Format

Send to

Choose Destination
Lancet Oncol. 2016 Oct;17(10):1386-1395. doi: 10.1016/S1470-2045(16)30297-2. Epub 2016 Aug 27.

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

Author information

1
Cancer Epigenetics and Biology Program (PEBC), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet, Barcelona, Catalonia, Spain.
2
Department of Pathology, Hospital Universitari Germans Trias i Pujol, C/ Ctra de Canyet s/n, Badalona, Barcelona, Catalonia, Spain.
3
Medical Oncology, Catalan Institute of Oncology (ICO), University Hospital Germans Trias i Pujol, Badalona, Barcelona, Catalonia, Spain.
4
Cardiothoracic and Vascular Department, Pneumology Unit, IRCCS Policlinico San Matteo Foundation, Pavia, Italy.
5
Institute for Cancer Research at Candiolo, Candiolo, Italy.
6
IRBLleida Biobank, Lleida, Catalonia, Spain.
7
Department of Pathology and Molecular Genetics/Oncologic Pathology Group, Hospital Universitari Arnau de Vilanova, Universitat de Lleida, IRBLleida, Lleida, Catalonia, Spain.
8
Medical Oncology Service, Hospital Miguel Servet, Zaragoza, Spain.
9
Medical Oncology Service, Complejo Hospitalario Universitario de Santiago, Santiago de Compostela, Spain.
10
Medical Oncology, Catalan Institute of Oncology (ICO), Hospital Duran i Reynals, L'Hospitalet de Llobregat, Barcelona, Catalonia, Spain.
11
Medical Oncology Service, Hospital Universitario Ramon y Cajal, Madrid, Spain.
12
Biobanco Vasco, Hospital Universitario de Araba, Vitoria, Spain.
13
Biobanco Vasco, Hospital Universitario de Basurto, Bilbao, Spain.
14
Division of Epigenomics and Cancer Risk Factors at the German Cancer Research Center (DKFZ), Heidelberg, Germany.
15
Oncology Department, Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona (UAB), Barcelona, Catalonia, Spain; Oncology Department, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Catalonia, Spain.
16
The Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; The Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia; The Department of Pathology, University of Melbourne, Parkville, VIC, Australia.
17
Liver Cancer Program, Division of Liver Diseases, Tisch Cancer Institute, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
18
The Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; The Department of Pathology, University of Melbourne, Parkville, VIC, Australia.
19
Liver Cancer Translational Research Laboratory, Barcelona Clinic Liver Cancer (BCLC) Group, Liver Unit, IDIBAPS, Hospital Clínic, CIBERehd, Barcelona, Catalonia, Spain; School of Medicine, University of Barcelona, Barcelona, Catalonia, Spain; Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain; Liver Cancer Program, Division of Liver Diseases, Tisch Cancer Institute, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
20
Cancer Epigenetics and Biology Program (PEBC), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet, Barcelona, Catalonia, Spain; School of Medicine, University of Barcelona, Barcelona, Catalonia, Spain; Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain. Electronic address: mesteller@idibell.cat.

Abstract

BACKGROUND:

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.

METHODS:

We established a classifier of cancer type based on the microarray DNA methylation signatures (EPICUP) in a training set of 2790 tumour samples of known origin representing 38 tumour types and including 85 metastases. To validate the classifier, we used an independent set of 7691 known tumour samples from the same tumour types that included 534 metastases. We applied the developed diagnostic test to predict the tumour type of 216 well-characterised cases of cancer of unknown primary. We validated the accuracy of the predictions from the EPICUP assay using autopsy examination, follow-up for subsequent clinical detection of the primary sites months after the initial presentation, light microscopy, and comprehensive immunohistochemistry profiling.

FINDINGS:

The tumour type classifier based on the DNA methylation profiles showed a 99·6% specificity (95% CI 99·5-99·7), 97·7% sensitivity (96·1-99·2), 88·6% positive predictive value (85·8-91·3), and 99·9% negative predictive value (99·9-100·0) in the validation set of 7691 tumours. DNA methylation profiling predicted a primary cancer of origin in 188 (87%) of 216 patients with cancer with unknown primary. Patients with EPICUP diagnoses who received a tumour type-specific therapy showed improved overall survival compared with that in patients who received empiric therapy (hazard ratio [HR] 3·24, p=0·0051 [95% CI 1·42-7·38]; log-rank p=0·0029).

INTERPRETATION:

We show that the development of a DNA methylation based assay can significantly improve diagnoses of cancer of unknown primary and guide more precise therapies associated with better outcomes. Epigenetic profiling could be a useful approach to unmask the original primary tumour site of cancer of unknown primary cases and a step towards the improvement of the clinical management of these patients.

FUNDING:

European Research Council (ERC), Cellex Foundation, the Institute of Health Carlos III (ISCIII), Cancer Australia, Victorian Cancer Agency, Samuel Waxman Cancer Research Foundation, the Health and Science Departments of the Generalitat de Catalunya, and Ferrer.

PMID:
27575023
DOI:
10.1016/S1470-2045(16)30297-2
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center