Breast cancer is the second most frequent cancer in the world. It is a heterogeneous disease and the leading cause of cancer mortality in women. Advances in molecular technologies allowed for the identification of new and more specifics biomarkers for breast cancer diagnosis, prognosis, and risk prediction, enabling personalized treatments, improving therapy, and preventing overtreatment, undertreatment, and incorrect treatment. Several breast cancer biomarkers have been identified and, along with traditional biomarkers, they can assist physicians throughout treatment plan and increase therapy success. Despite the need of more data to improve specificity and determine the real clinical utility of some biomarkers, others are already established and can be used as a guide to make treatment decisions. In this review, we summarize the available traditional, novel, and potential biomarkers while also including gene expression profiles, breast cancer single-cell and polyploid giant cancer cells. We hope to help physicians understand tumor specific characteristics and support decision-making in patient-personalized clinical management, consequently improving treatment outcome.
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?”.
Introdução: A diabetes tipo 2 (DM2) é uma desordem metabólica ocasionada pela disfunção das células beta pancreáticas que interferem na produção de insulina e/ ou pela resistência dos órgãos alvos a esse hormônio. Níveis elevados de radicais livres em conjunto com o declínio das defesas antioxidantes presente na DM2 podem ocasionar danos a organelas celulares, promovendo complicações da doença. As glutationas S-transferases (GST) são as principais enzimas antioxidantes que participam da defesa celular contra o estresse oxidativo. Os polimorfismos nos genes que codificam essas enzimas podem acarretar o surgimento de complicações oftalmológicas em diabéticos. Este trabalho avaliou a influência dos polimorfismos nos genes GST no desenvolvimento de doenças como a catarata e o glaucoma em pacientes com DM2 na Grande Vitória (ES). Metodologia: Os polimorfismos dos genes GSTM1 e GSTT1 foram investigados através da técnica de PCR multiplex. Para o gene GSTP1 utilizou-se a técnica PCR-RFLP. A análise estatística foi realizada através do teste exato de Fisher ou do teste do qui-quadrado com P-valor < 0.05.Resultados: Não foi encontrada relação entre os polimorfismos nos genes GSTM1, GSTT1 e GSTP1 e o surgimento de doenças como glaucoma e catarata em pacientes com DM2.Conclusão: Nossos dados sugerem que os polimorfismos nulos nos genes GSTM1 e GSTT1 e o polimorfismo Ile105Val no gene GSTP1 não estão associados com a suscetibilidade individual para o desenvolvimento de complicações oftalmológicas em pacientes com DM2.
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