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Microarrays and Renal Cell Cancer Biomarkers


Schraml, Peter; Beleut, Manfred (2015). Microarrays and Renal Cell Cancer Biomarkers. In: Preedy, Victor R; Patel, Vinood B. Biomarkers in Cancer. Dordrecht: Springer Science+Business Media, 273-301.

Abstract

The incidence of renal cell carcinoma (RCC) has steadily increased during the last decades. Although technological advances for early recognition of RCC exist, many tumors are accidentally detected, and clinical decision-making is still mainly based on morphological evaluation. Being a relatively chemotherapeutic-resistant and very heterogenic disease, the biological behavior of this tumor type is difficult to predict. Histologic subtyping, tumor staging, and grading are still the pathologic parameters with most valid prognostic and diagnostic significance. Novel high-throughput methodologies have been developed to depict the molecular constitution of individual tumors at the DNA, RNA, and protein levels in order to find relevant biomarkers for optimizing cancer patient care. In this chapter we recapitulate previous published efforts with different microarray platforms which were used to identify biomarkers in RCC. As a result, a large number of such markers, including pathways and gene signatures, have been described as promising biomarkers with significant prognostic and predictive value. However, at present and in contrast to other tumor types such as breast cancer, lung cancer, or melanoma, there is no RCC biomarker that can unrestrictedly be recommended for the use in routine diagnostics. In light of the increasing demand of targeted cancer therapies, vigorous biomedical studies will be needed to translate the molecular findings into clinical applications.

Abstract

The incidence of renal cell carcinoma (RCC) has steadily increased during the last decades. Although technological advances for early recognition of RCC exist, many tumors are accidentally detected, and clinical decision-making is still mainly based on morphological evaluation. Being a relatively chemotherapeutic-resistant and very heterogenic disease, the biological behavior of this tumor type is difficult to predict. Histologic subtyping, tumor staging, and grading are still the pathologic parameters with most valid prognostic and diagnostic significance. Novel high-throughput methodologies have been developed to depict the molecular constitution of individual tumors at the DNA, RNA, and protein levels in order to find relevant biomarkers for optimizing cancer patient care. In this chapter we recapitulate previous published efforts with different microarray platforms which were used to identify biomarkers in RCC. As a result, a large number of such markers, including pathways and gene signatures, have been described as promising biomarkers with significant prognostic and predictive value. However, at present and in contrast to other tumor types such as breast cancer, lung cancer, or melanoma, there is no RCC biomarker that can unrestrictedly be recommended for the use in routine diagnostics. In light of the increasing demand of targeted cancer therapies, vigorous biomedical studies will be needed to translate the molecular findings into clinical applications.

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Additional indexing

Item Type:Book Section, refereed, further contribution
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Surgical Pathology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2015
Deposited On:29 Oct 2015 10:43
Last Modified:05 Apr 2016 19:29
Publisher:Springer Science+Business Media
ISBN:978-94-007-7680-7
Publisher DOI:https://doi.org/10.1007/978-94-007-7681-4_9

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