ANÁLISE IN SILICO DO PROCESSO DE REGENERAÇÃO CELULAR ATRAVÉS DA INTERAÇÃO PIWI/PIRNA EM MUS MUSCULUS

Cell and tissue regeneration, much discussed in various areas of medicine and biology, still has gaps in its processes and functioning. In the last decade, the role of epigenetics in this function has been elucidated, with emphasis on non-coding RNAs, including piRNAs (PIWI-interacting RNAs), previously known for their role in germ cells and in controlling transposable elements. Recent studies have demonstrated piRNA functions in somatic tissue cells, such as the nervous system, and research in small rodents, especially Mus musculus, has indicated an important link between the expression of this pathway and the correct functioning of the regeneration process. As it is a relevant challenge for regenerative medicine to understand these processes, through the robust studies described here and using Bioinformatics tools, protein-protein interaction networks (PPIN) were built to identify target proteins for therapeutic treatments based on the functioning of the PIWI/piRNA gene pathway in Mus musculus. By analyzing these networks, we were able to identify relevant proteins, as well as their interactions, for the regenerative process in mammals and, with these results, in the future we will be able to develop in vivo tests based on the data obtained in silico, thus saving time and financial investment.La regeneración celular y tisular, muy discutida en diversos ámbitos de la medicina y la biología, aún presenta lagunas en cuanto a sus procesos y funcionamiento. En la última década se ha dilucidado el papel de la epigenética en esta función, con énfasis en los ARN no codificantes, entre ellos los piARN (ARN que interactúan con PIWI), antes conocidos por su papel en las células germinales y en el control de los elementos transponibles. Estudios recientes han demostrado las funciones de los piRNAs en células de tejidos somáticos, como el sistema nervioso, y la investigación en pequeños roedores, especialmente Mus musculus, ha indicado un importante vínculo entre la expresión de esta vía y el correcto funcionamiento del proceso de regeneración. Dado que entender estos procesos es un reto relevante para la medicina regenerativa, a través de los robustos estudios aquí descritos y utilizando herramientas de Bioinformática, se construyeron redes de interacción proteína-proteína (PPIN) para identificar proteínas diana para tratamientos terapéuticos basados en el funcionamiento de la vía génica PIWI/piRNA en Mus musculus. Mediante el análisis de estas redes, pudimos identificar proteínas relevantes, así como sus interacciones, para el proceso regenerativo en mamíferos y, con estos resultados, en el futuro podremos desarrollar ensayos in vivo basados en los datos obtenidos in silico, ahorrando así tiempo e inversión económica.A regeneração celular e tecidual, muito abordada em diversas áreas da medicina e da biologia, ainda permanece com lacunas sobre seus processos e funcionamento. Na última década, elucidou-se o papel da epigenética na referida função, dando-se ênfase para RNAs não codificantes, e entre eles, os piRNAs (PIWI-interacting RNAs), antes conhecidos por sua atuação em células germinativas e no controle de elementos transponíveis. Estudos recentes demonstraram funções dos piRNA em células de tecidos somáticos, como o nervoso, e pesquisas com pequenos roedores, especialmente em Mus musculus, apontaram uma importante ligação entre a expressão dessa via e o correto funcionamento do processo de regeneração. Por ser um desafio relevante para a medicina regenerativa entender esses processos, através de estudos robustos aqui descritos e utilizando ferramentas de Bioinformática, construiu-se redes de interação proteína-proteína (PPIN) para identificar proteínas-alvo para tratamentos terapêuticos com base no funcionamento da via do gene PIWI/piRNA em Mus musculus. A partir da análise dessas redes, conseguimos identificar proteínas relevantes, assim como suas interações, para o processo regenerativo em mamíferos e, com esses resultados, futuramente, poder-se-á desenvolver testes in vivo com base nos dados obtidos in silico, economizando, assim, tempo e investimentos financeiros.A regeneração celular e tecidual, muito abordada em diversas áreas da medicina e da biologia, ainda permanece com lacunas sobre seus processos e funcionamento. Na última década, elucidou-se o papel da epigenética na referida função, dando-se ênfase para RNAs não codificantes, e entre eles, os piRNAs (PIWI-interacting RNAs), antes conhecidos por sua atuação em células germinativas e no controle de elementos transponíveis. Estudos recentes demonstraram funções dos piRNA em células de tecidos somáticos, como o nervoso, e pesquisas com pequenos roedores, especialmente em Mus musculus, apontaram uma importante ligação entre a expressão dessa via e o correto funcionamento do processo de regeneração. Por ser um desafio relevante para a medicina regenerativa entender esses processos, através de estudos robustos aqui descritos e utilizando ferramentas de Bioinformática, construiu-se redes de interação proteína-proteína (PPIN) para identificar proteínas-alvo para tratamentos terapêuticos com base no funcionamento da via do gene PIWI/piRNA em Mus musculus. A partir da análise dessas redes, conseguimos identificar proteínas relevantes, assim como suas interações, para o processo regenerativo em mamíferos e, com esses resultados, futuramente, poder-se-á desenvolver testes in vivo com base nos dados obtidos in silico, economizando, assim, tempo e investimentos financeiros

