Life Supporting Technologies, Universidad Politécnica de Madrid, de Madrid 28040, Spain.
IEEE Trans Biomed Eng. 2013 Jan;60(1):216-20. doi: 10.1109/TBME.2012.2216879. Epub 2012 Aug 31.
One of the major problems related to cancer treatment is its recurrence. Without knowing in advance how likely the cancer will relapse, clinical practice usually recommends adjuvant treatments that have strong side effects. A way to optimize treatments is to predict the recurrence probability by analyzing a set of bio-markers. The NeoMark European project has identified a set of preliminary bio-markers for the case of oral cancer by collecting a large series of data from genomic, imaging, and clinical evidence. This heterogeneous set of data needs a proper representation in order to be stored, computed, and communicated efficiently. Ontologies are often considered the proper mean to integrate biomedical data, for their high level of formality and for the need of interoperable, universally accepted models. This paper presents the NeoMark system and how an ontology has been designed to integrate all its heterogeneous data. The system has been validated in a pilot in which data will populate the ontology and will be made public for further research.
癌症治疗相关的主要问题之一是其复发。由于无法事先预测癌症复发的可能性，临床实践通常建议采用具有强烈副作用的辅助治疗。通过分析一组生物标志物来预测复发概率是优化治疗的一种方法。通过从基因组、成像和临床证据中收集大量数据，NeoMark 欧洲项目已经确定了一组用于口腔癌的初步生物标志物。为了有效地存储、计算和交流，这组异构数据需要适当的表示形式。本体通常被认为是整合生物医学数据的合适方法，因为它们具有高度的形式化，并且需要可互操作的、普遍接受的模型。本文介绍了 NeoMark 系统以及如何设计本体来集成其所有异构数据。该系统已经在一个试点中进行了验证，其中数据将填充本体，并将公开供进一步研究。
