Myriad Oncology Live episodes are recordings of an open-forum webinar hosted by Dr. Thomas Slavin. The opinions and views expressed in this recording do not necessarily represent those of Myriad Genetics or its affiliates. To participate in a future recording, visit myriad-oncology.com/myriad-oncology-live for a list of dates, times, and subjects.
Myriad Oncology Live episodes are recordings of an open-forum webinar hosted by Dr. Thomas Slavin. The opinions and views expressed in this recording do not necessarily represent those of Myriad Genetics or its affiliates. To participate in a future recording, visit myriad-oncology.com/myriad-oncology-live for a list of dates, times, and subjects.
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0:00:11.5 Dr. Thomas Slavin: Welcome, this episode of Inside the Genome is a recent recording of Myriad Oncology Live. A webinar hosted by me, Dr. Thomas Slavin, Senior Vice President of Medical Affairs at Myriad Oncology. The opinions and views expressed in this recording do not necessarily represent those of Myriad Genetics or its affiliates, to participate in a future recording, please visit Myriad Oncology for a list of dates, times and subjects. I look forward to exploring the world of genetics with you all.
0:00:39.6 DS: Hello, everyone, and welcome to Myriad Oncology Live, this is a later one for our East Coast friends, 6:00 PM Eastern. So I'm trying to catch people after clinic, and so maybe a little lighter audience just because it's later in the day for many, but trying to accommodate clinic schedules, and this is a hot topic, so it's a good one for later in the day for those colleagues. A little housekeeping as always to start, so I'm Dr. Slavin, this is Myriad Oncology Live, you can ask literally whatever you want, they're theme based. Today's theme is around RNA, so let's talk about the use of RNA and hereditary cancer testing. Were joined by Paula Nicks our RNA Lab Director, and we also have Erin Mundt. Thank you for coming on, Erin, she also has a lot of expertise in this area, and then Shelley Cummings as always, is manning the chat, thank you for manning the chat there, Shelley.
0:01:43.6 DS: So you can unmute yourself, ask literally anything you want, doesn't necessarily have to be about RNA, if you have another question, you just can't catch these a lot and you just wanna ask anything, that's fine too. So you can always unmute yourself, ask anything there. If you want to, instead just send a chat question to Shelley, that is fine as well, and she will manage those and get them discussed.
0:02:14.5 DS: Also, so you should be seeing my screen. So let me know if not, but next week is tumor normal testing for treatment, so we'll talk about pairing of germline tissue with blood, saliva with general tumor sequencing and discuss how it's related to therapy, indications and things. And then I think we have an off week and then coming back in May, I'm gonna need to build out the rest of the schedule for me, and I'll probably put me on June. But this one should be a good one, we're gonna be talking about hereditary cancer in the LGBTQ plus community, and we have some external folks coming on, I believe Karen Hurley, who some of you may know, has expressed interest so she'll be joining, so she's an excellent psychologist in this area of germline genetic testing, but really, if anyone has ever met her, she's a very articulate speaker and really knows a lot about this topic in particular. Rob Fitch and our own Lauren, and I can't ever... I don't wanna butcher Lauren's last name, I don't think she's on. But Shelley, maybe you can chime in, [chuckle] one of our RMS team will also be helping with that discussion. Alright.
0:03:46.7 Shelley Cummings: Sferrazza is my guess.
0:03:49.8 DS: Yes.
0:03:49.9 SC: I butcher it too, but that's close.
0:03:52.1 DS: Yes, thank you. Alright. So I wanted just to start, just to get the conversation going a little bit with some updates that we've been doing, I think people have been hearing a lot about RNA in general, and hereditary cancer. Yeah, I wanna bring people up to speed, take a step back and to start and just explain really why is RNA even a point of discussion in hereditary cancer. Some people might know it from the tumor world, so let me share my screen real quick. There we go. Okay, I'm not gonna go through this whole deck, but I think... And honestly, people can disrupt me at any time. But this was a talk Paula and I have given a few times, but just to give people a little bit... A background... Yeah, about... When we do DNA sequencing, a good portion of genetic variance in about 10% or so will be involved in someway, shape or another, primarily with splicing, and that's the main thing that you would be concerned and think about needing RNA for. So splicing defects are at the ends of exon, so you have... Can people see my mouse when I'm moving it? Can anyone see that?
0:05:28.2 SC: Yes, it's... Yeah, so it's small but we can see it.
0:05:31.3 DS: Oh, okay. Is the screen small or is it big?
0:05:36.0 SC: No, it's fine.
