Validating antibodies for research applications in IHC

Video Transcript

• 00:00 - 00:10: Hello, everyone, and welcome to today’s webinar, Validating Antibodies for Research Applications
• 00:10 - 00:15: in IHC, presented by Dr. Will Howat and Damian Cockfield.
• 00:15 - 00:19: I’m Chrissy Joel of Labverts, and I’ll be your moderator for today’s event. 00:19 - 00:24: Today’s educational web seminar is presented by Labverts and brought to you by Leica Biosystems.
• 00:24 - 00:29: To learn more about our sponsor, please visit leicabiosystems.com.
• 00:29 - 00:34: Now, before we begin, I would like to remind everyone that this event is interactive.
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• 00:44 - 00:48: We will answer as many questions as we have time for at the end of the presentation.
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• 01:00 - 01:05: This presentation is educational and thus offers continuing education credits.
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• 01:14 - 01:23: I now present today’s speaker, Dr. Will Howat, Director of Antibody Validation and Characterization, Abcam.
• 01:23 - 01:30: Also speaking with Dr. Howat is Damian Cockfield, Global Product Manager, Bond, Leica Biosystems.
• 01:30 - 01:37: For complete biographies on our speakers, please visit the Biography tab at the top of your screen.
• 01:37 - 01:44: Dr. Howat, you may now begin our presentation.
• 01:44 - 01:53: Thank you, Chrissy, for that introduction and welcome to a webinar on validating antibodies for research applications in IHC.
• 01:53 - 01:59: I’m Will Howat and I would firstly like to thank Leica for the opportunity to present on this topic.
• 01:59 - 02:10: And I’m hoping that by the end of it, I will have given you an idea of the framework that is needed to successfully validate antibodies into your lab.
• 02:10 - 02:14: So the top plan is going to go around a general structure.
• 02:14 - 02:18: So the first thing to answer is really what is the problem?
• 02:18 - 02:24: So why is IHC so difficult for validating antibodies?
• 02:24 - 02:32: We’ll then go into some details around some of the problems that can come up during an IHC staining plan.
• 02:32 - 02:40: And then we can go into how we can resolve those using a particular method such as a Leica Bond in order to make that better.
• 02:40 - 02:50: And hopefully that will give you the framework or the foundations in this case to be able to build on those antibodies you’ve used into other applications.
• 02:50 - 02:56: So I would like to start firstly with the paper you can see in the bottom right hand corner.
• 02:56 - 03:00: And I’ve taken this quote from this paper and I particularly like it.
• 03:00 - 03:05: And it’s because, I will read out to you, if sharp and beautiful pictures obtained.
• 03:05 - 03:09: Investigators often tend to believe that the antibodies are specific.
• 03:09 - 03:18: The main concern is that the cost involved in disproving spurious results from other laboratories is huge and often much higher than the cost of proper testing in the first place.
• 03:18 - 03:26: And what I really want to take away from that is that antibody validation can be time-consuming and it can be difficult.
• 03:26 - 03:33: But if you put the right framework in place and you can be confident over the results of that framework,
• 03:33 - 03:40: then you can be confident the results of your antibody are specific and that data you can take forward into other applications.
• 03:40 - 03:48: So it’s getting all that framework right in your lab and in your hands is the important part and doing it correctly.
• 03:48 - 03:52: So why don’t antibodies work for formalin-fixed tissue?
• 03:52 - 03:59: Well, there are many reasons, but at least one of them, if you take a protein, a protein is obviously not just a long string of amino acids.
• 03:59 - 04:03: It’s folded up and there are many proteins alongside it.
• 04:03 - 04:14: And if you were to look at two particular epitopes, in this case, a blue epitope and a red epitope, after formalin fixation, you get disulfide bonds being formed.
• 04:14 - 04:21: And those do two things. One, they help to create a structure and they bind the proteins together.
• 04:21 - 04:27: And that is helpful for us in pathology because it means that the tissue in itself is harder.
• 04:27 - 04:33: And that means that when we try and come out with a microtome blade, then we can do so once it’s paraffin embedded.
• 04:33 - 04:37: So it’s helpful, but it also hinders us in many ways as well.
• 04:37 - 04:45: So if you take two antibodies, the blue antibody will find its epitope because it’s right next to it.
• 04:45 - 04:54: Whereas the red epitope is blocked and it’s blocked because the formalin bonds are blocking the access of the antibody to its epitope.
• 04:54 - 04:59: So then you add antigen retrieval. And by adding antigen retrieval, you break down some of those bonds.
• 04:59 - 05:09: You break down some parts of the protein itself that allows the blue antibody, in this case, to bind and the red antibody to find its target.
• 05:09 - 05:14: So you’ve got to remember that that’s where the problem lies.
• 05:14 - 05:21: And although you can use various methods to try and resolve that, you’ve got to remember that you’ve got to get this specificity.
• 05:21 - 05:27: You’ve got to know your target really well. And bear in mind that there are a number of things that can go wrong.
• 05:27 - 05:34: So the first one I want to demonstrate to you, and by all means, this is not an exclusive list.
• 05:34 - 05:40: Antigen retrieval can change the path of staining. So on the left-hand panel, you have a marker.
• 05:40 - 05:47: This is a marker for phospho-MSK1. It’s using, in this case, an epitope retrieval, probably ER1.
• 05:48 - 05:55: But this marker is a protein kinase. It’s used for phosphorylation of a transcription factor.
• 05:55 - 06:00: So you’d expect it to be nuclear staining, and it is. Perfect.
• 06:00 - 06:10: However, if you use an enzyme retrieval, which some markers prefer, in this case, you get a really nice, really beautiful staining pattern.
• 06:11 - 06:15: In the serial section, you can see exactly where it’s binding, but it’s wrong. 06:15 - 06:20: It’s not a nuclear marker. It’s not the right pattern, but can be very believable.
• 06:20 - 06:28: Going back to that first quote, just because it’s nice and strong does not mean that it’s necessarily correct.
• 06:28 - 06:35: And I’d like to thank my colleague Hayley Whittaker from UCL for allowing me to use this image and a number of other images in this presentation.
• 06:36 - 06:38: And it’s not just that. Fixation can change the pattern of staining.
• 06:38 - 06:47: So if you take this marker, it’s a cleaved caspase-3 on mouse paraffin, it’s got exactly as you would expect for a cleaved caspase-3 antibody.
• 06:47 - 06:54: It’s cytoplasmic. You can see the apoptotic body staining positively. Everything you would want.
• 06:54 - 07:01: But if you put that onto a piece of human frozen tissue, then you get entirely the wrong pattern of staining.
• 07:01 - 07:08: You’ve got a cell surface marker that’s already been expressed in epithelial tissue, and that’s not what you would expect from cleaved caspase-3.
• 07:08 - 07:11: So again, fixation can change the pattern of staining.
