Molecular Evaluation of Patient-Derived Colorectal Cancer Explants as a Pre-clinical Mouse Model of Colorectal Cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE35144 | GEO | 2012/06/07
SECONDARY ACCESSION(S): PRJNA150711
REPOSITORIES: GEO
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Project description:Mouse models have been developed to investigate colorectal cancer etiology and evaluate new anti-cancer therapies. While genetically engineered and carcinogen-induced mouse models have provided important information with regard to the mechanisms underlying the oncogenic process, xenograft models remain the standard for the evaluation of new chemotherapy and targeted drug treatments for clinical use. However, it remains unclear if drug efficacy data obtained from xenograft models translate into clinically-relevant treatment modalities. In this study, we have generated a panel of 28 patient-derived colorectal cancer explants (PDCCEs), an extension of our previous work, by direct transplantation of human colorectal cancer (CRC) tissues into NOD-SCID mice. A comprehensive histological and molecular evaluation of PDCCEs and their corresponding patient tumor demonstrates that PDCCEs maintain histological features and global biology through multiple passages. Furthermore, we demonstrate that in vivo sensitivity of PDCCEs to oxaliplatin can predict patient outcomes. Our findings suggest that PDCCEs maintain similarity to the patient tumor from which they are derived and can serve as a reliable preclinical model that can be incorporated into future strategies to optimize individual therapy for patients with CRC. 28 human primary colorectal and 37 mouse derived colorectal explant tumors
2012-06-06 | E-GEOD-35144 | biostudies-arrayexpress
Project description:Phenotypic plasticity is a major driver of cancer progression, metastasis, and treatment resistance. However, the principles governing human cancer plasticity associated with poor prognosis remain poorly understood due to the lack of in vitro models. Here we identified a unique cancer cell state at single-cell resolution to predict poor prognosis across several human cancers with different clinical features, especially colorectal cancer (CRC) progression and metastasis, named the poor prognostic plastic state (PPPS). A functional patient-derived organoid xenograft (PDOX) model was developed to capture and maintain the PPPS in CRC. With a marker gene of MSLN (encoding mesothelin), this model was used to validate the role of the PPPS in promoting CRC metastasis. Moreover, precise manipulation of human cancer plasticity through the PPPS allows us to identify small-molecule inhibitors of non-canonical IKKs to promote malignancy, with clinical implications for targeting the PPPS to prevent CRC progression and metastasis.
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Project description:Phenotypic plasticity is a major driver of cancer progression, metastasis, and treatment resistance. However, the principles governing human cancer plasticity associated with poor prognosis remain poorly understood due to the lack of in vitro models. Here we identified a unique cancer cell state at single-cell resolution to predict poor prognosis across several human cancers with different clinical features, especially colorectal cancer (CRC) progression and metastasis, named the poor prognostic plastic state (PPPS). A functional patient-derived organoid xenograft (PDOX) model was developed to capture and maintain the PPPS in CRC. With a marker gene of MSLN (encoding mesothelin), this model was used to validate the role of the PPPS in promoting CRC metastasis. Moreover, precise manipulation of human cancer plasticity through the PPPS allows us to identify small-molecule inhibitors of non-canonical IKKs to promote malignancy, with clinical implications for targeting the PPPS to prevent CRC progression and metastasis.
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Project description:Patient-derived xenograft models are considered to represent the heterogeneity of human cancers and might be more relevant preclinical models to evaluate effective therapeutic agents. Our consortium joins efforts to extensively develop and characterize a new collection of patient-derived colorectal cancer models. From 86 unsupervised surgical colon sample collection, 54 tumors were successfully xenografted in immunodeficient mice and rats, representing 35 primary tumors, 5 peritoneal carcinosis and 14 metastases. Our histological and molecular characterization of patient tumors, first passage on mice and later passages includes the sequence of key genes involved in CRC (ie APC, KRAS, TP53), CGH array and transcriptomic analysis. This comprehensive characterization demonstrates that our collection recapitulates the clinical situation regarding the histopathological and molecular diversity of colorectal cancers. Moreover, patient tumors and corresponding models are clustering together which gives the opportunity to look for relevant signatures and comparison studies between clinical and preclinical data. Hence, we performed pharmacological monotherapy studies with standard of care for colon cancer (5-FU, oxaliplatin, irinotecan, cetuximab). Through this extensive in vivo analysis, we have compared the molecular profile with the drug sensitivity of each tumor models, and run an equivalent of a cetuximab phase II clinical trial in a preclinical setting. Our results confirm the key role of KRAS mutation in the cetuximab resistance and demonstrate that such collection could bring benefit to evaluate novel targeted therapeutic strategies and potentially help the stratification strategy for cancer patients according to molecular marker. This set correspond to 82 CGH profiles, with 7 samples from patient tumor and 75 samples from mouse xenograft at different passages P0 to P9. All hybridizations are performed with Human CGH 244K Agilent arrays (amadid 014693) in dual color with Human DNA Promega (sex matched) as reference. ID for biosources without an -Px suffix correspond to tumor patients. ID with a suffix correspond to xenograft with 0 for the first passage.
