Stem cell mutations, associated cancer risk, and consequences for regenerative medicine

Perspective from developers: Tissue-engineered products for skin wound healing

Tissue-engineered products (TEPs) are at the forefront of developmental medicines, precisely where monoclonal antibodies and recombinant cytokines were 30 years ago. TEPs development for treating skin wounds has become a fast-growing field as it offers the potential to find novel therapeutic approaches for treating pathologies that currently have limited or no effective alternatives. This review aims to provide the reader with the process of translating an idea from the laboratory bench to clinical practice, specifically in the context of TEPs designing for skin wound healing It encompasses historical perspectives, approved therapies, and offers a distinctive insight into the regulatory framework in Brazil. We explore the essential guidelines for quality testing, and nonclinical proof-of-concept considering the Brazilian Network of Experts in Advanced Therapies (RENETA) and International Standards and Guidelines (ICH e ISO). Adopting a multifaceted approach, our discussion encompasses scientific and industrial perspectives, addressing quality, biosafety, non-clinical viability, clinical trial and real-word data for pharmacovigilance demands. This comprehensive analysis presents a panoramic view of the development of skin TEPs, offering insights into the evolving landscape of this dynamic and promising field.

Assessing the distribution of cancer stem cells in tumorspheres

Cancer Stem Cells presumably drive tumor growth and resistance to conventional cancer treatments. From a previous computational model, we inferred that these cells are not uniformly distributed in the bulk of a tumorsphere. To confirm this result, we cultivated tumorspheres enriched in stem cells, and performed immunofluorescent detection of the stemness marker SOX2 using confocal microscopy. In this article, we present an image processing method that reconstructs the amount and location of the Cancer Stem Cells in the spheroids. Its advantage is the use of a statistical criterion to classify the cells in Stem and Differentiated, instead of setting an arbitrary threshold. Moreover, the analysis of the experimental images presented in this work agrees with the results from our computational models, thus enforcing the notion that the distribution of Cancer Stem Cells in a tumorsphere is non-homogeneous. Additionally, the method presented here provides a useful tool for analyzing any image in which different kinds of cells are stained with different markers.

The Role of Cancer Stem Cell Markers in Ovarian Cancer

Ovarian cancer is the most lethal gynaecological cancer and the eighth most common female cancer. The early diagnosis of ovarian cancer remains a clinical problem despite the significant development of technology. Nearly 70% of patients with ovarian cancer are diagnosed with stages III-IV metastatic disease. Reliable diagnostic and prognostic biomarkers are currently lacking. Ovarian cancer recurrence and resistance to chemotherapy pose vital problems and translate into poor outcomes. Cancer stem cells appear to be responsible for tumour recurrence resulting from chemotherapeutic resistance. These cells are also crucial for tumour initiation due to the ability to self-renew, differentiate, avoid immune destruction, and promote inflammation and angiogenesis. Studies have confirmed an association between CSC occurrence and resistance to chemotherapy, subsequent metastases, and cancer relapses. Therefore, the elimination of CSCs appears important for overcoming drug resistance and improving prognoses. This review focuses on the expression of selected ovarian CSC markers, including CD133, CD44, CD24, CD117, and aldehyde dehydrogenase 1, which show potential prognostic significance. Some markers expressed on the surface of CSCs correlate with clinical features and can be used for the diagnosis and prognosis of ovarian cancer. However, due to the heterogeneity and plasticity of CSCs, the determination of specific CSC phenotypes is difficult.