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Enregistrement W2040905618 · doi:10.1158/1538-7445.tim2013-ia29

Abstract IA29: Models of postsurgical early and late stage metastasis for improving preclinical adjuvant and metastatic therapy investigations

2013· article· en· W2040905618 sur OpenAlexaff
Robert S. Kerbel

Notice bibliographique

RevueCancer Research · 2013
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueCancer Research and Treatments
Établissements canadiensSunnybrook Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineCancerPrimary tumorMetastatic breast cancerMetastasisMelanomaOncologyIn vivoBreast cancerDiseaseClinical trialAdjuvant therapyPathologyInternal medicineCancer research

Résumé

récupéré en direct d'OpenAlex

Abstract A long standing problem in anti-cancer drug development has been the limited value of preclinical mouse tumor models to reliably predict subsequent clinical activity. All too often highly encouraging preclinical results in mice are followed by complete failure in clinical trials, especially at the randomized phase III level. There are many possible reasons that have been postulated for this preclinical/clinical discrepancy. One which we have been studying for the past decade is the failure to use mouse models which duplicate the challenging circumstance of treating advanced (established) visceral metastatic disease after primary tumors have been surgically resected. Instead, preclinical treatment of established primary tumors or low volume (micro)metastatic disease, often confined to the lungs, have been the historical preclinical model norms. To address this problem we have developed several models of postsurgical advanced metastatic disease involving human tumor xenografts grown in SCID mice, including breast, colorectal or kidney cancer, and melanoma (1). This approach has been extended more recently for postsurgical adjuvant therapy of early stage microscopic metastatic disease (2,3). The established cell lines used for in vivo studies are variants previously selected in vivo for more aggressive spontaneous metastatic capability, which then are sometimes stably tagged with luciferase to permit whole body bioluminescent imaging. Using these models to evaluate the impact of several anti-cancer treatments, consisting mostly of antiangiogenic drugs and/or chemotherapy, either standard maximum tolerated dose or low-dose ‘metronomic’, has highlighted the critical contribution of the extent of metastatic disease to differential therapeutic outcomes, and the prospect of better correlation with clinical outcomes. For example, primary orthotopic tumors, e.g. breast cancer in the mammary fat pad, respond well to treatment with an antiangiogenic drug such as sunitinib, pazopanib or anti-VEGFR-2 antibodies whereas mice with advanced metastases in sites such as the liver or lungs do not, e.g. no prolongation of survival is observed (4). Adding chemotherapy, e.g. paclitaxel to sunitinib did not change the results, whereas adding DC101, an anti-VEGFR-2 antibody, to the same chemotherapy regimen did result in a modest survival improvement (thus mimicking the metastatic breast cancer E2100 phase III results of bevacizumab plus paclitaxel chemotherapy) (4). The observed lack of sunitinib efficacy alone or with chemotherapy when treating mice with advanced metastases mimics three failed phase III clinical trial results of this drug with or without chemotherapy in metastatic breast cancer patients (5). In addition, we have noted that successful treatment of mice with advanced systemic metastatic breast, melanoma or renal cell cancer, e.g. with low-dose metronomic chemotherapy plus an antiangiogenic drug such that overall survival is meaningfully prolonged, sometimes results in the emergence of overt spontaneous brain metastases(1,6,7). Thus, in mice, the brain appears to be a protective sanctuary for the survival and progressive growth of microscopic into macroscopic metastases, as already well known in the clinic. More recent studies have indicated how the brain microenvironment can contribute to the development of melanoma metastases in this organ environment e.g. the interaction of endothelins (ETs) with (elevated) endothelin receptor B expression by the brain melanoma metastatic variants (8). In summary, models of postsurgical advanced metastatic disease to undertake experimental therapeutic studies appear to have a greater degree of clinical relevance compared to most conventional primary tumor therapy models. We are now extending this approach to the development of postsurgical models of early stage microscopic metastatic disease to mimic adjuvant therapy in the clinic (2,9,10); some of our previous (2009) results indicated that adjuvant antiangiogenic therapy may actually worsen eventual survival outcomes of mice with early stage disease (2), a finding for which there is now some preliminary clinical support based on a recent phase III clinical trial assessing treatment of postsurgical early stage colorectal cancer patients with bevacizumab plus chemotherapy (11,12). References: 1. Francia G, Cruz-Munoz W, Man S, Xu P, Kerbel RS. Perspective: Mouse models of advanced spontaneous metastasis for experimental therapeutics. Nature Reviews Cancer 2011; 11:135-41. 2. Ebos JML, Lee CR, Cruz-Munoz W, Bjarnason GA, Christensen JG, Kerbel RS. Accelerated metastasis after short-term treatment with a potent inhibitor of tumor angiogenesis. Cancer Cell 2009; 15:232-9. 3. Ebos JML and Kerbel RS. Impact of antiangiogenic therapy on invasion, disease progression, and metastasis. Nat Rev Clin Oncol 2011; 8:210-21. 4. Guerin E, Man S, Xu P, Kerbel RS. Preclinical recapitulation of antiangiogenic drug clinical efficacy in breast cancer using mice with postsurgical advanced metastatic disease. Submitted for publication. 5. Kerbel RS. Strategies for improving the clinical benefit of antiangiogenic drug based therapies for breast cancer. J Mammary Gland Biol Neoplasia 2012; in press. 6. Francia G, Man S, Lee C-J, et al. Comparative impact of trastuzumab and cyclophosphamide on HER-2 positive human breast cancer xenografts. Clin Cancer Res 2009; 15:6358-66. 7. Cruz-Munoz W, Man S, Xu P, Kerbel RS. Development of a preclinical model of spontaneous human melanoma CNS metastasis. Cancer Res 2008; 68:4500-5. 8. Cruz-Munoz W, Jaramillo ML, Man S, et al. Roles for Endothelin Receptor B and BCL2A1 in Spontaneous CNS Metastasis of Melanoma. Cancer Res 2012; 72:4909-19. 9. Hackl C, Man S, Francia G, Xu P, Kerbel RS. Metronomic oral topotecan prolongs survival and reduces liver metastasis in improved preclinical orthotopic and adjuvant therapy colon cancer models. Gut 2012; epub ahead of print. 10. Wang D, Margalit O, DuBois RN. Metronomic topotecan for colorectal cancer: a promising new option. Gut 2012; epub ahead of print. 11. de GA, Van CE, Schmoll HJ, et al. Bevacizumab plus oxaliplatin-based chemotherapy as adjuvant treatment for colon cancer (AVANT): a phase 3 randomised controlled trial. Lancet Oncol 2012; 13:1225-33. 12. Seymour MT. Adjuvant bevacizumab in colon cancer: where did we go wrong? Lancet Oncol 2012; 13:1176-7. Citation Format: Robert S. Kerbel. Models of postsurgical early and late stage metastasis for improving preclinical adjuvant and metastatic therapy investigations. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Invasion and Metastasis; Jan 20-23, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;73(3 Suppl):Abstract nr IA29.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,021

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0020,001
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0060,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,166
Tête enseignante GPT0,442
Écart entre enseignants0,276 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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