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Patient-derived breast tumor xenografts facilitating personalized cancer therapy.

Landis MD, Lehmann BD, Pietenpol JA, Chang JC - Breast Cancer Res. (2013)

Bottom Line: Continued efforts in classification of breast cancers based on gene expression profiling and genomic sequencing have revealed an underlying complexity and molecular heterogeneity within the disease that continues to challenge therapeutic interventions.To successfully identify and translate new treatment regimens to the clinic, it is imperative that our preclinical models recapitulate this complexity and heterogeneity.In this review article, we discuss the recent advances in development and classification of patient-derived human breast tumor xenograft models that have the potential to facilitate the next phase of drug discovery for personalized cancer therapy based on the unique driver signaling pathways in breast tumor subtypes.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Despite improved detection and reduction of breast cancer-related deaths over the recent decade, breast cancer remains the second leading cause of cancer death for women in the US, with 39,510 women expected to succumb to metastatic disease in 2012 alone (American Cancer Society, Cancer Facts &Figures 2012. Atlanta: American Cancer Society; 2012). Continued efforts in classification of breast cancers based on gene expression profiling and genomic sequencing have revealed an underlying complexity and molecular heterogeneity within the disease that continues to challenge therapeutic interventions. To successfully identify and translate new treatment regimens to the clinic, it is imperative that our preclinical models recapitulate this complexity and heterogeneity. In this review article, we discuss the recent advances in development and classification of patient-derived human breast tumor xenograft models that have the potential to facilitate the next phase of drug discovery for personalized cancer therapy based on the unique driver signaling pathways in breast tumor subtypes.

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Schematic of preclinical clinical trials: from classification to patient selection for clinical trials. Based on the advances in generating patient-derived xenografts and breast cancer subtyping, preclinical trials can be designed to provide subtype-specific outcome data and to identify molecular profiles of tumors that respond to specific therapies, thus having the potential to better guide patient selection for clinical trials and to reduce costs and ineffective treatment options for patients. Patient-derived xenografts are subtyped by standard immunohistochemistry (IHC) and by molecular profiling and then placed on each arm of a preclinical clinical trial for direct comparison of treatment strategies. The treatment response is then correlated with subtype classification to identify the responsive versus non-responsive tumor subtypes that correspond to patient tumor subtypes to guide selection for clinical trials.
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Figure 1: Schematic of preclinical clinical trials: from classification to patient selection for clinical trials. Based on the advances in generating patient-derived xenografts and breast cancer subtyping, preclinical trials can be designed to provide subtype-specific outcome data and to identify molecular profiles of tumors that respond to specific therapies, thus having the potential to better guide patient selection for clinical trials and to reduce costs and ineffective treatment options for patients. Patient-derived xenografts are subtyped by standard immunohistochemistry (IHC) and by molecular profiling and then placed on each arm of a preclinical clinical trial for direct comparison of treatment strategies. The treatment response is then correlated with subtype classification to identify the responsive versus non-responsive tumor subtypes that correspond to patient tumor subtypes to guide selection for clinical trials.

Mentions: Personalized medicine is intended to select subsets of patients that will most likely respond to treatment regimens, thus reducing morbidity and mortality from ineffective treatments. To identify targeted therapies and effective treatment regimens based on subtype classification, representative breast tumor PDXs can be assigned to each arm of a preclinical clinical trial (Figure 1). Integration of in vivo models of PDXs, TP53 genetically engineered mouse tumor models, and representative cell line-derived xenograft tumors will allow representation of the full range of subtypes and tumor heterogeneity. Alternatively, preclinical clinical trials may focus on TNBC using the Pietenpol TNBC subtypes to identify the subtypes responsive to different treatment regimens. Based on the complexity of signaling pathways driving tumorigenesis and/or metastasis, cocktails of inhibitors will ultimately be required to prevent recurrence and treatment resistance. In the near future, the knowledge gained by the ongoing efforts of genomic classification from complete genome sequencing of patient tumors and PDX is expected to drive the next generation of preclinical clinical trials aimed at personalizing cancer therapy.