0:05:37.5 DS: Okay, good. Yeah, thanks Shelley. So you have exons, introns, a lot of us with genetic expertise, have some understanding of this, but not everyone on this call may be in that camp. So I'll just... It's good to walk through, and when we take DNA to protein, that intermediary step is RNA and really messenger RNA, so you have to essentially take out these introns and for the actual messenger RNA to be created, we have to know... Our bodies really need to know where to set up those cuts, 'cause it's really crucial. It's not like there's a label that says, "This is an exon, this is an intron." So there has to be some dictation in the DNA, and those are splice sites. And splice sites are highly conserved in general. So people may have heard the term canonical splice site that usually refers to the conserved nature of the splice site, minus two and plus two positions. So any time you're at the exon, you have two bases into the exon and then two bases into the intron are really crucial bases in general, and they help set the tone for that splice center for the donor or the acceptor. But you also have multiple important bases, I should say, still in that area. And then somewhere in the middle of the intron, usually have the lariat branch point sequence.
0:07:10.9 DS: And so as part of our normal DNA sequencing, we sequence into the intron and we always sequence the exon as part of it. And we have an RNA splicing lab which we've had since 2015. And just to give you a little sense, we've reclassified really over 1000 or thousands of reports at this point and well over 100 variants and done investigation on at least double that. And these are the genes that are primarily being looked at. A lot of times, it's looking at phenotype, looking at the actual variant itself, the ability and rationale to actually go after one of those variants with some in-depth splicing studies, so a lot of these are pretty actionable genes as you can see here, so no surprise given our history that we have a lot of expertise in VRC 1 and 2 in this area.
0:08:13.1 DS: And then the way we do splicing... I guess there's two ways in my mind to do splicing evaluation by RNA and I tried to find a good picture and I really couldn't, but there's one of really the... Really both of these, they're just kind of hard to explain and there's no good photos, I would say even our own slide deck, I don't think really does this justice. But essentially, you can either look at the mRNA, so you can take the messenger RNA that's made from the... If we go back to this original slide here, you have the messenger RNA here, so you can take that and you can sequence it, and that's actually what is done a lot of times. So if you've ever heard of RNA transcriptome analysis, especially if you're talking about somatic testing, tumor tissue testing, you'll hear of RNA transcriptome analysis. What is done there is you take this messenger RNA and you turn it into cDNA essentially, complementary DNA, and then you sequence that. And what that gives you is it can give you kind of a ratio... Or not a really ratio, it just gives you a ratio as it compares to everything else if you have some controls in the region. So if there's a problem with gene A, you might see just lower amount of messenger RNA from gene A compared to gene B and C and D, etcetera. So that's primarily what's being looked at when you just kind of do a blanket evaluation.
0:09:49.8 DS: And then the other way to do it is the way Paula really does it in our lab, which is you find a DNA variant in the area that's informative, so you can actually follow the alleles. So you actually know, "Okay, every time I see... If I look at the messenger RNA and every time I see this G allele, I know it came from this allele," 'cause remember, we always have two alleles for every gene. Really for hereditary cancer in general, there's not many that are on sex chromosomes, so usually you're always dealing with two alleles. And so yeah, any time I see the G present, I know it was produced and any time I see the C in this area present I know it was produced, and you can actually do ratios of the production, and I'll show an example of that. I know it's a little tricky at the moment. And I'll pause there for any questions. I don't know if there's any questions. 'Cause again, definitely wanna make this interactive so people know... Hopefully when you leave, you know what RNA analysis is.
0:11:00.8 SC: Nothing in the chat right now, TJ.
0:11:03.2 DS: Yeah. No, thanks. And then I didn't really mention this before, but kind of the purpose of RNA... Well, why aren't we all just... I've said this numerous times. Really, we should be protein biologists and not genetics people, but protein is really just finicky and hard to do accurate analysis on. A lot of times you have to have fresh tissue. So our field for diagnostics really shied away from protein. There's very few protein assays in medicine that I can even think of. There is a couple, but not many. DNA is what we all kind of trended towards, especially for hereditary, and then you look at the whole world of cancer tumor sequencing and everything else, it's all DNA for the most part. And then RNA is just kind of this middle ground, where it's still very finicky, which is part of the reason why it doesn't have... It was lackluster in the beginning and ultimately, arguably, it doesn't really give as much information as the DNA, because sometimes it's hard to quantify and different things. So overall, we've really just settled on looking at DNA, but you're starting to see RNA emerge. And again, we've been using it to help with variant classification for years, and you're seeing it more now in the somatic side. If you think of Oncotype DX or you think of...
