Hi again, this will be my last correspondence on this subject: quote: "Some people are convinced by adequate statistics." An education issue I think. The users here know that a dot on a dot profile is just a dot till proven otherwise. qoute: "we showed 100 million cells per control (run at 85,000 cells/sec which gave very good sampling statistics)and showed rare data of approximately 2 rare cell per 10 million cells." I'd hesitate to put a sample like this on a high speed cell sorter without finding a way to pre-enrich first. Especially if the material is limited. quote: "run at 85,000 cells/sec" ....is this instrument comercially available? What institute can afford it?? quote: "Now we are single cell sorting rare tumor cells..." When single cell sorting, e.g on a Vantage, you sort in the Count mode which gives you 100% purity and exact count, and by doing so manages to lose a high percentage of the cells you're interested in. The rarer the population the higher the loss; therefore you have to pre-enrich to sort as much cells as possible. quote; "but by that time I had pretty well switched my research over into minimal residual disease monitoring." Was FC ever an optimal method for detecting MRD?? Especially when you need so much sample to get reliable stats. At the annual German Flow Cytometry Symposium an instrument called MRDetect was introduced by MetaSystems:this instrument is microscope based equipped with a scanning stage and image analysis. Does 100 slides/run. If it's as good as the company claims it makes detecting MRD by FC obsolete. Most of us are in the following situation: this is the instrument, this is the sample, this is what I want, see you later. I don't mean to sound either critical or offensive but I think what I've written is the real FC world for most of us. all the best Ann At 10:25 07.12.99 -0600, you wrote: > >Phil -- The question of whether it is real or not means different things to >different people. Some people are convinced by adequate statistics. For >example in a major review article I wrote several years ago I also discussed >the rare sampling problem , with a nice discussion of the problem of >estimating rare cell frequencies with 95 percent confidence limits (page >353) for fetal cells in maternal blood (Leary, J.F. "Strategies for Rare >Cell Detection and Isolation", Methods in Cell Biology 42: 331-358, 1994). >On page 346 we showed 100 million cells per control (run at 85,000 cells/sec >which gave very good sampling statistics)and showed rare data of >approximately 2 rare cell per 10 million cells. But to really prove to >ourselves that we had fetal cells, we sorted rare cells at single cell level >and performed single-cell PCR to unequivocally prove (p. 309)that we had the >fetal genotype (Leary et al., "Isolation of Rare Cells by High-Speed Flow >Cytometry and High-Resolution Cell Sorting for Subsequent Molecular >Characterization - Applications in Prenatal Diagnosis, Breast cancer and >Autologous Bone Marrow Transplantation" In: Basic and Clinical Applications >of Flow Cytometry by Valeriote, Nakeff, and Valdivieso Kluwer Academic >Publishers 1996 pp.271-318). We subsequently went on to prove that we had >fetal cells in clinical samples, but by that time I had pretty well switched >my research over into minimal residual disease monitoring. Now we are single >cell sorting rare tumor cells and looking for single base pair mutations in >tumor suppressor genes by single cell DNA sequencing (Leary et >al.,"Real-Time Multivariate Statistical Classification of Cells for Flow >Cytometry and Cell Sorting: A Data Mining Application for Stem Cell >Isolation and Tumor Purging" SPIE 3604: 158-169, 1999; and Leary et al., >"Detection and Isolation of Single Tumor Cells Containing Mutated DNA >Sequences" SPIE 3603: 93-101, 1999). I think you will find these papers >interesting. You can download them as PDF documents readable with Acrobat >through our facility website at http://stem.utmb.edu (click on Recent >PDF-Formatted papers). > So truth is in the eyes of the beholder. After doing rare-event analysis >for almost 20 years, I am inherently a skeptic. Show me the unequivocal >molecular results to make me a believer! Good luck with your skeptics. I >hope you find the papers helpful. -- Best regards, Jim Leary > >-----Original Message----- >From: Barren, Phil [mailto:BarrenP@MedImmune.com] >Sent: Tuesday, December 07, 1999 8:20 AM >To: cyto-inbox >Subject: RE: rare event > > >Jim > >thank you for your reply. I also am one who continually has to fight the >battle of "Is it real or Not". In my case the users would believe a rare >event on a microscopic Immunofluorescence assay, but be skeptical in the >Flow numbers (Go figure) > >Tks > >Pb > >Pb > >-----Original Message----- >From: Leary, James F. [mailto:jleary@utmb.edu] >Sent: Monday, December 06, 1999 11:16 AM >To: cyto-inbox >Cc: 'Cytometry Mailing List'; 'Ann Atzberger' >Subject: RE: rare event > > >Phil -- No I am not saying that. I believe that Ann is probably getting >positive cells above