you’re assaying unless you do and it’s difficult to do of course single cell analysis, but I think it’s a very widespread phenomenon. And there’s even a connection again between epigenetic modifications particularly DNA methylation and the trends or the deamination steps that actually lead to the transversion of CpGs to thymidine CpGs and you see that obviously outside of the CpG islands. So there’s a big connection between the two as well.
Dr. Adam Karpf: Yeah. I think it’s more pointing out that Dr. Eason and folks at M.D.
Anderson have really shown that certain tumors have this so‐called subphenotype which you have a massive amount of hypermethylation and this is pretty clearly shown in the colorectal cancer area, whereas you have other sets of tumors that don’t show this phenotype, and when you assay hypermethylation events, they have much fewer events. And those two different types of tumors actually classify. They have different pathological characteristics, different mutational profiles, and so on. So there appears to be evidence for maybe a subset of tumors that have this real propensity to hypermethylate CpG islands in silenced genes.
Sean Sanders: Uh‐hum. So I’m going to come back to a more technical question quickly.
There’s been a very rapid development in the next‐generation sequencing area. Do you have any opinions on how this might advance epigenetic research? Dr. Meissner?
Dr. Alex Meissner: Well, it has greatly facilitated over the last few years. I mean, if you think
about it, all the principal approaches to look at methylation have been available for quite a few years, but only in the last few years they have been sort of initially coupled with arrays that are already sort of increased the capability of looking at different parts in the genome in a much sort of more comprehensive way. Now that we have sequencing and it’s fairly standard with a single lane of an Illumina machine, you can get a genome‐wide map of different histone modifications. Similar for DNA methylation, the whole methylomes have been created and all that is thanks to high throughput sequencing. So it’s very clear that there has been a huge impact, and again, sort of these global maps have obviously quite significantly increased our understanding of sort of epigenetic marks where they are in the genome, how they interact with each other and so forth. So…
Dr. Michael Teitell: You know, one of the things I presented in my talk was restriction
landmark genome scanning, which was an early global attempt at DNA methylation analysis, and as alluded to, that’s evolved into the current technologies and the costs have come down. That prior technique is a great technique but it’s very restricted in scope and with the assays it’s
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labor intensive. It’s cost prohibitive in terms of the apparatus and so forth. So I think it’s a natural evolution actually to move towards the sequencing technologies and they’re very, very advanced and helpful.
Sean Sanders: Great. Dr. Adam Karpf: Yeah, and it seems like one of the most exciting areas is the phylogeny of
the DNA methylation when you can take different organisms and compare the methylome between them using these technologies and really maybe learn more about the relationship between methylation in certain regions of the genome and how that relates to other cell physiological functions.
[0:59:55] Sean Sanders: Great. So we’re almost out of time but I’m going to throw the last
question over to you. Where do you want to see things in the next 35 years? I mean, what are the techniques, what are the technologies that you’re looking for in order to really drive your research forward? What do you hope to see in this area? Dr. Teitell?
Dr. Michael Teitell: I think that the developments in the high throughput sequencing and the
global genome analysis is really exciting. The new marks that are being identified and the different positions of the new marks is very exciting. I think as the techniques become more accessible as was alluded to earlier by Alex and cost non‐prohibitive, I think that’s really going to drive forward this area of research, and the bioinformatics has to keep up as well.
Sean Sanders: Right. Dr. Karpf? Dr. Adam Karpf: Yeah. Actually, I see these new technologies and all the data coming out
of it actually might lead us back to the more basic mechanistic studies to try and understand how methylation is related to different cell phenotypes and gene regulation. That new hypothesis will probably be generated from the type of work Alex and others are doing that are really going to come back to the laboratory for the mechanistic studies.
Sean Sanders: Uh‐hum. Dr. Meissner? Dr. Alex Meissner: Yes. I would just also argue it’s just making it more sensitive, being able
to look for example at single cells then applying it to most interesting tissue types will be very reliable. The bioinformatics was already mentioned. One other thing that’s really critical is trying to think about
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how to visualize these kinds of data, so more data and sort of complex sort of epigenetic patterns because it’s not a single sort of two‐dimensional sequence. It’s very complex and so you need to really think about how you can actually summarize it and make it accessible through for example something like the UCSC genome browser and how you display these things and give people tools to actually analyze it and so to make it most useful.
Sean Sanders: Excellent. Well, thank you very much. Slide 63 And unfortunately, we are now out of time so I’d like to once again thank
our panelists for being with us today and for generously sharing their knowledge and expertise: Dr. Michael Teitell from the David Geffen School of Medicine at UCLA, Dr. Adam Karpf from the Roswell Park Cancer Institute, and Dr. Alex Meissner from the Broad Institute. Many thanks to you all for your participation today. It was great to have you here.
A big thank you to our viewers for the excellent questions you submitted.
Apologies that we didn’t have time to get to all of them. Please go to the URL at the bottom of your slide viewer right now to learn more about products related to today’s discussion and look out for more webinars from Science available at www.sciencemag.org/webinar. This webinar will be made available to view again as an on‐demand presentation within approximately 48 hours from now. Please tell us what you thought of the webinar by sending an email to the address now up in your slide viewer; [email protected].
Again, thanks to the panel and to New England Biolabs for their kind
sponsorship of today’s educational seminar. Goodbye. [1:02:43] End of Audio