0:12:31.8 DS: Sorry. I have a little dog barking. [chuckle] If you think of Oncotype DX, we have a breast gene expression assay called EndoPredict, Polaris, Decipher for prostate cancer, these are other examples. They're not expression assays. They are expression assays, but they look at a specific set of genes for cell cycle progression and things like that, and that field has really taken off, so that's a really good use of RNA in clinical practice. And then you're starting to see it more, I would say, particularly in somatic testing, looking at fusions, because that's really where RNA shines, where it's hard to actually look at DNA, but it's great for looking at fusions and different things like that.
0:13:23.4 DS: So I try to keep these talks... Even though this is clearly a mirrored, branded slide deck, I do try to give these talks... Usually, if you ever come to me on Oncology Life, we try to keep things fairly unbranded. But I do think this is important, at least to show that we, just in the last week or so, we've changed the way our testing requisition is. So now there's actually a box for RNA analysis. So yeah, if you're ordering testing for hereditary, now there's an RNA analysis box. Not that we weren't doing it in the past, but we're trying to streamline a bit the way it's done and just make sure people know that we actually do it, because a lot of people have no idea that we were doing RNA. So the way this checkbox works is it's just a proactive way that we can go right to the patient if after 14 days, if we don't hear from the provider. So we will always send a notification, "Hey, we found something, on say your saliva test or blood test or whatever it may be that's indicative that it needs more analysis using our RNA analysis." Usually we would wait for the provider, and often it was just kind of a barrier. So now, we've set up mobile phlebotomy as an option, can go right to the patient at that point, obtain a blood sample in a RNA-stabilized tube and then proceed with the next step in the analysis. So I wonder if there are any questions there.
0:14:54.2 SC: So TJ, I have a question. I do, yeah.
0:14:56.3 DS: Yeah, sure. Then I'm just gonna show some examples to solidify everything.
0:15:00.7 SC: So with this check box, if I understood your explanation correctly, the patient's provider will be contacted only if it is an appropriate time to use RNA analysis, not for every patient compared with DNA.
0:15:20.2 DS: Yeah.
0:15:20.3 SC: Okay, just wanted to clarify.
0:15:21.8 DS: Yeah, and RNA is needed very seldomly in general. Well less than 1% of the time, where it's a splice variant that we don't have already classified in our database or that's not obvious, where we can also then use an informative snip in the region to actually inform on the variant itself. So yeah, and it doesn't mean... Again, even if you don't check this box, we can still go back to the provider. This is just kind of an ease of use convenience strategy. And then paired with a mobile phlebotomy, hopefully it does make a very nice offering. And also with the saliva as a reflex, to me, that's a big one, 'cause then it means that we can do this on any saliva sample, we can set up this reflex pathway. So just a couple of quick examples, and then I think it'll solidify the approach that we tend to use. So this is a check 2 variant here. It's a splice site, so it's a plus 3. So any time you see that minus or plus after a bunch of numbers, that usually means it's a splice site. That's a general rule of human genome variation society nomenclature.
0:16:37.0 DS: And so this is a splice site into the intron. And so the important thing here is, the reason you can't look directly at the RNA for this example is because if you turn this into cDNA, it's gone. If you're just looking at exons, now you don't... This isn't even gonna be there. So there's nothing to actually follow because it gets cut out, especially if it's working correctly. So it is nice to have a tracker in the area. So this is an example of something where our splice prediction tool said, "Yeah, it probably causes a bit of a problem." Had some information in our own database of 59 patients and alleles found in nomad were here and there. There was some literature showing observed skipping of exons 3 and 4, and there was a pro-band that looked a little concerning. Had breast cancer at 58, no other family history, and have this nice informative snip in exon 5, which is in the region of this splice variant. And so it was in trans, so you can use it to actually track, 'cause it sits in the exon, which is beautiful. And so Paula, and Paula, I don't know if you wanna explain this slide a little bit and kinda how you do your technique, 'cause I think it's really helpful for the audience to hear how the lab works.
0:18:06.3 Paula Nicks: Yeah. So I guess before I do that, I just wanna step back and maybe emphasize that the reason why it's a little more complicated in these cases is because we're dealing with a heterozygous variant carrier. So there's always the presence of the wild type normally spliced transcript, and then we're trying to understand whether the mutant allele might cause a splice defect, and if it does cause a splice defect, to what extent it does. And so that's why following a snip that's present in an exon can kinda help us keep track of the splicing events and which allele it's coming from. So in this particular case you can see that 47% of the transcript was normally spliced and because of the placement of the primers we're amplifying exons 2 through 8.
