Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • Log out
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
    • CME
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CCR Focus Archive
    • Meeting Abstracts
    • Collections
      • COVID-19 & Cancer Resource Center
      • Breast Cancer
      • Clinical Trials
      • Immunotherapy: Facts and Hopes
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • Log out
  • My Cart

Search

  • Advanced search
Clinical Cancer Research
Clinical Cancer Research
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
    • CME
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CCR Focus Archive
    • Meeting Abstracts
    • Collections
      • COVID-19 & Cancer Resource Center
      • Breast Cancer
      • Clinical Trials
      • Immunotherapy: Facts and Hopes
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

The Cooperative Group Bulletin Board

Testing of New Agents in Childhood Cancer Preclinical Models

Meeting Summary

Peter J. Houghton, Peter C. Adamson, Susan Blaney, Howard A. Fine, Richard Gorlick, Michelle Haber, Lee Helman, Steve Hirschfeld, Melinda G. Hollingshead, Mark A. Israel, Richard B. Lock, John M. Maris, Glenn Merlino, Wendy Patterson, C. Patrick Reynolds, Kevin Shannon, Alice Yu, John Yu and Malcolm A. Smith
Peter J. Houghton
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter C. Adamson
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Susan Blaney
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Howard A. Fine
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Richard Gorlick
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michelle Haber
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lee Helman
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Steve Hirschfeld
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Melinda G. Hollingshead
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mark A. Israel
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Richard B. Lock
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John M. Maris
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Glenn Merlino
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Wendy Patterson
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
C. Patrick Reynolds
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kevin Shannon
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alice Yu
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John Yu
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Malcolm A. Smith
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI:  Published December 2002
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

A workshop on pediatric preclinical testing, sponsored by the National Cancer Institute and the Children’s Oncology Group Phase 1 Consortium, was held on June 26–27, 2001 in Bethesda, Maryland. Drs. Peter Adamson, Peter Houghton, and Malcolm Smith organized and hosted the meeting. There were 20 participants from 12 institutions. The primary objectives of the workshop included: (a) development of a working inventory of available preclinical models (including human tumor xenografts in immunodeficient mice, transgenic and syngeneic tumors, and selected in vitro models), with a basic understanding of the strengths and weaknesses of each as possible components of a preclinical testing program; (b) identification of the key scientific issues related to establishment of a program for preclinical testing of new agents for their applicability to childhood cancers; and (c) identification of the key infrastructure requirements for a program for preclinical testing of new agents for their applicability to childhood cancers. This report is a synthesis of the workshop’s presentations and discussions.

Introduction

Approximately 400 new agents are currently under evaluation for cancer indications in adults (1) . Only a small fraction of these can be evaluated in children with cancer as a result of the thankfully small number of children eligible for clinical trials evaluating new agents and the inherent limitations this places on the number of pediatric clinical trials that can be conducted. Because of this increasing imbalance between the number of new agents potentially available for pediatric evaluation and the number that can actually be evaluated, it is essential to develop predictive preclinical models of pediatric cancers to help clinical investigators prioritize new anticancer agents for testing in children.

Preclinical testing of anticancer agents using pediatric cell lines and in vivo model systems has occurred for more than two decades. However, pediatric preclinical testing has never been consistently supported, and neither pharmaceutical companies nor the NCI2 has included pediatric models as standard components of preclinical testing programs. Consequently, a substantial proportion of pediatric Phase I trials have been conducted with limited or no prior testing of the agents in pediatric preclinical models.

There are, however, a select number of pediatric preclinical tumor models that appear to be predictive for future clinical activity. The best studied tumor has been rhabdomyosarcoma. Retrospective studies have demonstrated a strong correlation between the activity of agents against rhabdomyosarcoma xenografts and clinical activity of the same agents (2) . Melphalan was first identified as an active agent against rhabdomyosarcoma in xenograft models, and subsequent clinical experience with melphalan in children with newly diagnosed rhabdomyosarcoma mirrored the activity observed in the xenograft models (3) . The prospective identification of topoisomerase I inhibitors as active agents against rhabdomyosarcoma xenograft models (4) and the subsequent demonstration of antitumor activity for these agents in children with rhabdomyosarcoma further support the predictive ability of these xenograft models (5) .

Xenograft models of neuroblastoma, similar to rhabdomyosarcoma, also have predicted for the future clinical activity of topoisomerase I inhibitors in this disease (4 , 6) . The observation that neuroblastoma cell lines established at different points of therapy acquire a sustained drug-resistant phenotype that mirrors the clinical resistance pattern of patients supports the clinical relevance of the drug sensitivity pattern of these neuroblastoma cell lines (7) .

Despite these and other examples of correlations between drug activity in pediatric preclinical models and clinical activity against tumors in children, the absence of a coordinated and consistent approach to the preclinical evaluation of new agents has prevented a definitive determination of the role of preclinical testing in prioritizing new agents for evaluation in children with cancer. Because of this lack of a systematic approach to preclinical testing, questions remain about the validity of preclinical models as predictors of clinical benefit in children with cancer.

As an initial step in developing a systematic approach to the prioritization of new agents for pediatric evaluation, the Children’s Oncology Group Phase 1 Consortium and the Cancer Therapy Evaluation Program (NCI) sponsored a meeting on June 26–27, 2001 in Rockville, Maryland of investigators who have studied preclinical models potentially applicable to childhood cancer. Meeting participants were asked to address the following objectives: (a) development of a working inventory of available preclinical models, including a summary of the potential strengths and weaknesses of currently available models; (b) identification of the key scientific issues related to establishment of a program for preclinical testing of new agents for their applicability to childhood cancers; and (c) identification of the key infrastructure requirements for a program for preclinical testing of new agents for their applicability to childhood cancers.

Data presented at the meeting documented the existence of potential models (either xenograft, transgenic, or in vitro) for a number of childhood cancers, including rhabdomyosarcoma, osteosarcoma, Ewing’s sarcoma/peripheral PNET, neuroblastoma, various types of brain cancers, JMML, and ALL. The meeting summary that follows focuses primarily on the scientific issues related to the establishment and design of a system for analytically testing new anticancer agents in pediatric preclinical models and on issues related to the infrastructure requirements of such a system. Also included is a brief summary of existing preclinical models.

Existing Pediatric Tumor Models

In Vitro Model Systems.

In vitro model systems have been widely used to test the activity of anticancer agents against childhood cancer primary cells and cell lines, and such models continue to be used as a component of the NCI cell line screen for adult tumors (8 , 9) . Most in vitro model systems use either a clonogenic survival end point, measured by colony formation, or a cell proliferation end point, measured by cell metabolism [e.g., 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, 2,3-bis[2-methoxy-4-nitro-5-sulfophenyl]-2H-tetrazolium-5-carboxanilide inner salt] or biomass (e.g., SRB) assays (10) . One proliferative end point assay presented at the meeting utilizes a fluorescence-based system (DIMSCAN), which has a wide dynamic range (3–4 logs of cell kill) with moderately high throughput. DIMSCAN has been used to study neuroblastoma cell lines established from tumors at various stages of treatment [diagnosis, postinduction, and post bone marrow transplantation (7 , 11 , 12)] . The DIMSCAN assay and other in vitro assays are particularly well suited for defining synergistic interactions between drugs (13 , 14) . Whereas in vitro testing has generally shown limited success in predicting tumor-specific clinical activity in studies of adult tumors, it remains an open question whether testing against a broad panel of carefully selected and well-characterized childhood cancer cell lines can provide clinically useful information.

Primary tumor cells have also been used for in vitro drug testing. For example, primary blast cells from children with ALL have been used to test the antileukemia activity of agents and to correlate in vitro sensitivity to molecularly targeted agents with molecular alterations in the leukemia cells (15 , 16) .

In Vivo Model Systems.

Most pediatric preclinical in vivo testing has involved tumor xenografts, for which several host animal options exist, including SCID mice, NOD/SCID mice, athymic nude mice, and athymic rats. Most recent work in pediatric solid tumor models has used SCID mice, whereas for leukemia models, use of NOD/SCID mice has been more common. Tables 1⇓ and 2⇓ list some of the pediatric xenograft models and the anticancer drugs that have been studied in the models. Perhaps the most influential xenograft experiments have been those evaluating the activity of the camptothecin analogues against pediatric tumors. These experiments demonstrated the schedule-dependent activity of the topoisomerase I inhibitors and their high levels of activity against neuroblastoma and rhabdomyosarcoma xenografts at drug exposures achievable in humans (4 , 17 , 18) . The predicted activity of topotecan and irinotecan against neuroblastoma and rhabdomyosarcoma has been confirmed in clinical trials in children with these diagnoses (5 , 6 , 18) . Testing in pediatric xenograft models has not been limited to conventional cytotoxic agents. For example, antiangiogenic agents [e.g., TNP-470 (19) , the αv integrin antagonist EMD-121974 (20) , and an antibody to vascular endothelial growth factor (21 , 22)] and signal transduction inhibitors [e.g., the Trk family tyrosine kinase inhibitor CEP-751 (23) and the epidermal growth factor receptor inhibitor ZD1839 (24)] have all been evaluated in xenograft models. Although most work with pediatric xenograft models has been for solid tumors, xenograft models of childhood ALL have been developed that have the requisite characteristics of rapid, high-level, uniform leukemia engraftment (25 , 26) . These ALL xenograft models appear to have potential utility for preclinical testing (27 , 28) .

