The proposed PhD project aims to:

1. Build a list of epitranscriptomic prostate cancer biomarkers linked to disease progression by analyzing pre-existing primary and metastatic datasets on Nm, m6A, and A-to-I modifications.

2. Set up an optimized protocol for the routine profiling of the epitranscriptome in plasma liquid biopsies (using a collection of ~1,000 samples from patients and healthy controls). This includes developing improved long-read Oxford Nanopore Technologies (ONT) library preparation and sequencing approaches for circulating RNA in collaboration with the Novoa lab (www.novoalab.com) at the CRG.

3. Develop novel bioinformatics methods, computational algorithms, and pipelines for detecting and evaluating epitranscriptomic biomarkers in liquid biopsies.

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