0:19:15.3 PN: And the snip is in exon 5 and the splicing event is happening around exon 3. And so all of the normally spliced transcript have the C allele and all of the aberrantly spliced transcript have the T allele. And so by that we infer that C allele is the wild type allele and that T allele is associated with the plus three T mutation. And so there are two conclusions here. One is that the variant causes a splice defect and that defect is skipping of an exon, of one exon or two exons, and then in rare cases there was an insertion of some intronic sequence. But the second conclusion is that this is not a leaky splice defect and that the variant allele is not producing any normal transcript. And so it's those two conclusions that have to be reached before we can feel confident in re-classifying a variant.
0:20:29.7 DS: Yeah. Thanks, Paula. And can you explain actually how it's physically done, how you get it in wells and do these kind of percentages in the lab?
0:20:40.3 PN: Yeah. So there are a couple of ways this can be done. The way that we do it is simply by diluting the cDNA template down to the limit of detection. And so that... And then we just do repeated rounds of PCR. So we distribute the template in a very dilute concentration to lots of different wells and then we do the repeated rounds of PCR sequencing.
0:21:12.6 DS: Trying to get pretty much one C molecule per well.
0:21:16.6 PN: Per well. And so...
0:21:17.6 DS: Yeah, right.
0:21:20.5 PN: So in that case that then we're able to isolate those single alleles. And the way you showed that example, those sequencing traces, you could see... That was an example. Maybe you could go back to that slide.
0:21:34.6 DS: Yeah. Let me...
0:21:37.6 PN: So those two sequencing, that was from a heterozygous carrier. And under standard PCR conditions you would see those two traces basically on top of each other and you would see both that G peak and a C peak together in the same position. When you dilute the DNA and you amplify you're basically amplifying just a single molecule and you'll randomly get one allele versus the other. And then we can count those up in order to quantify how much of one allele is expressed versus the other. And this is kinda similar, a lot of other people do allele specific PCR by cloning their PCR products and that serves the same purpose, but we're just sort of eliminating that cloning step sequence.
0:22:29.5 DS: Yeah, no. Thank you. Very helpful. So yeah, so this particular variant was after because it met the criteria that Paula just laid out, so you don't see any wild type with the T ever in exon 5, so it means every time you know you see that C allele it's the only one that's producing a wild type and the other one seems to just cause a barren transcript. So it's changed from a VUS to likely pathogenic in this case, so a bunch of reports were amended after that. So I don't know if there's any questions on this case, but I can show two other use cases. But also happy to derail the conversation there and talk about anything anyone wants to. I don't know if there's any questions in the chat, I don't have it easily open on my screen.
0:23:14.6 SC: Yeah. Paula, when you describe the different ways and options of pursuing RNA analysis are there any... Is there any standard or any guideline that says, "This is how it should be done," or is it based on the preference of the lab, the expertise of the lab, and just their individual approach?
0:23:40.5 PN: There are some guidelines, and I would say, in the case of breast cancer genes there's the Enigma Consortium. And they have really defined when we're looking at data from RNA analysis that, again, that it should be allele specific. There's there's no real... You don't have to do it one way or another. I would say most people do it by cloning. But the concept is that you have to know... Because we're dealing with heterozygous cases you have to know whether the mutant allele is also contributing to the normal transcript and the only way to do that is by allele specific analysis.
0:24:32.2 DS: Yeah, and that might become clear here with some of these other cases. I think this one is... This one really drives that point home. So this was just in a recent publication. And Erin, I don't know if you wanna chime in on this one too, and Paula, I remember you were both on this publication. I don't remember what journal is on though. [chuckle] Anyone can refresh my memory.
0:25:00.4 SC: Familial cancer.
0:25:02.2 DS: Okay.
0:25:02.7 PN: No, this one was JCO Precision Oncology or Precision Medicine.
0:25:10.8 DS: Yeah, about precision medicine. So this was a... Yeah, any time again, you see pluses and minuses, it means you're usually talking about a splice site. So, this is minus 8 to minus 12 is deleted and so... Yeah, who knows what it does. Same kind of thing we're observing it in cases and just don't really know. This was a study that essentially did exactly what Paula and her lab would do, where when they actually cloned out the PCR products from colonies, and maybe we can talk a little bit about how colony works, 'cause actually, I'm fairly ignorant of it, so you can probably teach me something Paula, if you know but... [chuckle] Looking at the different colonies that were produced then, you see that some have the A, some have the C. So it just shows that, if you track something in the region and you see things with normal splicing, you tend to see both. If you see the exon 5 skipping, they had the C allele. When we looked at this particular variant, it actually looks very benign, so this is our pheno program...
