RNA-Seq Transcriptome Analysis for the Study of Prostate Cancer Development and Evolution
Int. J. Mol. Sci.2019, 20, x; doi: FOR PEER REVIEWwww.mdpi.com/journal/ijmsMaster ThesisRNA-Seq Transcriptome Analysis for the Study of Prostate Cancer Development and EvolutionEstherSauras Colón 1*, María Jesús Álvarez Cubero2,3*and Eduardo Andrés León4*1Master in Translational Research and Personalized Medicine. Faculty of Medicine, University of Granada. Granada, Spain.2GENYO. Centre for Genomics and Oncological Research.Pfizer / University of Granada /Andalusian Regional Government. Granada, Spain.3Department of Biochemistry and Molecular Biology III.Faculty of Medicine, University of Granada.Granada, Spain.4Bioinformatics Unit,Institute of Parasitology and Biomedicine "López-Neyra" (IPBLN).Spanish National Research Council (CSIC).Granada, Spain.*Correspondence: Esther Sauras Colón: esc6@correo.ugr.es. María Jesús Álvarez Cubero: mjesusac@ugr.es. Eduardo Andrés León: eduardo.andres@csic.es.September 2019Abstract: Prostate cancer (PCa) is one of the most common cancers worldwide.Even though prostate specific antigen (PSA) testis thenon-invasive routine blood test for the detection of asymptomatic disease, itcanresultinproblemsofdiagnostic accuracyandoverdiagnosis.Thus, it is necessary to continue investigating newefficientbiomarkers for the prevention, diagnosis and prognosis of PCa.Here, we analyse the transcriptome of seven individuals by the use of next-generation sequencing (NGS)techniqueto identify differentially expressed genes, which can help to better understand PCa aggressiveness. Presentanalysis show that there are two upregulated genes in PCa regarding to controls: HP(Haptoglobin)and HLA-G(Human Leukocyte Antigen-G). On the other hand, there are seven downregulated genes, where TP53TG3 and their transcripts should be highlighted.Also, we make a comparison between amoreaggressive PCa phenotype and the rest of PCa samples to investigate about genes implicated in aggressiveness, obtaining a high number of upregulated genesincludingCENPF, DLGAP5 and RRM2, among others.These genescould serve as predictive, diagnosticand prognosticbiomarkers, as well as molecular targets. Nevertheless, further studies would be needed to confirm the obtained results.