• 07:11 - 07:22: And lastly, also, as I said, it’s not an exclusive list, is you’ve got to remember the staining intensity is not a guide to positivity.
• 07:23 - 07:31: So in the bottom left-hand corner of the screen, you can see a marker called AZH2 expressed in the prostate gland.
• 07:31 - 07:37: It’s expected to be a nuclear marker, but its expression is very delicate.
• 07:37 - 07:44: So when we validated this antibody on the Bond machine, then we took it to a particular level.
• 07:44 - 07:48: We could not get it to really 3 plus intensity, but we had it.
• 07:48 - 07:53: So we had a really nice signal-to-noise. It was very minimal background, but it’s a delicate stain.
• 07:53 - 08:00: If you take the marker at the top, that is a nonspecific background of muscle and prostate.
• 08:00 - 08:04: I can’t show you the positive staining, which is somewhere in the epithelium. 08:04 - 08:09: But just because it is a darker intensity does not mean it’s real.
• 08:09 - 08:17: And that can be highlighted even further by some work demonstrated in a paper by Angelo DiMarzo recently.
• 08:17 - 08:28: And where he’s demonstrated on the left-hand side a concentration, 1 in 6400, on some negative and known to be untransfected negative cells.
• 08:28 - 08:33: And they are negative. And you get a nice positive staining in the positive transfected cells.
• 08:34 - 08:41: But if you take and dial that concentration up, you continue to have some really nice positive staining on your transfected cells.
• 08:41 - 08:48: But your negative cells start to turn positive. So you’re getting a lot of false negatives.
• 08:48 - 08:51: So you really got to know what you’re trying to achieve.
• 08:51 - 08:56: And you’ve got to have the right controls in place in order to be able to get this accurate.
• 08:58 - 09:01: I’m going to move on to what does a good framework look like.
• 09:01 - 09:07: And the two papers I’m going to refer to, mainly through this webinar.
• 09:07 - 09:15: The one at the bottom left was co-written by myself and a number of colleagues across industry as well as academia.
• 09:15 - 09:24: And then the one on the right is a paper that I helped work under when I was working in the pharma industry.
• 09:25 - 09:32: So to begin with, I think nobody would disagree that the first thing you need to understand is the target.
• 09:32 - 09:35: So you need to really understand the biology of that target.
• 09:35 - 09:41: You need to have a full literature review of what has already occurred, what has been stained, if anything.
• 09:41 - 09:44: In some cases, there might be nothing stained.
• 09:44 - 09:49: And that will help you to work out the subcellular localization of that target. 09:50 - 09:52: You know, what the biological relevance is.
• 09:52 - 09:58: And it will then also be able to help you to identify the cells and tissues you might use.
• 09:58 - 10:03: So you’ll be able to work out what your positive and negative cell lines are. 10:03 - 10:07: You’ll be able to identify your positive and negative control tissues.
• 10:07 - 10:14: And that allows you to be able to put together all the control material you need to be able to validate your assay.
• 10:14 - 10:23: And what I’d like to highlight to you is that the cell line controls you pick can be used as a surrogate for tissue if you treat them the right way.
• 10:23 - 10:33: So you can take cells, you can grow them up, you can spin them down, you can fix them in formaldehyde as if you were fixing a small biopsy or a piece of tissue.
• 10:33 - 10:36: You can process it into paraffin.
• 10:36 - 10:39: And then you’re treating it as a surrogate.
• 10:40 - 10:44: In that, what you’re trying to determine is the specificity of your antibody. 10:44 - 10:55: And by that, I mean that you’re asking the question whether the antibody binds to a protein that has been formally fixed and paraffin-embedded and has gone through an IHC process.
• 10:55 - 11:04: It’s not trying to tell you whether there’s any backgrounds there because it really can’t do that because the amount of material in there is only just cells.
• 11:04 - 11:10: It’s just asking the question, does it bind to FFPE tissue, FFPE stuff.
• 11:10 - 11:12: So there are a number of ways of doing that.
• 11:12 - 11:16: First one, I would highlight to use knockout.
• 11:16 - 11:20: So in a knockout cell line, we have truly knocked out the gene of interest. 11:21 - 11:29: In this particular case, this is PD-L1 and there’s been a gene excision by TALEN constructs to knock that exon of PD-L1 out.
• 11:29 - 11:35: And you get a positive in the parent and a complete negative in the knockout cell line.
• 11:35 - 11:41: But you can also, if you haven’t got a knockout to hand and they’re not always easy to be able to make, you can do a knockdown.
• 11:41 - 11:50: And in those cases, what you’re looking at is an siRNA transfection and you don’t get a perfect knockdown.
• 11:50 - 11:55: So some cells will take up the transfection reagent and will knock down and others will not.
• 11:55 - 12:03: So you get this heterogeneous pattern of staining, which is actually in some ways helpful because you can see the positivity and you can see the negativities.
• 12:03 - 12:06: You’ve got your in-house negative-positive control.
• 12:07 - 12:11: But the key thing here in each case is to confirm that.
• 12:11 - 12:17: So in the left-hand panel with the knockout, the knockout was confirmed by deep sequencing, so you know it’s a true knockout.
• 12:17 - 12:25: In the right-hand panel, they used the Western blot in order to be able to determine that there was a reduction in the amount of signal for AZH2.
• 12:26 - 12:36: And so that gives you confidence that the material you’re using will allow you to make a definitive conclusion over your cell line control.
• 12:36 - 12:41: So sometimes, again, you can’t knock them down.
• 12:41 - 12:43: So you can still use other methods.
• 12:43 - 12:51: So in this case, this is an overexpression and that can be using a native cell line that does not express the target.
• 12:52 - 13:03: In this particular example, this is a PD-L2 that’s transfected into a HEC293 cell line, but then stained with anti-PD-L1 and is negative.
• 13:03 - 13:05: So it’s a similar process.
• 13:05 - 13:11: And on the left-hand side, you’ve got PD-L1 transfected, 293 stained with anti-PD-L1.
• 13:11 - 13:16: So you can you overexpression cell lines as well where you need to.
• 13:16 - 13:20: Again, sometimes that might be difficult and you can still use native cell line expression.
• 13:20 - 13:30: An example I have here from the paper in the corner, RMG2 is negative for ARID1A and we can confirm that by a Western blot.
• 13:30 - 13:38: And the AZH2 cells are positive for ARID1A and you can use those by fixation and FFPE processing.
• 13:38 - 13:41: You can use those as a surrogate for tissue.
• 13:42 - 13:48: Ultimately though, you need to go to tissue because there’s only the tissue that’s going to be able to demonstrate your sensitivity and cross-reactivity.
• 13:48 - 14:00: So in this case, we would use a multi-tissue microarray and that tissue microarray contains all the information you want, both positive material and negative material.
• 14:00 - 14:07: You can do that a multitude of different tissue microarrays and it gives you confidence that your assay is working really well.
