WEBVTT 00:00:08.000 --> 00:00:09.733 Well, I'd just like to introduce myself. 00:00:09.733 --> 00:00:10.900 My name is John Andreasen. 00:00:10.900 --> 00:00:14.100 I'm the laboratory supervisor of the Immunologic Flow 00:00:14.100 --> 00:00:17.100 Cytometry Laboratory at a group. 00:00:17.266 --> 00:00:19.800 And I'm here today to present, 00:00:19.800 --> 00:00:22.800 the introduction to Flow cytometry. 00:00:22.866 --> 00:00:26.366 So we've got some learning objectives that we just wanted to go over first off. 00:00:26.833 --> 00:00:29.833 First is to describe the principle of flow cytometry. 00:00:30.933 --> 00:00:33.900 Then identify the components of a flow cytometer 00:00:33.900 --> 00:00:37.200 and finally discuss the clinical applications of flow cytometry. 00:00:38.300 --> 00:00:40.400 So by way of introduction, 00:00:40.400 --> 00:00:43.333 the concept of flow cytometry is not a new one. 00:00:43.333 --> 00:00:46.333 It's been in existence for more than 50 years. 00:00:46.833 --> 00:00:50.366 It really took on clinical prominence in the clinical laboratory 00:00:50.366 --> 00:00:53.400 in the 1980s in the wake of the HIV Aids epidemic. 00:00:54.733 --> 00:00:56.866 The clinical utility, 00:00:56.866 --> 00:01:01.033 initially recognized was the counting of CD4 positive T cells. 00:01:02.766 --> 00:01:06.000 As we know from our studies of HIV, this is a retrovirus 00:01:06.000 --> 00:01:09.833 that preferentially infects and destroys CD4 positive cells. 00:01:10.333 --> 00:01:12.700 So, the mechanism of this disease 00:01:12.700 --> 00:01:16.500 and how it affects the immune system is by destroying these cells. 00:01:16.833 --> 00:01:23.366 So that was the initial, the initial clinical utility of the methodology. 00:01:23.500 --> 00:01:28.200 But this was soon expanded to, assessing lymphoid and eventually myeloid 00:01:28.266 --> 00:01:32.600 hematopoietic neoplasms and to detecting primary immuno deficiencies. 00:01:33.166 --> 00:01:36.366 The first working cytometer was described 00:01:36.366 --> 00:01:39.700 way back in 1947 at Northwestern University, 00:01:40.266 --> 00:01:44.600 and this was a sponsored, by research from the US Army with the aim of rapid 00:01:44.600 --> 00:01:48.000 identification of biological warfare agents such as anthrax 00:01:48.600 --> 00:01:51.866 and the current generation of clinical flow cytometer 00:01:51.966 --> 00:01:55.400 use one or more, lasers. 00:01:55.766 --> 00:01:59.333 Back in 1947, what they were using is actually a Ford headlamp. 00:01:59.433 --> 00:02:00.833 So we've come a long way. 00:02:02.033 --> 00:02:04.900 So let's just discuss, the definition of flow cytometry. 00:02:04.900 --> 00:02:06.433 It's very simple. 00:02:06.433 --> 00:02:10.033 This is a system for measuring different properties of individual cells 00:02:10.033 --> 00:02:15.000 in physiologic saline solution as they move in a focused liquid stream 00:02:15.000 --> 00:02:18.766 through a fixed laser beam, scattering light and emitting fluorescence. 00:02:19.033 --> 00:02:22.033 That's then measured and converted into digitized data. 00:02:22.866 --> 00:02:25.533 If you break the word flow cytometry down 00:02:25.533 --> 00:02:29.966 flow, meaning fluid cytosol and metric measurement. 00:02:29.966 --> 00:02:32.366 So pretty straightforward. 00:02:32.366 --> 00:02:36.100 On the right we have a picture of a flow cytometry flow cell. 00:02:36.100 --> 00:02:40.066 So this is the interrogation area where the light source, 00:02:40.633 --> 00:02:43.900 as I mentioned previously, the flow cytometry 00:02:43.900 --> 00:02:46.900 lasers are going to interrogate the individual cells. 00:02:47.400 --> 00:02:48.933 So coming in from the top down, 00:02:48.933 --> 00:02:52.900 we've got the sample and it says stained cells in suspension. 00:02:52.900 --> 00:02:57.400 So by stained what typically we mean in flow cytometry is they have been incubated 00:02:57.400 --> 00:03:00.400 with a cocktail of different monoclonal antibodies 00:03:00.700 --> 00:03:03.733 that are then going to that are going to be specific for certain 00:03:03.900 --> 00:03:05.866 cell surface proteins. 00:03:05.866 --> 00:03:09.000 So the antibodies will attach very specifically to different markers 00:03:09.000 --> 00:03:10.200 on the surface of the cell. 00:03:10.200 --> 00:03:14.500 That will allow us to say this is a T cell or this is a B cell or NK cell. 00:03:15.433 --> 00:03:18.800 Each of those different monoclonal antibodies with a specificity 00:03:18.800 --> 00:03:21.366 to a certain cell type or a certain marker, 00:03:21.366 --> 00:03:24.033 are conjugated to different fluorophores or dyes 00:03:24.033 --> 00:03:27.900 that will fluoresce as the cell goes through the laser light source. 00:03:28.933 --> 00:03:31.466 Then also coming in, we have what we call sheath fluid. 00:03:31.466 --> 00:03:34.366 This is the physiologic saline. 00:03:34.366 --> 00:03:37.400 We use this to hydrodynamic focus. 00:03:37.400 --> 00:03:41.966 The cells into a single file or single cell stream orientation. 00:03:43.200 --> 00:03:45.900 And the way we accomplish this is by the interplay 00:03:45.900 --> 00:03:49.033 of the pressure of the sheath fluid relative to the sample pressure. 00:03:49.633 --> 00:03:52.566 So if the sheath pressure is higher than the sample pressure, 00:03:52.566 --> 00:03:56.933 we can effectively squeeze the cells into a single band or a single cell file. 00:03:57.366 --> 00:04:00.933 And then we're getting very fine measurements of each individual cell 00:04:00.933 --> 00:04:03.933 as that intersects the laser light source. 00:04:04.033 --> 00:04:05.833 Once that happens, you can see that 00:04:05.833 --> 00:04:08.833 we have the arrow coming from the laser, the green arrow. 00:04:08.900 --> 00:04:11.966 And we're going to measure some physical characteristics 00:04:11.966 --> 00:04:14.966 of the cells, those being forward and side scatter. 00:04:15.400 --> 00:04:17.400 So forward scatter is a measure of cell size. 00:04:17.400 --> 00:04:20.400 We'll talk a little bit more about that later in the presentation. 00:04:20.600 --> 00:04:24.066 Side scatter being a measure of how complex the cell is internally. 00:04:24.066 --> 00:04:27.066 How much light is passing into the cell 00:04:27.066 --> 00:04:29.700 hitting internal structure and then reflecting off to the sides. 00:04:29.700 --> 00:04:31.500 And we measure that. 00:04:31.500 --> 00:04:34.433 And then we also measure the floor fluorescence 00:04:34.433 --> 00:04:36.300 emitted from the stained cells. 00:04:36.300 --> 00:04:39.300 And this comes back to the monoclonal antibody cocktail that we've added. 00:04:39.566 --> 00:04:42.566 And we know now that oh this cell is fluorescing red. 00:04:42.766 --> 00:04:46.566 We know that red is the dye that's conjugated to our anti T cell marker. 00:04:46.600 --> 00:04:47.700 So this must be a T cell. 00:04:49.633 --> 00:04:51.233 So this slide is just detailing 00:04:51.233 --> 00:04:54.500 some of the advantages of flow cytometry versus light microscopy. 