Cell Culture Drug Resistance Testing in Ovarian Cancer
Larry M Weisenthal MD
PhD
Weisenthal Cancer Group
, Huntington Beach, CA 92649
mail@weisenthal.org
Introduction
Cell culture drug resistance tests (CCDRT) are laboratory tests in which
fresh biopsy specimens of human tumors are cultured in the presence and absence
of anticancer drugs. At the conclusion of the cell culture, measurements
are made to determine whether or not the drugs were effective in either killing
the tumor cells or in preventing the growth of the tumor cells. Proponents
of these tests maintain that this information correlates with drug effects
in the patient and can therefore be used to assist the clinical oncologist
in selecting the most appropriate drugs to be used in the treatment of individual
patients. This paper will review the data relevant to this point of view.
To begin with, there has been an unfortunate proliferation of names/terms
applying to this testing. It should be noted that the terms "chemosensitivity
assay," "chemoresistance assay," "drug resistance assay," and "drug response
assay" can be used interchangeably. Likewise, the terms "in vitro assay"
and "ex vivo assay" can be used interchangeably in this context. Some authors
have tried to draw a distinction between assays which are geared and/or used
more for the identification of inactive drugs versus active drugs. These
are, however, purely semantic distinctions. Depending on where cut-off lines
are drawn, all assays will have differing specificities and sensitivities
for identifying inactive drugs and active drugs. It is much more useful to
describe the specificity and sensitivity of an assay than to arbitrarily
label the assay to be either a "chemoresistance" or "chemosensitivity" assay.
The generic term "cell culture drug resistance testing" (CCDRT) describes
laboratory tests in which gradations of drug resistance are determined by
measuring drug effects on short term cultures of viable cells. Depending
on the conditions of the assays, they will have greater and lesser specificities
and sensitivities for identifying inactive drugs and active drugs.
One must begin by understanding that there is a clear divide between CCDRT
based on cell proliferation as an endpoint and CCDRT based on cell
death as an endpoint. Historically, the cell proliferation endpoint received
great attention, as a result of studies by Salmon, Von Hoff, and others during
the late 1970s and early 1980s [1,2]. These studies occurred during the heyday
of the oncogene discovery period in cancer research, where oncogene products
were frequently found to be associated with cell growth, and where cancer
was most prominently considered to be a disease of disordered cell growth.
In contrast, the concept of apoptosis (programmed cell death) had yet to
become widely recognized. Also unrecognized were the concepts that cancer
may be a disease of disordered apoptosis/cell death and that the mechanisms
of action of most if not all available anticancer drugs may be mediated through
apoptosis [3-5]. When problems with proliferation-based assays emerged [6,7],
there was little enthusiasm for studying cell death as an alternative endpoint.
These factors explain the abandonment of research into CCDRT by American
universities and cancer centers by the mid-80s. However, clinical laboratories
began to offer CCDRT as a service to patients in the USA by the late 1980s,
and studies of CCDRT continued in Europe and Asia.
Total Cell Kill/Cell Death Assays
As opposed to measuring cell proliferation, there is a closely-related family
of assays based on the concept of total cell kill, or, in other words, cell
death occurring in the entire population of tumor cells (as opposed to only
in a small fraction of the tumor cells, such as the proliferating fraction
or clonogenic fraction) [8-11]. The concepts underlying cell death assays
are relatively simple, even though the technical features and data interpretation
can be very complex. There has been considerable work based on these assays
reported during the past 15 years. This body of work is not currently well
appreciated among clinical oncologists, and the remainder of this review
will focus on the cell death assays.
The basic technology concepts are straightforward. A fresh specimen is obtained
from a viable neoplasm. The specimen is most often a surgical specimen from
a viable solid tumor. Less often, it is a malignant effusion, bone marrow,
or peripheral blood specimen containing "tumor" cells (a word used to describe
cells from either a solid or hematologic neoplasm). These cells are isolated
and then cultured in the continuous presence or absence of drugs, most often
for 3 to 7 days. At the end of the culture period, a measurement is made
of cell injury, which correlates directly with cell death. There is evidence
that the majority of available anticancer drugs may work through a mechanism
of causing sufficient damage to trigger so-called programmed cell death,
or apoptosis [3,4].
