(624.4) Identification of microRNA Targets in colorectal cancer through Data Sequencing

Poster Board Number: E662

Susana Rubio-Guevara (Universidad Nacional de Trujillo), Karyn Olascuaga-Castillo (Universidad Nacional de Trujillo), Elena Cáceres-Andonaire (Universidad Privada Antenor Orrego), Dan Altamirano-Sarmiento (Universidad Privada Antenor Orrego, Universidad Privado Antenor Orrego), Olga Caballero-Aquiño (Universidad Nacional de Trujillo), Elena Mantilla-Rodríguez (Universidad Nacional de Trujillo), Julio Hilario-Vargas (Universidad Nacional de Trujillo), Maxim Berezovski (University of Ottawa), José Andrés Morgado-Díaz (Instituto Nacional de Cancer)

Colorectal cancer (CRC) is the third leading cause of cancer-related mortality globally. MicroRNAs (miRNAs, miRs), a class of small non-coding RNA molecules, have demonstrated important roles in carcinogenesis and its progression through the regulation of the epithelialmesenchymal transition (EMT), oncogenic signaling pathways, and metastasis. Despite the increase in miRNA studies and extensive analyzes of their expression, the role and function of many individual miRNAs in CRC remains poorly understood. The aim of this study was to identify miRNA targets in CRC through data sequencing, which could be a solid prognostic prediction tool and help clinical strategy.

Methods: CRC gene expression data sets were collected from the public database, The Cancer Genome Atlas (TCGA). In addition, web-based tools were used to explore TCGA data, specifically the one developed by the Broad Institute TCGA GDAC Firehose, which provides data sets, algorithms, and analysis results standardized for TCGA. This pipeline has the following steps: The CLR (Context Likelihood of Relatedness) approach is applied to infer putative miRNA regulatory connections: gene; miRNA filtering: gene pairs based on Pearsons correlation (lt;= -0.3); and miRNA filtering: gene pairs based on predicted interactions in three sequence prediction databases (Miranda, Pictar, Targetscan). The CLR algorithm was applied on 617 miRs and 18012 mRNAs across 220 samples. After 2 filtering steps, the number of 9 miR:genes pairs were detected.

Results: The initial search with the term "Colorectal adenocarcinoma", "COADREAD" yielded 631 cases. After the analysis of these samples, data on the significance miR:gene pairs were obtained and Table 1 shows the results of miR:gene pairs with corr lt; -0.30 and predicted interactions in three sequence prediction databases. About the miRNA connections, Table 2 shows all miRNA hubs with their associated genes in the putative direct target network. Finally, about gene connections, Table 3 shows all gene hubs with their associated miRNAs in the putative direct target network.

Conclusion: The use of miRNAs as biomarkers for CRC could provide a new and less invasive technique to detect CRC and help determine prognosis. These miRNAs and their targets require further evaluation for a better understanding of their associations, ultimately, with the potential to develop new therapeutic targets. Therefore, it is proposed to develop a screening panel that should consist of multiple miRNAs that would provide a more accurate and efficient screening tool for CRC.

This research was funded by the Doctoral Program in Pharmacy and Biochemistry of the National University of Trujillo. Peru and the National Council of Science and Technology - Peru (CONCYTEC) in cooperation with the World Bank (Contract N 07-2018-FONDECYTBM-IADT-MU)