background. What I am saying is that if Ann runs >another sample she might get 10 cells or 2 cells, etc. At this level of >sampling, the sampling is combinatorial - which is the point we tried making >in our paper on sampling statistics (and the degree of assurance you can >have that the frequency you measured is likely to be accurate at a certain >statistical confidence level). If you refer to Hai Qi's most recent posting >to the Cytometry Mailing List you can see his estimates of frequency >bouncing around. If you have enough data you can prove whether your sampling >is truly within the limits of combinatorial statistics. If not then >something might be changing the results, e.g. sedimentation, etc. However, >what I am telling you, based on considerable experience over the past 20 >years that I have performed rare-event analysis, is that you must have >enough data if you want to say with any confidence what the rare cell >frequency is. That is precisely why I got into development of high-speed >systems. I once was approached at an ISAC conference and asked if I believed >some claims on a poster. The authors claimed sensitivity of detection at one >cell in a million. Their sample size was one positive cell in one sample and >none in that region in the control sample. Wishing to be polite I just >smiled and walked away. But underneath I was angry that I had spent at the >time over 12 years of my life to address this problem by developing a large >number of rare-event methods and technology, and that someone could insult >everyone's intelligence at that level. Since people kept asking me how much >is enough to sample, we attempted to give some answers in that Cytometry >paper (Cytometry 27: 233-238, 1997). I'm not claiming that it is the >definitive paper on the subject. I did hope that it would help generate a >useful scientific discussion - and it has. So I am happy. I have spent a >sizable fraction of my career over the past 20 years trying to open the door >for others to study some pretty interesting rare cell problems that I >believe will become increasingly important in the years ahead. I hope people >find this work useful - and keep asking me questions! -- Jim Leary > > -----Original Message----- > From: Barren, Phil [SMTP:BarrenP@MedImmune.com] > Sent: Monday, December 06, 1999 8:46 AM > To: 'Leary, James F.' > Subject: RE: rare event > > DOes this mean that you don't believe the data on the 5 cells?/ > > Pb > > -----Original Message----- > From: Leary, James F. [mailto:jleary@utmb.edu] > Sent: Friday, December 03, 1999 2:34 PM > To: Cytometry Mailing List > Subject: RE: rare event > > > > Ann - -I am a little puzzled. The statistics of a 0.05% population >in 10,000 > total cells is only 5 cells. Even with the best possible background, >the > confidence limits of that frequency are statistically pretty poor. >In the > paper I gave to Hai Qi (see corrected reference on Flow Cytometry >Mailing > List), we explored this issue and showed that accurate frequency >prediction > is relatively poor below about 20 cells and only really gets stable >at about > 50 cells. If you see something that I don't, I would really want to >know! > --Jim Leary > > -----Original Message----- > From: Ann Atzberger [mailto:Ann.Atzberger@EMBL-Heidelberg.de] > Sent: Friday, December 03, 1999 7:32 AM > To: cyto-inbox > Subject: Re: rare event > > > > Hallo Hai Qi, > > if I understand correctly, you ran a total of 200 thousand cells of >the > same sample through the machine twice. As you say the subpopulation >is not > that rare at 0.15%. I have often analysed samples with rare events >at > 0.05% of the total population with good precision,(granted the >signal was > way above background) and only saving 10,000 events. > > If you have a lot of debris or dead cells in the sample the %s can >vary; so > you can either: 1.use a ficoll gradient to clean up the sample. > 2.reset your threshold value to cut out as much debris as possible. > 3.live gate. > 4.Run the cells slowly through the machine. > 5.Make sure the machine is clean, as bits of junk stuck in the >sample probe > can effect your values. > > I might be wrong but I think saving 200,000 cells has to be more >than ample > to detect this subpopulation. > > Ann > At 16:49 01.12.99 -0600, you wrote: > > > > > >It is really not too rare, a cell population about 0.04% to 0.15%, >while > the > >background is 0.01-0.05%. The problem is the variation among >different > >measurements, presumably due to the systematic error. For example, >I had > >10e7 total cells and ran 2*10e5 out of them for two times: one time >I got > >0.04% and the other time I got 0.15%. In order to have smaller >variation, > >obviously I have to increase my sample size, but the last thing I >want to > do > >is to run through all 10e7 cells. Can anyone give me a handy >statistical > >method for estimating the sample size that makes a cost-effective > >compromise? Thank you very much. > > > >Hai Qi > >Dept. of Pathology, UTMB > > > > > >
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