00:04:55.333 --> 00:04:56.600 So flow is very fast. 00:04:56.600 --> 00:04:59.366 The clinical generation of flow cytometry 00:04:59.366 --> 00:05:02.366 can count upwards of 30,000 cells per second. 00:05:02.533 --> 00:05:05.533 So it becomes pretty powerful to count millions of cells 00:05:05.533 --> 00:05:07.633 in a relatively short amount of time. 00:05:07.633 --> 00:05:11.100 It's less a it's less subjective than traditional light microscopy. 00:05:11.933 --> 00:05:15.600 So, there is some subjectivity inherent in flow cytometry, 00:05:15.733 --> 00:05:18.733 but much less so than than light microscopy. 00:05:18.733 --> 00:05:22.433 So you can, define regions where your different cell populations 00:05:22.433 --> 00:05:25.366 should fall. And, 00:05:25.366 --> 00:05:28.933 and that takes some of the subjectivity out of the, out of the analysis. 00:05:29.233 --> 00:05:31.200 It's highly reproducible. 00:05:31.200 --> 00:05:34.100 And that's due to the specificity of the antibodies that we use, 00:05:34.100 --> 00:05:38.133 and also to the number of events that we're able to count. 00:05:39.200 --> 00:05:40.166 And the 00:05:40.166 --> 00:05:43.333 sensitivity and specificity of the flow cytometry analyzers. 00:05:44.200 --> 00:05:46.800 As I mentioned, you can count up to upwards of 30,000 00:05:46.800 --> 00:05:49.800 cells a second on the current generation of clinical flow cytometry. 00:05:50.100 --> 00:05:53.766 So you can analyze many, many cells very quickly relative 00:05:53.766 --> 00:05:57.666 to just a few cells, a few hundred cells, if you're looking at a slide, 00:05:58.966 --> 00:06:01.966 it can be semi-automated relative to just being manual. 00:06:02.100 --> 00:06:06.200 So we're constantly trying to further automate the process. 00:06:06.933 --> 00:06:09.933 You can purchase currently clinical, 00:06:10.033 --> 00:06:12.966 instruments that will automate the sample prep 00:06:12.966 --> 00:06:16.133 and load the samples onto the flow Cytometer. 00:06:16.800 --> 00:06:18.800 So we're so it can be automated. 00:06:18.800 --> 00:06:20.400 And that's a big advantage. 00:06:20.400 --> 00:06:23.000 And then the results can be quantitative relative to just 00:06:23.000 --> 00:06:26.000 being kind of semi quantitative for the light microscopy. 00:06:26.266 --> 00:06:29.500 So we can report out numbers in terms of 00:06:29.500 --> 00:06:32.800 what's the percentage of the patient's lymphocytes that are T cells. 00:06:33.300 --> 00:06:35.366 This is important as we know for HIV. 00:06:36.633 --> 00:06:39.633 It can be important for other things to be able to quantitate 00:06:39.700 --> 00:06:42.666 exactly the percentage as well as the number of cells 00:06:42.666 --> 00:06:45.933 per microliter for of each different cell population. 00:06:49.433 --> 00:06:52.500 The disadvantages, and there are some big ones. 00:06:53.100 --> 00:06:56.100 Cost the flow cytometry are expensive. 00:06:56.166 --> 00:07:00.000 Just the, the cost of building the unit, the cost to maintain it, 00:07:00.500 --> 00:07:03.866 the training that's involved, all of that rolls into the cost of the instrument. 00:07:04.466 --> 00:07:07.466 Availability is a big, issue. 00:07:07.900 --> 00:07:11.633 Not every clinical lab in a hospital is going to be able to afford 00:07:11.733 --> 00:07:14.733 or want to have a flow cytometer. 00:07:16.033 --> 00:07:19.700 Short sample stability, which kind of rolls back to the availability. 00:07:20.166 --> 00:07:23.466 So the samples we want to look at live viable cells. 00:07:23.466 --> 00:07:27.266 So we typically have pretty short stabilities, usually maybe 00:07:27.266 --> 00:07:30.500 48 to 72 hours at max for most of the testing. 00:07:31.000 --> 00:07:35.066 So that coupled with the fact that you may have to fly a sample 00:07:35.400 --> 00:07:38.400 to another state, to another, to a big reference lab 00:07:38.400 --> 00:07:41.833 in order to do this testing, can cause some problems. 00:07:43.133 --> 00:07:44.833 The loss of the sample. 00:07:44.833 --> 00:07:47.800 So if you're just dealing with a peripheral blood sample, probably 00:07:47.800 --> 00:07:48.600 not a big issue. 00:07:48.600 --> 00:07:51.866 But for bone marrow, for the lymph node, different types of tumors 00:07:51.866 --> 00:07:54.866 where we may want to look at the cells 00:07:55.033 --> 00:07:57.600 having the cells lost just to the waste. 00:07:57.600 --> 00:07:59.900 After you are analyzing it, 00:07:59.900 --> 00:08:03.433 it can present some issues and then a loss of tissue architecture. 00:08:03.733 --> 00:08:07.300 So if you imagine, looking at section 00:08:07.300 --> 00:08:10.300 of lymph node on a slide versus mincing that tissue up 00:08:10.300 --> 00:08:14.266 and staining the individual cells and, and, running it through a flow Cytometer, 00:08:14.900 --> 00:08:19.066 you're going to lose the relation of one cell to another when you're doing it. 00:08:19.066 --> 00:08:19.666 The flow away. 00:08:19.666 --> 00:08:21.133 And there are some new instruments 00:08:21.133 --> 00:08:23.433 or relatively new instruments that can bind both. 00:08:23.433 --> 00:08:28.266 But, as far as I know, those aren't, in routine use in clinical labs. 00:08:31.566 --> 00:08:34.633 So let's go into a little bit more detail about the different components 00:08:34.633 --> 00:08:37.566 of a flow Cytometer what makes this instrument work? 00:08:37.566 --> 00:08:38.700 So there are three main ones. 00:08:38.700 --> 00:08:42.633 There's the fluid x component, an optical component, and an electronic component. 00:08:43.766 --> 00:08:45.733 So we've got three different bubbles here. 00:08:45.733 --> 00:08:47.666 Fluid X provides the flow. 00:08:47.666 --> 00:08:50.666 This is the pressurized physiologic saline. 00:08:50.800 --> 00:08:55.100 And the pressurized patient sample stained up with monoclonal antibodies. 00:08:55.733 --> 00:08:58.933 We've got the optical component which is the focus laser light. 00:08:59.133 --> 00:09:02.000 And then all of the optics that are used to focus 00:09:02.000 --> 00:09:05.000 that those light signals to intersect the cell stream 00:09:05.666 --> 00:09:08.566 and the electronics, which converts the light signals 00:09:08.566 --> 00:09:11.566 to digital information. 00:09:12.866 --> 00:09:14.566 So the fluid IC subsystem. 00:09:14.566 --> 00:09:14.933 Right. 00:09:14.933 --> 00:09:16.833 Again, this is this the transportation system 00:09:16.833 --> 00:09:19.100 that moves the cells towards the laser intercept. 00:09:20.100 --> 00:09:23.066 It requires that pressurized patient sample and saline 00:09:23.066 --> 00:09:24.900 which we call sheath fluid. 00:09:24.900 --> 00:09:27.433 And we call it sheath fluid because it, 00:09:27.433 --> 00:09:30.433 produces a sheath around the stream of cells. 00:09:30.900 --> 00:09:33.933 This is going to create laminar flow or hydrodynamic focusing 00:09:33.933 --> 00:09:38.400 of the cell stream as the sample cells are squeezed into a single cell band, 00:09:39.233 --> 00:09:42.400 within the flow cell for interrogation by one or more lasers. 