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?”
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.