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Genomweite Expressionsprofile als klinische Entscheidungshilfe

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Genome-wide expression profiling as a clinical tool

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  • Schwerpunkt: Mammapathologie
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Zusammenfassung

Das Mammakarzinom ist eine heterogene Erkrankung mit einer Fülle von histologischen Typen und stark variierendem klinischen Verlauf. Die histopathologischen Klassifikationssysteme basieren auf deskriptiven Entitäten und besitzen prognostische Signifikanz. Es gibt nur wenige Prognosefaktoren, die nicht auf der histologischen Untersuchung basieren. Bislang ist nur eine sehr kleine Zahl prädiktiver Biomarker in die klinische Praxis eingeführt. Unter den modernen molekularen Techniken erlangte die Genexpressionsanalyse auf Microarray-Basis die größte Aufmerksamkeit. Diese Methode wurde mit Erfolg benutzt, um eine neue molekulare Taxonomie für das Mammakarzinom aufzustellen, die interessante Einsichten in die Biologie dieser Erkrankung erlaubt. Durch Microarray-basierte Studien sind zahlreiche prognostische bzw. prädiktive Signaturen erarbeitet worden, die eine Verbesserung bei der Entscheidungsfindung zur Brustkrebstherapie versprechen. Die diskriminierende Power der meisten bisher entwickelten Signaturen scheint auf Östrogenrezeptor-positive Karzinome beschränkt. Diese Übersicht versucht zu klären, welchen Beitrag Genexpressionsprofile derzeit zu unserem Verständnis des Mammakarzinoms und zum klinischen Management leistet. Darüber hinaus soll aufgezeigt werden, was zu tun bleibt, um verschiedene prädiktive Klassifikationsmöglichkeiten in die klinische Praxis zu überführen.

Abstract

Breast cancer is a heterogeneous disease, encompassing a plethora of histological types and clinical courses. Current histopathological classification systems for breast cancer are based on descriptive entities that are of prognostic significance. Few prognostic markers beyond those offered by histopathological analysis are available. Furthermore, a very limited armamentarium of predictive biomarkers has been introduced in clinical practice. High throughput molecular technologies are reshaping our understanding of breast cancer, of which microarray-based gene expression has received the most attention. This method has been successfully used to derive a molecular taxonomy for breast cancer, which has provided interesting insights into the biology of the disease. Microarray-based class prediction studies have generated a multitude of prognostic/predictive signatures. Although these signatures have not been fully translated to clinical practice as yet, they herald the promise of an improvement in breast cancer treatment decision-making. It should be noted, however, that most of the signatures developed to date seem to have discriminatory power almost restricted to oestrogen receptor-positive disease. This review addresses the contribution of gene expression profiling to our understanding of breast cancer and its clinical management and what has yet to be done for these classifiers to be incorporated in clinical practice.

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Danksagung

Wir danken Britta Weigelt für das kritische Lesen des Manuskripts. Jorge S. Reis-Filho und Felipe C. Geyer wurden vom Breakthrough Breast Cancer Research Centre unterstützt.

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Authors and Affiliations

  1. Molecular Pathology Laboratory, The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK

    F.C. Geyer & J.S. Reis-Filho MD PhD FRCPath

  2. Gerhard Domagk Institut für Pathologie, Universitätsklinikum Münster, Münster, Deutschland

    T. Decker

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  1. F.C. Geyer
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Correspondence to J.S. Reis-Filho MD PhD FRCPath.

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Geyer, F., Decker, T. & Reis-Filho, J. Genomweite Expressionsprofile als klinische Entscheidungshilfe. Pathologe 30, 141–146 (2009). https://doi.org/10.1007/s00292-008-1104-1

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