View this table:
  • View inline
  • View popup
Table 1

Pediatric murine and xenograft tumor models presented at the meeting

View this table:
  • View inline
  • View popup
Table 2

Preclinical testing of new agents in pediatric tumor models

Most xenograft testing of anticancer agents has been done with tumors implanted s.c., which has a number of practical advantages (e.g., the ease of evaluating tumor response). The biology of pediatric tumors growing s.c. may differ from that of tumors growing in environments that more closely mimic their site of origin. Alternatives to s.c. models include orthotopic xenograft models (20) and models in which i.v. injection of tumor cells into SCID mice achieves various organ distributions (29) . Assessing response is a challenge with any of these intracavitary mouse tumor models, but new capabilities for small animal imaging may help address this challenge (30, 31, 32) .

Transgenic models may make important contributions to a pediatric preclinical testing program. At the pretesting stage, transgenic models offer the opportunity to identify and validate targets for specific tumor types. Transgenic models may be particularly useful in evaluating targeted therapies for which the model has been engineered to focus on the target pathway of the agent of interest. As an example, JMML has been modeled using Nf1 mutant mice. Approximately 10% of mice with heterozygous inactivation of Nf1 develop a myeloproliferative disorder during the second year of life (33) , although the limited penetrance precludes use of Nf1 heterozygous mice for drug testing. However, adoptive transfer of homozygous Nf1 mutant fetal liver hematopoietic cells to irradiated recipients consistently produces a JMML-like myeloproliferative disorder (34 , 35) . This model of pediatric JMML has been used to evaluate the antileukemia activity of a farnesyl transferase inhibitor, although the process for drug testing is time- and labor-intensive (36) .

A mouse model of neuroblastoma involving overexpression of the MYCN gene has also been used for drug testing. In this model, N-myc expression is targeted to neural crest cells by linkage to the tyrosine hydroxylase promoter (37) . Homozygous MYCN transgenic mice develop neuroblastoma within a tight window at 6–7 weeks of age, with amplification of the transgene observed in the majority of tumors (38) . The high rate of tumor development occurring with a predictable time course makes this model quite tractable for drug testing. MYCN transgenic mice respond to the conventional chemotherapy agent cyclophosphamide, and MYCN transgenic mice treated with MYCN antisense oligonucleotides have reduced tumor incidence and develop smaller tumor mass than animals treated with control oligonucleotides (39) . Table 3⇓ provides a listing of some of the genetically engineered murine models for pediatric tumors that have been developed.

View this table:
  • View inline
  • View popup
Table 3

Mouse genetic models of childhood cancers

Core Model Requirements

The primary goal of a preclinical testing program is to improve outcome for children with cancer by the early identification of potential pediatric applications for new agents in clinical development. The premise for establishing a testing program is that its activities will allow agents (or combinations of agents) to be selected for clinical evaluation that have increased likelihood for clinical benefit. In the absence of an effective preclinical testing program, a preponderance of ineffective agents will be selected for evaluation, thus slowing progress in improving outcome. This hypothesis, although not testable in a randomized manner, requires validation. A pediatric preclinical testing program, although based on scientific principles and designed to pursue scientific opportunities as they arise, would have the very pragmatic objective of providing reliable information to clinical investigators to allow an enlightened prioritization among the multiple agents available for clinical evaluation in children.

A leading issue in the design of a preclinical testing program is the selection of tumor models to study. The first determination will be the tumor types to be studied, because it will likely not be possible to study every type of childhood cancer initially. Factors influencing the selection of tumor types for study include tumor incidence, the adequacy of current therapy for the tumor (i.e., the need for new treatment strategies), overlap with adult tumor types (i.e., can data from adult preclinical testing be applied to the pediatric setting), the availability of tractable preclinical models, and the scientific opportunities related to evaluation of targeted therapies that require study in tumor models for which the target is relevant. If selection of tumor types was based on incidence and mortality rates, then ALL would be at the top of the list, and JMML would be near the bottom. However, if adequacy of current therapy and availability of engineered models of scientific interest is considered, then tumor types such as JMML, for which current therapy is relatively ineffective and for which there are transgenic models suitable for testing targeted agents, would be near the top of the list. In making the initial selection of tumor types to study in a preclinical testing program, it may be preferable to focus on a limited number of tumor types. Once the preclinical testing program’s ability to efficiently and expeditiously test new agents is established with the initial panel of tumors, then expansion to other tumor types could be considered.

In Vitro Model Systems.

Preclinical testing programs have historically included an in vitro testing component. In comparison with in vivo testing, in vitro testing is less expensive and less time-consuming. Thus, an in vitro testing panel could potentially allow more tumor cell lines to be tested per tumor type and could allow additional agents to be tested. Furthermore, the initial testing of combinations of agents can be conducted on a cost-effective basis in vitro, whereas testing multiple drug combinations in animal models is difficult. It is important to perform in vitro testing using clinically relevant drug concentrations and schedules.

In Vivo Model Systems.

For in vivo tumor model systems, once the tumor types for initial inclusion in a preclinical testing program are identified, decisions need to be made about the number of models and the specific models that should be studied for each tumor type. The selection of tumor models will depend to some extent on the type of agent to be tested. For example, an immune modulating agent would require testing in immunocompetent animals and would not be testable in SCID mice. Ideally, however, the tumor models selected should be robust enough to be suitable for studying multiple classes of agents. Another consideration is whether models should be based on tumors from diagnosis or on recurrent tumors. A potential benefit for studying tumors from relapse is that these tumors have clinically relevant mechanisms of drug resistance. Testing using drug-resistant tumors may select for agents that are active against tumors incurable with current therapy. Agents identified as active in relapsed/recurrent tumor models may better predict activity in conventional Phase II studies, whereas models based on tumors at diagnosis may be more applicable to predicting activity in Phase II window studies. Selecting the number of models for each tumor type represents a compromise between the ideal of studying a multitude of models for each tumor type and the resource constraints that limit the number of models that can be studied. This practical limit is probably between 5–10 tumor models for each tumor diagnosis. The number of models studied for each tumor type should reflect the diversity of biological subtypes for the tumor type (e.g., embryonal and alveolar rhabdomyosarcoma and the various molecular subtypes of ALL).

Characteristics of transgenic models suitable for inclusion in a preclinical testing program include: (a) uniform tumor development among independent transgenic lines; (b) high penetrance; (c) early initiation and time to progression; and (d) ability to be bred in large numbers. Transgenic animal models may not be optimal for testing against all agents because many of these models are resource-intensive when used for testing. For transgenic models that are resource-intensive, testing might be restricted to agents shown to be active in xenografts of the same tumor type and to agents that target biochemical pathways that are deregulated as a result of the engineered genetic lesion(s) of the model. For example, the JMML model described above may be useful for testing agents that target constitutively active Ras, but not other molecularly targeted therapeutics. One concern about the applicability of transgenic models is that to have high penetrance and early initiation, some transgenic models are engineered to have two or more specific genetic hits in relatively large numbers of cells. It is reasonable to question how accurately models of this type recapitulate the pathogenesis of human cancer. Also, transgenic models likely reflect more the status of the human cancer at diagnosis (i.e., before treatment) than the status at the time of disease recurrence (i.e., after exposure to cytotoxic therapy). Also, the issues related to the importance of pharmacokinetics in interpreting testing results for xenograft models (see below) apply to transgenic models.

A potential approach that has not been exploited extensively involves combining traditional xenograft and transgenic strategies. That is, cancers from genetically engineered mice or cell lines derived from these tumors might be injected into syngeneic immunocompetent recipients to increase the efficiency of drug testing in vivo.

Once a set of candidate tumor models is selected, there may be value in testing these models against conventional agents with a known clinical response rate to characterize the operating characteristics of each tumor model. This would serve to demonstrate that benchmark agents are active in appropriate tumor models and would enhance confidence in the preclinical testing program. It will also be important to have a periodic assessment of the screen in successfully identifying effective new drugs. Benchmarks for success should be identified prospectively, and analytic methods for determining whether these benchmarks have been met should be developed.

