Personalised medicine in cervical cancer
The present invention consists of a method and a kit of predictive response to radiochemotherapy in patients with locally advanced cervical cancer. In particular, through the analysis of gene expression profile of 3 biomarkers and the subsequent use of an algorithm it is possible to predict treatment response for each patient at the time of diagnosis, thus defining personalised therapeutic strategies.
The expression of the 3 genes identified as associated with radiochemotherapy treatment response is measured by RT-qPCR, following RNA extraction from a fresh or frozen biopsy sample. The application of Random Forest algorithm (trained to prediction of sensitivity/resistance phenotype to treatment) allows to predict response for each single patient using the data set related to the 3 genes expression. From a commercial point of view, this invention might be configured as a creation of customised plates for RT-qPCR containing specific primers for amplification of the genes object of the invention, together with a credential link to access a programme where the prediction model described above is applied. If predictive algorithm assigns a sensitivity phenotype to patient, a standard therapeutic path will be launched; on the contrary, patients with resistant phenotypes will be treated with alternative therapies to radiochemotherapy, thus avoiding not only ineffective but potentially harmful treatments.
- Cervical cancer;
- Medical-pharmaceutical fields of personalised medicine.
- Patient stratification for improvement of therapeutic efficacy;
- Support for clinical decisions;
- Reduction of care direct costs;
- Reduction of disease-associated indirect costs;
- Simple and sensitive analysis procedures;
- Limited costs and times.