Limits...
Translation of anticancer efficacy from nonclinical models to the clinic.

Stroh M, Duda DG, Takimoto CH, Yamazaki S, Vicini P - CPT Pharmacometrics Syst Pharmacol (2014)

Bottom Line: Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging.This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points.A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm.

View Article: PubMed Central - PubMed

Affiliation: Clinical Pharmacology, Genentech, South San Francisco, California, USA.

ABSTRACT
Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging. This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points. A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm.

No MeSH data available.


Related in: MedlinePlus

The tumor microenvironment. The tumor microenvironment is comprised of blood and lymphatic vessels, nonmalignant host cells, and extracellular matrix, all of which shape tumor progression and response or resistance to therapy. Courtesy of Lance L. Munn, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4150926&req=5

fig1: The tumor microenvironment. The tumor microenvironment is comprised of blood and lymphatic vessels, nonmalignant host cells, and extracellular matrix, all of which shape tumor progression and response or resistance to therapy. Courtesy of Lance L. Munn, Massachusetts General Hospital and Harvard Medical School, Boston, MA.

Mentions: Our understanding of the factors that influence extrapolation of mouse findings to the clinic is evolving and suggests a high degree of complexity. Though cancer is characterized by uncontrolled cell proliferation caused by oncogenic driver mutations, the tumor microenvironment—comprised of blood and lymphatic vessels, nonmalignant host cells, and extracellular matrix—is critical to cancer progression and treatment (Figure 1). Indeed, 10 drugs targeting the tumor vasculature are currently approved by the US Food and Drug Administration.2 Others targeting the immunosuppressive or desmoplastic tumor microenvironment are in clinical development. Accordingly, our ability to reasonably approximate the human disease in mice should not be determined solely by selection of a relevant cancer cell line or model, but also by local interactions with the stroma and parenchyma, as well as systemic interactions with the host. Our current understanding of “cancer as an organ system” suggests that such interactions are influential, at both individual tumor compartment (i.e., tumor vessels, perivascular cells, extracellular matrix, etc.) and molecular levels. For example, at the compartmental level, intravital imaging provided direct evidence that tumor vessel morphology is vastly different following transplantation of the same cancer cell line at multiple sites in mice.2 These morphological changes in vessel characteristics bring important consequences for drug delivery to the tumor. Accordingly, extrapolation of preclinical tumor drug delivery findings to the clinic may be especially sensitive to this kind of cancer cell–stromal cell interaction. In addition, we see evidence of cancer cell–stromal cell interactions at the molecular level. A first example comes from medulloblastoma, the most frequent pediatric brain malignancy. A recent study suggests that medulloblastoma growth depends upon PlGF secretion from the cerebellar stroma irrespective of its genetic subtype and that PlGF expression is mediated by tumor-derived Sonic hedgehog.3 As with the previous example at compartmental level, this molecular level cancer cell–stromal cell interaction finding has potentially important ramifications for clinical translation; selection of a relevant preclinical model was essential in revealing this tissue-specific interaction. Similarly, at molecular level, a growing body of evidence implicates activation of the chemokine CXCL12 (stromal cell-derived factor-1α) pathway in tumor resistance to various treatments.4 The resistance mechanism involves direct promotion of cancer cell survival and invasion, as well as indirect effects on tumor recurrence and metastasis via the stroma. Accordingly, the clinical translation of anti-CXCL12 agents for use as sensitizers to existing cancer therapies should rely upon the development and use of preclinical models capable of capturing the response to these same therapies in patients.


Translation of anticancer efficacy from nonclinical models to the clinic.

Stroh M, Duda DG, Takimoto CH, Yamazaki S, Vicini P - CPT Pharmacometrics Syst Pharmacol (2014)

The tumor microenvironment. The tumor microenvironment is comprised of blood and lymphatic vessels, nonmalignant host cells, and extracellular matrix, all of which shape tumor progression and response or resistance to therapy. Courtesy of Lance L. Munn, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4150926&req=5

fig1: The tumor microenvironment. The tumor microenvironment is comprised of blood and lymphatic vessels, nonmalignant host cells, and extracellular matrix, all of which shape tumor progression and response or resistance to therapy. Courtesy of Lance L. Munn, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
Mentions: Our understanding of the factors that influence extrapolation of mouse findings to the clinic is evolving and suggests a high degree of complexity. Though cancer is characterized by uncontrolled cell proliferation caused by oncogenic driver mutations, the tumor microenvironment—comprised of blood and lymphatic vessels, nonmalignant host cells, and extracellular matrix—is critical to cancer progression and treatment (Figure 1). Indeed, 10 drugs targeting the tumor vasculature are currently approved by the US Food and Drug Administration.2 Others targeting the immunosuppressive or desmoplastic tumor microenvironment are in clinical development. Accordingly, our ability to reasonably approximate the human disease in mice should not be determined solely by selection of a relevant cancer cell line or model, but also by local interactions with the stroma and parenchyma, as well as systemic interactions with the host. Our current understanding of “cancer as an organ system” suggests that such interactions are influential, at both individual tumor compartment (i.e., tumor vessels, perivascular cells, extracellular matrix, etc.) and molecular levels. For example, at the compartmental level, intravital imaging provided direct evidence that tumor vessel morphology is vastly different following transplantation of the same cancer cell line at multiple sites in mice.2 These morphological changes in vessel characteristics bring important consequences for drug delivery to the tumor. Accordingly, extrapolation of preclinical tumor drug delivery findings to the clinic may be especially sensitive to this kind of cancer cell–stromal cell interaction. In addition, we see evidence of cancer cell–stromal cell interactions at the molecular level. A first example comes from medulloblastoma, the most frequent pediatric brain malignancy. A recent study suggests that medulloblastoma growth depends upon PlGF secretion from the cerebellar stroma irrespective of its genetic subtype and that PlGF expression is mediated by tumor-derived Sonic hedgehog.3 As with the previous example at compartmental level, this molecular level cancer cell–stromal cell interaction finding has potentially important ramifications for clinical translation; selection of a relevant preclinical model was essential in revealing this tissue-specific interaction. Similarly, at molecular level, a growing body of evidence implicates activation of the chemokine CXCL12 (stromal cell-derived factor-1α) pathway in tumor resistance to various treatments.4 The resistance mechanism involves direct promotion of cancer cell survival and invasion, as well as indirect effects on tumor recurrence and metastasis via the stroma. Accordingly, the clinical translation of anti-CXCL12 agents for use as sensitizers to existing cancer therapies should rely upon the development and use of preclinical models capable of capturing the response to these same therapies in patients.

Bottom Line: Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging.This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points.A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm.

View Article: PubMed Central - PubMed

Affiliation: Clinical Pharmacology, Genentech, South San Francisco, California, USA.

ABSTRACT
Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging. This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points. A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm.

No MeSH data available.


Related in: MedlinePlus