00:09:42.966 --> 00:09:46.500 So, we mentioned up top about, 00:09:46.766 --> 00:09:50.733 you know, way back in the 1940s, using what was available 00:09:50.766 --> 00:09:54.600 at that time, Ford headlamp for an excitation light source. 00:09:55.466 --> 00:09:58.733 When I started in flow cytometry 25 years ago, we had single 00:09:58.733 --> 00:10:02.133 laser instruments that were capable of exciting two different fluorophores. 00:10:02.500 --> 00:10:06.300 And so you could potentially look at two different cell surface markers or, 00:10:06.733 --> 00:10:10.333 or detect and quantitate two different cell populations. 00:10:10.866 --> 00:10:15.933 The current instruments that are in use in, in influence cytometry labs clinically 00:10:16.266 --> 00:10:21.633 can do up to 12 different colors with three or more lasers. 00:10:22.500 --> 00:10:27.000 So that gives you really a lot of power to look at very small subsets 00:10:27.000 --> 00:10:30.000 of different populations of cells by drilling down 00:10:30.000 --> 00:10:33.000 from one population to another based on antigen expression. 00:10:33.266 --> 00:10:35.800 But it all goes back to this idea of 00:10:35.800 --> 00:10:39.566 having a clean cell signal, looking at one cell at a time. 00:10:39.566 --> 00:10:41.366 As the cells go through the laser, 00:10:42.400 --> 00:10:45.166 and again, the cell stream needs to be precisely aligned 00:10:45.166 --> 00:10:47.400 within the laser and the optical path 00:10:47.400 --> 00:10:49.833 so that we don't just clip the edge of the cell, 00:10:49.833 --> 00:10:53.400 or we don't have two cells going through the flow cell at the same time, 00:10:53.733 --> 00:10:57.900 it may look to the flow cytometer into the analyzer, like one cell that has, 00:10:58.233 --> 00:10:59.800 you know, abnormal phenotype. 00:10:59.800 --> 00:11:01.700 It looks like a T cell combined with a B cell. 00:11:01.700 --> 00:11:04.700 We might mistake that for a cancer cell or something. 00:11:05.000 --> 00:11:08.433 So air bubbles and clumps of cells can cause problems. 00:11:09.066 --> 00:11:11.700 As you might imagine, by altering the stream and affecting 00:11:11.700 --> 00:11:13.400 the quality of the data. 00:11:13.400 --> 00:11:15.766 And then once we've interrogated the cells, 00:11:15.766 --> 00:11:18.966 the sample and the ceiling just ends up in a waste tank with some bleach. 00:11:21.900 --> 00:11:22.266 So here's 00:11:22.266 --> 00:11:25.500 just a picture of, kind of a generic flow cytometer. 00:11:26.100 --> 00:11:30.466 And in contrast to the the first or second slide where we showed the sample 00:11:30.466 --> 00:11:34.100 and the saline coming in from the top, in fact, most clinical flow 00:11:34.100 --> 00:11:37.100 cytometer is the sample is actually loaded from the bottom. 00:11:37.333 --> 00:11:40.266 So you see the sample there on a stage, and then you see 00:11:40.266 --> 00:11:43.833 the saline coming in on either side up into the flow cell. 00:11:43.833 --> 00:11:46.666 And there are all the different parts and components that probably aren't 00:11:46.666 --> 00:11:48.066 too important to mention here. 00:11:48.066 --> 00:11:52.633 But the end result is we want pressurized saline, pressurized sample 00:11:53.366 --> 00:11:56.366 moving up into the interrogation point with the laser, 00:11:57.166 --> 00:11:59.200 and then you can see over to the right 00:11:59.200 --> 00:12:02.933 this bubble we have, just an example. 00:12:02.933 --> 00:12:03.900 If you can see this, it's 00:12:03.900 --> 00:12:07.466 kind of difficult to read, but there's low pressure versus high pressure 00:12:07.866 --> 00:12:10.466 and the effect that that has on hydrodynamic focusing. 00:12:10.466 --> 00:12:14.700 So if you increase the sample pressure, you get more wiggle room for the cells 00:12:14.700 --> 00:12:15.166 to go through. 00:12:15.166 --> 00:12:19.700 That increases the variability of the data that you're looking at. 00:12:19.700 --> 00:12:23.533 So if you want very fine, very low CVEs and very good quality data, 00:12:23.766 --> 00:12:26.666 we should count on the low flow rate, high flow rate for things that 00:12:26.666 --> 00:12:27.800 where that's not so critical. 00:12:30.600 --> 00:12:31.566 Optics subsystem. 00:12:31.566 --> 00:12:34.133 So this is the lasers. 00:12:34.133 --> 00:12:38.366 The light source, provides a source of constant monochromatic light. 00:12:38.633 --> 00:12:41.833 So, most flow cytometry, if not all of them, 00:12:41.833 --> 00:12:44.833 will have A488 nanometer argon ion laser. 00:12:45.600 --> 00:12:48.733 And then the newer generation instruments, as I mentioned before, will have, 00:12:49.800 --> 00:12:52.666 up to two additional lasers, 00:12:52.666 --> 00:12:56.966 red laser, violet laser, ultraviolet there and numerous options. 00:12:57.433 --> 00:13:00.933 And this just excites the sample particles, in particular 00:13:01.200 --> 00:13:04.033 the fluorescent fluorophores that are bound 00:13:04.033 --> 00:13:07.566 to the monoclonal antibodies that we use to really drill down 00:13:07.566 --> 00:13:10.566 and find out what types of cells we're looking at. 00:13:10.733 --> 00:13:13.733 Again, the flow cell is where the cells intersect the laser beam, 00:13:13.733 --> 00:13:16.300 and then fiber optic cables that collect the emitted light 00:13:16.300 --> 00:13:19.500 and route it to specific detectors based on wavelength. 00:13:19.900 --> 00:13:22.766 And these detectors, which we call for the multiplier tubes, 00:13:22.766 --> 00:13:27.100 then detect the light and amplify it further, because you can imagine 00:13:27.100 --> 00:13:31.200 the amount of light coming off one individual cell is going to be very tiny. 00:13:31.200 --> 00:13:34.100 So we need to have a mechanism to detect and then amplify that light. 00:13:35.566 --> 00:13:37.900 So here's a picture showing kind of how this works. 00:13:37.900 --> 00:13:40.900 Again going back to having this sample coming in from the top. 00:13:40.966 --> 00:13:43.266 You've got a laser off to the left side. 00:13:43.266 --> 00:13:47.333 There is a forward scatter detector to measure cell size. 00:13:47.600 --> 00:13:50.266 And then at 90 degrees to the line of the laser, 00:13:50.266 --> 00:13:53.166 we have all of our fluorescence channel detectors 00:13:53.166 --> 00:13:57.300 and a side scatter detector to, to measure cell complexity. 00:13:57.800 --> 00:14:00.866 And then all of this data goes to the electronic system, 00:14:00.866 --> 00:14:02.866 which we'll discuss next, which is the computer 00:14:02.866 --> 00:14:05.866 that's attached to the flow cytometry workstation. 00:14:07.800 --> 00:14:09.033 And the electronic subsystem 00:14:09.033 --> 00:14:12.666 finally converts the light signals to proportional electronic signals. 00:14:12.666 --> 00:14:16.500 It's assigned a channel number which is then plotted on a graph. 00:14:16.500 --> 00:14:17.233 And that's the data 00:14:17.233 --> 00:14:21.266 that the analyst actually sees when they're analyzing the patient result, 00:14:22.400 --> 00:14:24.400 converts it from an analog to digital signal, 00:14:24.400 --> 00:14:27.466 and then it sends it to the computer for analysis and for storage. 