TY - JOUR
T1 - Approaches to identifying drug resistance mechanisms to clinically relevant treatments in childhood rhabdomyosarcoma
AU - Ghilu, Samson
AU - Morton, Christopher L.
AU - Vaseva, Angelina V.
AU - Zheng, Siyuan
AU - Kurmasheva, Raushan T.
AU - Houghton, Peter J.
N1 - Publisher Copyright:
© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License
PY - 2022
Y1 - 2022
N2 - Aim: Despite aggressive multiagent protocols, patients with metastatic rhabdomyosarcoma (RMS) have poor prognosis. In a recent high-risk trial (ARST0431), 25% of patients failed within the first year, while on therapy and 80% had tumor progression within 24 months. However, the mechanisms for tumor resistance are essentially unknown. Here we explore the use of preclinical models to develop resistance to complex chemotherapy regimens used in ARST0431. Methods: A Single Mouse Testing (SMT) protocol was used to evaluate the sensitivity of 34 RMS xenograft models to one cycle of vincristine, actinomycin D, cyclophosphamide (VAC) treatment. Tumor response was determined by caliper measurement, and tumor regression and event-free survival (EFS) were used as endpoints for evaluation. Treated tumors at regrowth were transplanted into recipient mice, and the treatment was repeated until tumors progressed during the treatment period (i.e., became resistant). At transplant, tumor tissue was stored for biochemical and omics analysis. Results: The sensitivity to VAC of 34 RMS models was determined. EFS varied from 3 weeks to > 20 weeks. Tumor models were classified as having intrinsic resistance, intermediate sensitivity, or high sensitivity to VAC therapy. Resistance to VAC was developed in multiple models after 2-5 cycles of therapy; however, there were examples where sensitivity remained unchanged after 3 cycles of treatment. Conclusion: The SMT approach allows for in vivo assessment of drug sensitivity and development of drug resistance in a large number of RMS models. As such, it provides a platform for assessing in vivo drug resistance mechanisms at a “population” level, simulating conditions in vivo that lead to clinical resistance. These VAC-resistant models represent “high-risk” tumors that mimic a preclinical phase 2 population and will be valuable for identifying novel agents active against VAC-resistant disease.
AB - Aim: Despite aggressive multiagent protocols, patients with metastatic rhabdomyosarcoma (RMS) have poor prognosis. In a recent high-risk trial (ARST0431), 25% of patients failed within the first year, while on therapy and 80% had tumor progression within 24 months. However, the mechanisms for tumor resistance are essentially unknown. Here we explore the use of preclinical models to develop resistance to complex chemotherapy regimens used in ARST0431. Methods: A Single Mouse Testing (SMT) protocol was used to evaluate the sensitivity of 34 RMS xenograft models to one cycle of vincristine, actinomycin D, cyclophosphamide (VAC) treatment. Tumor response was determined by caliper measurement, and tumor regression and event-free survival (EFS) were used as endpoints for evaluation. Treated tumors at regrowth were transplanted into recipient mice, and the treatment was repeated until tumors progressed during the treatment period (i.e., became resistant). At transplant, tumor tissue was stored for biochemical and omics analysis. Results: The sensitivity to VAC of 34 RMS models was determined. EFS varied from 3 weeks to > 20 weeks. Tumor models were classified as having intrinsic resistance, intermediate sensitivity, or high sensitivity to VAC therapy. Resistance to VAC was developed in multiple models after 2-5 cycles of therapy; however, there were examples where sensitivity remained unchanged after 3 cycles of treatment. Conclusion: The SMT approach allows for in vivo assessment of drug sensitivity and development of drug resistance in a large number of RMS models. As such, it provides a platform for assessing in vivo drug resistance mechanisms at a “population” level, simulating conditions in vivo that lead to clinical resistance. These VAC-resistant models represent “high-risk” tumors that mimic a preclinical phase 2 population and will be valuable for identifying novel agents active against VAC-resistant disease.
KW - Acquired drug resistance
KW - Combination therapy
KW - Intrinsic drug resistance
KW - Patient-derived xenografts
KW - Rhabdomyosarcoma
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U2 - 10.20517/cdr.2021.112
DO - 10.20517/cdr.2021.112
M3 - Article
C2 - 35450020
AN - SCOPUS:85127577253
SN - 2578-532X
VL - 5
SP - 80
EP - 89
JO - Cancer Drug Resistance
JF - Cancer Drug Resistance
IS - 1
ER -