• 14:08 - 14:11: But sometimes tissue microarrays won’t work.
• 14:11 - 14:16: So you can’t always rely on exactly the same thing every time you go through your framework.
• 14:16 - 14:19: You have to be specific to your target.
• 14:19 - 14:22: So some specific targets require specific validation.
• 14:22 - 14:29: On the right-hand side, you can see the tissue microarray we’ve run in this case is completely negative, but that’s because it’s a very specific marker.
• 14:30 - 14:37: There’s only expressed mature functioning olfactory neurons and therefore you have to use that single piece of tissue in order to validate that antibody.
• 14:37 - 14:39: All that makes sense.
• 14:41 - 14:43: And the last thing to highlight is orthogonal validation.
• 14:43 - 14:57: So we talk about orthogonal validation regularly within the validation field as using other methodologies to try and prove or add additional information to try and prove your antibody is specific.
• 14:58 - 15:00: Now, that’s great when it works.
• 15:00 - 15:12: And in this case, this is a great antibody to CCR6, works in immunohistochemistry and the Western blot, which you expect to work at 42 kilodaltons, is entirely doing that on the Western blot.
• 15:12 - 15:14: But that’s not always the case.
• 15:14 - 15:20: And I’ve seen many antibodies where the Western blot is positive, but the IHC antibody doesn’t stain.
• 15:20 - 15:22: And also some the other way around.
• 15:22 - 15:24: IHC is positive and Western blot is negative.
• 15:25 - 15:35: And you’ve got to know the strengths and weaknesses of your method and you’ve got to use those in conjunction with each other, but not simply rely on one method to validate another.
• 15:35 - 15:47: Because if you take this individual clone, we know because we’ve tested this, you can take that antibody, you can run it in immunohistochemistry on fixed cells and it will be negative.
• 15:48 - 15:50: We can run it in flow cytometry and it will also be negative.
• 15:50 - 15:56: And we can run it in a cross-species assay with mouse immunohistochemistry and rat immunohistochemistry and it will also be negative.
• 15:56 - 15:58: This is a human-specific marker.
• 15:58 - 16:04: And we will highlight that within the data sheet to make sure that everybody is aware of that.
• 16:04 - 16:12: So you’ve just got to make sure you know how your assays are acting and you don’t always follow the same route because it might not always work.
• 16:12 - 16:15: This comes up in the next slide about one size does not fit all.
• 16:15 - 16:20: And what I mean by that, if you’re lovers of golf, this will help you.
• 16:20 - 16:24: So you need a number of different clubs in your bag.
• 16:24 - 16:31: Because in an example such as this, if you’re a golfer, you can look at that pathway where you think that’s not particularly difficult.
• 16:31 - 16:38: If you don’t hit it straight, you’ve not got any particularly bad bits and rough to hold you up while you try and get out of that trouble.
• 16:39 - 16:43: However, you would take a different approach if you were a list golfer.
• 16:43 - 16:48: The two approaches have to be different because they are different holes. 16:48 - 16:51: The same applies to antibody validation.
• 16:51 - 16:55: So I’d like to refer to the paper in the bottom right-hand corner.
• 16:55 - 17:01: And although this particular validation method might look really complicated, it’s actually not.
• 17:01 - 17:05: So everything that’s on the screen now is similar to what we just talked around.
• 17:05 - 17:08: It’s around detecting your target protein.
• 17:08 - 17:10: It’s specific to your target.
• 17:10 - 17:14: And it doesn’t detect other proteins with no background, for example.
• 17:14 - 17:18: And this is what you want for your basic validation package.
• 17:18 - 17:24: So there are a number of golf clubs that you need in order to get across to the hole.
• 17:24 - 17:28: So you need a driver, a putter and an ant. That’s about all you would require. 17:29 - 17:36: But when you need to go into something that’s much more dedicated, where you need to do an IVD and a Vita diagnosis,
• 17:36 - 17:42: such as like we do or a companion diagnostic or an antibody that is required for clinical trial work,
• 17:42 - 17:48: which is what the purpose of this paper was, then you need to add extra clubs to your bag.
• 17:48 - 17:54: Or you may need to ask for some additional assistance and some experts in order to be able to help you do that.
• 17:54 - 17:59: So this is the additional level of validation or enhanced validation.
• 17:59 - 18:02: So, for example, and again, this is not exclusive.
• 18:02 - 18:08: For example, if you are looking at a phosphorylation marker such as phosphorylated 50 here,
• 18:08 - 18:14: you must put in a dephosphorylation to demonstrate that you’re looking at phosphorylated 50 and not RAD 50.
• 18:14 - 18:16: That’s an absolute requisite.
• 18:16 - 18:21: And equally, if you’re going to be making a clinical trial marker
• 18:21 - 18:25: and that’s going to be going across a number of different disease indications, you know,
• 18:25 - 18:27: you need to be able to test in those.
• 18:27 - 18:32: And, you know, this is the data from this particular phosphorylated 50 on gastric TMBC and CRC.
• 18:32 - 18:38: So you need to tailor the information and the validation to the target that you’re looking for.
• 18:38 - 18:39: And it doesn’t stop there.
• 18:39 - 18:48: So you can also, for an IVD, you can add all of these things and you need to know the inter-assay variability. 1
• 8:48 - 18:53: You need to know how stable the antigen is, the epitope is, when you cut a section.
• 18:53 - 18:56: You need to know the stability of the antibody.
• 18:56 - 18:58: You need to have portability between sites.
• 18:58 - 19:01: All of these things are really important to get right.
• 19:01 - 19:07: But that’s for your enhanced validation, not necessarily for your simple basic package.
• 19:07 - 19:09: So what does a good framework look like?
• 19:09 - 19:17: Just in this particular section of the stock, it is around making sure you get full literature review.
• 19:17 - 19:21: That you know from that where your sub-cellular localizations are,
• 19:21 - 19:27: what your negative and positive cell lines or controls are going to be in tissue and in cell lines.
• 19:27 - 19:31: And using cell lines is appropriate to do that up to a point.
• 19:31 - 19:35: That you’ve got a good IHC method available to you,
• 19:35 - 19:39: and you should consider using automation in order to be able to tie that up where you can.
• 19:39 - 19:41: And you’ve got good controls.
• 19:41 - 19:48: So by doing all of this, you will generate the good controls that you need to be able to use in the rest of your validation framework.
• 19:48 - 19:54: So once you’ve done that, you can start to put antibodies through that process,
• 19:54 - 19:56: and it should be relatively easy to do.
• 19:56 - 20:02: So you can take an example here, which is Cal10 as a PD-1 clone.
• 20:02 - 20:06: And which is, you know, we’ve got from the basic validation package,
• 20:06 - 20:10: we have some data on the human tonsil, looks very good.
• 20:10 - 20:13: But we can enhance that with some cell line data.
