Epigenetic profiling to classify cancer of unknown primary: a multicentre, retrospective analysis

Author

Moran, Sebastian

Martínez Cardús, Anna

Sayols, Sergi

Musulén, Eva

Balañá, Carme

Estival Gonzalez, Anna

Moutinho, Cátia

Heyn, Holger

Diaz-Lagares, Ángel

Castro de Moura, Manuel

Stella, Giulia M.

Comoglio, Paolo M.

Ruiz Miró, Maria

Pazo Cid, Roberto

Antón, Antonio

Lopez Lopez, Rafael

Soler, Gemma

Longo, Federico

Guerra, Isabel

Fernandez, Sara

Assenov, Yassen

Plass, Christoph

Morales, Rafael

Carles, Joan

Bowtell, David

Mileshkin, Linda

Sia, Daniela

Tothill, Richard

Tabernero, Josep

Llovet, Josep M.

Esteller, Manel

Matias-Guiu, Xavier

Publication date

2016-12-05T10:27:56Z

2025-01-01

2016

Abstract

Cancer of unknown primary ranks in the top ten cancer presentations and has an extremely poor prognosis. Identification of the primary tumour and development of a tailored site-specific therapy could improve the survival of these patients. We examined the feasability of using DNA methylation profiles to determine the occult original cancer in cases of cancer of unknown primary.


The research leading to these results has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme by the ERC Proof-of-Concept Grant EPICUP, under grant agreement No 640696 (to ME); the Cellex Foundation (to ME); the Institute of Health Carlos III (ISCIII) under the Integrated Project of Excellence number PIE13/00022 (ONCOPROFILE); Cancer Research Australia APP1048193 and AP1082604 and Victorian Cancer Agency TRP13062 (to DB, LM, and RT); the Samuel Waxman Foundation (to JML); the Health and Science Deapartments of the Generalitat de Catalunya (to JML and ME); and Ferrer (to ME).

Document Type

article
publishedVersion

Language

English

Publisher

Elsevier

Related items

Reproducció del document publicat a https://doi.org/10.1016/S1470-2045(16)30297-2

The Lancet Oncology, 2016, vol. 17, núm. 10, p. 1286-1395

info:eu-repo/grantAgreement/EC/H2020/640696

Rights

(c) Elsevier Ltd, 2016

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