00:14:30.800 --> 00:14:31.400 So let's talk 00:14:31.400 --> 00:14:34.666 now about how we analyze the data in flow cytometry. 00:14:34.666 --> 00:14:37.333 So we've talked about how the instrument actually works. 00:14:37.333 --> 00:14:38.100 We want to talk now 00:14:38.100 --> 00:14:41.166 about how you actually analyze the data that's generated by the flow. 00:14:41.166 --> 00:14:44.166 Cytometer. 00:14:44.433 --> 00:14:46.600 So a couple of ways that that we can look at this, 00:14:46.600 --> 00:14:49.600 we can look at what we call a histogram or a dot plot. 00:14:49.766 --> 00:14:52.766 So a histogram is 00:14:52.833 --> 00:14:55.433 the cell count on the y axis 00:14:55.433 --> 00:14:58.933 versus the light scatter or fluorescence on the x axis. 00:14:59.400 --> 00:15:03.900 So in this example we have a an antibody added 00:15:03.900 --> 00:15:08.133 against the lab 27 antigen on the surface of human white cells. 00:15:08.733 --> 00:15:11.733 And we're looking to read the fluorescence. 00:15:11.733 --> 00:15:15.300 And if the fluorescence exceeds the marker line of positive versus 00:15:15.300 --> 00:15:18.300 negative it's interpreted as a positive result. 00:15:18.333 --> 00:15:19.533 If it stays to the left 00:15:19.533 --> 00:15:22.533 as it is in this case, it's interpreted as a negative result. 00:15:22.533 --> 00:15:25.800 And I'll just say that HLA b 27 is a test that's run, 00:15:27.300 --> 00:15:30.200 not by a lot of clinical flow labs, but certainly some. 00:15:30.200 --> 00:15:33.333 And it's used to screen for certain autoimmune disorders 00:15:33.866 --> 00:15:37.600 that are typically associated with HLA b27 expression. 00:15:39.300 --> 00:15:40.733 And then the dot plot option. 00:15:40.733 --> 00:15:44.033 So here we have 45 versus side scatter. 00:15:44.033 --> 00:15:44.933 And as an example. 00:15:44.933 --> 00:15:48.533 So we're looking at two different measure parameters one against another. 00:15:49.200 --> 00:15:51.833 So in this case we're looking at side scatter which is again 00:15:51.833 --> 00:15:55.166 a measure of the complexity of the cell internally 00:15:55.500 --> 00:15:58.366 plotted against CD 45. 00:15:58.366 --> 00:16:02.266 And this is conjugated to P which is a red dye molecule. 00:16:02.500 --> 00:16:05.433 So CD 45 is an antigen. 00:16:05.433 --> 00:16:07.400 That's expressed only on white blood cells, 00:16:07.400 --> 00:16:10.133 never, platelets or red blood cells. 00:16:10.133 --> 00:16:13.233 And so we this is typically the starting point 00:16:13.233 --> 00:16:16.433 for most of the assays that are run in clinical flow cytometry labs. 00:16:16.600 --> 00:16:19.700 A plot such as this Cd40 45 versus side scatter. 00:16:20.066 --> 00:16:24.833 And we're looking at gating on cells that have Cd40 45 expression. 00:16:24.833 --> 00:16:26.333 So you can see they're moved out to the right 00:16:27.566 --> 00:16:28.900 with low side scatter. 00:16:28.900 --> 00:16:31.233 So that's a characteristic of lymphocytes. 00:16:31.233 --> 00:16:34.033 Monocytes have a little bit more side scatter as you imagine. 00:16:34.033 --> 00:16:36.433 They have vacuoles in the cytoplasm. 00:16:36.433 --> 00:16:38.733 They're a little bit more complex. 00:16:38.733 --> 00:16:41.333 So they present a higher side scatter signal. 00:16:41.333 --> 00:16:43.966 And then the granulocytes the 00:16:43.966 --> 00:16:46.966 the basal fills eosinophils neutrophils 00:16:47.200 --> 00:16:51.766 have a much more complicated nucleus and granules in the cytoplasm. 00:16:51.766 --> 00:16:54.233 So there's much more structure for light to bounce off of. 00:16:54.233 --> 00:16:56.800 So they present with the highest side scatter signal. 00:16:56.800 --> 00:16:59.400 So looking in just at a very simple plot like this 00:16:59.400 --> 00:17:02.400 we can separate out three different cell populations. 00:17:02.433 --> 00:17:05.366 The two little stripes of bands up in the upper right 00:17:05.366 --> 00:17:09.233 hand corner are internal reference beads that are added to the tube. 00:17:09.233 --> 00:17:12.800 And that provides a mechanism for us to count beads relative to cells 00:17:13.033 --> 00:17:15.200 and calculate absolute cell counts. 00:17:15.200 --> 00:17:18.200 So we could potentially report to the clinician 00:17:18.300 --> 00:17:21.633 not only the percentage of lymphocytes in the patient sample, but 00:17:21.633 --> 00:17:25.666 also the number of of cells of lymphocytes per microliter of blood. 00:17:29.433 --> 00:17:31.366 So electronic gating. 00:17:31.366 --> 00:17:36.066 So in the previous on the previous slide, we looked at an example 00:17:36.066 --> 00:17:39.633 of a forward scatter or rather a side scatter versus CD 45 plot. 00:17:40.166 --> 00:17:44.600 And the little gate that was around the CD 45 positive lymphocytes we call a gate. 00:17:44.666 --> 00:17:46.000 Right? It's an electronic gate. 00:17:46.000 --> 00:17:48.266 This is just a window that allows us to focus 00:17:48.266 --> 00:17:51.366 in on a certain population of cells that we're going to analyze further. 00:17:52.166 --> 00:17:55.633 So here's an example looking at CD 45 again versus side scatter. 00:17:55.933 --> 00:17:59.900 And we've got a gate drawn around the CD 45. 00:17:59.900 --> 00:18:02.800 Positive lymphocytes. 00:18:02.800 --> 00:18:04.033 So sorry the CD 00:18:04.033 --> 00:18:07.033 45 positive white blood cells. 00:18:07.466 --> 00:18:09.333 And then we're moving to the right. 00:18:09.333 --> 00:18:12.300 The plot on the upper right is looking at 00:18:12.300 --> 00:18:15.333 within that population of cells gated in the first plot. 00:18:15.900 --> 00:18:19.333 Now we're looking at two markers plotted against one versus the other, CD 00:18:19.433 --> 00:18:22.400 15 versus CD 64. 00:18:22.400 --> 00:18:25.400 So this allows us now to separate out that kind of, 00:18:25.600 --> 00:18:28.800 that population in the first plot into two distinct populations 00:18:28.800 --> 00:18:30.100 that we want to further characterize. 00:18:31.433 --> 00:18:34.633 The CD 15 is in blue, the CD 64 is in green. 00:18:35.033 --> 00:18:37.966 So now we're looking at the CD 15 positive 00:18:37.966 --> 00:18:40.966 cells in the plot on the lower left, 00:18:41.100 --> 00:18:44.100 the CD 64 positive cells in the plot on the lower right. 00:18:44.766 --> 00:18:47.866 And we can see that the two markers that are now 00:18:47.866 --> 00:18:51.500 displayed on these plots are CD 157 versus flare. 00:18:51.666 --> 00:18:53.366 Right. 00:18:53.366 --> 00:18:56.333 This is a panel that we use to screen for 00:18:56.333 --> 00:19:00.066 this disease called paroxysmal nocturnal Hemoglobin area or PNH. 00:19:00.366 --> 00:19:02.200 And what we're looking for here is 00:19:02.200 --> 00:19:04.066 we want to first look at all the white blood cells. 00:19:04.066 --> 00:19:07.633 Then we want to drill down to the CD 15 positive neutrophils. 00:19:07.933 --> 00:19:10.400 The CD 64 positive monocytes. Right. 