• 20:13 - 20:20: These are from Histocyte Laboratories where we’ve got PD-L1 known levels of expression,
• 20:20 - 20:22: a 3 plus down to a negative.
• 20:22 - 20:25: And we can demonstrate using the same protocol on the same instrument. 20:25 - 20:28: 3 plus 2 plus 1 plus and a negative.
• 20:28 - 20:31: But we can enhance that further.
• 20:31 - 20:36: So we can put that onto a non-small cell lung cancer TMA, 160 core TMA. 20:37 - 20:40: And from that, we can demonstrate the sensitivity of the assay.
• 20:40 - 20:49: So in that panel of four tissue microarray cores, you have PD-L1 staining on a tumor that’s strong.
• 20:49 - 20:54: In the bottom right-hand corner, you’ve got a tumor that’s staining negatively for PD-L1,
• 20:54 - 21:00: but has got PD-L1 positivity in the immune cell fraction and macrophages. 21:01 - 21:06: So you can take all of that to enhance your individual data.
• 21:06 - 21:09: And then you can take it to another level, which we do in Abcam,
• 21:09 - 21:15: which is to put it onto other TMA sets of multiple different tumors
• 21:15 - 21:20: to help to tease out if there’s any other areas, any other cancer areas that could be relevant.
• 21:20 - 21:22: We can put it onto normal tissues.
• 21:22 - 21:24: We can put it onto mouse rat tissues.
• 21:24 - 21:26: In this case, we know it happens to be negative.
• 21:26 - 21:29: We can put it, we can test it in immunocytochemistry, which we do,
• 21:29 - 21:34: and demonstrate that it works for immunocytochemistry, this particular marker.
• 21:34 - 21:37: And we can demonstrate it works for Western blot.
• 21:37 - 21:40: Equally, we know it doesn’t work for flow cytometry.
• 21:40 - 21:46: So you can use that whole package of datasets to give you confidence on what you’re doing.
• 21:46 - 21:49: And once you’ve done that, you’ve got your framework.
• 21:49 - 21:53: Once you’ve got your framework, you can bolt on the other applications that you want to run.
• 21:54 - 21:57: In this case, I’m showing some multiplexing data.
• 21:57 - 22:03: So you can take that groundwork you’ve done for validating the antibody. 22:03 - 22:07: You know it’s specific. You know that it works on your tissue type.
• 22:07 - 22:12: But what you don’t know in this particular stain and wipe assay is what position it’s going to stain in.
• 22:12 - 22:18: So you can do that work having confidence that you know well how the antibody performs.
• 22:18 - 22:21: And so you can put that in multiple different positions.
• 22:21 - 22:29: You can multiplex it in a number of variety of ways on different tissues that you know it’s expressed on.
• 22:29 - 22:41: And it makes that extra validation work really well within the multiplexing area because of the foundations that you’ve already built.
• 22:41 - 22:47: So to end off and to summarize, for me, the key to good validation is good framework.
• 22:47 - 22:51: You’ve got to have high-quality literature analysis.
• 22:51 - 22:59: You can use cell line controls as a surrogate for tissue when you’re looking for specificity.
• 22:59 - 23:10: But you need to extend onto multiple tissues to try and look at background levels as well as the sensitivity of that in normal tissue expression and in multiple patients per tissue.
• 23:11 - 23:14: You can extend the reproducible stability where you need to.
• 23:14 - 23:17: There’s your additional golf clubs you might want to add in.
• 23:17 - 23:26: But that solid foundation and that solid framework allows you to build confidence in your antibody and to build other methods on top of that.
• 23:27 - 23:33: And I’d just like to end with some acknowledgments to my colleagues in Cambridge and Nanjing in China.
• 23:33 - 23:42: To my colleagues in Pleasanton and also in Birmingham in the US who have provided data into this particular data pack.
• 23:42 - 23:48: And also to my former colleague, Dr. Hayley Whittaker, who is currently at UCL.
• 23:48 - 23:51: So thank you very much for listening to this webinar.
• 23:51 - 23:56: And I’d like to take the opportunity to pass you now on to Damian for his presentation.
• 24:00 - 24:02: Thank you, Dr. Howat.
• 24:02 - 24:08: Following on from Dr. Howat’s excellent presentation on setting up a good framework for validating antibodies.
• 24:08 - 24:18: I’m going to take a step backwards before that to when you’re first optimizing your antibodies and show you how the Bond Research Platform can support this.
• 24:18 - 24:23: I’ll do this by first giving an introduction to the Bond Research Platform. 24:23 - 24:31: Run through the tools and parameters to support the optimization for both and touch on singleplex and multiplex.
• 24:32 - 24:38: As well as providing a description of the protocol parameters that you can alter to support this activity.
• 24:38 - 24:44: And then finish up with a bit of a live demo of the software so you can see how to do this.
• 24:46 - 24:55: The Bond Rx Platform is designed around three very important pillars, which is focused around research as a whole.
• 24:55 - 24:59: It also can apply to the process of validating antibodies.
• 24:59 - 25:14: The first pillar links to the openness of the system, which allows antibody validation to be as simple or as broad as research is like with a plethora of variables at their disposal.
• 25:14 - 25:23: The second one for accelerate your test program really talks around the speed and the consistency of the platform that lets you accelerate your work.
• 25:23 - 25:30: And finally, the selected antibodies allow you to further your research into the laboratory.
• 25:32 - 25:38: The purpose of this slide is to show that Bond Rx is really an enabler to automate your technology.
• 25:38 - 25:44: It’s gentle on chosen samples. It’s flexible in its ability to find the optimal staining performance.
• 25:44 - 25:54: And it’s consistent and efficient in its ability to apply the same protocol over and over again in a standardized manner.
• 25:58 - 26:03: To start this, you obviously need to start with a Bond Rx or a Bond Rxn. 26:03 - 26:14: The other things that you’ll need are detection systems. These could be a Bond Polymer Refine Kit or your DAB kits, your Refine Red or your AP Red kits.
• 26:14 - 26:29: As well as you can use the research detection systems, which will allow you to use essentially any technology that you want to use to do your IHC optimization, whether or not it’s chromogenic or fluorescent.
• 26:30 - 26:40: You’ll need your antibodies and your antibody diluent and your package insert is very important as that will provide you with guidance of where to start with your antibody optimization.
• 26:41 - 26:50: Your retrieval solutions for using Bond, there are things like the Epitope Retrieval 1, which is a low pH. Epitope Retrieval 2 is a high pH.
• 26:50 - 26:55: And your different enzyme retrievals. Your titration containers and open containers are very important.
• 26:55 - 27:01: This is what you’ll be putting your diluted antibodies into to perform your optimizations.
• 27:01 - 27:08: And then your obvious laboratory tools that you’ll need as part of your process, like your prepared kits, etc.
• 27:08 - 27:21: An IHC stain can be broken down into 3 main parts. You have your deparaffinization, your epitope retrieval, and your stain infections.
