New computational biology tools for the systematic analysis of the structure and expression of human genes

From the late 1980s, the automation of sequencing techniques and the computer spread gave rise to a flourishing number of new molecular structures and sequences and to proliferation of new databases in which to store them. Here are presented three computational approaches able to analyse the massive amount of publicly avalilable data in order to answer to important biological questions. The first strategy studies the incorrect assignment of the first AUG codon in a messenger RNA (mRNA), due to the incomplete determination of its 5' end sequence. An extension of the mRNA 5' coding region was identified in 477 in human loci, out of all human known mRNAs analysed, using an automated expressed sequence tag (EST)-based approach. Proof-of-concept confirmation was obtained by in vitro cloning and sequencing for GNB2L1, QARS and TDP2 and the consequences for the functional studies are discussed. The second approach analyses the codon bias, the phenomenon in which distinct synonymous codons are used with different frequencies, and, following integration with a gene expression profile, estimates the total number of codons present across all the expressed mRNAs (named here "codonome value") in a given biological condition. Systematic analyses across different pathological and normal human tissues and multiple species shows a surprisingly tight correlation between the codon bias and the codonome bias. The third approach is useful to studies the expression of human autism spectrum disorder (ASD) implicated genes. ASD implicated genes sharing microRNA response elements (MREs) for the same microRNA are co-expressed in brain samples from healthy and ASD affected individuals. The different expression of a recently identified long non coding RNA which have four MREs for the same microRNA could disrupt the equilibrium in this network, but further analyses and experiments are needed.

Characterization of the molecular mechanisms mediated by the insulin-like growth factor-2 mRNA-binding proteins and Ephrin receptor A2 (EPHA2) signaling in the malignancy of CIC-DUX4 sarcomas

Ewing sarcoma (EWS) and CIC-DUX4 sarcoma (CDS) are pediatric fusion gene-driven tumors of mesenchymal origin characterized by an extremely stable genome and limited clinical solutions. Post-transcriptional regulatory mechanisms are crucial for understanding the development of this class of tumors. RNA binding proteins (RBPs) play a crucial role in the aggressiveness of these tumors. Numerous RBP families are dysregulated in cancer, including IGF2BPs. Among these, IGF2BP3 is a negative prognostic factor in EWS because it promotes cell growth, chemoresistence, and induces the metastatic process. Based on preliminary RNA sequencing data from clinical samples of EWS vs CDS patients, three major axes that are more expressed in CDS have been identified, two of which are dissected in this PhD work. The first involves the transcription factor HMGA2, IGF2BP2-3, and IGF2; the other involves the ephrin receptor system, particularly EphA2. EphA2 is involved in numerous cellular functions during embryonic stages, and its increased expression in adult tissues is often associated with pathological conditions. In tumors, its role is controversial because it can be associated with both pro- and anti-tumoral mechanisms. In EWS, it has been shown to play a role in promoting cell migration and neoangiogenesis. Our study has confirmed that the HMGA2/IGF2BPs/IGF2 axis contributes to CDS malignancy, and Akt hyperactivation has a strong impact on migration. Using loss/gain of function models for EphA2, we confirmed that it is a substrate of Akt, and Akt hyperactivation in CDS triggers ligand-independent activation of EphA2 through phosphorylation of S897. Moreover, the combination of Trabectedin and NVP/BEZ235 partially inhibits Akt/mTOR activation, resulting in reduced tumor growth in vivo. Inhibition of EphA2 through ALWII 41_27 significantly reduces migration in vitro. The project aim is the identification of target molecules in CDS that can distinguish it from EWS and thus develop new targeted therapeutic strategies.