0:26:30.2 PN: TJ, I'm sorry to interrupt.
0:26:31.2 DS: Yeah, sure.
0:26:31.3 PN: If you go back, just go back to the cloning, so, the previous slide that you were just...
0:26:37.1 DS: This one?
0:26:38.6 PN: So the key take from this experiment is the fact that if you look at the 10 colonies that showed normal splicing, that there was a mixture of the two alleles, so that says...
0:26:48.9 DS: Yeah.
0:26:50.9 PN: It's a partial splice defect. So the variant allele is still, although it's producing aberrant transcript with exon 5 skipping, it's still also producing normal transcript. So when you see those types of results, we don't know whether the amount of transcript, in addition to the wild type allele is of... You know, that could be plenty for normal protein function.
0:27:17.0 DS: Yes, yeah, thanks for being clear there. And I don't know if you wanna explain this slide, this is looking at a minigene assay.
0:27:29.6 PN: So that's a minigene assay there too. I just wanna make sure. So it's just... It's showing that... So in the minigene assay, you're only looking at the variants in question. And you're looking at the different splicing events produced by a particular variant. And so there too, you can see that there are two bands, one represents the normal splicing and one represents the aberrant splicing. So, the darker band is aberrant splicing, so you can conclude that, maybe there's more of that happening. But the fact that there's a significant amount of normal transcript, also confirms the observation that this causes a partial splice defect. So if you look at the, I don't know what the variant is, but if you look at the lane next door, lane number three, you don't see that wild type, the full length transcript. And so in that case, you can see that, that variant would cause a full defect. Whereas the... Our variant in... Or the variant in question, that we're talking about is a partial.
0:28:41.6 DS: Yeah, and then this is what really, kinda drives home that there seems to be only a partial splice defect here, because that may or may not have any effect on the phenotype. So this is our pheno program and... Erin, I don't know if you wanna explain a little bit about pheno? You're more intimately involved.
0:29:02.7 Erin Mundt: Sure, yeah. So for those who haven't heard, pheno is our history rating algorithm, so it's essentially looking at phenotypes, looking at the personal and family histories of individuals that are tested, so those histories are based on what's reported on the TRF and any... So in this case, we have a variant of interest represented by the blue line, so pheno is weighing those... Placing weights for each individual, based on their personal and family history reported, and coming up with a combined variance score, for each of the eligible individuals that can be counted in pheno. So what pheno does is, again, it gives each patient a score and then it also matches thousands of controls to that patient, both controls that have a pathogenic variant in that gene, so in this case in BRCA too, and then thousands of controls, these are matched controls, that have, from our own testing population, that have no pathogenic variants and no V-less in this similar type of gene.
0:30:04.2 EM: And so that's where we see the two control curves, the red representing the pathogenic control curve, the green representing the benign control curve. And then pheno can plot that, or show that score of the variant... The variant's specific score within those controls. And so it is a two-tailed test. So in order for it to make a call, a score for a variant has to be significantly in one curve and significantly out of one curve. We obviously have some ascertainment bias, so we need to make sure that we're not... There's not overlap there. And it's tested often and always performs at greater than 99.5% positive and negative predictive values, so we're very confident in this tool. And as you can see, this score is well within that benign curve, well out of the pathogenic curve. And so pheno is making a benign call for that variant.
0:30:52.8 DS: Yeah, thank you. So essentially, these families, at least by putting in their TRF results and things like that, absolutely are not... And personal cancer history, are not looking like the pathogenic controls. And then this was a recent publication evaluating this, also this variant. Oh, and on this slide, yes, here's that JCO paper, 2020. But then this was a recent paper, actually looking at one of our competitors, I will not say who, but their technique, and if you remember to go full circle, when you... When I first described there's kind of two general ways to do RNA analysis to look at splice defects, this is really the other way to do it. So now you probably have a healthy understanding of the variant-specific approach. The other way to do it is you just sequence the whole, essentially the MRNA from all the genes, and that's what this is. So these are what's called Sashimi plots. So I don't have it in front of me, but I think these are exons 3, 4 and 5, or whatever they are, 4, 5, 6.
0:31:58.0 DS: But essentially, this says, okay, in almost 5400 reads, it went... There was a read that went from this exon directly to this exon, however in 2000 reads or so, this exon was cut out. It actually went... The MRNA sequencing reads just went from this exon straight to this exon and cut this out and you see what the control should look like, that you should have a nice... Okay, all 9000 were here and another 9000 here so that there's no exon splicing. So clearly, there's something going on. It's going from this exon on all the way to the other one, but then it's... What does that ultimately mean?