Although there are methods for specifically measuring apoptosis, per se,
there are practical difficulties in applying these methods to mixed (and clumpy)
populations of tumor cells and normal cells. Thus, more general measurements
of cell death have been applied. These include: (1) delayed loss of cell
membrane integrity (which has been found to be a useful surrogate for apoptosis),
as measured by differential staining in the DISC assay method, which
allows selective drug effects against tumor cells to be recognized in a mixed
population of tumor and normal cells [12,13], (2) loss of mitochondrial Krebs
cycle activity, as measured in the MTT assay [14], (3) loss of cellular
ATP, in the ATP assay [15-17], and (4) loss of cell membrane esterase
activity and cell membrane integrity, as measured by the fluorescein diacetate
assay [18-20].
It is very important to realize that all of the above 4 endpoints can and
do, in most cases, produce valid and reliable measurements of cell death,
which correlate very well with each other on direct comparisons of the different
methods [14,19-30]. This should not be surprising, any more than should the
fact that auscultating heart sounds, observing spontaneous breathing, palpating
a carotid pulse, measuring core body temperature, and recording an electroencelphalogram
or electrocardiogram are all good and reliable methods of determining patient
death.
We have performed direct correlations between the DISC and MTT assays in
approximately 4,000 fresh human tumor specimens, testing an average of 15
drugs per specimen at two different concentrations. Thus, we have approximately
120,000 direct comparisons between DISC (membrane integrity) and MTT (mitochondrial
Krebs cycle activity) endpoints in fresh human tumor specimens. The overall
correlation coefficient between these endpoints in specimens containing >
60% tumor cells is 0.85 (These data do not include assays on 5FU, which,
for biological reasons, may be tested in the MTT assay but not the DISC assay.
These data also do not include assays for paclitaxel and docetaxel, which,
for different biological reasons, may be tested in the DISC assay but not
the MTT assay).
The above studies, demonstrating the comparability of results with the 4
different cell death endpoints, are important for the following reason. For
perfectly understandable reasons, clinical studies correlating assay results
with clinical outcome are very difficult to perform. The literature in this
field may be characterized as including a great many small studies, but no
big studies. Additionally, different investigators have favored different
cell death endpoints, depending on the laboratory and clinical situation.
For example, the DISC assay is extremely labor intensive, and requires expertise
in recognizing and counting tumor cells using a microscope, but it may be
applied to specimens containing a heterogeneous mixture of tumor cells and
normal cells. MTT, ATP, and FDA endpoints use semi-automated instrument readouts,
but can only be applied to specimens which are relatively homogeneous for
tumor cells. In addition, there are a number of additional reasons why one
type of cell death endpoint may be advantageous in a given tumor specimen
and why laboratories may apply several different cell death endpoints in
the testing of a single specimen.
It should be noted that, historically, the DISC assay studies of the early
1980s provided the prototype for later studies of the other cell death endpoints.
When the MTT endpoint was first introduced in the late 1980s, the first published
studies compared the MTT results to the DISC results, with culture conditions
and drug exposures being otherwise identical [14,21,23,25]. Many laboratories
have preferred the MTT endpoint (and later the ATP and FDA endpoints), because
of the difficulty in manually scoring the DISC assay microscope slides. But
what is important is that each of the above cell death endpoints do give
essentially the same results (except in the case of isolated drugs, such
as taxanes and 5FU). Thus, it is entirely reasonable and proper to consider
as a whole the clinical validation data which has been published using the
above 4 endpoints.
The second point to understand is that cell death assays are not intended
to be scale models of chemotherapy in the patient. The DISC assay was designed
to address the major practical problems with the popular clonogenic assays
of the late-70s/early-80s. Chief among these problems were (1) low evaluability
rates and (2) uncertainty of what was being measured in individual assays
(true tumor cell colonies, arising from clonogenic cell growth versus artifactual
colonies arising from cell aggregation). Unlike the case with the clonogenic
assays, there was no attempt to model in vivo pharmacokinetics (i.e. no attempt
to utilize clinically-achievable drug concentrations or to determine something
analogous to an anti-bacterial minimal inhibitory concentration). Instead,
the assay conditions were rigorously fixed, with respect to culture media
and drug exposure time (the latter being, most typically, 96 hours). Drugs
were first tested in training set assays to determine the drug concentration
which gave the widest scatter of results (mathematically defined as the greatest
standard deviation).
The hypothesis to be tested with clinical correlations was a very simple
one - that above-average drug effects in the assays would correlate with above-average
drug effects in the patient, as measured by both response rates and patient
survival. The above hypothesis has been confirmed to be true in every single
study of these assays ever carried out.