Proposed Approach

A possible design for a preclinical testing program is presented in Fig. 1⇓ . The design anticipates that many of the agents available for testing will have known molecular targets and that relevant transgenic models will exist for some of these targeted agents. The design additionally recognizes that even when an agent has a putative cellular target, there may be other cell signaling pathways affected by the agent that may have relevance to the therapy of childhood cancers [e.g., CEP-701 inhibits both Trk receptor tyrosine kinase activity and Flt3 (40 , 41) , and STI571 inhibits Bcr-Abl, c-Kit, and platelet-derived growth factor receptor (42, 43, 44)] .

Fig. 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig. 1.

Diagram of proposed pediatric testing program (see the text for description).

For agents with general cytotoxic activity for which a molecular target is not defined, the agent would initially be tested at its MTD against the entire xenograft panel. For tumor types in which responses were observed, a full dose-response curve would be developed, and the agent would also be studied in orthotopic or transgenic models of these tumor types when they are available. This sequential design would minimize the resources required to study drugs by avoiding complete dose-response studies for agents with little or no activity in tumor models.

For those agents with defined molecular targets, testing could be performed at doses below the MTD if there were convincing data documenting significant target modulation at lower doses. Even for agents with known molecular targets, there may be an advantage to performing the initial testing at the MTD because antitumor activity associated with modulation of the agent’s known target would likely be detected by testing at the highest dose level tolerated, and activity associated with previously unrecognized targets may be recognized. Regardless of the dose used for the initial testing, if activity was observed, a full dose-response study would be performed to relate antitumor response to target inhibition. If the target of an agent was one for which there was a murine genetic model with suitable characteristics for preclinical testing, evaluation against this model would occur in the first tier of testing. If activity was observed in the first tier of testing for specific tumor types, then the agent would also be studied in available orthotopic models for these tumors.

The role of in vitro testing is not specified in Fig. 1⇓ . For those tumor types with well-characterized cell lines, in vitro testing could occur in parallel with in vivo testing. For those agents showing activity in one or more xenograft or transgenic models, in vitro testing could be especially useful in identifying combinations including the active agent that warrant further preclinical testing.

The infrastructure of a preclinical testing program would include a steering committee responsible for the overall direction and activities of the consortium, the institutions performing the testing for specific tumor types, and core resources for biostatistical, pharmacokinetic, and correlative study support. The institutions participating in the testing program would need to have the animal care infrastructure to support the requisite tumor model systems. They would need to maintain a cell line bank and/or animal tumor models ready for testing when required. Each institution performing testing would need to meet quality control guidelines, report data in a timely manner, share models and data as necessary, and abide by terms of negotiated material transfer agreements. Institutions would standardize treatment protocols to the extent possible across the tumor types being tested.

Essential Core Functions for a Preclinical Testing Program

Three of the essential core functions for a preclinical testing program are presented below.

Pharmacology Core.

Pharmacokinetic data are essential for interpreting the activity observed in preclinical models. Mice may tolerate much higher systemic exposures of some drugs than humans (e.g., DMP0840, 15–20× higher; carzelesin, 80× higher; and sulofenur, 8× higher) and may tolerate lower systemic exposures of other drugs (e.g., etoposide).3 An example of the importance of pharmacokinetic data in interpreting the likely clinical antitumor activity of “active” agents identified in animal models is that of 9-aminocamptothecin and irinotecan (the former is an agent with disappointing clinical activity, whereas the latter has substantial activity against a range of tumor types). Comparison of the pharmacokinetic behavior of 9-aminocamptothecin and irinotecan in mice and humans indicated that the systemic exposures associated with antitumor activity in mice were achievable in man for irinotecan (18) , but not for 9-aminocamptothecin (45) . Thalidomide is another example of the importance of identifying systemic exposure to active metabolites because the active metabolite of thalidomide produced in man is not produced in mice (46) .

A preclinical testing program would need a central resource to generate pharmacokinetic data. Such a central resource could be at a single institution or, alternatively, could be a “pharmacology committee” representing researchers at a several institutions who would support the performance of pharmacokinetic analyses as needed by the consortium. To minimize the pharmacokinetic studies that need to be performed for each agent tested, it would be advantageous for the preclinical testing program to standardize its testing schema to a limited number of animal strains.

Correlative Science Core.

The ability to perform correlative tumor biology studies in the preclinical setting will be increasingly important as agents targeting specific signal transduction pathways are evaluated. Correlative studies may establish whether molecularly targeted agents have achieved target inhibition under test conditions (e.g., Ref. 47 ). Results from these studies will be important in understanding a targeted agent’s activity or lack of activity (i.e., illustrating an association between pathway modulation and antitumor activity) and may serve as a basis for establishing doses of targeted agents for use in combination studies (i.e., selecting doses that modulate target, even though these doses may not have antitumor activity as a single agent). Proteomic and gene expression profiling of tumor models could be used to characterize the presence and activation status of specific cell signaling pathways, to compare gene expression in preclinical model specimens with specimens from patients, and to study changes in pathway activation status and gene expression after drug treatment (e.g., Ref. 48 ). Assays developed for use in the preclinical setting may also prove applicable in evaluating target modulation in the clinical setting, using either tumor tissue or a surrogate normal tissue.

Biostatistical Core.

A preclinical testing program would need biostatistical support to design and analyze its experiments. Design and analytic methods for testing new agents using xenograft models are established and are generally based on comparisons of either response rate or tumor volume in control animals and animals receiving the tested agent. Five to 10 animals are used for each dose of the tested agent. Methods for using transgenic animals for testing experimental agents are less well developed. Specifically, the challenge of using time from symptom development to death as an end point needs to be addressed. For example, to detect a 2-fold difference in this time between control and experimental animals with standard statistical parameters (90% power and α = 0.05) would require 45 events/group.

Obstacles to Implementation of a Pediatric Preclinical Testing Program

Multiple challenges require resolution before a pediatric preclinical testing program becomes a reality. There are scientific issues, such as the most appropriate tumor models (be they in vitro, xenograft, or transgenic) for inclusion in a testing program and the most efficient strategies for testing different classes of new agents. Resource issues must be addressed because establishment of a testing program will require a substantial initial and ongoing investment. Overcoming the perception that preclinical models have inherently poor predictive value in identifying disease-specific activity for new agents (49) must be addressed by validating models used in the program. Perhaps most importantly, a preclinical testing program will need consistent and ongoing support from pharmaceutical companies, as demonstrated by the timely provision of agents for systematic preclinical testing.

Addressing intellectual property right issues and other issues related to collaborations with pharmaceutical sponsors (e.g., data rights and confidentiality, publications, timely access to data, and control of experimental design) will be critical to the ultimate success of a pediatric preclinical testing program. The NCI has established collaborations with a number of sponsors for clinical development of investigational agents, and the solutions developed in the clinical context may be applicable in some instances to preclinical collaborations. With regard to data rights, the clinical collaborative agreements between the NCI and pharmaceutical collaborators stipulate that clinical trial primary data regarding proprietary compounds generated in NCI-sponsored clinical trials are made available exclusively to NCI, the Food and Drug Administration, and the pharmaceutical collaborator. With regard to publications, pharmaceutical collaborators are given 30 days to review manuscripts before submission to assure that no collaborator confidential/proprietary information is released. Collaborators may request an additional 30-day delay in publication to allow time for patent filing. With regard to patent rights, an issue for pharmaceutical collaborators is their access to inventions of federally funded researchers. Federal legislation (Bayh-Dole) prevents academic institutions from assigning intellectual property rights to another party except under narrowly specified conditions. The intellectual property option offers the rights of first negotiation to the pharmaceutical collaborator that supplied the investigational agent when there is an invention related to the agent as a result of federally funded research. If federal funds support some part of the preclinical testing consortium, then a similar option may be appropriate for the consortium to use. The Cancer Therapy Evaluation Program is introducing language into agreements with pharmaceutical sponsors for companies to provide agents for pediatric preclinical testing in accordance with the overall development objectives of the drug. For agents being developed with this stipulation, the agent is distributed under a material transfer agreement with intellectual property and data rights provisions similar to those that govern clinical trials.