0:32:44.5 DS: And so based on this result alone... And so this is some of the trick to all this. Based on this result alone, at this lab, now calls this a likely pathogenic variant. However, when we look at our pheno data, then paired with published data showing that, yeah, even the normal splicing... And when there's normal splicing, so everything that looks totally fine, you actually see both alleles. So this is probably just a partial splice defect that really ultimately doesn't have any effect on the phenotype shown here. So we now call this variant a... Even from a VUS we went all the way to benign, so talk about two labs calling something completely different. I mean, one's calling this variant a likely pathogenic variant, one's calling it, us, a completely benign variant based on all this data. And it's really well-supported here. I mean, there's nothing... Clearly, the splicing defect is still allowing normal variants. And the way I tend to think about things are you don't really...
0:33:50.2 DS: If you have two alleles and one is always working fine, 'cause we're talking about heterozygous mutations, if one's working fine, you're already at 50% protein of what your body normally would want. So if you're thinking, "Yeah, we should all be around 100% for BRCA2 with both alleles working," you're already at 50%. So then if this other splicing issue, I mean, even if it's causing a 5% drop or a 10% drop, you're probably fine even if you're functioning with 90% protein or something, or maybe there's some compensation mechanisms that are kicking in. Who knows? But either way, yeah, it's not looking like you have hereditary breast and ovarian cancer syndrome. So I'll pause there for questions, and then I only have one more case that really then...
0:34:38.7 PN: Can you go back to the slide...
0:34:39.7 DS: Even further solidifies some of this.
0:34:40.8 PN: Yeah, with the Sashimi plot? And we can just again, hammer home the message that there is a limitation to RNA sequencing data, which is a very powerful technique, and it does allow you to quantify the events to some extent. So in this case, you can quantify how much normal transcript there was and how much aberrant transcript there was. But what you can't see from this type of data is of those 5399 reads that were normally spliced, which ones were made by the wild type allele and which ones were made by the variant allele. And so that's the limitation.
0:35:28.0 DS: Yeah, and that becomes pretty evident here. So this is another one that was just published. I don't know what journal... Maybe this is the familial cancer one.
0:35:38.2 PN: Yep.
0:35:39.2 DS: Yes, so you guys have been busy. So this is a plus two. Again, there's your plus sign, so it's a splice issue, so around exon 18. And I'll skip some of this and just kinda go here just for the essence of time. But again, here's our pheno plot and there's a... It's touching on the red, so this blue line here is where this variant sits. So it's really sitting in that benign polymorphism group, but the curves aren't necessarily as spread as the last one we looked at. So there's just the inkling of a little touch on the top into the deleterious. And so here, looking at, okay, so what's actually made? So here's this patient, and then this is a... And I've been meaning to ask, Paula, I think you put together these slides. What is the breast control here?
0:36:36.7 PN: It's RNA from breast tissue.
0:36:39.3 DS: From breast tissue?
0:36:40.4 PN: Versus blood.
0:36:42.9 DS: Yeah. So what you'll see is even in normal people, a lot of times in normal tissues and things, it's not uncommon to have some aberrant splicing. It's just kind of part of biology, I guess I would say, so. But this patient, when you actually look... Just looking at what's made from PCR, if you're looking at the RNA, about 54% has exon 18 there, but then you see a significant amount that actually is skipping exon 18. So it has an exon 18 deletion. But based on this data, the pheno data, there must be something else going on. So then Paula and her team went deeper and said, "Okay, if we track an informative snip in the region which is shown here in exon 14, we can actually see what's produced." And so if you then say, "Okay, of all the traces that are made, about 62% are part of the A allele and 38% have the G allele." So it shows you here that it looks like they're of the normal product that's being created because this primer is laying down in 18, meaning that anytime 18 is there. So if it was spliced out, this primer wouldn't lay down but if it was there, then the primer will lay down. So anytime it's normal, so this would be the normal messenger RNA, you're still seeing that the G is contributing to a significant amount of the normal RNA. Hopefully that makes sense for people 'cause it's an important concept. So I'll stop for any questions or any further explanation.
0:38:33.8 DS: And then what's going on here, at least Paula and her team think, is that this was a G to T change to a G to C and that at some splice sites, a G to C is actually very functional, and so it can still work appropriately, which seems to be what's going on. So actually, this was reclassified from deleterious all the way down to a VUS. I'm not sure why you didn't go all the way to benign in this case but is that just because we wanted to see pheno completely in the green without any red overlap?
0:39:12.9 PN: No, pheno is making a call but I think because this variant...
0:39:18.5 DS: Yeah, I guess they're saying it's in polymorphism.
