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
>
>
This archive was generated by hypermail 2b29 : Wed Apr 03 2002 - 11:54:18 EST