The Italian Association for Cancer Research (AIRC) has recently founded the proposal entitled “Radiogenomics Framework for Non-Invasive Personalized Medicine in Head and Neck Cancer” by Loris De Cecco, BD2Decide team member from Partner INT.
The project, arising from BD2decide, will validate both the genomic subtype stratification and the signatures in response to EGFR-inhibitors, previously published by INT's PI (dr. Lisa Licitra) and the clinicians involved in her team. In addition the project will also extend the genomics analysis including the mutational patterns.
Below follows an abstract of this new exciting project.
ABSTRACT
Background
Overall survival of HPV-negative Head and Neck Squamous carcinoma (HNSCC) patients, with locally advanced disease (stage III–IV), persists to be dismal (less than 50% at 5 years), despite the advances in the treatment approaches in the last years. Concomitant chemo-radiation still represents the standard of care either alone or in combination with surgery. By a microarray meta-analysis based on 1386 cases, we provided evidence that HPV-negative and HPV-positive HNSCC patients have different gene expression patterns and HPV-negative cases can be stratified in five different subtypes (De Cecco, Oncotarget 2015). Furthermore, the PI, as first, clearly associated a subtype (Cl3-Hypoxia) to the response to EGFR-inhibitors treatment (Bossi, Clin Cancer Res 2016). Meanwhile, correlations between radiological imaging features in cancer and specific genomic features (i.e. gene-expression, mutations) were identified and this new field, named “radiogenomics”, has been proposed as surrogate of genomic features.
Aims
The present project aims to:
i. Validate the subtype stratification of HNSCC (task 1) and identify the mutational determinant(s) for each subtype (task 2) in the frame of well established national/international studies.
ii. Understand the molecular basis of the tumor subtypes by a surrogate non invasive methodology, i.e. radiomics (task 3).
iii. Use our well characterized HNSCC subtype, Cl3-Hypoxia, as a proof of principle of the validity of the radiogenomics approach (task 4).
Hypothesis
The main hypothesis of the project is that the radiological imaging traits can serve as surrogates of genomic features (i.e. gene-expression, mutations)
Experimental Design
The project will take advantage of samples and data from well established clinical trials, three of which included in large national/international studies and in particular to the project Horizon 2020-PHC-2014-15 “BD2Decide: Big Data and models for personalized Head and Neck Cancer Decision support”.
The aims of the present proposal will be obtained through the following tasks:
1) analysis of heterogeneity in HNSCC by whole-transcriptomic analysis to validate the HNSCC subtype classification
2) identification of the mutational determinant(s) for each HNSCC subtype
3) analysis of radiomics features, their integration with genomic data and their validation in a prospective cohort of patients
4) use of our well characterized HNSCC subtype, Cl3-Hypoxia, as a proof of principle of the validity of radiogenomics approach
Expected Results
We expect to develop innovative translational models linking genomics and radiomics information paving the way for the non-invasive subtype characterization of HNSCC. If suitable radiomics surrogates would be found in Cl3-Hypoxia subtype, clinicians might have an easy accessible tool for selecting the patients who would benefit of anti-EGFR treatments.
Impact on Cancer
Genomics analyses are based on the availability of tissue specimens requiring surgery, which is not always feasible and even not indicated since most of the curative treatments are based on full dose RT without tumor removal. Therefore, a non-invasive, widely available, easy to apply, reliable and inexpensive method would be of great importance. Radiological imaging is known to meet these needs and radiogenomics features have the potential to be developed as new tools in personalized cancer treatment enabling physicians to identify specific treatment modalities for each HNSCC subtype.