0:39:19.7 PN: It was at... So a change at a plus two would usually be classified as likely pathogenic.
0:39:28.0 DS: Yeah, 'cause that's phenonic.
0:39:30.0 PN: And there was published evidence showing that the exon skipping defect, and so that's what brought the variant to deleterious. And then when we saw the pheno calling as polymorphism, that's when we said, "There's probably something else going on and this may not be pathogenic." And so we reclassified this to VUS but I think we'd like to see a little bit more lines of evidence to support a benign effect.
0:40:01.8 DS: Yeah. Do you wanna walk through maybe other lines of evidence? We didn't really get into that but I guess I can go back here.
0:40:08.0 PN: Well, like the previous example that you showed where you showed the PhenoGraph. So in that case, that one's benign because we also have observed that variant in trans with a known deleterious mutation in a patient without features of Fanconi anemia, and so that's another line of evidence. So that would be another strong piece of evidence that we would use in the case of this plus two T to C. I don't know, Erin, do you have anything else?
0:40:44.9 DS: Yeah, I don't know if there's anything else but clearly, there's many different ways we attack variants [chuckle] and that was what I was showing, is that gonna go co-occurrence and...
0:40:55.6 EM: Yeah, and I would just add, I think as has been mentioned a little bit, the partial splice defects are difficult. So because a splice defect is partial doesn't mean that it's benign or pathogenic. So that's when we depend on other evidence, like clinical evidence, to help us get there. And it's sometimes tricky to use pheno when we see a partial splice defect because the variant is doing something abnormal. It's causing... Their splicing isn't normal. And so then we have the pheno data. If a pheno is saying it's benign, it's not necessarily conflicting but we just wanna make sure that we're looking at everything, that we have all the information. In this case, we have a good idea of why this variant isn't behaving like a typical variant at the plus two position based on the RNA data but as Paula said, I think we just want to make sure we have additional evidence before we take it down one more step because there are a lot of different things going on here.
0:41:56.0 DS: Yeah, no, great. Thank you. So we can pause there for some questions and things. And I'm new to the recording but I apologize, I forgot to read the disclaimer. We actually just started recording, Myriad Oncology Live, that's why you do see it recording in the top left of your screen, probably. So we're recording it simply so other people that can't make the call can still be part of this. If you are uncomfortable with anything... Clearly, people haven't really been asking questions or anything like that but since we're gonna go into question mode, if you have any concerns or anything, just let me know. But yeah, we will eventually post this just for... They go up on our Myriad Oncology education site just for anyone to peruse later. But we do come back to this topic every three months or so, so sorry I forgot in the beginning.
0:42:52.3 SC: TJ...
0:42:53.9 DS: Yes?
0:42:54.3 SC: I know we're talking about RNA this evening but are there new and other techniques, approaches emerging to address hereditary risks for variant classification?
0:43:09.0 DS: Yeah, and I'm gonna defer first to Erin or Paula. Anything really amazing on your radar? I think of long-range sequencing but that's futuristic, I feel. That's probably gonna be something over time. As sequencing costs come down, maybe at some point we will be sequencing the entire gene. Right now, everybody... When you hear, "Oh, BRCA1 was sequenced," it actually wasn't sequenced, just the coding exons of BRCA1 and some bit into the splice were sequenced. So I could see a world where we're... Especially as we start getting better at handling line and Alu insertions, and weird things like that in the genome that we start sequencing out entire genes, which a lot of that would get at anything else that is going on but I think we're pretty... It's not like that research hasn't been going on to some extent, and even RNA. This is nothing new, we've been doing it for years, and there's nothing magical.
0:44:08.3 DS: I think what we're learning in hereditary genetics... And I'm talking about just hereditary genetics, but I think what we're learning in hereditary genetics is really it comes down to, primarily, the coding exons, which is what people get sequenced in today's era. And then after that, if I had to take one thing into the woods, it would probably be polygenic risk scoring because after coding exons, you're really... Yeah, there's some variants that we can find but like I said in the beginning, sub-1% are gonna have any sort of information from RNA. And then, really, other techniques, like long-range sequencing, probably aren't really gonna uncover anything else major, so at that point... And we've really... And then I'll even add to that. If you think of all the other genes that we've sequenced and tried to associate with cancer and hereditary cancer, and things like that, we're not really finding a lot of [chuckle] other genes. It's not like we haven't been doing it for the last decade in every research lab around the country, world even.