• 27:21 - 27:29: And the Bond Research Software allows each of these variables or each of these parameters to be changed to support your optimization.
• 27:30 - 27:35: From your deparaffinization, you can choose whether or not you’re de-waxing or not, or baking.
• 27:35 - 27:43: And you can also alter how you want to de-wax your samples by altering the de-wax or the alcohol steps.
• 27:43 - 27:54: For your epitope retrieval, you can choose between different solutions for your heat-induced epitope retrieval or your enzyme-induced, or you can choose not to have it at all.
• 27:54 - 28:01: And as part of each of those steps, you can choose different times and temperatures to support that application.
• 28:01 - 28:06: And finally, the staining protocol, you can design your own.
• 28:06 - 28:16: There are templates to start with there with the standard sort of IHC protocols with your IHC-F as an example, which works with the Leica Biosystems RTU range.
• 28:17 - 28:37: You can use that as a template to create your own staining protocols, which can also support your different dilutions, your different incubation times, your temperatures, as well as even changing different dispense profiles to support a full application for how you want to optimize for that particular test.
• 28:38 - 28:47: This slide just shows an example of two of those potential protocols, and I’ll run through these in a bit more detail when I do a demo at the end.
• 28:47 - 28:58: You can see just in the slide here that there are a number of variables which, as a user, you have complete control to edit these parameters.
• 28:59 - 29:08: I’m not going to spend too much time in going into the protocol optimization parameters, but there’s a few things that I’d like to touch on.
• 29:08 - 29:14: The first is that it’s really good to change one variable at a time.
• 29:14 - 29:21: This will help you attribute the performance of your stain to the change variable.
• 29:22 - 29:36: The second thing we recommend is often to do things in triplicate so, again, that you can be ensured that you’ve designed a protocol or optimized antibody that is going to be consistent with the workflow that you have.
• 29:36 - 29:43: And then, finally, it’s important to consider protocol compatibility with your existing workflows.
• 29:43 - 29:49: You can use the Bond to design protocols to basically do anything that you want.
• 29:50 - 29:59: The way the Bond works is that you get optimum time and speed from the system if you’re using like protocols with different times.
• 29:59 - 30:12: So, by planning around your design of experiments to use different times and to get similar times, you can get the most out of your system with really rapid IHC in two and a half hours.
• 30:14 - 30:17: I’ll touch on multiplexing briefly.
• 30:17 - 30:23: It has an added complexity that needs to be considered versus validating a single stain.
• 30:23 - 30:32: If the product and protocol are not designed for reproducibility, even the most consistent automated stainer will have variable results.
• 30:32 - 30:36: Key considerations are antibody optimization.
• 30:36 - 30:42: You should optimize them by themselves and then as a panel to show that staining is not lost or altered.
• 30:43 - 30:45: Consider what pre-treatment is best.
• 30:45 - 30:49: What works well for one antibody may negatively impact another.
• 30:50 - 30:54: What sequence the antibodies and detection components should be added. 30:54 - 30:59: This can vary between different technologies and the different antibodies that you want to use.
• 31:00 - 31:03: Consider marker localization and multiplex type.
• 31:03 - 31:06: Do you expect your markers to be co-localized?
• 31:06 - 31:08: Do you need a permanent stain?
• 31:08 - 31:14: What contrast do you need will all feed into your decisions in terms of how you design your test.
• 31:15 - 31:21: And finally, will you need to strip or remove previous components in the assay or simply neutralize them?
• 31:21 - 31:36: All these things, you know, when you’re designing an experiment or an optimization or getting to a point where you want to validate an antibody, you really need to consider the system as a whole, which is your antibody, your detection system,
• 31:37 - 31:42: and your automated solution and design them together to get the best possible solution.
• 31:47 - 31:55: Now I’m going to run through a bit of a demo of the software with you so you can see how easy it is to optimize your antibodies in practice,
• 31:55 - 32:02: and then eventually move that from your optimization into your chosen protocol for your validated product.
• 32:06 - 32:15: Now I’m going to give you a run-through of the BOND software and show you how easy it is to set up optimization protocols and schedules,
• 32:15 - 32:22: and then what you can eventually use for your final antibodies, final validated antibodies.
• 32:23 - 32:26: So this is the BOND research software login screen.
• 32:27 - 32:34: So the first thing you’re going to want to do as part of your research is to set up a study.
• 32:35 - 32:42: And this will be the thing that you’re going to do to set up your different protocols and your slides so you can do your optimization.
• 32:51 - 33:00: As part of this, you can name it anything you want and add in different study names or different comments that help you identify what it is that you’re trying to do. 33:01 - 33:10: As part of the selection, you can also choose different DOX protocols as a preempt to save you time later on when you’re trying to set these things up.
• 33:13 - 33:19: Now one of the first things you’ll often think of is setting up the antibody that you want to optimize.
• 33:20 - 33:26: But actually if we sort of take a step back from that, when we set up an antibody on the BOND software,
• 33:26 - 33:29: what we usually do is we link it to the protocol that we want to test.
• 33:29 - 33:33: And this saves time in the long run, and I’ll show you why that is soon.
• 33:34 - 33:42: I guess if we go backwards first, one of the things I want to show you is that you may not necessarily want to use the protocols that come standard
• 33:43 - 33:47: if you want to optimize two different parameters that you know this antibody might perform better on.
• 33:48 - 33:53: So one of the things you may want to do is create your own protocol.
• 33:54 - 34:01: The IHCF protocol is often a good place to start for standard DAB IHC tests, 34:02 - 34:06: just because this is what’s used for all the Novocastra HD antibodies,
• 34:07 - 34:13: and it’s been designed to be a very consistent product with a two and a half hour turnaround time on the BOND.
• 34:14 - 34:19: But if we use this as a template, one of the first things you want to do if you want to change it is you first copy this,
• 34:20 - 34:26: and then you define a name that is unique to you.
• 34:26 - 34:31: So for instance, it might be just IHCF with a heated antibody.
• 34:35 - 34:39: Define an abbreviated name.
• 34:41 - 34:47: And then from here, you can then go through and tailor the protocol such that it fits.
• 34:47 - 34:53: So this is a very standard sort of protocol that you’ll often see with your peroxide block, your polymer, and your DAB.
• 34:54 - 34:56: The marker here is your primary antibody.
• 34:57 - 34:59: And within this, you can change your time.
• 34:59 - 35:05: So if, for instance, you want to test to a longer incubation time, you can change this.
• 35:07 - 35:09: And you can also change your temperature.
• 35:09 - 35:13: So one of the things you do is you can take it from the standard ambient temperature,
• 35:13 - 35:17: and then you can choose a temperature that makes sense to you.
• 35:17 - 35:22: So this could be 42 degrees in this instance.
• 35:22 - 35:26: You also have the ability to include extra washes if that’s what you want to do.
• 35:26 - 35:29: And you have this as a BOM washer with DR water here.