2012-07-27 | E-MTAB-991 | biostudies-arrayexpress
Project description:Patient-derived xenograft models are considered to represent the heterogeneity of human cancers and might be more relevant preclinical models to evaluate effective therapeutic agents. Our consortium joins efforts to extensively develop and characterize a new collection of patient-derived colorectal cancer models. From 86 unsupervised surgical colon sample collection, 54 tumors were successfully xenografted in immunodeficient mice and rats, representing 35 primary tumors, 5 peritoneal carcinosis and 14 metastases. Our histological and molecular characterization of patient tumors, first passage on mice and later passages includes the sequence of key genes involved in CRC (ie APC, KRAS, TP53), CGH array and transcriptomic analysis. This comprehensive characterization demonstrates that our collection recapitulates the clinical situation regarding the histopathological and molecular diversity of colorectal cancers. Moreover, patient tumors and corresponding models are clustering together which gives the opportunity to look for relevant signatures and comparison studies between clinical and preclinical data. Hence, we performed pharmacological monotherapy studies with standard of care for colon cancer (5-FU, oxaliplatin, irinotecan, cetuximab). Through this extensive in vivo analysis, we have compared the molecular profile with the drug sensitivity of each tumor models, and run an equivalent of a cetuximab phase II clinical trial in a preclinical setting. Our results confirm the key role of KRAS mutation in the cetuximab resistance and demonstrate that such collection could bring benefit to evaluate novel targeted therapeutic strategies and potentially help the stratification strategy for cancer patients according to molecular marker. This set correspond to 82 CGH profiles, with 7 samples from patient tumor and 75 samples from mouse xenograft at different passages P0 to P9. All hybridizations are performed with Human CGH 244K Agilent arrays (amadid 014693) in dual color with Human DNA Promega (sex matched) as reference. ID for biosources without an -Px suffix correspond to tumor patients. ID with a suffix correspond to xenograft with 0 for the first passage.
2012-07-27 | E-MTAB-992 | biostudies-arrayexpress
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Project description:Claret2009 - Predicting phase III overall survival in colorectal cancer
This model is described in the article:
Model-based prediction of
phase III overall survival in colorectal cancer on the basis of
phase II tumor dynamics.
Claret L, Girard P, Hoff PM, Van
Cutsem E, Zuideveld KP, Jorga K, Fagerberg J, Bruno R.
J. Clin. Oncol. 2009 Sep; 27(25):
4103-4108
Abstract:
PURPOSE: We developed a drug-disease simulation model to
predict antitumor response and overall survival in phase III
studies from longitudinal tumor size data in phase II trials.
METHODS: We developed a longitudinal exposure-response
tumor-growth inhibition (TGI) model of drug effect (and
resistance) using phase II data of capecitabine (n = 34) and
historical phase III data of fluorouracil (FU; n = 252) in
colorectal cancer (CRC); and we developed a parametric survival
model that related change in tumor size and patient
characteristics to survival time using historical phase III
data (n = 245). The models were validated in simulation of
antitumor response and survival in an independent phase III
study (n = 1,000 replicates) of capecitabine versus FU in CRC.
RESULTS: The TGI model provided a good fit of longitudinal
tumor size data. A lognormal distribution best described the
survival time, and baseline tumor size and change in tumor size
from baseline at week 7 were predictors (P < .00001).
Predicted change of tumor size and survival time distributions
in the phase III study for both capecitabine and FU were
consistent with observed values, for example, 431 days (90%
prediction interval, 362 to 514 days) versus 401 days observed
for survival in the capecitabine arm. A modest survival
improvement of 39 days (90% prediction interval, -21 to 110
days) versus 35 days observed was predicted for capecitabine.
CONCLUSION: The modeling framework successfully predicted
survival in a phase III trial on the basis of capecitabine
phase II data in CRC. It is a useful tool to support
end-of-phase II decisions and design of phase III studies.
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