ISSN:
1573-0646
Keywords:
resistance
;
active
;
passive
;
competitive
;
noncompetitive
;
dose-response curve
Source:
Springer Online Journal Archives 1860-2000
Topics:
Chemistry and Pharmacology
,
Medicine
Notes:
Summary With chemotherapy, the in vitro and clinical dose-response curve is steep in some situations, but is relatively flat in others, possibly due to the mechanism by which tumors are resistant to chemotherapy. For tumors with resistance due to factors that actively decrease chemotherapy efficacy (e.g., p-glycoprotein, glutathione, etc.), one would predict that high dose chemotherapy and therapy with some resistance modulating agents would increase therapeutic efficacy. Such “active” resistance would most likely generally arise from gene amplification or over expression, and would be characterized by a shoulder on the log response vs. dose curve, with eventual saturation of the protective mechanism. On the other hand, one would expect that high dose chemotherapy and most resistance modulating agents would be of little value for rumors with resistance due to defective apoptosis or due to a deficiency in or decreased drug affinity for a drug target, drug activating enzyme, drug active uptake system, or essential cofactor. Such “passive” resistance would most likely generally arise from gene down regulation, deletion, or mutation, and would probably be characterized by a relatively flat log response vs. dose curve, or by a curve in which a steep initial section is followed by a plateau, as target, etc., is saturated. (If response were plotted vs. log dose, then compared to the curve for a sensitive cell line, the curve for active resistance would be analogous to the pharmacodynamic curve seen with competitive antagonism [i.e., a sigmoid curve shifted to the right], and the curve for most types of passive resistance would be analogous to the pharmacodynamic curve seen with noncompetitive antagonism [i.e., a sigmoid curve with reduced maximal efficacy]. As such, one might also refer to active vs. passive resistance as competitive vs. noncompetitive resistance, respectively.) Many tumor types probably possess a combination of active and passive mechanisms of resistance. New in vivo strategies could be helpful in defining dose-response relationships, mechanisms of resistance, and targets for resistance modulation. Such in vivo studies would be conducted initially in animals, but might also be tested clinically if animal studies demonstrated them to be feasible and useful. These in vivo studies would be conducted by randomizing 5–25 subjects to one of 10–20 dose levels over a potentially useful therapeutic range. Nonlinear regression analysis would then be used to define the characteristics of a curve generated by plotting against dose the log percent tumor remaining after the first course of therapy. While this might offer insight into the nature of resistance mechanisms present initially, plotting further tumor shrinkage vs. dose-intensity vs. course number for each later treatment course (or plotting dose-intensity vs. time to tumor progression) might provide information on how tumors become increasingly resistant to drugs following treatment.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00210782
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