Computational biology helps understand how polyploid giant cancer cells drive tumor success

Precision and organization govern the cell cycle, ensuring normal proliferation. However, some cells may undergo abnormal cell divisions (neosis) or variations of mitotic cycles (endopolyploidy). Consequently, the formation of polyploid giant cancer cells (PGCCs), critical for tumor survival, resistance, and immortalization, can occur. Newly formed cells end up accessing numerous multicellular and unicellular programs that enable metastasis, drug resistance, tumor recurrence, and self-renewal or diverse clone formation. An integrative literature review was carried out, searching articles in several sites, including: PUBMED, NCBI-PMC, and Google Academic, published in English, indexed in referenced databases and without a publication time filter, but prioritizing articles from the last 3 years, to answer the following questions: (i) “What is the current knowledge about polyploidy in tumors?”; (ii) “What are the applications of computational studies for the understanding of cancer polyploidy?”; and (iii) “How do PGCCs contribute to tumorigenesis?

Translational Bioinformatics Applied to the Study of Complex Diseases

Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment of cancer. An integrative literature review was carried out, obtaining articles through several websites, among them: PUBMED, Science Direct, NCBI-PMC, Scientific Electronic Library Online (SciELO), and Google Academic, published in English, Spanish, and Portuguese, indexed in the referred databases and answering the following guiding question: “How does TBI provide a scientific understanding of complex diseases?” An additional effort is aimed at the dissemination, inclusion, and perpetuation of TBI knowledge from the academic environment to society, helping the study, understanding, and elucidating of complex disease mechanics and their treatment

Prognostic Factors and Markers in Non-Small Cell Lung Cancer: Recent Progress and Future Challenges

Lung cancer is a highly aggressive neoplasm and, despite the development of recent therapies, tumor progression and recurrence following the initial response remains unsolved. Several questions remain unanswered about non-small cell lung cancer (NSCLC): (1) Which patients will actually benefit from therapy? (2) What are the predictive factors of response to MAbs and TKIs? (3) What are the best combination strategies with conventional treatments or new antineoplastic drugs? To answer these questions, an integrative literature review was carried out, searching articles in PUBMED, NCBI-PMC, Google Academic, and others. Here, we will examine the molecular genetics of lung cancer, emphasizing NSCLC, and delineate the primary categories of inhibitors based on their molecular targets, alongside the main treatment alternatives depending on the type of acquired resistance. We highlighted new therapies based on epigenetic information and a single-cell approach as a potential source of new biomarkers. The current and future of NSCLC management hinges upon genotyping correct prognostic markers, as well as on the evolution of precision medicine, which guarantees a tailored drug combination with precise targeting