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Defining a mutational signature for endometrial cancer screening and early detection

2019; Elsevier BV; Volume: 61; Linguagem: Inglês

10.1016/j.canep.2019.06.003

1877-783X

Laura Costas, Luís Palomero, Yolanda Benavente, Magdalena Guardiola, Jon Frias‐Gomez, Miguel Ángel Pavón, Maite Climent, José Manuel Martínez, Marc Barahona, Mònica Salinas, Marta Pineda, Ilaria Bianchi, Jaume Reventós, Gabriel Capellá, Mireia Díaz, August Vidal, Josep M. Piulats, Jordi Ponce, Joan Brunet, F. Xavier Bosch, Xavier Matías‐Guiu, Laia Alemany, Sílvia de Sanjosé, Àlvaro Aytés,

Endometrial and Cervical Cancer Treatments

The current availability of genomic information represents an opportunity to develop new strategies for early detection of cancer. New molecular tests for endometrial cancer may improve performance and failure rates of histological aspirate-based diagnosis, and provide promising perspectives for a potential screening scenario. However, the selection of relevant biomarkers to develop efficient strategies can be a challenge. We developed an algorithm to identify the largest number of patients with endometrial cancer using the minimum number of somatic mutations based on The Cancer Genome Atlas (TCGA) dataset. The algorithm provided the number of subjects with mutations (sensitivity) for a given number of biomarkers included in the signature. For instance, by evaluating the 50 most representative point mutations, up to 81.9% of endometrial cancers can be identified in the TCGA dataset. At gene level, a 92.9% sensitivity can be obtained by interrogating five genes. We developed a computational method to aid in the selection of relevant genomic biomarkers in endometrial cancer that can be adapted to other cancer types or diseases.