0:45:08.5 DS: So I think, at this point, we're moving into... For hereditary, I think polygenic risk score is that new frontier where now, you can actually give a result to a 100% of people taking the assay, the test, because you can actually look at, Do they have a coding exon mutation in the genes that we care about that we know are associated with cancer risk and if not, can we apply their other background, genetics, other clinical family history variables through models like Tyrer-Cuzick or BOADICEA CanRisk, whatever, and start giving them a more true risk estimate for cancer? It's a good question. Good, any other questions on the chat? Oh, I have a question here, Can RNA be reclassified? That's a great question. [chuckle] I don't know, Paula, can we reclassify RNA? DNA variants are reclassified. I don't tend to think of... We're doing research...
0:46:17.5 PN: Do you mean, Can we reclassify based on our splicing results?
0:46:24.6 DS: Yeah, I guess in general. Have we ever reclassified an RNA variant where you've said, "Okay, this is VUS," and then for some reason, you would upgrade it. It's not like you would do another RNA study on it. Have you ever done more than one... I guess that's a good question. Have you ever done multiple different allele-specific RNAs on one variant? Probably not, I would think, is there...
0:46:54.8 PN: So in different patients with the same variant?
0:46:58.0 DS: Yeah. Have you ever come across that where they...
0:47:01.0 PN: Yeah, we've done that a handful of times. Generally, it's just on one patient and that's sufficient to get an idea but every time, of the small handful of cases where we've had multiple patients, we've always seen the same outcome, so the defect is the same in unrelated patients.
0:47:27.4 DS: Yeah. So yes, unlikely that the RNA result would get reclassified. But again, RNA is one picture of the whole puzzle in the DNA variant classification, so I guess, technically, that could always get reclassified for some odd reason. And one example is one we were just talking about, where that RNA variant looks like it could potentially go to benign but we do want some more evidence and maybe if more evidence comes in over time, that would get reclassified from a VUS all the way down to a benign polymorphism.
0:48:00.4 SC: I'm curious, with a lot of the attention that's been focused on using RNA analysis, from your perspective, what is the most challenging aspect of using this to help with variant classification and in what we're doing here?
0:48:21.3 DS: Yeah, Paula, you can probably take this one but the allele-specific is fairly labor-intensive.
0:48:30.9 PN: Well, the burden is demonstrating the contribution of the variant allele to the normal transcript, and that's the major limitation and difficulty with this. So if there were a way around that, then it would make life easier.
0:48:54.0 DS: Yeah, you really need to know that informative allele, so you can track it. But just beyond that, I guess, why aren't we just rolling this out for everything? A, we wanna see that there's a DNA variant that is looking like it's affecting splicing, overall, and then it can move into this pathway. And again, we can do that off saliva DNA variants or blood. It's a good question.
0:49:21.8 SC: So if you, in theory, had an option that everybody had RNA and DNA paired, there'd be a very small percentage, less than 1%, that would have any level of informativeness using that?
0:49:35.0 DS: Yes. And I don't know, in your mind, Paula or Erin, what that actual number would be but it would be very low because also then you're taking into account... It's not like we're starting from zero, so we already have information on, arguably, thousands, if not hundreds of thousands of variants. And so, in today's era, I don't know, it would be well less than 1%, I would think, would actually need some sort of RNA for informative calling, but I can't really give an exact number on it. [chuckle]
0:50:16.3 PN: And if you think about it, especially intronic variants are the ones that are difficult. So variants that might impact splicing but are in the exon, those ones are easy to analyze. But the intronic ones, a read window at the acceptor side goes all the way out 20 bases upstream of the start of the exon and 10 bases downstream of the exon, so that's 30 positions where you could a variant and very often, changes at those positions are gonna cause a partial splicing defect. So you have to know, Is it partial and it's okay or is it partial and it's bad, or is it complete and it's bad? And that's the challenge. And so just because it's in the intron, not every variant is gonna make a good candidate for a study and not every patient is gonna be a good candidate for study. So you need to combine the two. You have to get a good patient with a good variant. [chuckle]
0:51:31.4 DS: Yeah, exactly. Good, anything else from the audience? And if anyone else has any burning questions, now is the time. [chuckle] And then I'm gonna... Sorry, let me put this back and I'm gonna show next week's schedule again, but I do wanna... I really appreciate Paula coming on and Erin, your expertise is greatly appreciated. And Shelley, thanks as always for running the chat. And then next week, if you're doing some tumor sequencing and you wanna get into tumor normal, this is the place, April 22nd, noon, Eastern. So come with some questions 'cause that's a hot area for sure. And otherwise, I hope everyone has a great rest of their day and thanks for the East Coast folks for staying late with us. It's 7:00 PM, so till next week. Thanks, everyone.
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