Patient-derived breast tumor xenografts facilitating personalized cancer therapy.

Landis MD, Lehmann BD, Pietenpol JA, Chang JC - Breast Cancer Res. (2013)

Schematic of preclinical clinical trials: from classification to patient selection for clinical trials. Based on the advances in generating patient-derived xenografts and breast cancer subtyping, preclinical trials can be designed to provide subtype-specific outcome data and to identify molecular profiles of tumors that respond to specific therapies, thus having the potential to better guide patient selection for clinical trials and to reduce costs and ineffective treatment options for patients. Patient-derived xenografts are subtyped by standard immunohistochemistry (IHC) and by molecular profiling and then placed on each arm of a preclinical clinical trial for direct comparison of treatment strategies. The treatment response is then correlated with subtype classification to identify the responsive versus non-responsive tumor subtypes that correspond to patient tumor subtypes to guide selection for clinical trials.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3672825&req=5

Figure 1: Schematic of preclinical clinical trials: from classification to patient selection for clinical trials. Based on the advances in generating patient-derived xenografts and breast cancer subtyping, preclinical trials can be designed to provide subtype-specific outcome data and to identify molecular profiles of tumors that respond to specific therapies, thus having the potential to better guide patient selection for clinical trials and to reduce costs and ineffective treatment options for patients. Patient-derived xenografts are subtyped by standard immunohistochemistry (IHC) and by molecular profiling and then placed on each arm of a preclinical clinical trial for direct comparison of treatment strategies. The treatment response is then correlated with subtype classification to identify the responsive versus non-responsive tumor subtypes that correspond to patient tumor subtypes to guide selection for clinical trials.
Mentions: Personalized medicine is intended to select subsets of patients that will most likely respond to treatment regimens, thus reducing morbidity and mortality from ineffective treatments. To identify targeted therapies and effective treatment regimens based on subtype classification, representative breast tumor PDXs can be assigned to each arm of a preclinical clinical trial (Figure 1). Integration of in vivo models of PDXs, TP53 genetically engineered mouse tumor models, and representative cell line-derived xenograft tumors will allow representation of the full range of subtypes and tumor heterogeneity. Alternatively, preclinical clinical trials may focus on TNBC using the Pietenpol TNBC subtypes to identify the subtypes responsive to different treatment regimens. Based on the complexity of signaling pathways driving tumorigenesis and/or metastasis, cocktails of inhibitors will ultimately be required to prevent recurrence and treatment resistance. In the near future, the knowledge gained by the ongoing efforts of genomic classification from complete genome sequencing of patient tumors and PDX is expected to drive the next generation of preclinical clinical trials aimed at personalizing cancer therapy.

Bottom Line: Continued efforts in classification of breast cancers based on gene expression profiling and genomic sequencing have revealed an underlying complexity and molecular heterogeneity within the disease that continues to challenge therapeutic interventions.To successfully identify and translate new treatment regimens to the clinic, it is imperative that our preclinical models recapitulate this complexity and heterogeneity.In this review article, we discuss the recent advances in development and classification of patient-derived human breast tumor xenograft models that have the potential to facilitate the next phase of drug discovery for personalized cancer therapy based on the unique driver signaling pathways in breast tumor subtypes.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Despite improved detection and reduction of breast cancer-related deaths over the recent decade, breast cancer remains the second leading cause of cancer death for women in the US, with 39,510 women expected to succumb to metastatic disease in 2012 alone (American Cancer Society, Cancer Facts &Figures 2012. Atlanta: American Cancer Society; 2012). Continued efforts in classification of breast cancers based on gene expression profiling and genomic sequencing have revealed an underlying complexity and molecular heterogeneity within the disease that continues to challenge therapeutic interventions. To successfully identify and translate new treatment regimens to the clinic, it is imperative that our preclinical models recapitulate this complexity and heterogeneity. In this review article, we discuss the recent advances in development and classification of patient-derived human breast tumor xenograft models that have the potential to facilitate the next phase of drug discovery for personalized cancer therapy based on the unique driver signaling pathways in breast tumor subtypes.

Show MeSH
Related in: MedlinePlus