00:19:10.400 --> 00:19:13.400 And from the previous slide discussion that I mentioned, you can see that 00:19:13.600 --> 00:19:17.833 the lymphocytes are the very smallest population with in pink. 00:19:18.233 --> 00:19:20.000 Monocytes are in green. 00:19:20.000 --> 00:19:22.133 Neutrophils are in blue. 00:19:22.133 --> 00:19:25.066 So when we look at the neutrophils in the monocyte in the two bottom plots 00:19:25.066 --> 00:19:28.133 we can see that they express both the markers 157 and flare. 00:19:28.866 --> 00:19:30.666 That's a normal situation. 00:19:30.666 --> 00:19:33.500 What would be abnormal would be to see these populations lack 00:19:33.500 --> 00:19:35.266 expression of both of those two molecules. 00:19:35.266 --> 00:19:40.166 So they would fall down into the little lower left box in each of those two plots. 00:19:41.100 --> 00:19:42.600 So this is a normal result. 00:19:42.600 --> 00:19:46.300 But this is a very a very common example of kind of a gating strategy 00:19:46.500 --> 00:19:50.300 for how to refine the data down to a subpopulation 00:19:50.300 --> 00:19:53.300 and then look for an abnormality within that population. 00:19:55.900 --> 00:19:56.700 So let's talk a little bit 00:19:56.700 --> 00:19:59.700 more about light scatter and fluorescence. 00:20:00.433 --> 00:20:02.666 So we mentioned that as the cell intersects 00:20:02.666 --> 00:20:06.433 the laser beam we're going to measure two different parameters of scattered 00:20:06.433 --> 00:20:08.166 light forward scatter versus light scatter. 00:20:08.166 --> 00:20:11.166 Forward scatter is the cell size again or surface area. 00:20:11.533 --> 00:20:15.866 Side scatter is the granularity or nuclear structure internal complexity 00:20:15.866 --> 00:20:19.066 of the cell that's measured at 90 degrees to the angle of the laser beam. 00:20:19.700 --> 00:20:24.633 And just with those two signals, we can we can break out the mixed population 00:20:24.633 --> 00:20:28.566 of white blood cells, for instance, into lymphocytes, monocytes and granulocytes. 00:20:28.833 --> 00:20:32.400 The amount of light that scattered is proportional to the size 00:20:32.400 --> 00:20:33.633 or the complexity of the cell. 00:20:35.400 --> 00:20:36.933 But that only takes us so far, right? 00:20:36.933 --> 00:20:39.300 That takes us to a point where we can. Sure we can. 00:20:39.300 --> 00:20:41.700 We can tell by the how the cells are scattering the light, 00:20:41.700 --> 00:20:42.566 whether they're a lymphocyte 00:20:42.566 --> 00:20:45.566 or a monocyte, but we want to get more detailed information. 00:20:45.900 --> 00:20:47.100 So we want to begin 00:20:47.100 --> 00:20:50.766 adding our monoclonal antibody reagents with different fluorophores attached 00:20:50.966 --> 00:20:53.600 so that we can tell okay, within the lymphocytes 00:20:53.600 --> 00:20:56.600 that I can now differentiate by forward and side scatter. 00:20:56.666 --> 00:21:00.066 I want to be able to tell are these what's the percentage of T cells. 00:21:00.066 --> 00:21:01.966 What's the percentage of natural killer cells. 00:21:01.966 --> 00:21:03.666 What's the percentage of B cells. 00:21:03.666 --> 00:21:05.233 For instance. 00:21:05.233 --> 00:21:09.300 So three of the common floor rooms that we use in clinical flow 00:21:09.300 --> 00:21:13.866 cytometry are Fitzy P and P, and there are many others. 00:21:14.000 --> 00:21:16.800 As I mentioned before, we can do up to 12 different colors currently. 00:21:18.166 --> 00:21:19.900 So they emit at different wavelengths. 00:21:19.900 --> 00:21:23.866 They have to be excitable by one of the laser beams that we use on the flow. 00:21:23.866 --> 00:21:24.400 Cytometer. 00:21:24.400 --> 00:21:25.733 So you can see that Fitzy 00:21:25.733 --> 00:21:29.133 absorbs light at a certain wavelength and it emits it it in the green range. 00:21:29.133 --> 00:21:33.000 So 525 for reference, absorbs light and emits. 00:21:33.000 --> 00:21:38.000 At 570, Percy Pig absorbs light and emits at 678. 00:21:38.833 --> 00:21:41.566 So ideally these 00:21:41.566 --> 00:21:45.000 emission ranges are far enough apart 00:21:45.166 --> 00:21:48.866 that we can cleanly detect one population from the other. 00:21:49.733 --> 00:21:53.600 The amount of fluorescence that comes off any individual cell is proportional 00:21:53.600 --> 00:21:57.200 to the amount of antibody that's bound, and thus it's a direct measure 00:21:57.200 --> 00:21:59.100 of the antigen density on the surface of the cell. 00:21:59.100 --> 00:22:02.100 And that becomes important for certain types of disorders. 00:22:02.100 --> 00:22:05.533 And when you're when you're analyzing certain types of samples 00:22:06.300 --> 00:22:08.566 and this fluorescence is measured again at 90 degrees to 00:22:08.566 --> 00:22:09.866 the line of the laser beam. 00:22:12.600 --> 00:22:15.400 So fluorescence signals, 00:22:15.400 --> 00:22:19.433 the fluorescent signals are detected by again what we call photomultiplier tubes. 00:22:19.733 --> 00:22:22.733 And these detect and amplify the very small light signals. 00:22:23.400 --> 00:22:27.900 So one of the limiting factors of flow cytometry for a long time 00:22:27.900 --> 00:22:32.133 has been the fact that we're reliant on different wavelengths of light, 00:22:32.533 --> 00:22:36.300 different fluorophores that are excitable by our lasers 00:22:36.966 --> 00:22:39.966 in order to differentiate different cell populations. 00:22:40.300 --> 00:22:45.066 And unfortunately, these fluorescent signals 00:22:45.066 --> 00:22:49.600 that we're measuring don't emit light at only one wavelength light. 00:22:49.600 --> 00:22:52.600 So they emit over a range of wavelengths. 00:22:53.200 --> 00:22:56.700 So that presents a problem because it's very difficult 00:22:56.700 --> 00:23:00.333 for the flow cytometer or detector array to clean and cleanly detect 00:23:01.566 --> 00:23:03.033 one signal from another. 00:23:03.033 --> 00:23:05.500 If there's a lot of overlap. 00:23:05.500 --> 00:23:09.233 So one of the big QC pieces that we have to do each day 00:23:09.233 --> 00:23:12.600 for the flow cytometry or depending upon the the instrument 00:23:12.600 --> 00:23:15.200 and how often it's supposed to be have this calculation 00:23:15.200 --> 00:23:17.500 done, is to do what we call fluorescence compensation. 00:23:18.733 --> 00:23:19.600 So and 00:23:19.600 --> 00:23:19.933 that's a 00:23:19.933 --> 00:23:23.933 mechanism, a mathematical mechanism for us to subtract out overlapping light 00:23:23.933 --> 00:23:26.933 so that we can cleanly detect each individual signal. 00:23:26.933 --> 00:23:29.933 And you can accomplish this using fluorescently labeled beads. 00:23:30.266 --> 00:23:32.633 You can use light cells. 00:23:32.633 --> 00:23:33.966 There are a number of different ways to do this. 00:23:33.966 --> 00:23:37.166 But the the the end result or what we're trying to do 00:23:37.166 --> 00:23:40.633 is to clean up the signal, subtract out the overlapping light. 00:23:41.266 --> 00:23:43.933 So here's just an example of what this might look like. 00:23:43.933 --> 00:23:48.433 We have say we have one monoclonal antibody conjugated to green 00:23:48.433 --> 00:23:53.400 or Fitzy emission and one conjugated to P or orange red emission. 