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Immune cell infiltration pattern in non-small cell lung cancer PDX models is a model immanent feature and correlates with a distinct molecular and phenotypic make-up.
Oswald, Eva; Bug, Daniel; Grote, Anne; Lashuk, Kanstantsin; Bouteldja, Nassim; Lenhard, Dorothee; Löhr, Anne; Behnke, Anke; Knauff, Volker; Edinger, Anna; Klingner, Kerstin; Gaedicke, Simone; Niedermann, Gabriele; Merhof, Dorit; Feuerhake, Friedrich; Schueler, Julia.
Afiliación
  • Oswald E; Charles River Discovery Research Services Gemany GmbH, Charles River Laboratories Inc, Freiburg, Germany.
  • Bug D; Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany.
  • Grote A; Department of Pathology, Hannover Medical School, Hannover, Germany.
  • Lashuk K; Charles River Discovery Research Services Gemany GmbH, Charles River Laboratories Inc, Freiburg, Germany.
  • Bouteldja N; Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany.
  • Lenhard D; Charles River Discovery Research Services Gemany GmbH, Charles River Laboratories Inc, Freiburg, Germany.
  • Löhr A; Charles River Discovery Research Services Gemany GmbH, Charles River Laboratories Inc, Freiburg, Germany.
  • Behnke A; Charles River Discovery Research Services Gemany GmbH, Charles River Laboratories Inc, Freiburg, Germany.
  • Knauff V; Charles River Discovery Research Services Gemany GmbH, Charles River Laboratories Inc, Freiburg, Germany.
  • Edinger A; Charles River Discovery Research Services Gemany GmbH, Charles River Laboratories Inc, Freiburg, Germany.
  • Klingner K; Charles River Discovery Research Services Gemany GmbH, Charles River Laboratories Inc, Freiburg, Germany.
  • Gaedicke S; Department of Radiation Oncology, Medical Center-University of Freiburg, Freiburg, Germany.
  • Niedermann G; Department of Radiation Oncology, Medical Center-University of Freiburg, Freiburg, Germany.
  • Merhof D; German Cancer Consortium, Heidelberg, Germany.
  • Feuerhake F; Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany.
  • Schueler J; Department of Pathology, Hannover Medical School, Hannover, Germany.
J Immunother Cancer ; 10(4)2022 04.
Article en En | MEDLINE | ID: mdl-35483746
ABSTRACT

BACKGROUND:

The field of cancer immunology is rapidly moving towards innovative therapeutic strategies, resulting in the need for robust and predictive preclinical platforms reflecting the immunological response to cancer. Well characterized preclinical models are essential for the development of predictive biomarkers in the oncology as well as the immune-oncology space. In the current study, gold standard preclinical models are being refined and combined with novel image analysis tools to meet those requirements.

METHODS:

A panel of 14 non-small cell lung cancer patient-derived xenograft models (NSCLC PDX) was propagated in humanized NOD/Shi-scid/IL-2Rnull mice. The models were comprehensively characterized for relevant phenotypic and molecular features, including flow cytometry, immunohistochemistry, histology, whole exome sequencing and cytokine secretion.

RESULTS:

Models reflecting hot (>5% tumor-infiltrating lymphocytes/TILs) as opposed to cold tumors (<5% TILs) significantly differed regarding their cytokine profiles, molecular genetic aberrations, stroma content, and programmed cell death ligand-1 status. Treatment experiments including anti cytotoxic T-lymphocyte-associated protein 4, anti-programmed cell death 1 or the combination thereof across all 14 models in the single mouse trial format showed distinctive tumor growth response and spatial immune cell patterns as monitored by computerized analysis of digitized whole-slide images. Image analysis provided for the first time qualitative evaluation of the extent to which PDX models retain the histological features from their original human donors.

CONCLUSIONS:

Deep phenotyping of PDX models in a humanized setting by combinations of computational pathology, immunohistochemistry, flow cytometry and proteomics enables the exhaustive analysis of innovative preclinical models and paves the way towards the development of translational biomarkers for immuno-oncology drugs.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Carcinoma de Pulmón de Células no Pequeñas / Neoplasias Pulmonares Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: J Immunother Cancer Año: 2022 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Carcinoma de Pulmón de Células no Pequeñas / Neoplasias Pulmonares Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: J Immunother Cancer Año: 2022 Tipo del documento: Article