Investigating the role of single point mutations in the human proteome: a computational study

In the post genomic era with the massive production of biological data the understanding of factors affecting protein stability is one of the most important and challenging tasks for highlighting the role of mutations in relation to human maladies. The problem is at the basis of what is referred to as molecular medicine with the underlying idea that pathologies can be detailed at a molecular level. To this purpose scientific efforts focus on characterising mutations that hamper protein functions and by these affect biological processes at the basis of cell physiology. New techniques have been developed with the aim of detailing single nucleotide polymorphisms (SNPs) at large in all the human chromosomes and by this information in specific databases are exponentially increasing. Eventually mutations that can be found at the DNA level, when occurring in transcribed regions may then lead to mutated proteins and this can be a serious medical problem, largely affecting the phenotype. Bioinformatics tools are urgently needed to cope with the flood of genomic data stored in database and in order to analyse the role of SNPs at the protein level. In principle several experimental and theoretical observations are suggesting that protein stability in the solvent-protein space is responsible of the correct protein functioning. Then mutations that are found disease related during DNA analysis are often assumed to perturb protein stability as well. However so far no extensive analysis at the proteome level has investigated whether this is the case. Also computationally methods have been developed to infer whether a mutation is disease related and independently whether it affects protein stability. Therefore whether the perturbation of protein stability is related to what it is routinely referred to as a disease is still a big question mark. In this work we have tried for the first time to explore the relation among mutations at the protein level and their relevance to diseases with a large-scale computational study of the data from different databases. To this aim in the first part of the thesis for each mutation type we have derived two probabilistic indices (for 141 out of 150 possible SNPs): the perturbing index (Pp), which indicates the probability that a given mutation effects protein stability considering all the “in vitro” thermodynamic data available and the disease index (Pd), which indicates the probability of a mutation to be disease related, given all the mutations that have been clinically associated so far. We find with a robust statistics that the two indexes correlate with the exception of all the mutations that are somatic cancer related. By this each mutation of the 150 can be coded by two values that allow a direct comparison with data base information. Furthermore we also implement computational methods that starting from the protein structure is suited to predict the effect of a mutation on protein stability and find that overpasses a set of other predictors performing the same task. The predictor is based on support vector machines and takes as input protein tertiary structures. We show that the predicted data well correlate with the data from the databases. All our efforts therefore add to the SNP annotation process and more importantly found the relationship among protein stability perturbation and the human variome leading to the diseasome.

High sensitivity analysis of BRAF mutations in neoplastic and non-neoplastic thyroid lesions

The clonal distribution of BRAFV600E in papillary thyroid carcinoma (PTC) has been recently debated. No information is currently available about precursor lesions of PTCs. My first aim was to establish whether the BRAFV600E mutation occurs as a subclonal event in PTCs. My second aim was to screen BRAF mutations in histologically benign tissue of cases with BRAFV600E or BRAFwt PTCs in order to identify putative precursor lesions of PTCs. Highly sensitive semi-quantitative methods were used: Allele Specific LNA quantitative PCR (ASLNAqPCR) and 454 Next-Generation Sequencing (NGS). For the first aim 155 consecutive formalin-fixed and paraffin-embedded (FFPE) specimens of PTCs were analyzed. The percentage of mutated cells obtained was normalized to the estimated number of neoplastic cells. Three groups of tumors were identified: a first had a percentage of BRAF mutated neoplastic cells > 80%; a second group showed a number of BRAF mutated neoplastic cells < 30%; a third group had a distribution of BRAFV600E between 30-80%. The large presence of BRAFV600E mutated neoplastic cell sub-populations suggests that BRAFV600E may be acquired early during tumorigenesis: therefore, BRAFV600E can be heterogeneously distributed in PTC. For the second aim, two groups were studied: one consisted of 20 cases with BRAFV600E mutated PTC, the other of 9 BRAFwt PTCs. Seventy-five and 23 histologically benign FFPE thyroid specimens were analyzed from the BRAFV600E mutated and BRAFwt PTC groups, respectively. The screening of BRAF mutations identified BRAFV600E in “atypical” cell foci from both groups of patients. “Unusual” BRAF substitutions were observed in histologically benign thyroid associated with BRAFV600E PTCs. These mutations were very uncommon in the group with BRAFwt PTCs and in BRAFV600E PTCs. Therefore, lesions carrying BRAF mutations may represent “abortive” attempts at cancer development: only BRAFV600E boosts neoplastic transformation to PTC. BRAFV600E mutated “atypical foci” may represent precursor lesions of BRAFV600E mutated PTCs.

Next-Generation Sequencing-Based Mutations Scanning Strategy of the BCR-ABL Kinase Domain in Patients with PhiladelPhia-Chromosome Positive Leukemias Treated with Tyrosine Kinase Inhibitors

In chronic myeloid leukemia and Philadelphia-positive acute lymphoblastic leukemia patients resistant to tyrosine kinase inhibitors (TKIs), BCR-ABL kinase domain mutation status is an essential component of the therapeutic decision algorithm. The recent development of Ultra-Deep Sequencing approach (UDS) has opened the way to a more accurate characterization of the mutant clones surviving TKIs conjugating assay sensitivity and throughput. We decided to set-up and validated an UDS-based for BCR-ABL KD mutation screening in order to i) resolve qualitatively and quantitatively the complexity and the clonal structure of mutated populations surviving TKIs, ii) study the dynamic of expansion of mutated clones in relation to TKIs therapy, iii) assess whether UDS may allow more sensitive detection of emerging clones, harboring critical 2GTKIs-resistant mutations predicting for an impending relapse, earlier than SS. UDS was performed on a Roche GS Junior instrument, according to an amplicon sequencing design and protocol set up and validated in the framework of the IRON-II (Interlaboratory Robustness of Next-Generation Sequencing) International consortium.Samples from CML and Ph+ ALL patients who had developed resistance to one or multiple TKIs and collected at regular time-points during treatment were selected for this study. Our results indicate the technical feasibility, accuracy and robustness of our UDS-based BCR-ABL KD mutation screening approach. UDS was found to provide a more accurate picture of BCR-ABL KD mutation status, both in terms of presence/absence of mutations and in terms of clonal complexity and showed that BCR-ABL KD mutations detected by SS are only the “tip of iceberg”. In addition UDS may reliably pick 2GTKIs-resistant mutations earlier than SS in a significantly greater proportion of patients.The enhanced sensitivity as well as the possibility to identify low level mutations point the UDS-based approach as an ideal alternative to conventional sequencing for BCR-ABL KD mutation screening in TKIs-resistant Ph+ leukemia patients