00:23:54.033 --> 00:23:57.133 And for the most part we can cleanly detect the two different signals. 00:23:57.133 --> 00:24:00.900 The cells labeled with green are going to be emitting around 520. 00:24:01.200 --> 00:24:05.633 The cells labeled with with, flicker or with red or orange 00:24:05.633 --> 00:24:10.633 red are going to be, for the most part, around 605, 70 ranges or something. 00:24:10.633 --> 00:24:12.466 But then there's this overlap region 00:24:12.466 --> 00:24:14.700 where we can't tell the difference between the two. 00:24:14.700 --> 00:24:16.066 That's what we have to correct for 00:24:16.066 --> 00:24:18.733 when we're doing our daily fluorescence compensation. 00:24:18.733 --> 00:24:22.133 And it's just a mathematical compensation calculation 00:24:22.133 --> 00:24:25.566 that luckily now is done automatically by the flow cytometry software. 00:24:25.566 --> 00:24:26.566 To correct that out. 00:24:28.266 --> 00:24:31.966 So let's talk now about some clinical applications of flow cytometry. 00:24:31.966 --> 00:24:35.433 So how do we use these this tool to help us help patients 00:24:35.433 --> 00:24:38.433 and the clinicians that are caring for them. 00:24:38.633 --> 00:24:41.300 So one of the big testing umbrellas of flow cytometry 00:24:41.300 --> 00:24:42.966 is what we call immuno phenotyping. 00:24:42.966 --> 00:24:46.700 So phenotyping is just what we've described so far 00:24:46.700 --> 00:24:50.766 in this presentation that is labeling surface proteins on cells 00:24:51.600 --> 00:24:54.133 to help us tell something about the lineage of a cell, 00:24:54.133 --> 00:24:57.300 the maturation of the cell, immuno meaning white blood cell. 00:24:57.300 --> 00:25:00.200 So phenotype being white blood cells, 00:25:00.200 --> 00:25:03.000 that's most of what clinical flow cytometry is about. 00:25:03.000 --> 00:25:05.100 We do do some red blood cell assays. 00:25:05.100 --> 00:25:07.933 But for the most part we're looking at white blood cells. 00:25:07.933 --> 00:25:10.800 So you can look at two different types of markers 00:25:10.800 --> 00:25:13.800 on when you're doing immuno phenotyping cell surface markers. 00:25:13.866 --> 00:25:15.833 So if you want to say 00:25:15.833 --> 00:25:18.566 we want to tell the difference between T cells and B cells, it's very easy. 00:25:18.566 --> 00:25:22.533 By adding an antibody cocktail that would mark those two different populations. 00:25:22.766 --> 00:25:25.633 It just has to stick to the surface markers on the cell. 00:25:25.633 --> 00:25:28.666 But then you can also look at cytoplasmic or nuclear markers. 00:25:29.266 --> 00:25:32.300 It's a little bit more complicated because you have to fix and then permeable 00:25:32.466 --> 00:25:33.266 the cells. 00:25:33.266 --> 00:25:35.600 But then you could add something like an anti TD 00:25:35.600 --> 00:25:38.600 which is terminal deoxy nuclear tidal transferase. 00:25:38.800 --> 00:25:41.666 So this is a this is an enzyme 00:25:41.666 --> 00:25:44.666 that's found in immature lineage lymphoid lineage cells. 00:25:44.733 --> 00:25:50.166 So if you wanted to look at a patient who potentially has an acute leukemia 00:25:50.433 --> 00:25:51.666 and you wanted to tell the difference 00:25:51.666 --> 00:25:55.766 between a myeloid lineage leukemia and a lymphoid lineage leukemia, 00:25:56.800 --> 00:25:59.800 adding this particular antibody to TD 00:25:59.933 --> 00:26:02.933 could be very helpful. 00:26:03.833 --> 00:26:06.833 So different types of antibodies that we use in flow cytometry, 00:26:06.933 --> 00:26:09.933 polyclonal antibodies and monoclonal antibodies. 00:26:10.266 --> 00:26:13.433 So the polyclonal antibodies we don't use as much as we used to. 00:26:13.500 --> 00:26:16.500 These are made by injecting the antigen into an animal. 00:26:16.766 --> 00:26:18.466 Go to a rabbit or something. 00:26:18.466 --> 00:26:20.000 And then the animal's immune system 00:26:20.000 --> 00:26:23.000 is going to produce antibodies against that foreign antigen. 00:26:23.033 --> 00:26:28.066 That's those antibodies are then harvested and then sold 00:26:28.066 --> 00:26:31.900 to conjugated to fluorophores or sold on conjugated. 00:26:32.166 --> 00:26:34.300 And we use those in flow cytometry testing. 00:26:34.300 --> 00:26:36.133 They're different difficult to standardize. 00:26:36.133 --> 00:26:39.133 They're prone to more nonspecific binding. 00:26:39.400 --> 00:26:42.033 But they do have their place in certain applications. 00:26:42.033 --> 00:26:44.166 More commonly we use monoclonal antibodies. 00:26:44.166 --> 00:26:46.833 These are produced in myeloma cell lines. 00:26:46.833 --> 00:26:49.566 We they are more targeted or more specific 00:26:49.566 --> 00:26:52.566 to a single portion of an antigen or an epitope. 00:26:52.566 --> 00:26:54.666 They're more pure and they're more reproducible 00:26:54.666 --> 00:26:56.400 than the polyclonal antibodies. 00:26:56.400 --> 00:26:59.600 And we just threw this slide in here just just to give you kind of a background 00:26:59.600 --> 00:27:02.100 of the different types. You might hear. 00:27:02.100 --> 00:27:03.600 Especially with Covid 00:27:04.833 --> 00:27:07.833 we're hearing monoclonal antibody that term thrown around a lot. 00:27:07.833 --> 00:27:09.900 And that's basically what we've got here. 00:27:09.900 --> 00:27:13.166 In that case it's a drug to help us with the disease. 00:27:13.166 --> 00:27:17.300 In this case we're using the monoclonal antibody to label different cells. 00:27:19.366 --> 00:27:22.600 So in order to kind of 00:27:22.600 --> 00:27:26.333 standardize flow cytometry this CD system was 00:27:26.500 --> 00:27:29.433 was invented to name different 00:27:29.433 --> 00:27:32.433 antibodies according to their reactivity. 00:27:32.566 --> 00:27:37.033 So you'll often hear things like CD3 or CD4 or CD8. 00:27:37.033 --> 00:27:38.633 I've used those terms so far in this. 00:27:38.633 --> 00:27:42.566 In this conversation, and we'll continue to talk about them as we go through. 00:27:43.100 --> 00:27:47.400 That's basically just an invented system to try and lump these antibodies together 00:27:47.700 --> 00:27:50.466 before the advent of this system, you know, different 00:27:50.466 --> 00:27:53.466 manufacturers would name the antibodies different things. 00:27:53.466 --> 00:27:57.366 For instance, antibodies to look for 00:27:57.366 --> 00:28:00.900 or okt three previously were known by those names. 00:28:00.900 --> 00:28:02.766 Now they're both designated as CD3. 00:28:02.766 --> 00:28:06.200 So it makes things a little easier, more standardized and off to the right 00:28:06.200 --> 00:28:10.800 in the colored squares, we have just the some examples of the different types 00:28:10.800 --> 00:28:15.266 of cells, different lineages of cells, and some of the common antibodies 00:28:15.700 --> 00:28:18.600 that are markers that we use to to look at those cells. 