Banca de DEFESA: GENILDA CASTRO DE OMENA NETA

IN SILICO PREDICTION OF TUMOR ANTIGEN MULTI-EPITOP VACCINE CANDIDATE FOR TESTICULAR CANCER ANTIGEN - TFDP3

breast cancer; immunoinformatics; epitope prediction; peptide vaccine.

Breast cancer. considered the main malignant neoplasm that affects women in the Brazil and in the World. Molecular subtypes are categorized into luminal and non-luminal. Non-luminal tumors have an unfavorable prognosis, high recurrence rate and few treatment possibilities, and those available do not significantly increase patient survival. Therefore, the need to prospect new, more effective and specific treatment strategies for non-luminal subtypes. The objective proposed in this work is the in silico prediction of tumor antigenic multi-epitope vaccine candidates for non-luminal subtypes. The choice of targets for the development of multi-epitope vaccines was performed based on the analysis of 170 RNA expression samples from patients with breast cancer of the invasive ductal carcinoma type and non-luminal subtypes (HER2 and basal) and 80 samples of breast tissue standard available for download in public banks. In these data, the most differentially expressed genes were obtained using the limma package and considering p<0.05 and |logFC| >1 for each subtype. These genes were compared to each other using the Venn diagram. The enriched pathways of genes unique to each subtype were evaluated in KEGG and Reactome. In addition, the protein interaction of the differentially expressed transcripts and the subcellular localization in the cell membrane were evaluated in the Cytoscape 3.9.1 software by STRING plugging. Amino acid sequences of selected target proteins, in canonical FASTA format, were obtained from the UniProt database. Each sequence was evaluated for its tumor antigenicity by the Vaxijen server v.2.0. Then be. The prediction of the linear epitopes of the B lymphocytes, which stimulate the humoral response, was carried out by the ABCpred server. In the epitopes of class I and class II of T lymphocytes, which trigger the cellular response, the analyzes will be performed by the IEDB server. All selected epitopes will be evaluated for antigenicity, allergenicity, immunogenicity and toxicity by servers. They will also be modeled and evaluated for affinity with experimentally validated software alleles. With all epitopes selected be. The estimate of population coverage of MHC class I and II epitopes was performed by the IEDB servers. After being. The prediction of the epitopes that stimulate the production of interferon-gamma cytokines was performed by the IFN epitope software. The construction of the multi-epitope vaccine involved the use of several tools that enabled structural modifications to increase immunogenicity, evaluation of cross-reactivity, evaluation of physicochemical properties, allergenicity, antigenicity and toxicity, prediction of secondary and tertiary structure, refinement and validation, assessment of immunogenicity and receptor binding affinity. Also, be. Optimization of in silico cloning of the multi-epitope vaccine was performed to ensure in vivo expression. At this stage of the study, proteins PPP4C and PAK4 in the Her2 subtype, and ENO1 and SEPHS1 in the Basal subtype, were identified as potential targets for predicting the epitopes that will compose multi-epitope vaccines. These genes present pathways associated with important events in the tumor development process, as well as interaction with other proteins that play a regulatory role. It is expected to find, from all analyzes carried out, promising tumor antigenic multi-epitope vaccine candidates for the immunotherapeutic treatment of non-luminal subtypes.