Studies have reported more than 2,000 correlations between assay results
and clinical tumor response and/or patient survival. This work has been carried
out in a broad range of human neoplasms, including acute and chronic lymphocytic
and non-lymphocytic leukemia, non-Hodgkin's lymphoma, breast, lung, ovarian,
and other solid cancers. The following reviews results relating only to
ovarian cancer. Data relative to breast, colon, lung, and other solid
tumors, as well as to acute and chronic leukemias, lymphomas, and multiple
myeloma are briefly presented elsewhere on this web site. In future installments,
a detailed description of published results in each of the above neoplasms
will be presented.
Summary of Data Correlating Clinical Response with Cell Death Assay Results in Ovarian Cancer
(note: RR = response rate; "Sensitive" = response rate for patients
with tumors "sensitive" in the assays; "Resistant" = response rate for patients
with tumors "resistant" in the assays; "Overall = response rate for
the entire group of patients ("sensitive" and "resistant") reported in each
particular study; "n" = number of individual patients in each study).
Author Endpoint
n Overall RR RR,"Sensitive" RR,"Resistant"
Ref: clickable
Weisenthal DISC
3 33%
100% 0%
[12]
Blackman FDA
72 44%
72%
4% [31]
Carstensen DISC 22
27% 60%
0%
[32
]
Ng
ATP 20
31% 50%
0% [33]
Konecny ATP
38 54%
66%
11% [34]
Ohie MTT
15 53%
88%
14%
[35]
Sargent MTT
25 42%
60% 10%
[36]
Sevin
ATP 31 81%
100%
25% [37]
Sevin
ATP 65
77% 94%
29%
[38]
Taylor MTT
37 46%
65%
15%
[39]
O'Meara ATP
161 65%
83%
43%
[40]
Taylor
MTT (n=120,see linked paper
) [
41
]
Total N=609,see
text
Specificity
= 0.92 (Specificity for drug resistance)
Sensitivity
= 0.72 (Sensitivity for drug resistance)
The above table shows the results of each individual study. In every single
case, without exception, assay "sensitive" patients were more likely
to respond than the total patient population as a whole and assay "resistant"
patients were much less likely to respond than the patient population as
a whole. In every case, patients treated with assay "resistant" drugs were
considerably less likely to respond than patients treated with assay "sensitive"
drugs. This should not be a surprising finding. Intuitively, tumors relatively
resistant to drugs in vitro would seem, on the whole, to be less likely to
respond to the same drugs in vivo. This is precisely what the published data
show.
Also reported were highly positive associations between assay results and
patient survival following chemotherapy [40-42]. Elsewhere on this web site
are shown correlations between patient overall survival
and assay results obtained in our laboratory
. (After viewing graph, click on browser's "back arrow" to return).
Kurbacher and colleagues treated 25 patients with ovarian cancer with ATP-assay-directed
chemotherapy and compared outcomes with 30 non-randomized but clinically well-matched
controls [43]. In the control group, there was a response rate of 37% (2
complete responders), with median progression-free survival of 20 weeks and
median overall survival of 69 weeks. In the assay-directed group, there was
a response rate of 64% (8 complete responders), with a median progression-free
survival of 50 weeks (P2=0.003) and a median overall survival of 97 weeks
(P2=0.145). Assay directed therapy also produced a greater benefit with respect
to both response rate and progression-free survival in the subgroup of patients
with platinum-resistant disease. A current multi-institutional, international
trial is currently in progress to determine if assay-directed therapy is
superior to empiric therapy.
Editorial Remarks
While evaluating the data discussed here, please consider that it has
taken 20 years to amass this body of evidence in an environment of continued
hostility and non-support by the academic oncology community toward work in
this area and consider also the little which has been achieved in the area
of empiric methods of drug selection, despite billions of dollars spent on
empiric clinical trials enthusiastically supported by this same academic
oncology community.
If one critically evaluates the clinical trials data
in ovarian cancer
, for example, one finds that there is little or no advantage for platinum-based
combination chemotherapy over single agent alkylator therapy and no advantage
for platinum + paclitaxel over single agent cisplatin or carboplatin [44-46].
But this did not prevent platinum combination therapy from becoming "standard
of care" before the introduction of paclitaxel and it did not prevent platinum/paclitaxel
from becoming standard of care over single agent carboplatin or cisplatin.
And there are absolutely no data to support any of the half dozen or so available
drug choices for second and third line therapy over any other choice. So
what is the "risk" in using currently available assays to help guide these
choices? Only when these assays are widely performed and used and routinely
included as an integral part of clinical trials will these already promising
technologies be improved and only then will their role in patient management
become better defined. But this is true for all complex laboratory technologies
(a good example being immunohistochemical staining for batteries of cell
antigens).