Concluding Remarks

Meeting participants considered that the scientific opportunities and clinical need discussed at the meeting provide a strong rationale for establishing a pediatric preclinical testing program to prioritize new agents for evaluation in children with cancer. There is reason to be optimistic that current tumor model systems may have tumor-specific predictive value. Among the recent advances that support this optimism are the increased understanding of the importance of comparisons of systemic drug exposures in mouse models and man (18 , 45 , 50) , the increased availability of pediatric cell lines and xenograft tumor models that have undergone molecular characterization, and the increasing availability of mouse genetic models for many cancer types. Meeting participants recognized, however, that validation of the predictive value of preclinical models is essential and that appropriate analytic methods will be needed to define the ability of specific preclinical testing methods to predict clinical activity for new agents in children.

The initial framework for the successful establishment of a pediatric preclinical testing program has now been outlined. Moving forward with such a program will require ongoing commitment from academia, the pharmaceutical industry, the Children’s Oncology Group, the NCI, and the Food and Drug Administration. Acceptance by pharmaceutical companies of the concept of early access for pediatric preclinical testing to agents under clinical development will be a major factor determining the success or failure of a pediatric testing program. Because one of the purposes of publishing the meeting summary is to obtain feedback from academic investigators and pharmaceutical companies concerning the feasibility and utility of a preclinical testing program, persons with interest in such a program or with suggestions regarding how it should be developed are invited to contact the authors.1

Footnotes

  • ↵1 To whom requests for reprints should be addressed, at Pediatric Section, Cancer Therapy Evaluation Program, National Cancer Institute, 6130 Executive Boulevard, Room 7025, Bethesda, MD 20892-7436. Phone: (301) 496-2522; Fax: (301) 402-0557; E-mail: smithm{at}ctep.nci.nih.gov

  • ↵2 The abbreviations used are: NCI, National Cancer Institute; JMML, juvenile myelomonocytic leukemia; ALL, acute lymphoblastic leukemia; PNET, primitive neuroectodermal tumor; MTD, maximum tolerated dose.

  • ↵3 P. J. Houghton, unpublished observations.

  • Received March 5, 2002.
  • Revision received July 9, 2002.
  • Accepted July 30, 2002.

