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5th International ACC Symposium: Classification of Adrenocortical Cancers from Pathology to Integrated Genomics: Real Advances or Lost in Translation?

Overview of attention for article published in Discover Oncology, December 2015
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Title
5th International ACC Symposium: Classification of Adrenocortical Cancers from Pathology to Integrated Genomics: Real Advances or Lost in Translation?
Published in
Discover Oncology, December 2015
DOI 10.1007/s12672-015-0242-1
Pubmed ID
Authors

Ronald E. de Krijger, Jérôme Bertherat

Abstract

For the clinician, despite its rarity, adrenocortical cancer is a heterogeneous tumor both in term of steroid excess and tumor evolution. For patient management, it is crucial to have an accurate vision of this heterogeneity, in order to use a correct tumor classification. Pathology is the best way to classify operated adrenocortical tumors: to recognize their adrenocortical nature and to differentiate benign from malignant tumors. Among malignant tumors pathology also aims at prognosis assessment. Although progress has being made for prognosis assessment, there is still a need for improvement. Recent studies have established the value of Ki67 for adrenocortical cancer (ACC) prognostication, aiming also at standardization to reduce variability. The use of genomics to study adrenocortical tumors gives a very new insight in their pathogenesis and molecular classification. Genomics studies of ACC give now a clear description of the mRNA (transcriptome) and miRNA expression profile, as well as chromosomal and methylation alterations. Exome sequencing also established firmly the list of the main ACC driver genes. Interestingly, genomics study of ACC also revealed subtypes of malignant tumors with different pattern of molecular alterations, associated with different outcome. This leads to a new vision of adrenocortical tumors classification based on molecular analysis. Interestingly, these molecular classifications meet also the results of pathological analysis. This opens new perspectives on the development and use of various molecular tools to classify, along with pathological analysis, ACC, and guides patient management at the area of precision medicine.

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Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 33%
Student > Master 3 20%
Other 2 13%
Student > Doctoral Student 1 7%
Researcher 1 7%
Other 1 7%
Unknown 2 13%
Readers by discipline Count As %
Medicine and Dentistry 8 53%
Agricultural and Biological Sciences 2 13%
Computer Science 1 7%
Unknown 4 27%