00:28:21.900 --> 00:28:22.466 So some of the 00:28:22.466 --> 00:28:25.500 applications of immuno phenotyping, clinical applications, 00:28:26.433 --> 00:28:27.633 so we can use this technology 00:28:27.633 --> 00:28:30.766 to diagnose and classify mature lymphoid malignancies. 00:28:31.433 --> 00:28:34.600 And you can see I think how this would be powerful if you can count 00:28:34.966 --> 00:28:39.666 30,000 cells a second, if you can use a highly specific monoclonal antibody 00:28:39.666 --> 00:28:43.000 that's going to bind to a certain protein on the surface of the cell, 00:28:43.500 --> 00:28:46.666 it's going to tell you, is this a lymphoid malignancy? 00:28:47.100 --> 00:28:49.733 And what type of lymphoid malignancy is a T lineage thing. 00:28:49.733 --> 00:28:50.700 Is it a B-cell thing. 00:28:50.700 --> 00:28:51.966 So it becomes very powerful 00:28:51.966 --> 00:28:55.033 as opposed to trying to look at a cell on a slide and say, boy, 00:28:55.033 --> 00:28:57.433 that looks like a T-cell to me or a B-cell. 00:28:57.433 --> 00:29:00.566 So that's really, really important and very powerful. 00:29:01.500 --> 00:29:02.133 Next is the 00:29:02.133 --> 00:29:05.133 diagnosis and classification of acute leukemias. 00:29:05.266 --> 00:29:08.866 So acute leukemias are those that are characterized 00:29:08.866 --> 00:29:11.666 by immature cells blast typically. 00:29:11.666 --> 00:29:16.800 So again using these very targeted highly specific monoclonal antibodies 00:29:17.100 --> 00:29:20.766 we can tell something about the type of leukemia 00:29:20.766 --> 00:29:24.133 that you can't tell as easily by looking at a slide. 00:29:24.200 --> 00:29:24.666 Right. 00:29:24.666 --> 00:29:27.933 So using an antibody against a myeloid lineage marker 00:29:27.933 --> 00:29:31.166 and a lymphoid lineage marker you could tell something about 00:29:31.166 --> 00:29:33.766 is this a myeloid leukemia or a lymphoid leukemia. 00:29:33.766 --> 00:29:36.966 The treatments are different and it's in the prognoses may be different. 00:29:36.966 --> 00:29:38.600 So it's important for us to know, 00:29:38.600 --> 00:29:41.300 to be able to tell that information and to be able to provide that 00:29:41.300 --> 00:29:42.633 to the clinician. 00:29:42.633 --> 00:29:46.566 We can also use this to diagnose and monitor primary immunodeficiency. 00:29:47.000 --> 00:29:50.033 So we've got some more information about that on the next slide. 00:29:50.033 --> 00:29:53.666 But these primary immunodeficiency these are disorders that are 00:29:54.333 --> 00:29:56.833 as opposed to having an abnormal cell population 00:29:56.833 --> 00:30:01.166 that you would see in a lymphoid or malignancy or a acute leukemia. 00:30:01.600 --> 00:30:05.633 This is typically the absence of a normal cell population. 00:30:05.800 --> 00:30:09.166 So a baby that is, having recurrent infections 00:30:09.500 --> 00:30:14.000 and the doctor doesn't know why they may send a sample to a flow 00:30:14.000 --> 00:30:18.900 cytometry lab to see does the patient have adequate numbers of T cells? 00:30:19.133 --> 00:30:20.900 Do they have adequate numbers of B-cells. 00:30:20.900 --> 00:30:22.833 And that's something that we can easily provide them. 00:30:23.966 --> 00:30:25.133 And then another example, and 00:30:25.133 --> 00:30:28.133 this is an example of a red cell assay that we run. 00:30:28.200 --> 00:30:32.333 And that is looking at PNH, we also do a white cell assay for 00:30:32.900 --> 00:30:35.400 in, in many of the clinical flow labs. 00:30:35.400 --> 00:30:39.266 And this is the disorder, proximal nocturnal hemoglobin area 00:30:39.633 --> 00:30:43.466 where the patients have, red kind of blood colored urine. 00:30:43.966 --> 00:30:47.966 In some cases in the morning, the hemolysis happens overnight. 00:30:48.233 --> 00:30:53.500 And it's due to a genetic defect that makes it impossible for the patient 00:30:53.500 --> 00:30:57.100 to have certain protective proteins on the surface of the red cells 00:30:57.300 --> 00:30:59.733 that protect those cells from activated complement. 00:30:59.733 --> 00:31:02.700 That can happen in overnight or in response to trauma. 00:31:02.700 --> 00:31:05.700 Those types of things. 00:31:06.300 --> 00:31:09.000 So some of the primary immunodeficiency 00:31:09.000 --> 00:31:12.833 so that we can detect by flow cytometry in the clinical lab. 00:31:13.466 --> 00:31:14.733 The Georgia syndrome is one. 00:31:14.733 --> 00:31:17.000 That's the lack of of T cells. 00:31:17.000 --> 00:31:21.733 So if we have a monoclonal antibody directed against the CD3 antigen site 00:31:22.600 --> 00:31:25.600 and we see no fluorescence for that particular marker, 00:31:25.766 --> 00:31:27.900 we know that there's a problem with the T cells. 00:31:29.033 --> 00:31:29.566 Bruton's 00:31:29.566 --> 00:31:32.566 gamma globule anemia, which is a B-cell deficiency. 00:31:32.733 --> 00:31:36.800 Cd19 is a marker that we like to use to detect and enumerate B cells. 00:31:36.933 --> 00:31:40.800 So lack of Cd19 positivity, no green fluorescence. 00:31:40.800 --> 00:31:45.366 For instance, if we have an anti Cd19 antibody conjugated to a green for a crime 00:31:45.766 --> 00:31:48.533 would be indicative of a B-cell deficiency. 00:31:48.533 --> 00:31:50.266 Severe combined immunodeficiency. 00:31:50.266 --> 00:31:53.533 This is, used to be referred to as the bubble boy disease. 00:31:53.900 --> 00:31:57.566 So the patient has essentially no functional T-cells or B cells. 00:31:58.500 --> 00:32:02.166 And another example, that's not related to lymphocytes. 00:32:02.166 --> 00:32:04.533 This is leukocyte adhesion deficiency. 00:32:04.533 --> 00:32:08.400 This is a disease that's typically, diagnosed in infancy. 00:32:09.400 --> 00:32:12.966 If it's a severe form and this disorder affects the patient's 00:32:12.966 --> 00:32:18.233 granulocytes, they are not able to produce certain adhesion molecules 00:32:18.233 --> 00:32:22.133 that allow the granulocytes to stick to the vascular endothelial cells 00:32:22.400 --> 00:32:25.866 and then, push out into the tissue space to fight infection. 00:32:26.733 --> 00:32:29.733 So the patients have, you know, very little pus formation. 00:32:30.333 --> 00:32:31.233 Typically they're, 00:32:32.500 --> 00:32:34.500 recurrent mouth and throat infections. 00:32:34.500 --> 00:32:37.500 The umbilical cord doesn't separate as it's supposed to. 00:32:38.266 --> 00:32:41.700 So pretty, pretty nasty disorder on the treatment. 00:32:41.700 --> 00:32:43.600 It's typically a bone marrow transplant of the patient. 00:32:43.600 --> 00:32:46.033 Severely. In fact affected. 00:32:46.033 --> 00:32:49.800 And it's very easy to detect the absence of these markers by flow cytometry. 00:32:49.866 --> 00:32:54.000 You add an antibody cocktail that includes an antibody to the antigens 00:32:54.000 --> 00:32:55.733 that might potentially be affected. 00:32:55.733 --> 00:32:57.833 And if you get a fluorescent signal there, there. 00:32:57.833 --> 00:32:58.800 That's a normal result. 00:32:58.800 --> 00:33:02.700 No fluorescent signal means there is a deficiency and the patient's abnormal. 