ABSTRACT
Cancer therapy is facing increasingly significant challenges, marked by a wide range of techniques and research efforts centered around somatic mutations, precision oncology, and the vast amount of big data. Despite this abundance of information, the quest to cure cancer often seems more elusive, with the "war on cancer" yet to deliver a definitive victory. A particularly pressing issue is the development of tumor treatment resistance, highlighting the urgent need for innovative approaches. Evolutionary, Quantum Biology and System Biology offer a promising framework for advancing experimental cancer research. By integrating theoretical studies, translational methods, and flexible multidisciplinary clinical research, there's potential to enhance current treatment strategies and improve outcomes for cancer patients. Establishing stronger links between evolutionary, quantum, entropy and chaos principles and oncology could lead to more effective treatments that leverage an understanding of the tumor's evolutionary dynamics, paving the way for novel methods to control and mitigate cancer. Achieving these objectives necessitates a commitment to multidisciplinary and interprofessional collaboration at the heart of both research and clinical endeavors in oncology. This entails dismantling silos between disciplines, encouraging open communication and data sharing, and integrating diverse viewpoints and expertise from the outset of research projects. Being receptive to new scientific discoveries and responsive to how patients react to treatments is also crucial. Such strategies are key to keeping the field of oncology at the forefront of effective cancer management, ensuring patients receive the most personalized and effective care. Ultimately, this approach aims to push the boundaries of cancer understanding, treating it as a manageable chronic condition, aiming to extend life expectancy and enhance patient quality of life.
ABSTRACT
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.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Humans , Carcinoma, Non-Small-Cell Lung/drug therapy , Carcinoma, Non-Small-Cell Lung/genetics , Carcinoma, Non-Small-Cell Lung/metabolism , Lung Neoplasms/diagnosis , Lung Neoplasms/drug therapy , Lung Neoplasms/genetics , Prognosis , Drug Resistance, Neoplasm/genetics , ErbB Receptors/genetics , Protein Kinase Inhibitors/pharmacology , MutationABSTRACT
OBJECTIVES: To contribute to a better understanding of the maternal genetic mechanisms that influence obstetric outcomes and that are involved in maternal and child health, this study aimed to evaluate the association between maternal genetic variants and the offspring birth weight by analyzing single-nucleotide polymorphisms (SNPs) in genes related to glucose homeostasis. METHODS: Three polymorphisms were analyzed (GCK rs1799884, TCF7L2 rs7903146 and LEPR rs1137101) in 250 pregnant women who participated in a Brazilian prospective cohort study. Genotyping was performed by Real-Time Polymerase Chain Reaction (qPCR) using pre-designed TaqMan® SNP genotyping assays. Vitamin D dosage was performed by chemiluminescence. Variance, Pearson's chi-square test and multiple linear regression were used for the statistical analysis. RESULTS: It was possible to verify a significant association between birth weight and maternal GCK rs1799884 when obstetric outcomes, clinical and anthropometric characteristics were taken into consideration. The children of homozygous women for the minor allele GCK rs1799884 presented lower birth weight (ß = -335.25, 95% CI = -669.39; -1.17, p = 0.04). Furthermore, a direct link between a leptin receptor variant and gestational duration was found (p = 0.037). CONCLUSION: The variant GCK rs1799884 (mm) was associated with a reduction in newborn weight in the miscegenated Brazilian population.