References

  1. ↵
    Pharmaceutical Research and Manufacturers of America. . New Medicines in Development for Cancer 2001, Pharmaceutical Research and Manufacturers of America Washington, DC 2001.
  2. ↵
    Houghton P. J., Horton J. K., Houghton J. A. Drug sensitivity and resistance in the xenograft model Maurer H. M. Ruymann F. B. Pochedly C. eds. . CRC Rhabdomyosarcoma and Related Tumors in Children and Adolescents, 187-203, CRC Press Boca Raton, FL 1991.
  3. ↵
    Horowitz M. E., Etcubanas E., Christensen M. L., Houghton J. A., George S. L., Green A. A., Houghton P. J. Phase II testing of melphalan in children with newly diagnosed rhabdomyosarcoma: a model for anticancer drug development. J. Clin. Oncol., 6: 308-314, 1988.
    OpenUrlAbstract
  4. ↵
    Houghton P. J., Cheshire P. J., Hallman J. D., Lutz L., Friedman H. S., Danks M. K., Houghton J. A. Efficacy of topoisomerase I inhibitors, topotecan and irinotecan, administered at low dose levels in protracted schedules to mice bearing xenografts of human tumors. Cancer Chemother. Pharmacol., 36: 393-403, 1995.
    OpenUrlCrossRefPubMed
  5. ↵
    Pappo A. S., Lyden E., Breneman J., Wiener E., Teot L., Meza J., Crist W., Vietti T. Up-front window trial of topotecan in previously untreated children and adolescents with metastatic rhabdomyosarcoma: an intergroup rhabdomyosarcoma study. J. Clin. Oncol., 19: 213-219, 2001.
    OpenUrlAbstract/FREE Full Text
  6. ↵
    Kretschmar C., Kletzel M., Murray K., Joshi V., Smith E., Pao P., Castleberry R. Upfront Phase II therapy with Taxol and topotecan in untreated children (>365 days) with disseminated (INSS stage 4) neuroblastoma: a Pediatric Oncology Group study. Med. Pediatr. Oncol., 25: 243 1995.
    OpenUrl
  7. ↵
    Keshelava N., Seeger R. C., Groshen S., Reynolds C. P. Drug resistance patterns of human neuroblastoma cell lines derived from patients at different phases of therapy. Cancer Res., 58: 5396-5405, 1998.
    OpenUrlAbstract/FREE Full Text
  8. ↵
    Monks A., Scudiero D., Skehan P., Shoemaker R., Paull K., Vistica D., Hose C., Langley J., Cronise P., Vaigro-Wolff A. Feasibility of a high-flux anticancer drug screen using a diverse panel of cultured human tumor cell lines. J. Natl. Cancer Inst. (Bethesda), 83: 757-766, 1991.
    OpenUrlAbstract/FREE Full Text
  9. ↵
    Scherf U., Ross D. T., Waltham M., Smith L. H., Lee J. K., Tanabe L., Kohn K. W., Reinhold W. C., Myers T. G., Andrews D. T., Scudiero D. A., Eisen M. B., Sausville E. A., Pommier Y., Botstein D., Brown P. O., Weinstein J. N. A gene expression database for the molecular pharmacology of cancer. Nat. Genet., 24: 236-244, 2000.
    OpenUrlCrossRefPubMed
  10. ↵
    Rubinstein L. V., Shoemaker R. H., Paull K. D., Simon R. M., Tosini S., Skehan P., Scudiero D. A., Monks A., Boyd M. R. Comparison of in vitro anticancer-drug-screening data generated with a tetrazolium assay versus a protein assay against a diverse panel of human tumor cell lines. J. Natl. Cancer Inst. (Bethesda), 82: 1113-1118, 1990.
    OpenUrlAbstract/FREE Full Text
  11. ↵
    Keshelava N., Groshen S., Reynolds C. P. Cross-resistance of topoisomerase I and II inhibitors in neuroblastoma cell lines. Cancer Chemother. Pharmacol., 45: 1-8, 2000.
    OpenUrlCrossRefPubMed
  12. ↵
    Keshelava N., Zuo J. J., Chen P., Waidyaratne S. N., Luna M. C., Gomer C. J., Triche T. J., Reynolds C. P. Loss of p53 function confers high-level multidrug resistance in neuroblastoma cell lines. Cancer Res., 61: 6185-6193, 2001.
    OpenUrlAbstract/FREE Full Text
  13. ↵
    Anderson C. P., Keshelava N., Satake N., Meek W. H., Reynolds C. P. Synergism of buthionine sulfoximine and melphalan against neuroblastoma cell lines derived after disease progression. Med. Pediatr. Oncol., 35: 659-662, 2000.
    OpenUrlCrossRefPubMed
  14. ↵
    Maurer B. J., Melton L., Billups C., Cabot M. C., Reynolds C. P. Synergistic cytotoxicity in solid tumor cell lines between N-(4-hydroxyphenyl)retinamide and modulators of ceramide metabolism. J. Natl. Cancer Inst. (Bethesda), 92: 1897-1909, 2000.
    OpenUrlAbstract/FREE Full Text
  15. ↵
    Omura-Minamisawa M., Diccianni M. B., Batova A., Chang R. C., Bridgeman L. J., Yu J., de Wit E., Kung F. H., Pullen J. D., Yu A. L. In vitro sensitivity of T-cell lymphoblastic leukemia to UCN-01 (7-hydroxystaurosporine) is dependent on p16 protein status: a Pediatric Oncology Group study. Cancer Res., 60: 6573-6576, 2000.
    OpenUrlAbstract/FREE Full Text
  16. ↵
    Batova A., Diccianni M. B., Omura-Minamisawa M., Yu J., Carrera C. J., Bridgeman L. J., Kung F. H., Pullen J., Amylon M. D., Yu A. L. Use of alanosine as a methylthioadenosine phosphorylase-selective therapy for T-cell acute lymphoblastic leukemia in vitro. Cancer Res., 59: 1492-1497, 1999.
    OpenUrlAbstract/FREE Full Text
  17. ↵
    Zamboni W. C., Stewart C. F., Thompson J., Santana V. M., Cheshire P. J., Richmond L. B., Luo X., Poquette C., Houghton J. A., Houghton P. J. Relationship between topotecan systemic exposure and tumor response in human neuroblastoma xenografts. J. Natl. Cancer Inst. (Bethesda), 90: 505-511, 1998.
    OpenUrlAbstract/FREE Full Text
  18. ↵
    Furman W. L., Stewart C. F., Poquette C. A., Pratt C. B., Santana V. M., Zamboni W. C., Bowman L. C., Ma M. K., Hoffer F. A., Meyer W. H., Pappo A. S., Walter A. W., Houghton P. J. Direct translation of a protracted irinotecan schedule from a xenograft model to a Phase I trial in children. J. Clin. Oncol., 17: 1815-1824, 1999.
    OpenUrlAbstract/FREE Full Text
  19. ↵
    Shusterman S., Grupp S. A., Barr R., Carpentieri D., Zhao H., Maris J. M. The angiogenesis inhibitor TNP-470 effectively inhibits human neuroblastoma xenograft growth, especially in the setting of subclinical disease. Clin. Cancer Res., 7: 977-984, 2001.
    OpenUrlAbstract/FREE Full Text
  20. ↵
    MacDonald T. J., Taga T., Shimada H., Tabrizi P., Zlokovic B. V., Cheresh D. A., Laug W. E. Preferential susceptibility of brain tumors to the antiangiogenic effects of an αv integrin antagonist. Neurosurgery, 48: 151-157, 2001.
    OpenUrlCrossRefPubMed
  21. ↵
    Soffer S. Z., Moore J. T., Kim E., Huang J., Yokoi A., Manley C., O’Toole K., Stolar C., Middlesworth W., Yamashiro D. J., Kandel J. J. Combination antiangiogenic therapy: increased efficacy in a murine model of Wilms tumor. J. Pediatr. Surg., 36: 1177-1181, 2001.
    OpenUrlCrossRefPubMed
  22. ↵
    Rowe D. H., Huang J., Kayton M. L., Thompson R., Troxel A., O’Toole K. M., Yamashiro D., Stolar C. J., Kandel J. J. Anti-VEGF antibody suppresses primary tumor growth and metastasis in an experimental model of Wilms’ tumor. J. Pediatr. Surg., 35: 30-32, 2000.
    OpenUrlPubMed
  23. ↵
    Evans A. E., Kisselbach K. D., Yamashiro D. J., Ikegaki N., Camoratto A. M., Dionne C. A., Brodeur G. M. Antitumor activity of CEP-751 (KT-6587) on human neuroblastoma and medulloblastoma xenografts. Clin. Cancer Res., 5: 3594-3602, 1999.
    OpenUrlAbstract/FREE Full Text
  24. ↵
    Houghton P. J., Cheshire P. J., Harwood F. C. Evaluation of ZD1839 (Iressa) alone and in combination with irinotecan (CPT-11) against pediatric solid tumor xenografts. Clin. Cancer Res., 6 (Suppl. 11): 379 2000.
    OpenUrl
  25. ↵
    Lock R. B., Liem N., Farnsworth M. L., Milross C., Collins C., Rice A. M. Suitability of the NOD/SCID mouse for engraftment and chemosensitivity testing of childhood acute lymphoblastic leukemia. Proc. Am. Assoc. Cancer Res., 42: 480-481, 2001.
    OpenUrl
  26. ↵
    Dialynas D. P., Shao L., Billman G. F., Yu J. Engraftment of human T-cell acute lymphoblastic leukemia in immunodeficient NOD/SCID mice which have been preconditioned by injection of human cord blood. Stem Cells, 19: 443-452, 2001.
    OpenUrlCrossRefPubMed
  27. ↵
    Dialynas D. P., Lee M. J., Gold D. P., Shao L., Yu A. L., Borowitz M. J., Yu J. Preconditioning with fetal cord blood facilitates engraftment of primary childhood T-cell acute lymphoblastic leukemia in immunodeficient mice. Blood, 97: 3218-3225, 2001.
    OpenUrlAbstract/FREE Full Text
  28. ↵
    Lock R. B., Liem N., Farnsworth M. L., Milross C. G., Xue C., Tajbakhsh M., Haber M., Norris M. D., Marshall G. M., Rice A. M. The nonobese diabetic/severe combined immunodeficient (NOD/SCID) mouse model of childhood acute lymphoblastic leukemia reveals intrinsic differences in biologic characteristics at diagnosis and relapse. Blood, 99: 4100-4108, 2002.
    OpenUrlAbstract/FREE Full Text
  29. ↵
    Thompson J., Guichard S. M., Cheshire P. J., Richmond L. B., Poquette C. A., Ragsdale S. T., Webber B., Lorsbach R., Danks M. K., Houghton P. J. Development, characterization and therapy of a disseminated model of childhood neuroblastoma in SCID mice. Cancer Chemother. Pharmacol., 47: 211-221, 2001.
    OpenUrlCrossRefPubMed
  30. ↵
    Nikas D. C., Foley J. W., Black P. M. Fluorescent imaging in a glioma model in vivo. Lasers Surg. Med., 29: 11-17, 2001.
    OpenUrlCrossRefPubMed
  31. ↵
    Yang M., Baranov E., Jiang P., Sun F. X., Li X. M., Li L., Hasegawa S., Bouvet M., Al Tuwaijri M., Chishima T., Shimada H., Moossa A. R., Penman S., Hoffman R. M. Whole-body optical imaging of green fluorescent protein-expressing tumors and metastases. Proc. Natl. Acad. Sci. USA, 97: 1206-1211, 2000.
    OpenUrlAbstract/FREE Full Text
  32. ↵
    Moats R., Ma L. Q., Wajed R., Sugiura Y., Lazaryev A., Tyszka M., Jacobs R., Fraser S., Nelson M. D., Jr., DeClerck Y. A. Magnetic resonance imaging for the evaluation of a novel metastatic orthotopic model of human neuroblastoma in immunodeficient mice. Clin. Exp. Metastasis, 18: 455-461, 2000.
    OpenUrlCrossRefPubMed
  33. ↵
    Jacks T., Shih T. S., Schmitt E. M., Bronson R. T., Bernards A., Weinberg R. A. Tumour predisposition in mice heterozygous for a targeted mutation in Nf1. Nat. Genet., 7: 353-361, 1994.
    OpenUrlCrossRefPubMed
  34. ↵
    Largaespada D. A., Brannan C. I., Jenkins N. A., Copeland N. G. Nf1 deficiency causes Ras-mediated granulocyte/macrophage colony stimulating factor hypersensitivity and chronic myeloid leukaemia. Nat. Genet., 12: 137-143, 1996.
    OpenUrlCrossRefPubMed
  35. ↵