• 35:30 - 35:38: So you can not only alter the washes in between, but you can also add extra washes if that’s what you want to do through this insert wash step here.
• 35:39 - 35:43: Once you’ve designed a protocol that you’re happy with, just hit save.
• 35:44 - 35:48: And this will be automatically shown up in your protocol.
• 35:53 - 35:58: So you can also do this with not just your staining protocols,
• 35:58 - 36:05: but you can also do this with your pre-staining protocols, like your heat retrieval protocols.
• 36:06 - 36:09: Again, if we want to edit these, we can change the names.
• 36:13 - 36:14: Copy.
• 36:16 - 36:17: We can change the name here.
• 36:22 - 36:24: Let’s say I want to change the temperature.
• 36:25 - 36:35: And again, we can click onto this and change the temperature from 100 degrees down to 97,
• 36:35 - 36:38: and I can alter the time too if I want to.
• 36:38 - 36:42: So you really have a lot of flexibility in terms of how you want to design these things.
• 36:42 - 36:44: And save that.
• 36:44 - 36:51: So now that I have my heat retrieval protocol and my staining protocol, 36:52 - 36:54: I then want to think about what my antibody is that I want to test.
• 36:55 - 36:59: So if I move to the reagent setup screen, I have a number of options that I can do here.
• 37:00 - 37:14: If you think of CD3, for example, I may want to set that up as a CD3 1 in 50 as a starting point for my optimization.
• 37:14 - 37:17: And maybe I’ll do a 1 in 50, a 1 in 100, and a 1 in 200.
• 37:18 - 37:23: When you think of optimizing a large number of antibodies and validating a large number of antibodies,
• 37:23 - 37:28: if you’re doing this for 100 different antibodies with three different optimizations,
• 37:28 - 37:31: that’s 300 different antibodies that you want to create.
• 37:32 - 37:36: What we find is a lot of people like to simplify this for themselves
• 37:36 - 37:40: and set up templates for their optimizations.
• 37:40 - 37:44: And I might call it something as simple as antibody 1,
• 37:45 - 37:51: or the popular one is T1, and keep it nice and simple.
• 37:53 - 37:57: You can choose your antibody, but you can also do things like your probes as well.
• 37:58 – 38:02 And then from here, you can set your default staining protocol.
• 38:03 - 38:06: So for instance, here’s the protocol that I set up earlier.
• 38:07 - 38:11: And this means, this just saves time later when I’m setting up the slide. It will automatically be programmed in.
• 38:12 - 38:14: I can still change these parameters when I’m setting up the slide,
• 38:15 - 38:17: but by having it here already, it saves quite a bit of time.
• 38:19 - 38:21: And we’ll set up heat retrieval 1,
• 38:21 - 38:26: and you can choose to do heat retrieval and enzyme, or one or either, or both.
• 38:26 - 38:27: And then we can save that.
• 38:29 - 38:33: And then we can do the same again for the next one,
• 38:33 - 38:37: and this one I might end up using for my other dilution.
• 38:40 - 38:43: So now I’ve got my antibody, and I’ve got my protocol.
• 38:43 - 38:46: I can then move back to my slide setup screen.
• 38:46 - 38:49: I have my case here, and then I can add a slide.
• 38:52 - 38:55: And in here, I can select my first antibody.
• 38:55 - 38:59: Now, let’s say I was doing a CD3 at 1 in 50.
• 39:01 - 39:04: I can then add this up here in the slide comment section,
• 39:05 - 39:08: and when I print my label, this will show up on my label,
• 39:09 - 39:12: and so I can identify what my reagent is in that way.
• 39:13 - 39:16: And that means I can use my P1 for lots of different experiments
• 39:16 - 39:19: throughout time, and I just alter my comment here.
• 39:20 - 39:22: So as mentioned previously,
• 39:22 - 39:25: I probably want to do three of these just to be consistent,
• 39:26 - 39:29: and then let’s say I also may want to do my T2,
• 39:31 - 39:34: which will allow me to do my 1 in 100,
• 39:34 - 39:37: and again, I’ll set up three of those and add three slides.
• 39:38 - 39:40: And you can see on the right-hand side here,
• 39:41 - 39:43: my six slides are now set up.
• 39:43 - 39:45: So once I’ve got my slides,
• 39:45 - 39:48: I then want to set up on the instrument.
• 39:48 - 39:50: So I’ll go through a few steps here.
• 39:50 - 39:52: The first thing is I’ll print my label,
• 39:54 - 39:57: and I’ll put these on my slides and get it prepped for my instrument.
• 39:57 - 40:01: The second thing I want to do is set up my antibody
• 39:02 - 40:04: so that the instrument can recognize it.
• 40:04 - 40:06: So as I showed earlier, there were different…
• 40:06 - 40:08: You can use Bond titration containers,
• 40:09 - 40:11: or you can use a different type of container,
• 40:11 - 40:15: titration containers or Bond-open containers.
• 40:15 - 40:16: You grab one of those,
• 40:16 - 40:20: and that is what you’ll put your diluted antibody into.
• 40:20 - 40:22: So I have a container here in front of me.
• 40:22 - 40:24: I have my scanner next to me.
• 40:24 - 40:27: What I’ll do is I’ll scan the barcode that’s on the container,
• 40:28 - 40:30: and this will pop up like so.
• 40:31 - 40:33: I then select the antibody
• 40:33 - 40:36: that I want to designate this container to,
• 40:38 - 40:39: T1.
• 40:39 - 40:41: I can define a lot number,
• 40:41 - 40:43: so I have traceability to this container,
• 40:43 - 40:46: and then I can choose an expiry date that makes sense.
• 40:50 - 40:51: And press OK.
• 40:54 - 40:57: I can do that for as many antibodies as I want,
• 40:57 - 40:59: and that will be registered.
• 41:01 - 41:05: So now I have my antibody container registered.
• 41:05 - 41:06: I have my slides.
• 41:06 - 41:08: The next thing I want to do is set up on the instrument.
• 41:08 - 41:12: So what I’ll do now is I’ll load the container onto the instrument,
• 41:12 - 41:14: which in this instance is a Bond Rx,
• 41:14 - 41:15: which you can see here,
• 41:15 - 41:18: and there’s already a pre-loaded refine kit,
• 41:18 - 41:20: and I’ll load my slides up.
• 41:20 - 41:22: I’ll do that now quickly.
• 41:32 - 41:36: OK, so I’ll load the antibody onto the instrument
• 41:36 - 41:40: as well as the slides,
• 41:40 - 41:43: and once that loads up now,
• 41:43 - 41:45: we’ll then be able to…
• 41:45 - 41:48: Once it’s loaded up, we can then press play and start the run.
• 41:48 - 41:50: And that essentially is the completion
• 41:50 - 41:54: of our first antibody optimisation experiment.
