DECODING THE CANCER CODE:

UNVEILING THE POTENTIAL OF LONG NON-CODING RNAS IN ONCOLOGY

Autores/as

DOI:

https://doi.org/10.61229/mpj.v2i1.32

Palabras clave:

Cancer, lncRNA, Biomarker

Resumen

Carcinogenesis predicts 30 million new cases by 2040, making it the second leading cause of death globally. In Brazil, neoplastic diseases resulted in more than 229,000 deaths in 2020, with 704,000 new cases expected between 2023 and 2025. Factors such as smoking, stress and genetic predisposition influence oncogenesis. Oncology interventions face challenges such as therapeutic resistance and tumor heterogeneity. Around 75% of the human genome is made up of non-coding RNAs (ncRNAs), with a focus on long ncRNAs. Previously considered 'evolutionary junk', lncRNAs regulate genes and affect cancer. Nuclear lncRNAs impact chromatin architecture, transcription and RNA processing. They function via complex pathways, modulating oncogenes and affecting resistance to treatment. Several lncRNAs, including MALAT1, ANRIL, HOTAIR, GAS5, MEG3 and H19, modulate oncogenic pathways and influence cellular processes and treatment resistance. Although promising as biomarkers, the structural complexity of lncRNAs hinders their clinical application.

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Biografía del autor/a

Laurence Rodrigues do Amaral, Laboratório de Bioinformática e Análises Moleculares, Universidade Federal de Uberlândia, Patos de Minas, MG, Brazil

Laurence Rodrigues do Amaral is an associate professor at the Faculty of Computing (FACOM) of the Federal University of Uberlândia (UFU), based in Patos de Minas - MG. He holds a doctorate from PPGCC/UFSCar (Artificial Intelligence), a master's degree from PPGCO/UFU (Artificial Intelligence) and a bachelor's degree from FACOM/UFU in Computer Science, as well as a specialization in Biotechnology from the Federal University of Lavras (UFLA). He did post-doctoral studies at the René Rachou Institute at Fiocruz Minas. He is a permanent lecturer in the postgraduate program in Computer Science (PPGCO/UFU), in the area of Artificial Intelligence, supervising master's and doctoral students. He is a permanent lecturer and current coordinator of the postgraduate program in Biotechnology (PPGBIOTEC/UFU), in the area of Bioinformatics. He has a CNPq productivity grant for Technological Development and Innovative Extension, level 2. Areas of interest: Artificial Intelligence, especially Genetic Algorithms, Machine Learning, Data mining, Bioinformatics and Evolutionary Robotics. He participated in the worldwide sequencing of the organisms Biomphalaria glabrata and Rhodnius prolixus. He collaborates in research projects linked to the National University of Ireland (Galway), Fiocruz, UFSCar, UFRJ, UFLA, UFOP, USP/Ribeirão Preto, UFAM, Unb, UFF, among others. He has reviewed articles for the following journals: IEEE Transactions on Neural Networks and Learning Systems, Bioinformatics (Oxford), Artificial Intelligence Review, Computers in Biology and Medicine, International Journal of Information Technology & Decision Making, among others. He is the coordinator of the Internet of Things Laboratory and one of the heads of the Bioinformatics and Molecular Analysis Laboratory (LBAM) at INGEB/FACOM at the Federal University of Uberlândia - Advanced Campus Patos de Minas.

Pedro Luiz Lima Bertarini, Laboratório de Bioinformática e Análises Moleculares, Universidade Federal de Uberlândia, Patos de Minas, MG, Brazil

He has a degree in Electrical Engineering from the University of São Paulo (2006) and a PhD in Electrical Engineering from the University of São Paulo (2012). He completed a post-doctorate at USP/São Carlos between 2013 and 2014. He is currently a professor and researcher at the Faculty of Electrical Engineering (FEELT) - Federal University of Uberlândia (UFU), Patos de Minas campus. He has experience in Electrical Engineering, with an emphasis on Telecommunications. His interests include modeling Telecommunications Systems, Metamaterials, Information Theory and Coding, Digital Signal Processing, Internet of Things (IoT) and Artificial Intelligence. He is the coordinator of the Urban and Rural Technologies Laboratory (LATUR) at FEELT/UFU on the Patos de Minas campus.