    Zhang Y. Y., Vik T. A., Ryder J. W., Srour E. F., Jacks T., Shannon K., Clapp D. W. Nf1 regulates hematopoietic progenitor cell growth and ras signaling in response to multiple cytokines. J. Exp. Med., 187: 1893-1902, 1998.
    OpenUrlAbstract/FREE Full Text
  36. ↵
    Mahgoub N., Taylor B. R., Gratiot M., Kohl N. E., Gibbs J. B., Jacks T., Shannon K. M. In vitro and in vivo effects of a farnesyltransferase inhibitor on Nf1-deficient hematopoietic cells. Blood, 94: 2469-2476, 1999.
    OpenUrlAbstract/FREE Full Text
  37. ↵
    Weiss W. A., Aldape K., Mohapatra G., Feuerstein B. G., Bishop J. M. Targeted expression of MYCN causes neuroblastoma in transgenic mice. EMBO J., 16: 2985-2995, 1997.
    OpenUrlAbstract
  38. ↵
    Norris M. D., Burkhart C. A., Marshall G. M., Weiss W. A., Haber M. Expression of N-myc and MRP genes and their relationship to N-myc gene dosage and tumor formation in a murine neuroblastoma model. Med. Pediatr. Oncol., 35: 585-589, 2000.
    OpenUrlCrossRefPubMed
  39. ↵
    Burkhart C. A., Norris M. D., Marshall G. M., Weiss W. A., Mili M., Haber M. Reduction of neuroblastoma tumorigenesis following N-myc antisense treatment in a transgenic mouse model. Proc. Am. Assoc. Cancer Res., 43: 857 2002.
    OpenUrl
  40. ↵
    Weeraratna A. T., Dalrymple S. L., Lamb J. C., Denmeade S. R., Miknyoczki S., Dionne C. A., et al Pan-trk inhibition decreases metastasis and enhances host survival in experimental models as a result of its selective induction of apoptosis of prostate cancer cells. Clin. Cancer Res., 7: 2237-2245, 2001.
    OpenUrlAbstract/FREE Full Text
  41. ↵
    Levis M., Allebach J., Tse K. F., Zheng R., Baldwin B. R., Smith B. D., Jones-Bolin S., Ruggeri B., Dionne C., Small D. A FLT3-targeted tyrosine kinase inhibitor is cytotoxic to leukemia cells in vitro and in vivo. Blood, 99: 3885-3891, 2002.
    OpenUrlAbstract/FREE Full Text
  42. ↵
    Druker B. J., Talpaz M., Resta D. J., Peng B., Buchdunger E., Ford J. M., Lydon N. B., Kantarjian H., Capdeville R., Ohno-Jones S., Sawyers C. L. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N. Engl. J Med., 344: 1031-1037, 2001.
    OpenUrlCrossRefPubMed
  43. ↵
    Demetri G. D. Targeting c-kit mutations in solid tumors: scientific rationale and novel therapeutic options. Semin. Oncol., 28: 19-26, 2001.
    OpenUrlCrossRefPubMed
  44. ↵
    George D. Platelet-derived growth factor receptors: a therapeutic target in solid tumors. Semin. Oncol., 28: 27-33, 2001.
  45. ↵
    Kirstein M. N., Houghton P. J., Cheshire P. J., Richmond L. B., Smith A. K., Hanna S. K., Stewart C. F. Relation between 9-aminocamptothecin systemic exposure and tumor response in human solid tumor xenografts. Clin. Cancer Res., 7: 358-366, 2001.
    OpenUrlAbstract/FREE Full Text
  46. ↵
    Parman T., Wiley M. J., Wells P. G. Free radical-mediated oxidative DNA damage in the mechanism of thalidomide teratogenicity. Nat. Med., 5: 582-585, 1999.
    OpenUrlCrossRefPubMed
  47. ↵
    Dudkin L., Dilling M. B., Cheshire P. J., Harwood F. C., Hollingshead M., Arbuck S. G., Travis R., Sausville E. A., Houghton P. J. Biochemical correlates of mTOR inhibition by the rapamycin ester CCI-779 and tumor growth inhibition. Clin. Cancer Res., 7: 1758-1764, 2001.
    OpenUrlAbstract/FREE Full Text
  48. ↵
    Cho Y. S., Kim M. K., Cheadle C., Neary C., Becker K. G., Cho-Chung Y. S. Antisense DNAs as multisite genomic modulators identified by DNA microarray. Proc. Natl. Acad. Sci. USA, 98: 9819-9823, 2001.
    OpenUrlAbstract/FREE Full Text
  49. ↵
    Johnson J. I., Decker S., Zaharevitz D., Rubinstein L. V., Venditti J. M., Schepartz S., Kalyandrug S., Christian M., Arbuck S., Hollingshead M., Sausville E. A. Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials. Br. J. Cancer, 84: 1424-1431, 2001.
    OpenUrlCrossRefPubMed
  50. ↵
    Takimoto C. H. Why drugs fail: of mice and men revisited. Clin. Cancer Res., 7: 229-230, 2001.
    OpenUrlFREE Full Text
  51. ↵
    Khanna C., Prehn J., Yeung C., Caylor J., Tsokos M., Helman L. An orthotopic model of murine osteosarcoma with clonally related variants differing in pulmonary metastatic potential. Clin. Exp. Metastasis, 18: 261-271, 2000.
    OpenUrlCrossRefPubMed
  52. ↵
    Khanna C., Khan J., Nguyen P., Prehn J., Caylor J., Yeung C., Trepel J., Meltzer P., Helman L. Metastasis-associated differences in gene expression in a murine model of osteosarcoma. Cancer Res., 61: 3750-3759, 2001.
    OpenUrlAbstract/FREE Full Text
  53. ↵
    Uckun F. M., Manivel C., Arthur D., Chelstrom L. M., Finnegan D., Tuel-Ahlgren L., Irvin J. D., Myers D. E., Gunther R. In vivo efficacy of B43 (anti-CD19)-pokeweed antiviral protein immunotoxin against human pre-B cell acute lymphoblastic leukemia in mice with severe combined immunodeficiency. Blood, 79: 2201-2214, 1992.
    OpenUrlAbstract/FREE Full Text
  54. ↵
    Waddick K. G., Myers D. E., Gunther R., Chelstrom L. M., Chandan-Langlie M., Irvin J. D., Tumer N., Uckun F. M. In vitro and in vivo antileukemic activity of B43-pokeweed antiviral protein against radiation-resistant human B-cell precursor leukemia cells. Blood, 86: 4228-4233, 1995.
    OpenUrlAbstract/FREE Full Text
  55. ↵
    Waurzyniak B., Schneider E. A., Tumer N., Yanishevski Y., Gunther R., Chelstrom L. M., Wendorf H., Myers D. E., Irvin J. D., Messinger Y., Ek O., Zeren T., Langlie M. C., Evans W. E., Uckun F. M. In vivo toxicity, pharmacokinetics, and antileukemic activity of TXU (anti-CD7)-pokeweed antiviral protein immunotoxin. Clin. Cancer Res., 3: 881-890, 1997.
    OpenUrlAbstract
  56. ↵
    Hare C. B., Elion G. B., Houghton P. J., Houghton J. A., Keir S., Marcelli S. L., Bigner D. D., Friedman H. S. Therapeutic efficacy of the topoisomerase I inhibitor 7-ethyl-10-(4-[1-piperidino]-1-piperidino)-carbonyloxy-camptothecin against pediatric and adult central nervous system tumor xenografts. Cancer Chemother. Pharmacol., 39: 187-191, 1997.
    OpenUrlCrossRefPubMed
  57. ↵
    Friedman H. S., Dolan M. E., Pegg A. E., Marcelli S., Keir S., Catino J. J., Bigner D. D., Schold S. C., Jr. Activity of temozolomide in the treatment of central nervous system tumor xenografts. Cancer Res., 55: 2853-2857, 1995.
    OpenUrlAbstract/FREE Full Text
  58. ↵
    Middlemas D. S., Stewart C. F., Kirstein M. N., Poquette C., Friedman H. S., Houghton P. J., Brent T. P. Biochemical correlates of temozolomide sensitivity in pediatric solid tumor xenograft models. Clin. Cancer Res., 6: 998-1007, 2000.
    OpenUrlAbstract/FREE Full Text
  59. ↵
    Aaron R. H., Elion G. B., Colvin O. M., Graham M., Keir S., Bigner D. D., Friedman H. S. Busulfan therapy of central nervous system xenografts in athymic mice. Cancer Chemother. Pharmacol., 35: 127-131, 1994.
    OpenUrlPubMed
  60. ↵
    Boland I., Vassal G., Morizet J., Terrier-Lacombe M. J., Valteau-Couanet D., Kalifa C., Hartmann O., Gouyette A. Busulphan is active against neuroblastoma and medulloblastoma xenografts in athymic mice at clinically achievable plasma drug concentrations. Br. J. Cancer, 79: 787-792, 1999.
    OpenUrlCrossRefPubMed
  61. ↵
    Fontaniere C., Terrier-Lacombe M. J., Santos A., Aubert G., Morizet J., Jimeno J. M., Faircloth G., Vassal G. Antitumor Activity of Et-743 (ecteinascidin-743) in neuroblastoma and medulloblastoma xenografts. Proc. Am. Assoc. Cancer Res., 42: 88 2001.
    OpenUrl
  62. ↵
    Vassal G., Boland I., Santos A., Bissery M. C., Terrier-Lacombe M. J., Morizet J., Sainte-Rose C., Lellouch-Tubiana A., Kalifa C., Gouyette A. Potent therapeutic activity of irinotecan (CPT-11) and its schedule dependency in medulloblastoma xenografts in nude mice. Int. J. Cancer, 73: 156-163, 1997.
    OpenUrlCrossRefPubMed
  63. ↵
    Engler S., Thiel C., Forster K., David K., Bredehorst R., Juhl H. A novel metastatic animal model reflecting the clinical appearance of human neuroblastoma: growth arrest of orthotopic tumors by natural, cytotoxic human immunoglobulin M antibodies. Cancer Res., 61: 2968-2973, 2001.
    OpenUrlAbstract/FREE Full Text
  64. ↵
    Thompson J., Zamboni W. C., Cheshire P. J., Lutz L., Luo X., Li Y., Houghton J. A., Stewart C. F., Houghton P. J. Efficacy of systemic administration of irinotecan against neuroblastoma xenografts. Clin. Cancer Res., 3: 423-431, 1997.
    OpenUrlAbstract
  65. ↵
    Thompson J., Zamboni W. C., Cheshire P. J., Richmond L., Luo X., Houghton J. A., Stewart C. F., Houghton P. J. Efficacy of oral irinotecan against neuroblastoma xenografts. Anticancer Drugs, 8: 313-322, 1997.
    OpenUrlCrossRefPubMed
  66. ↵
    Weitman S., Barrera H., Moore R., Gonzalez C., Marty J., Hilsenbeck S., MacDonald J. R., Waters S. J., Von Hoff D. MGI 114: augmentation of antitumor activity when combined with topotecan. J. Pediatr. Hematol. Oncol., 22: 306-314, 2000.
    OpenUrlCrossRefPubMed
  67. ↵
    Thompson J., George E. O., Poquette C. A., Cheshire P. J., Richmond L. B., de Graaf S. S., Ma M., Stewart C. F., Houghton P. J. Synergy of topotecan in combination with vincristine for treatment of pediatric solid tumor xenografts. Clin. Cancer Res., 5: 3617-3631, 1999.
    OpenUrlAbstract/FREE Full Text
  68. ↵
    Anderson P. M., Meyers D. E., Hasz D. E., Covalcuic K., Saltzman D., Khanna C., Uckun F. M. In vitro and in vivo cytotoxicity of an anti-osteosarcoma immunotoxin containing pokeweed antiviral protein. Cancer Res., 55: 1321-1327, 1995.
    OpenUrlAbstract/FREE Full Text
  69. ↵
    Ek O., Waurzyniak B., Myers D. E., Uckun F. M. Antitumor activity of TP3 (anti-p80)-pokeweed antiviral protein immunotoxin in hamster cheek pouch and severe combined immunodeficient mouse xenograft models of human osteosarcoma. Clin. Cancer Res., 4: 1641-1647, 1998.
    OpenUrlAbstract
  70. ↵
    Houghton P. J., Cheshire P. J., Myers L., Stewart C. F., Synold T. W., Houghton J. A. Evaluation of 9-dimethylaminomethyl-10-hydroxycamptothecin against xenografts derived from adult and childhood solid tumors. Cancer Chemother. Pharmacol., 31: 229-239, 1992.
    OpenUrlCrossRefPubMed
  71. ↵
    Houghton P. J., Cheshire P. J., Hallman J. C., Bissery M. C., Mathieu-Boue A., Houghton J. A. Therapeutic efficacy of the topoisomerase I inhibitor 7-ethyl-10-(4-[1-piperidino]-1-piperidino)-carbonyloxy-camptothecin against human tumor xenografts: lack of cross-resistance in vivo in tumors with acquired resistance to the topoisomerase I inhibitor 9-dimethylaminomethyl-10-hydroxycamptothecin. Cancer Res., 53: 2823-2829, 1993.