• 41:55 - 41:57: And once you’ve done this once,
• 41:57 - 42:00: setting them up each time gets quicker and quicker and easier and easier 42:00 - 42:05: because you have your predefined antibodies and protocols
• 42:05 - 42:06: already prepped there,
• 42:06 - 42:11: so you don’t have to go through the big set-up effort each time.
• 42:11 - 42:13: So your protocol’s already there,
• 42:13 - 42:15: your antibody templates are already there,
• 42:15 - 42:17: so each time you want to set up a new case,
• 42:17 - 42:21: it’s just as simple as selecting your antibody,
• 42:21 - 42:23: creating your slides,
• 42:23 - 42:26: doing your dilution, which is probably the biggest part,
• 42:26 - 42:28: and then pressing play.
• 42:28 - 42:31: So these normally will pre-load,
• 42:31 - 42:33: but one of these…
• 42:33 - 42:36: I haven’t selected, but it’s quite easy to fix.
• 42:36 - 42:39: Select which one we want, and that’s loaded there.
• 42:39 - 42:41: I’ve just put in the first antibody,
• 42:41 - 42:44: just as the example, with the three slides.
• 42:44 - 42:49: And once that is ready, you then press play,
• 42:49 - 42:54: and the instrument will schedule and that will run.
• 42:54 - 42:56: And it is as simple as that.
• 42:57 - 43:01: And that concludes the demo that I was going to show you today.
• 43:01 - 43:07: And I think what we can do now is open it up for questions.
• 43:07 - 43:09: Thank you.
• 43:19 - 43:22: Thank you, gentlemen, for your informative presentations.
• 43:23 - 43:26: We will now start the live Q&A portion of the webinar.
• 43:26 - 43:29: If you have a question you’d like to ask, please do so now.
• 43:29 - 43:31: Just click on the Ask a Question box
• 43:31 - 43:33: located on the far left of your screen.
• 43:33 - 43:36: We will answer as many of your questions as we have time for.
• 43:36 - 43:39: Now, those questions we are able to answer live today
• 43:39 - 43:42: and those submitted during the on-demand period
• 43:42 - 43:44: will be answered via the e-mail address you provided
• 43:44 - 43:49: at the time of registration.
• 43:49 - 43:52: Okay, Dr. Howat, let’s start with you.
• 43:52 - 43:54: Let’s go with this question.
• 43:54 - 43:58: For labs that are entrenched with their existing antibodies,
• 43:58 - 44:01: what suggestions do you have for lab staff
• 44:01 - 44:06: to encourage their labs to validate new antibodies?
• 44:06 - 44:09: Thank you for that question, Chrissy.
• 44:09 - 44:11: I think that’s a really important point.
• 44:11 - 44:15: And if this is a clinical assay,
• 44:15 - 44:17: then obviously the patient has to come first.
• 44:17 - 44:19: So the question you then have to ask is,
• 44:19 - 44:23: what additional data does this particular antibody provide?
• 44:23 - 44:25: Now, if it’s more sensitive,
• 44:25 - 44:28: if it can be demonstrated to be more sensitive,
• 44:28 - 44:34: or the variability is minimal from this particular supplier,
• 44:34 - 44:37: then you’re gaining a patient benefit.
• 44:37 - 44:40: And by doing that, I think it’s clear
• 44:40 - 44:44: that you would want to do that within your clinical workflow.
• 44:44 - 44:47: So you’ve got to be able to – you’ve made a lot of work
• 44:47 - 44:49: in order to make your antibody working in your hands.
• 44:49 - 44:52: So you need to have a really good idea
• 44:52 - 44:53: of why you want to change that.
• 44:53 - 44:59: But if that change either gives you less background staining
• 44:59 - 45:03: or higher sensitivity with a lower concentration of antibodies,
• 45:03 - 45:05: then those are the reasons for why you would want
• 45:05 - 45:09: to move on to validate a new marker.
• 45:11 - 45:13: Thank you, Dr. Howat.
• 45:13 - 45:15: Now, Damian, let’s go over to you for this question.
• 45:15 - 45:17: Now, it’s two parts.
• 45:17 - 45:20: How do I keep track of all the changes and variations
• 45:20 - 45:23: that I make from protocol to protocol
• 45:23 - 45:25: when doing optimizations?
• 45:25 - 45:27: And do I need to write them down separately,
• 45:27 - 45:30: or does the instrument record all of these for me?
• 45:34 - 45:36: Thank you, Chrissy.
• 45:36 - 45:38: The instrument can record all of this.
• 45:38 - 45:40: So it’s really up to your lab processes
• 45:40 - 45:42: in terms of how you want to write it down
• 45:42 - 45:44: or if you need to at all.
• 45:44 - 45:47: But after you’ve done a run or set up your antibodies
• 45:47 - 45:50: or your cases, you can then go into the software
• 45:50 - 45:52: and you can pull out the information
• 45:52 - 45:55: for not only each run through your slide history
• 45:55 - 45:58: so you can see the run as it went on the instrument
• 45:58 - 46:01: on the time, and that will give you your antibody details,
• 46:01 - 46:03: your kit details, your lot numbers,
• 46:03 - 46:05: and all the information that you’ve sort of
• 46:05 - 46:07: first programmed into it,
• 46:07 - 46:11: as well as you can then go into your protocol screen
• 46:11 - 46:13: and you can get a protocol report.
• 46:13 - 46:15: So the protocols that we designed earlier,
• 46:15 - 46:19: you can export a PDF protocol report,
• 46:19 - 46:23: and what that will give you is every step of the protocol
• 46:23 - 46:27: from the reagents, the different times and temperatures,
• 46:27 - 46:29: until you have a record of that to cross-reference.
• 46:29 - 46:31: So you’ll have all the information
• 46:31 - 46:34: in some easy-to-export PDFs
• 46:34 - 46:37: that you can put with your case records.
• 46:38 - 46:40: Thank you, Damian.
• 46:40 - 46:42: Dr. Howat, let’s go over to you.
• 46:44 - 46:49: And this question has a few parts, so I’ll start here.
• 46:49 - 48:53: Sometimes an antibody target isn’t one-size-fits-all.
• 47:00 - 47:00: For example, CB-11, breast and gastric,
• 47:57 - 47:06: ALK, lung and heme, and could be better supported
• 47:06 - 47:10: by an antibody for each indication
• 47:10 - 47:14: versus one that covers all.
• 47:14 - 47:20: Multiple same-target antibodies, retrievals, et cetera,
• 47:20 - 47:26: create a burden on a lab
• 47:26 - 47:29: and create a risk of mix-ups versus a single solution.
• 47:29 - 47:33: Do you think labs should tailor their antibodies to the test
• 47:33 - 47:35: or prioritize workflow and risk reduction?
• 47:38 - 47:41: Thank you, Chrissy. I think that’s a great question
• 47:41 - 47:43: and quite a difficult one.