Absent this testing, on what basis are drugs chosen today for use in the
myriad clinical settings in which a single "best" empiric regimen has not
been well-defined? An objective reviewer would admit that many oncology practices
would base choice of drug regimen, at least in part, on the profit "spread"
between the wholesale cost of the drug(s) and the reimbursement which the
third party payers provide. This is a conflict of interest as well as a cost-ineffective
method for selecting therapy; yet it is a method which the oncology and insurance
communities support every single day in their treatment and coverage decisions.
It is the loss of this "freedom to choose" and the overzealous dedication
to a weak clinical trials paradigm (identification of the "best" treatment
to give to the average patient) which is largely behind the reluctance to
introduce these technologies as an important component of current clinical
trials and as a part of the process of clinical drug selection in situations
where clear empiric "best regimens" have not been well defined through prior
clinical trials.
The private sector laboratories offering CCDRT as a patient service have
been able to make considerable progress in improving the assay technologies
and in building databases which improve the interpretation of "raw" assay
results. But this progress has only been possible because insurers and often
patients have been willing to pay for the tests and because clinicians have
wanted to have the information provided by the tests. The progress would
have been much faster (and doubtless even more substantial) had the academic
oncology community not done everything it could to oppose this work at every
step of the way.
By raising the bar of acceptance to levels unprecedented for a laboratory
test, in essence a tariff has been erected to protect the paradigm of the
"best" empiric treatment for the average patient, as identified in appallingly
non-productive clinical trials. This tariff also serves to protect the paradigm
of drug selection with consideration of the spread between wholesale cost
and reimbursement. Finally, the tariff discourages discovery of new, effective
drug regimens through the use of CCDRT to guide drug selection. Take, for
example, the gemcitabine/cisplatin combination. Years before gemcitabine/cisplatin
became a widely used drug regimen, CCDRT identified this as the most active
regimen in a patient with pancreatic cancer metastatic to kidney, omentum,
and liver, despite the poor activity of gemcitabine and cisplatin tested
as single agents. This patient went on to achieve a complete remission with
gemcitabine/cisplatin and remains alive with an excellent quality of life
5 years later [47,48]. A second such patient was an ovarian cancer patient
with primary resistance to paclitaxel/carboplatin who then underwent tandem
stem cell transplant/high dose chemotherapy regimens (at a cost of more than
$200,000) without ever achieving a response. At a time when she had bulky,
non-cytoreducible abdominal and pleural disease, CCDRT confirmed resistance
to single agent cisplatin, carboplatin, and gemcitabine, but good activity
for the gemcitabine/carboplatin combination. She subsequently received gemcitabine/carboplatin
as an outpatient, achieved a durable complete response, and returned to work
full time as an oncology nurse, and remains well as of this time, more than
three years later [49]. Indeed, early anecdotal results of this type occurring
in diseases in which there was no existing clinical trials literature accelerated
clinical trials of this regimen in diseases in which assay-directed responses
had been observed [50].
With more widespread use of these assays in clinical oncology, it is very
likely that the activity of new drugs and new regimens would be identified
at a much earlier time than with the current system relying exclusively on
usually-empiric, Phase II trials [51].
Why is it so necessary to protect the patient from the information provided
by a perfectly rational laboratory test, supported by a wealth of entirely
consistent, if understandably incomplete data? Think of all the objections
to this testing. Now try to design all of the clinical trials which would
be needed to meet all of these objections and think of how much money these
would require and who is going to provide this money and how many years the
studies would take and how many patients will continue to receive ineffective
or suboptimum treatment in the interim. The body of information will never
be sufficiently large and complete and definitive to encompass even a reasonable
fraction of the situations where the information provided by the tests would
be helpful. Now ask the questions: What is the potential risk? What are the
potential benefits? What is the probability that these tests really do provide
information which can improve the drug selection process in individual clinical
situations? what is the potential cost? How does the benefit/risk ratio balance
out? What is the (financial) cost as a percentage of total costs relating
to management of patients on chemotherapy (including the costs of radiographic
and laboratory studies performed only to determine if a given form of treatment
is working or not)? What are the long term costs if drug selection always
remains an empiric, one-size-fits-all, trial and error process? What would
be the impact on improving existing technologies (through the attraction
of more laboratory and clinical investigators into the field) and developing
new technologies should these assays become more widely used?
If one wishes to see an example of an entirely rational technology advance,
in a human disease crying out for precisely such a technology advance, supported
by an entirely consistent (if understandably incomplete) body of data, where
the advance continues to be held hostage to a high bar of extraordinarily
difficult clinical trials which the critics have been entirely unwilling
to support, in an area (laboratory testing) for which such trials would be
entirely unprecedented, one need look no further.
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