Merging person-specific bio-markers for predicting oral cancer recurrence through an ontology

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

MRI-based radiomic prognostic signature for locally advanced oral cavity squamous cell carcinoma: development, testing and comparison with genomic prognostic signatures

Background. At present, the prognostic prediction in advanced oral cavity squamous cell carcinoma (OCSCC) is based on the tumor-node-metastasis (TNM) staging system, and the most used imaging modality in these patients is magnetic resonance image (MRI). With the aim to improve the prediction, we developed an MRI-based radiomic signature as a prognostic marker for overall survival (OS) in OCSCC patients and compared it with published gene expression signatures for prognosis of OS in head and neck cancer patients, replicated herein on our OCSCC dataset.MethodsFor each patient, 1072 radiomic features were extracted from T1 and T2-weighted MRI (T1w and T2w). Features selection was performed, and an optimal set of five of them was used to fit a Cox proportional hazard regression model for OS. The radiomic signature was developed on a multi-centric locally advanced OCSCC retrospective dataset (n = 123) and validated on a prospective cohort (n = 108).ResultsThe performance of the signature was evaluated in terms of C-index (0.68 (IQR 0.66-0.70)), hazard ratio (HR 2.64 (95% CI 1.62-4.31)), and high/low risk group stratification (log-rank p < 0.001, Kaplan-Meier curves). When tested on a multi-centric prospective cohort (n = 108), the signature had a C-index of 0.62 (IQR 0.58-0.64) and outperformed the clinical and pathologic TNM stage and six out of seven gene expression prognostic signatures. In addition, the significant difference of the radiomic signature between stages III and IVa/b in patients receiving surgery suggests a potential association of MRI features with the pathologic stage.ConclusionsOverall, the present study suggests that MRI signatures, containing non-invasive and cost-effective remarkable information, could be exploited as prognostic tools

Joint practice guidelines for radionuclide lymphoscintigraphy for sentinel node localization in oral/oropharyngeal squamous cell carcinoma

Involvement of the cervical lymph nodes is the most important prognostic factor for patients with oral/oropharyngeal squamous cell carcinoma (OSCC), and the decision whether to electively treat patients with clinically negative necks remains a controversial topic. Sentinel node biopsy (SNB) provides a minimally invasive method of determining the disease status of the cervical node basin, without the need for a formal neck dissection. This technique potentially improves the accuracy of histological nodal staging and avoids over-treating three-quarters of this patient population, minimizing associated morbidity. The technique has been validated for patients with OSCC, and larger-scale studies are in progress to determine its exact role in the management of this patient population. This article was designed to outline the current best practice guidelines for the provision of SNB in patients with early-stage OSCC, and to provide a framework for the currently evolving recommendations for its use. These guidelines were prepared by a multidisciplinary surgical/nuclear medicine/pathology expert panel under the joint auspices of the European Association of Nuclear Medicine (EANM) Oncology Committee and the Sentinel European Node Trial Committee

Multilevel and multiscale modeling approach for VPH-based prediction of oral cancer reoccurrences. Results of the FP7 NeoMark project

In this work we present the approach adopted to stratify patients at high vs. low risk for reoccurrence of Oral Squamous Cell Carcinoma (OSCC) and to model the disease progression after remission. For this purpose we developed a multiscale and multilevel model, which integrates thousands of heterogeneous data including genomics, collected by means of innovative technologies such as Point-of-Care (PoC) Real Time PCR and lab-on-chip and advanced image fusion techniques. The realized predictive model produced a bio-signature of high-risk patients and identified a set of biomarkers from tumor tissues and blood cells, indicative of potential disease reoccurrence. The NeoMark predictive model was trained and initially validated in a multicentre pilot study (three European clinical centers involved in Italy and in Spain) on a cohort of 86 patients affected by OSCC with a minimum follow up of 12 months. We discuss how the disease bio-profile identified by NeoMark was considered extremely useful by the clinicians to evaluate the risk of disease reoccurrence of a patient at the time of diagnosis and to provide a "tailored therapy" to each case