Matheus de Souza Gomes, Laboratório de Bioinformática e Análises Moleculares, Universidade Federal de Uberlândia, Patos de Minas, MG, Brazil

Prof. Dr. Matheus de Souza Gomes has a degree in Pharmacy from the Federal University of Ouro Preto (2005), a Master's and PhD in Biological Sciences with an emphasis on Molecular Biology (2008) and a sandwich internship at the National University of Ireland - Galway - Genetics and Biotechnology Laboratory - Centre for Chromosome Biology under the supervision of Professor Dr. Charles Spillane. He was Professor of Biochemistry at the Federal University of Ouro Preto in 2011 and 2012. He is currently Associate Professor at the Biotechnology Institute and Advisor to the Rector at the Federal University of Uberlândia Patos de Minas Campus. He was Coordinator of the Undergraduate Biotechnology course between 2012 and 2015 and Coordinator of the Postgraduate Biotechnology Program in 2016 and 2017 at the same institution. He is a permanent professor in the Graduate Programs in Genetics and Biochemistry (PPGGB - UFU) and Biotechnology (PPGBIOTEC - UFU). He teaches undergraduate and graduate courses such as Structural Biochemistry, Metabolic Biochemistry, Genetics, Molecular Biology and Bioinformatics. He has experience in Molecular Biology, Bioinformatics, Genetics and Biochemistry. He is currently a CNPq Level 2 Researcher and Coordinator of the Bioinformatics and Molecular Analysis Laboratory (LBAM) at the Biotechnology Institute of the UFU Patos de Minas Campus.

Fábio Ribeiro Queiroz, Instituto de Inovação, Ensino e Pesquisa do Instituto Mário Penna


Biologist, MSc and PhD in Health Sciences from the Oswaldo Cruz Foundation - IRR/MG. He is currently doing a post-doctoral internship in Translational Research in Oncology at the Mário Penna Institute for Teaching, Research and Innovation - IEPI. She is responsible for the Next Generation Sequencing and Bioinformatics Platforms, working on the transcriptome of small RNAs, gene expression and analysis of sequencing data. She has experience in bioinformatics, genetics, molecular biology, cell culture, flow cytometry and molecular parasitology. He also has more than twelve years' experience as a teacher in the state education system. He was vice-principal at Dom Cabral State School and is currently a teacher at the same institution. He teaches on the postgraduate course in Bioinformatics Applied to Health at PUC Minas.

Leticia da Conceição Braga , Instituto de Inovação, Ensino e Pesquisa do Instituto Mário Penna

Biologist, Master in Genetics from the Federal University of Minas Gerais, PhD in Health Sciences from the Botucatu/UNESP Medical School and Post-Doctorate in Drug Discovery in Oncology. MBA in Business Management from USP-ESALQ. Co-founder of the startup OncoTag. Her experience has helped to develop scientific entrepreneurship and innovation in Brazil. She is currently the coordinator of the Basic and Translational Research Laboratory at the Mário Penna Institute, working on lines of research in precision oncology and translational medicine, with an emphasis on the following topics: tumor genomics and transcriptomics, bioinformatic analysis of DNA and RNA sequences and analysis of differential gene expression and signaling related to prognostic and predictive factors of radiochemotherapy treatment. She has been accredited as a voluntary collaborator in the postgraduate courses in Morphofunctional Sciences at UFSJ and Genetics at UFMG. She has received several awards and honors as a scientist and entrepreneur, including: II Fleury Innovation Award, Outstanding in the InovAtiva Brazil Demoday, Carlos Ribeiro Diniz Award (Funed), UNA Teaching Merit and Francisco Mauro Salsano Award - Human Genetics. Allied Doctoral Scientist of the American Society of Oncology (ASCO) and member of the Brazilian Group of Gynecological Tumors EVA.

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2024-08-16

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Custódio Dias Duarte, B., Rodrigues do Amaral, L., Lima Bertarini, P. L., de Souza Gomes, M., Ribeiro Queiroz, F., & da Conceição Braga , L. (2024). DECODING THE CANCER CODE: : UNVEILING THE POTENTIAL OF LONG NON-CODING RNAS IN ONCOLOGY. Mário Penna Journal, 2(1), 68–99. https://doi.org/10.61229/mpj.v2i1.32

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Vol. 2 Núm. 1 (2024): Mário Penna Journal

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