• 47:43 - 47:47: However, I think my personal view is that, again,
• 47:47 - 47:50: it comes back to what does the patient get out of this?
• 47:50 - 47:55: So if the best way to treat that patient
• 47:55 - 48:00: is to have multiple-target antibodies
• 48:00 - 48:04: to be able to pull those different indications
• 48:04 - 48:08: out from each other, then that’s the way it should be.
• 48:08 - 48:12: And the lab is able to use other means,
• 48:12 - 48:16: such as some great LIM systems that are available
• 48:16 - 48:21: from Leica and others,
• 48:21 - 48:24: in order to be able to minimize the risk of mix-ups
• 48:24 - 48:29: by printing labels directly onto the slide.
• 48:29 - 48:30: Then that should help to solve that.
• 48:30 - 48:32: However, you’ve got to balance that out
• 48:32 - 48:37: and that if the single solution is feasible
• 48:37 - 48:41: and it does not deliver any difficulty to that patient,
• 48:41 - 48:43: and if it’s possible
• 48:43 - 48:46: and also delivers additional patient benefit,
• 48:46 - 48:51: then there would be no reason to minimize that risk,
• 48:51 - 48:53: and that’s why I would recommend. 48:53 - 48:59: So it’s kind of down to being very patient-centric.
• 48:59 - 49:01: Now, our next question. 49:01 - 49:05: Dr. Howat, I believe this one’s for you, and it’s two parts.
• 49:05 - 49:09: Do you recommend on-slide controls, 49:09 - 49:15: and do you prefer known tissue positives or cell lines, and why?
• 49:17 - 49:20: So thank you for that.
• 49:17 - 49:20: If you look at slide 20, where I am now,
• 49:20 - 49:30: then I would recommend on-slide controls where you can do them,
• 49:30 - 49:32: and sometimes that’s difficult to do 49:32 - 49:36: because sometimes it will depend on the size of the piece of tissue
• 49:36 - 49:39: that you are putting on your block, 49:39 - 49:41: and you have to fit all of these things onto your slide at the same time.
• 49:41 - 49:43: However, I would recommend them. 49:43 - 49:48: I think if you can use a known tissue positive, that’s great,
• 49:48 - 49:51: or a cell line that’s equally great. 49:51 - 49:54: I think the key thing is what those cell lines
• 49:54 - 49:57: or tissue controls are demonstrating, 49:57 - 49:59: which is that you’ve not just got a single level of expression.
• 49:59 - 50:03: So you’re not just looking at three plus positive 50:03 - 50:06: when the test tissue that you’ve got on the same slide
• 50:06 - 50:10: may be a one plus positive 50:10 - 50:14: because that on-slide control is then not referencing in the right way.
• 50:14 - 50:21: So a change in the character of the slide doesn’t run particularly well, etc. 50:21 - 50:24: You might not detect that difference in a three plus positive,
• 50:24 - 50:28: but your test tissue can become negative.
• 50:28 - 50:34: For that reason, you need to have on your tissue positive
• 50:34 - 50:35: a mix, where possible, of positivity.
• 50:35 - 50:42: So three plus turned to one plus. 50:42 - 50:43: Or in this particular case, the cell lines,
• 50:43 - 50:46: in the reference here, the Histocyte cell lines here,
• 50:46 - 50:51: you’ve got anywhere from a three plus, two plus and a one plus and a negative.
• 50:51 - 50:54: By having those in there, you can see a negative that could become backgroundy,
• 50:54 - 50:56: or you can see a one plus will become a negative.
• 50:56 - 51:03: And in those cases, you can flag very easily 51:03 - 51:05: whether you have an issue with your staining run on that individual slide at the time.
• 51:05 - 51:10: So, you know, I don’t think it matters overall,
• 51:10 - 51:12: but as long as you’ve got that mix of staining,
• 51:12 - 51:15: that you can help to give you confidence over your run at the time.
• 51:16 - 51:17: Thank you, Dr. Howat. 51:17 - 51:20: And, you know, let’s have you answer this next question as well.
• 51:20 - 51:25: What are the best tricks and tools for mouse-on-mouse staining?
• 51:25 - 51:27: Oh, another one. Thank you very much. 51:27 - 51:31: I think what’s really important for mouse-on-mouse, 51:31 - 51:36: which is something that happens in the research market frequently, 51:36 - 51:40: is to try and design your methodology
• 51:40 - 51:43: by using some of the available kits on the market.
• 51:43 - 51:47: But what I would recommend strongly
• 51:47 - 51:55: is you tailor your secondary agents around the isotype of the primary.
• 51:55 - 51:58: So you can use a blocking reagent in order to be able to block
• 51:58 - 52:04: most of the IgG within the mouse tissue.
• 52:04 - 52:09: In the initial pre-primary antibody step,
• 52:09 - 52:11: put your primary antibody on.
• 52:11 - 52:14: If your primary antibody happens to be an IgG1,
• 52:14 - 52:17: you can use an anti-IgG1 antibody
• 52:17 - 52:21: that is whatever species you wish to link into your polymer kit.
• 52:21 - 52:24: It could be a rabbit or a goat or whatever it happens to be.
• 52:24 - 52:29: And by doing that, you’re minimizing the amount of mouse-on-mouse reaction
• 52:29 - 52:31: that you will find.
• 52:31 - 52:35: And I find that that protocol, which we have on the Leica Bond,
• 52:35 - 52:39: works really well.
• 52:39 - 52:41: Now it looks like we have time for one more question.
• 52:41 - 52:46: Dr. Howat, let’s end this Q&A with you.
• 52:46 - 52:50: How does KO validation in Western blot and IHC
• 52:50 - 52:55: relate to performing IHC successfully?
• 52:55 - 52:57: So thank you.
• 52:57 - 53:01: I think the knockout validation is a really good way of validating IHC.
• 53:01 - 53:04: It’s something that we do a lot in Abcam.
• 53:04 - 53:08: And you can see the examples of this in this slide.
• 53:08 - 53:12: So I referred to this previously in the talk,
• 53:12 - 53:15: but where you’re knockout validating,
• 53:15 - 53:19: you can use Western blot very clearly and easily and quickly
• 53:19 - 53:24: to be able to show that you’ve knocked out that pad of interest.
• 53:24 - 53:27: And you need to do that in order to confirm
• 53:27 - 53:30: when you’re using a cell line pellet
• 53:30 - 53:34: that truly you have knocked it out or knocked it down
• 53:34 - 53:36: as is the case in the right-hand panel.
• 53:36 - 53:39: So they do relate really very well.
• 53:39 - 53:42: But ultimately, if you want to demonstrate it in immunochemistry,
• 53:42 - 53:45: you will have to take those knockout cell lines.
• 53:45 - 53:48: You will have to pellet them, put them through FFPE and put them on a tissue slide and stain and that would give you absolute confidence that you’ve got that knockout and there should be reason why it wouldn’t work.