Cell Culture Drug Resistance Testing in Ovarian Cancer
Larry M Weisenthal MD PhD
Weisenthal Cancer Group , Huntington Beach, CA 92649
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 , (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% 
Blackman FDA 72 44% 72% 4% 
Carstensen DISC 22 27% 60% 0% [32 ]
Ng ATP 20 31% 50% 0% 
Konecny ATP 38 54% 66% 11% 
Ohie MTT 15 53% 88% 14% 
Sargent MTT 25 42% 60% 10% 
Sevin ATP 31 81% 100% 25% 
Sevin ATP 65 77% 94% 29% 
Taylor MTT 37 46% 65% 15% 
O'Meara ATP 161 65% 83% 43% 
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
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 . 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.
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 . 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 .
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 .
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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