The role of the Functional and Bioinformatics Genomics is to promote active multidisciplinary collaborations to perform experiments with high processivity and sensitivity, able to measure miRNA expression levels or to characterize the mutation profile of circulating tumor DNA.
Results so far obtained allowed the identification of candidate biomarkers in breast, prostate, lung and colorectal cancer; their validation will provide answers to clinically relevant questions in the field of oncological research.
The role of the Functional and Bioinformatics Genomics (Applied Research Department and Technological Development) is to promote active multidisciplinary collaborations to perform experiments with high processivity and sensitivity to provide answers to clinically relevant questions in the field of oncological research. The group has expertise in multiple genomics and bioinformatics applications, such as the identification of new cancer subtypes and biomarkers, the development of predictors, data integration and meta-analysis from different data sets. The group is able to handle all stages of genomic experiments: it provides support for experimental design and planning; conducts the required techniques, starting with the extraction of nucleic acids and quality controls; applies strict statistical and bioinformatics methods for data processing and for the discovery and validation of potential biomarkers; supports biomedical research teams in interpreting results. It also carries out independent research activities aimed at: optimize the laboratory protocols required for different applications in relation to reference samples (tissues, liquid biopsies, FFPE or exosomes); evaluate the computational methods available for different types of analyses, such as those related to circulating miRNA profiles and to development of clinically useful predictors; define specific computational algorithms. Finally, the group provides training support through the organization of internal and external seminars.
Role in the project, experimental design
Within the project, the group led by Dr. Marialuisa Sensi will mainly deal with: i) implementation of appropriate technologies to determine miRNA profiles in clinical practice; ii) optimization of the experimental approach required by the various technologies; iii) analysis of miRNAs circulating in validation cases, using the OpenArray platform; iv) selection and optimization of computational methods appropriate to the understanding of biology and data integration, within each project and between different projects; v) technological and bioinformatic support to all research groups involved. Previously, the group contributed to the definition of circulating miRNA signatures for the specific pathologies under examination, through the OpenArray platform. The results obtained were very promising, so we now propose to reproduce them with a different technology, more suited to clinical transposition. Therefore, the evaluation of the performance of nCounter assay (nCounter V3 miRNA) developed by nanoString and of the nCounter Dx Analysis System FLEX platform, suitable for clinical use, is already underway, The assay, which allows the analysis of 800 miRNAs, allows, with minimal technical manipulation, the production of digital counts that will be used to evaluate, in the same samples, the overlap of data with those previously obtained with OpenArray. If this technology produces satisfactory results, we will be able to create custom nCounter miRNA assays for different tumor pathologies. Other activities planned for the development of a suitable clinical assay are the independent validation of miRNA signatures on new patient cohorts using OpenArray. A new miRNA assay (TaqMan ™ Advanced) has been recently introduced for use on the same platform. As the previous one, it allows a highly sensitive and specific quantification of the same miRNAs through qPCR and is applicable to circulating miRNAs. Unlike the previous one, it uses a universal retrotranscription for all miRNAs that diminishes the possible technical bias and simplifies the workflow. A number of samples are currently evaluated with both assays (old and new technology) to confirm the reproducibility of the results. The results of this experiment will allow the choice of the OpenArray technology to be used during validation. The above described studies will allow us to evaluate whether the proposed technologies could be suitable for clinical use.
Biologist, Staff Scientist
Loris De Cecco
Bioinformatician, PhD Student
Staff Laboratory Technician
Staff Laboratory Technician
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