00:33:04.900 --> 00:33:08.566 So, way back at the top, we talked about kind of the first 00:33:08.900 --> 00:33:11.800 clinical application of flow cytometry was in 00:33:11.800 --> 00:33:14.800 HIV Aids patients in the 1980s. 00:33:14.866 --> 00:33:17.700 And it remains to this day, one of the top 00:33:17.700 --> 00:33:21.100 highest volume tests that we perform in clinical flow cytometry labs. 00:33:22.266 --> 00:33:22.766 And this 00:33:22.766 --> 00:33:26.700 this plot simply shows kind of the important markers that we're looking at 00:33:26.700 --> 00:33:31.466 in this type of testing CD4, which is expressed on helper 00:33:31.466 --> 00:33:36.366 inducer T cells, and CD8, which is expressed on cytotoxic T cells. 00:33:37.800 --> 00:33:41.666 So we know from HIV that it infects CD4 T cells. 00:33:41.666 --> 00:33:44.733 So we would expect the CD4 positive population to decline 00:33:44.733 --> 00:33:46.533 relative to the CD8 population. 00:33:46.533 --> 00:33:50.366 So what happens is the patient's overall lymphocyte number decreases. 00:33:51.000 --> 00:33:54.433 The ratio of CD4 T cells to CD8 T cells decreases, 00:33:55.366 --> 00:33:58.966 and the counts of these CD4 positive T cells, 00:33:59.533 --> 00:34:02.233 when they get to kind of a critically low point, 00:34:02.233 --> 00:34:04.400 then the patients are severely immunocompromised. 00:34:04.400 --> 00:34:09.966 So a normal CD4 count would be, say, 515 hundred CD4 T cells per Microliter. 00:34:10.466 --> 00:34:15.466 So if we using our flow cytometer as a tool, can detect these cells 00:34:15.733 --> 00:34:19.400 and quantitate them and say your patient has a CD4 T cell 00:34:19.400 --> 00:34:22.433 count of 150. 00:34:22.500 --> 00:34:24.233 And that's very that's a low result. 00:34:24.233 --> 00:34:26.533 The patient is going to be immunocompromised. 00:34:26.533 --> 00:34:28.633 And with the medications that the patients are on 00:34:28.633 --> 00:34:32.266 now that may indicate that the patient is is not responding as they should. 00:34:36.600 --> 00:34:39.333 So there's some other applications of flow cytometry, 00:34:39.333 --> 00:34:43.266 that are maybe lower volume or maybe a little bit less common. 00:34:44.533 --> 00:34:47.333 We can look at DNA data analysis. 00:34:47.333 --> 00:34:52.500 And this is just looking at the amount of DNA in a cell nucleus. 00:34:52.900 --> 00:34:56.833 So this is important and can be important in looking at different types of tumor 00:34:56.833 --> 00:35:01.966 cells, where the amount of DNA present may be a prognostic indicator 00:35:02.100 --> 00:35:05.100 of how aggressive the tumor is going to be. 00:35:05.266 --> 00:35:08.466 And this is comparing the amount of DNA in a tumor 00:35:08.466 --> 00:35:11.466 cell relative to the normal cells that are also in the sample 00:35:12.300 --> 00:35:14.266 reticular site counting. 00:35:14.266 --> 00:35:18.533 You can use the flow cytometry to account to count and enumerate reticular sites. 00:35:18.533 --> 00:35:21.533 And these are the the less mature red blood cells. 00:35:21.833 --> 00:35:25.500 You just have to use a dye that will, bind to RNA. 00:35:28.300 --> 00:35:30.533 Enumeration of, 00:35:30.533 --> 00:35:32.866 fetal red blood cells. 00:35:32.866 --> 00:35:35.866 This is a test that we perform in my department. 00:35:36.000 --> 00:35:39.000 And this is used to 00:35:39.766 --> 00:35:43.366 detect whether there has been a fetal to maternal hemorrhage 00:35:44.300 --> 00:35:48.900 and then quantitate the amount of fetal red cells in moms circulation 00:35:49.166 --> 00:35:52.166 with an eye towards determining how much, 00:35:53.133 --> 00:35:55.166 rhodium 00:35:55.166 --> 00:35:59.200 needs to be given to prevent sensitization to the baby's red cells. 00:35:59.200 --> 00:36:05.266 And it's it's important, of course, within the context of the RH antigen system. 00:36:05.500 --> 00:36:09.600 So if mom is RH negative and dad is RH positive, 00:36:10.133 --> 00:36:13.133 then mom will see that 00:36:13.500 --> 00:36:16.466 that RH positivity as a foreign antigen 00:36:16.466 --> 00:36:20.100 and can will mount an immune response to the D antigen positivity. 00:36:20.433 --> 00:36:25.000 So if mom is negative and dad is positive, then then the clinician 00:36:25.000 --> 00:36:28.133 is going to be concerned that if the baby is positive 00:36:28.133 --> 00:36:31.800 and any of baby's red cells come into contact with mom's circulation 00:36:31.800 --> 00:36:34.900 and thus her immune system, that she might become sensitized 00:36:35.066 --> 00:36:38.933 and start producing an immune response against baby's red cells. 00:36:39.100 --> 00:36:43.133 Those antibodies can cross the placenta in subsequent pregnancies 00:36:43.366 --> 00:36:46.366 and cause problems for the for the fetus. 00:36:46.566 --> 00:36:50.300 So hemolytic disease of the newborn is a is a potential. 00:36:50.466 --> 00:36:54.900 And so it's important to as soon as possible after delivery 00:36:55.166 --> 00:36:58.700 be able to tell the clinician yes there was a fetal hemorrhage, 00:36:58.800 --> 00:37:00.066 maternal hemorrhage or no. 00:37:00.066 --> 00:37:02.066 And if there was, how many? 00:37:02.066 --> 00:37:06.900 What's the percentage of fetal cells that that that escaped into mom's circulation. 00:37:07.133 --> 00:37:09.333 And then that will dose the patient accordingly. 00:37:10.866 --> 00:37:12.900 You can also look at immune complexes. 00:37:12.900 --> 00:37:17.366 So quantitate in a patient who has lupus or another autoimmune disorder. 00:37:17.966 --> 00:37:19.133 What's the number. 00:37:19.133 --> 00:37:22.133 What's the what's the concentration of circulating immune complexes. 00:37:22.133 --> 00:37:25.466 Using flow cytometry you can look at nucleic acid probes. 00:37:25.800 --> 00:37:29.700 And you can also monitor patients that have undergone, bone marrow 00:37:30.000 --> 00:37:33.000 or stem cell transplantation. 00:37:35.100 --> 00:37:38.566 So just wrapping up some of the key points that we've discussed, 00:37:39.533 --> 00:37:41.633 flow cytometry is an automated measurement 00:37:41.633 --> 00:37:44.700 system of physical or antigenic characteristics 00:37:44.700 --> 00:37:47.900 of single cells passing in a fluid media through a laser light source. 00:37:48.966 --> 00:37:53.433 Flow cytometry consists of three subsystems fluid optics and electronics, 00:37:54.200 --> 00:37:57.700 and there are various clinical applications related to flow cytometry, 00:37:57.866 --> 00:38:02.933 with examples being immuno phenotyping for primary immuno deficiencies. 00:38:03.233 --> 00:38:05.300 As we discussed, 00:38:05.300 --> 00:38:10.700 abnormal cell populations in mature lymphoid malignancies 00:38:10.700 --> 00:38:15.366 and immature acute myeloid or lymphoid 00:38:15.766 --> 00:38:19.066 leukemias, DNA or RNA analysis, 00:38:19.933 --> 00:38:24.433 fetal hemoglobin determination, and then others that are always upcoming. 00:38:24.733 --> 00:38:28.100 So it's been my pleasure to present this talk to you today. 00:38:29.533 --> 00:38:30.833 And I thank you for your time.