    OpenUrlAbstract/FREE Full Text
  72. ↵
    Harris A. W., Pinkert C. A., Crawford M., Langdon W. Y., Brinster R. L., Adams J. M. The E mu-myc transgenic mouse. A model for high-incidence spontaneous lymphoma and leukemia of early B cells. J. Exp. Med., 167: 353-371, 1988.
    OpenUrlAbstract/FREE Full Text
  73. ↵
    Adams J. M., Harris A. W., Pinkert C. A., Corcoran L. M., Alexander W. S., Cory S., Palmiter R. D., Brinster R. L. The c-myc oncogene driven by immunoglobulin enhancers induces lymphoid malignancy in transgenic mice. Nature (Lond.), 318: 533-538, 1985.
    OpenUrlCrossRefPubMed
  74. ↵
    Schmitt C. A., McCurrach M. E., de Stanchina E., Wallace-Brodeur R. R., Lowe S. W. INK4a/ARF mutations accelerate lymphomagenesis and promote chemoresistance by disabling p53. Genes Dev., 13: 2670-2677, 1999.
    OpenUrlAbstract/FREE Full Text
  75. ↵
    Schmitt C. A., Rosenthal C. T., Lowe S. W. Genetic analysis of chemoresistance in primary murine lymphomas. Nat. Med., 6: 1029-1035, 2000.
    OpenUrlCrossRefPubMed
  76. ↵
    Schmitt C. A., Lowe S. W. Bcl-2 mediates chemoresistance in matched pairs of primary E(mu)-myc lymphomas in vivo. Blood Cells Mol. Dis., 27: 206-216, 2001.
    OpenUrlCrossRefPubMed
  77. ↵
    Ding H., Roncari L., Shannon P., Wu X., Lau N., Karaskova J., Gutmann D. H., Squire J. A., Nagy A., Guha A. Astrocyte-specific expression of activated p21-ras results in malignant astrocytoma formation in a transgenic mouse model of human gliomas. Cancer Res., 61: 3826-3836, 2001.
    OpenUrlAbstract/FREE Full Text
  78. ↵
    Reilly K. M., Loisel D. A., Bronson R. T., McLaughlin M. E., Jacks T. Nf1;Trp53 mutant mice develop glioblastoma with evidence of strain-specific effects. Nat. Genet., 26: 109-113, 2000.
    OpenUrlCrossRefPubMed
  79. ↵
    Kamijo T., Bodner S., van de Kamp E., Randle D. H., Sherr C. J. Tumor spectrum in ARF-deficient mice. Cancer Res, 59: 2217-2222, 1999.
    OpenUrlAbstract/FREE Full Text
  80. ↵
    Maddalena A. S., Hainfellner J. A., Hegi M. E., Glatzel M., Aguzzi A. No complementation between TP53 or RB-1 and v-src in astrocytomas of GFAP-v-src transgenic mice. Brain Pathol., 9: 627-637, 1999.
    OpenUrlPubMed
  81. ↵
    Goodrich L. V., Milenkovic L., Higgins K. M., Scott M. P. Altered neural cell fates and medulloblastoma in mouse patched mutants. Science (Wash. DC), 277: 1109-1113, 1997.
    OpenUrlAbstract/FREE Full Text
  82. ↵
    Hahn H., Wojnowski L., Specht K., Kappler R., Calzada-Wack J., Potter D., Zimmer A., Muller U., Samson E., Quintanilla-Martinez L., Zimmer A. Patched target Igf2 is indispensable for the formation of medulloblastoma and rhabdomyosarcoma. J. Biol. Chem., 275: 28341-28344, 2000.
    OpenUrlAbstract/FREE Full Text
  83. ↵
    Wetmore C., Eberhart D. E., Curran T. The normal patched allele is expressed in medulloblastomas from mice with heterozygous germ-line mutation of patched. Cancer Res., 60: 2239-2246, 2000.
    OpenUrlAbstract/FREE Full Text
  84. ↵
    Wetmore C., Eberhart D. E., Curran T. Loss of p53 but not ARF accelerates medulloblastoma in mice heterozygous for patched. Cancer Res., 61: 513-516, 2001.
    OpenUrlAbstract/FREE Full Text
  85. ↵
    Krynska B., Otte J., Franks R., Khalili K., Croul S. Human ubiquitous JCV(CY) T-antigen gene induces brain tumors in experimental animals. Oncogene, 18: 39-46, 1999.
    OpenUrlCrossRefPubMed
  86. ↵
    Gan D. D., Reiss K., Carrill T., Del Valle L., Croul S., Giordano A., Fishman P., Khalili K. Involvement of Wnt signaling pathway in murine medulloblastoma induced by human neurotropic JC virus. Oncogene, 20: 4864-4870, 2001.
    OpenUrlCrossRefPubMed
  87. ↵
    Dobson C. L., Warren A. J., Pannell R., Forster A., Lavenir I., Corral J., Smith A. J., Rabbitts T. H. The MLL-AF9gene fusion in mice controls myeloproliferation and specifies acute myeloid leukaemogenesis. EMBO J., 18: 3564-3574, 1999.
    OpenUrlCrossRefPubMed
  88. ↵
    Heisterkamp N., Jenster G., ten Hoeve J., Zovich D., Pattengale P. K., Groffen J. Acute leukaemia in bcr/abl transgenic mice. Nature (Lond.), 344: 251-253, 1990.
    OpenUrlCrossRefPubMed
  89. ↵
    Voncken J. W., Griffiths S., Greaves M. F., Pattengale P. K., Heisterkamp N., Groffen J. Restricted oncogenicity of BCR/ABL p190 in transgenic mice. Cancer Res., 52: 4534-4539, 1992.
    OpenUrlAbstract/FREE Full Text
  90. ↵
    Reichert A., Heisterkamp N., Daley G. Q., Groffen J. Treatment of Bcr/Abl-positive acute lymphoblastic leukemia in P190 transgenic mice with the farnesyl transferase inhibitor SCH66336. Blood, 97: 1399-1403, 2001.
    OpenUrlAbstract/FREE Full Text
  91. ↵
    Hemmeryckx B., van Wijk A., Reichert A., Kaartinen V., de Jong R., Pattengale P. K., Gonzalez-Gomez I., Groffen J., Heisterkamp N. Crkl enhances leukemogenesis in BCR/ABL P190 transgenic mice. Cancer Res., 61: 1398-1405, 2001.
    OpenUrlAbstract/FREE Full Text
  92. ↵
    Rhoades K. L., Hetherington C. J., Harakawa N., Yergeau D. A., Zhou L., Liu L. Q., Little M. T., Tenen D. G., Zhang D. E. Analysis of the role of AML1-ETO in leukemogenesis, using an inducible transgenic mouse model. Blood, 96: 2108-2115, 2000.
    OpenUrlAbstract/FREE Full Text
  93. ↵
    Yuan Y., Zhou L., Miyamoto T., Iwasaki H., Harakawa N., Hetherington C. J., Burel S. A., Lagasse E., Weissman I. L., Akashi K., Zhang D. E. AML1-ETO expression is directly involved in the development of acute myeloid leukemia in the presence of additional mutations. Proc. Natl. Acad. Sci. USA, 98: 10398-10403, 2001.
    OpenUrlAbstract/FREE Full Text
  94. ↵
    He L. Z., Tribioli C., Rivi R., Peruzzi D., Pelicci P. G., Soares V., Cattoretti G., Pandolfi P. P. Acute leukemia with promyelocytic features in PML/RARα transgenic mice. Proc. Natl. Acad. Sci. USA, 94: 5302-5307, 1997.
    OpenUrlAbstract/FREE Full Text
  95. ↵
    Rego E. M., He L. Z., Warrell R. P., Jr., Wang Z. G., Pandolfi P. P. Retinoic acid (RA) and As2O3 treatment in transgenic models of acute promyelocytic leukemia (APL) unravel the distinct nature of the leukemogenic process induced by the PML-RARα and PLZF-RARα oncoproteins. Proc. Natl. Acad. Sci. USA, 97: 10173-10178, 2000.
    OpenUrlAbstract/FREE Full Text
  96. ↵
    Kogan S. C., Brown D. E., Shultz D. B., Truong B. T., Lallemand-Breitenbach V., Guillemin M. C., Lagasse E., Weissman I. L., Bishop J. M. BCL-2 cooperates with promyelocytic leukemia retinoic acid receptor α chimeric protein (PMLRARα) to block neutrophil differentiation and initiate acute leukemia. J. Exp. Med., 193: 531-544, 2001.
    OpenUrlAbstract/FREE Full Text
  97. ↵
    Rego E., Wang Z., Peruzzi D., He L., Cordon-Cardo C., Pandolfi P. Role of promyelocytic leukemia (PML) protein in tumor suppression. J. Exp. Med., 193: 521-530, 2001.
    OpenUrlAbstract/FREE Full Text
  98. ↵
    Condorelli G. L., Facchiano F., Valtieri M., Proietti E., Vitelli L., Lulli V., Huebner K., Peschle C., Croce C. M. T-cell-directed TAL-1 expression induces T-cell malignancies in transgenic mice. Cancer Res., 56: 5113-5119, 1996.
    OpenUrlAbstract/FREE Full Text
  99. ↵
    Kelliher M. A., Seldin D. C., Leder P. Tal-1 induces T cell acute lymphoblastic leukemia accelerated by casein kinase IIα. EMBO J., 15: 5160-5166, 1996.
    OpenUrlPubMed
  100. ↵
    O’Neil J., Billa M., Oikemus S., Kelliher M. The DNA binding activity of TAL-1 is not required to induce leukemia/lymphoma in mice. Oncogene, 20: 3897-3905, 2001.
    OpenUrlCrossRefPubMed
  101. ↵
    Aplan P. D., Jones C. A., Chervinsky D. S., Zhao X., Ellsworth M., Wu C., McGuire E. A., Gross K. W. An scl gene product lacking the transactivation domain induces bony abnormalities and cooperates with LMO1 to generate T-cell malignancies in transgenic mice. EMBO J., 16: 2408-2419, 1997.
    OpenUrlAbstract
  102. ↵
    Larson R. C., Lavenir I., Larson T. A., Baer R., Warren A. J., Wadman I., Nottage K., Rabbitts T. H. Protein dimerization between Lmo2 (Rbtn2) and Tal1 alters thymocyte development and potentiates T cell tumorigenesis in transgenic mice. EMBO J., 15: 1021-1027, 1996.
    OpenUrlPubMed
  103. ↵
    Yan W., Young A. Z., Soares V. C., Kelley R., Benezra R., Zhuang Y. High incidence of T-cell tumors in E2A-null mice and E2A/Id1 double- knockout mice. Mol. Cell. Biol., 17: 7317-7327, 1997.
    OpenUrlAbstract/FREE Full Text
  104. ↵
    Bain G., Engel I., Robanus Maandag E. C., te Riele H. P., Voland J. R., Sharp L. L., Chun J., Huey B., Pinkel D., Murre C. E2A deficiency leads to abnormalities in αβ T-cell development and to rapid development of T-cell lymphomas. Mol. Cell. Biol., 17: 4782-4791, 1997.
    OpenUrlAbstract/FREE Full Text
  105. ↵
    Roberts C. W., Galusha S. A., McMenamin M. E., Fletcher C. D., Orkin S. H. Haploinsufficiency of Snf5 (integrase interactor 1) predisposes to malignant rhabdoid tumors in mice. Proc. Natl. Acad. Sci. USA, 97: 13796-13800, 2000.
    OpenUrlAbstract/FREE Full Text
  106. ↵
    Guidi C. J., Sands A. T., Zambrowicz B. P., Turner T. K., Demers D. A., Webster W., Smith T. W., Imbalzano A. N., Jones S. N. Disruption of Ini1 leads to peri-implantation lethality and tumorigenesis in mice. Mol. Cell. Biol., 21: 3598-3603, 2001.
    OpenUrlAbstract/FREE Full Text
  107. ↵
    Klochendler-Yeivin A., Fiette L., Barra J., Muchardt C., Babinet C., Yaniv M. The murine SNF5/INI1 chromatin remodeling factor is essential for embryonic development and tumor suppression. EMBO Rep., 1: 500-506, 2000.
    OpenUrlAbstract/FREE Full Text
  108. ↵
    Cichowski K., Shih T. S., Schmitt E., Santiago S., Reilly K., McLaughlin M. E., Bronson R. T., Jacks T. Mouse models of tumor development in neurofibromatosis type 1. Science (Wash. DC), 286: 2172-2176, 1999.
    OpenUrlAbstract/FREE Full Text
  109. ↵
    Vogel K. S., Klesse L. J., Velasco-Miguel S., Meyers K., Rushing E. J., Parada L. F. Mouse tumor model for neurofibromatosis type 1. Science (Wash. DC), 286: 2176-2179, 1999.
    OpenUrlAbstract/FREE Full Text
View Abstract
PreviousNext
Back to top
December 2002
Volume 8, Issue 12
  • Table of Contents

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Clinical Cancer Research article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Testing of New Agents in Childhood Cancer Preclinical Models
(Your Name) has forwarded a page to you from Clinical Cancer Research
(Your Name) thought you would be interested in this article in Clinical Cancer Research.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Testing of New Agents in Childhood Cancer Preclinical Models
Peter J. Houghton, Peter C. Adamson, Susan Blaney, Howard A. Fine, Richard Gorlick, Michelle Haber, Lee Helman, Steve Hirschfeld, Melinda G. Hollingshead, Mark A. Israel, Richard B. Lock, John M. Maris, Glenn Merlino, Wendy Patterson, C. Patrick Reynolds, Kevin Shannon, Alice Yu, John Yu and Malcolm A. Smith
Clin Cancer Res December 1 2002 (8) (12) 3646-3657;

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Testing of New Agents in Childhood Cancer Preclinical Models
Peter J. Houghton, Peter C. Adamson, Susan Blaney, Howard A. Fine, Richard Gorlick, Michelle Haber, Lee Helman, Steve Hirschfeld, Melinda G. Hollingshead, Mark A. Israel, Richard B. Lock, John M. Maris, Glenn Merlino, Wendy Patterson, C. Patrick Reynolds, Kevin Shannon, Alice Yu, John Yu and Malcolm A. Smith
Clin Cancer Res December 1 2002 (8) (12) 3646-3657;
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Existing Pediatric Tumor Models
    • Core Model Requirements
    • Proposed Approach
    • Essential Core Functions for a Preclinical Testing Program
    • Obstacles to Implementation of a Pediatric Preclinical Testing Program
    • Concluding Remarks
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Targeted Delivery in Primary and Metastatic Brain Tumors
  • Cooperative Group Tissue Banks As Research Resources
Show more The Cooperative Group Bulletin Board
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook  Twitter  LinkedIn  YouTube  RSS

Articles

  • Online First
  • Current Issue
  • Past Issues
  • CCR Focus Archive
  • Meeting Abstracts

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Clinical Cancer Research

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Clinical Cancer Research
eISSN: 1557-3265
ISSN: 1078-0432

Advertisement