3D Sponge-Matrix Histoculture: An Overview

Mouse models in colon cancer, inferences, and implications

Mouse models of colorectal cancer (CRC) have been crucial in the identification of the role of genes responsible for the full range of pathology of the human disease and have proved to be dependable for testing anti-cancer drugs. Recent research points toward the relevance of tumor, angiogenic, and immune microenvironments in CRC progression to late-stage disease, as well as the treatment of it. This study examines important mouse models in CRC, discussing inherent strengths and weaknesses disclosed during their construction. It endeavors to provide both a synopsis of previous work covering how investigators have defined various models and to evaluate critically how researchers are most likely to use them in the future. Accumulated evidence regarding the metastatic process and the hope of using checkpoint inhibitors and immunological inhibitor therapies points to the need for a genetically engineered mouse model that is both immunocompetent and autochthonous.

Metabolic Priming as a Tool in Redox and Mitochondrial Theragnostics

Theragnostics is a promising approach that integrates diagnostics and therapeutics into a single personalized strategy. To conduct effective theragnostic studies, it is essential to create an in vitro environment that accurately reflects the in vivo conditions. In this review, we discuss the importance of redox homeostasis and mitochondrial function in the context of personalized theragnostic approaches. Cells have several ways to respond to metabolic stress, including changes in protein localization, density, and degradation, which can promote cell survival. However, disruption of redox homeostasis can lead to oxidative stress and cellular damage, which are implicated in various diseases. Models of oxidative stress and mitochondrial dysfunction should be developed in metabolically conditioned cells to explore the underlying mechanisms of diseases and develop new therapies. By choosing an appropriate cellular model, adjusting cell culture conditions and validating the cellular model, it is possible to identify the most promising therapeutic options and tailor treatments to individual patients. Overall, we highlight the importance of precise and individualized approaches in theragnostics and the need to develop accurate in vitro models that reflect the in vivo conditions.

Current status and future outlook for patient-derived cancer models from a rare cancer research perspective

Rare cancers are a group of approximately 200 malignancies with extremely low incidences and with a wide variety of genotypes and phenotypes. Collectively, they are more common than any single malignancy. However, given the small numbers of individuals diagnosed with rare cancers, it is difficult to design clinical trials with sufficient patient numbers. Therefore, few effective anticancer drugs have been developed, and evidence‐based medicine is not always feasible for rare cancers. Consequently, their clinical outcomes are generally poorer. Cancer research requires adequate models that faithfully recapitulate molecular features and reproduce treatment responses of the original tumors. Such models allow us to focus on more efficacious drugs in the clinical studies. For rare cancers, patient‐derived cancer models are particularly important because the enrollment of sufficient patients is rarely attainable within a reasonable period of time. However, extremely few models are available for rare cancers. For example, cell lines and xenografts are available for only a limited number of histological subtypes of sarcomas; therefore, most sarcoma research is performed without such models, and a lack of adequate cancer models causes a lag in therapeutic development. The establishment of novel rare cancer models will dramatically facilitate rare cancer research and treatment development in the near future. This review focuses on the status of patient‐derived rare cancer models and discusses their pivotal problems and possibilities, using sarcomas as a representative rare cancer type. Multi‐institutional collaboration will help address the scarcity of patient‐derived rare cancer models.

Designer Self-Assembling Peptide Hydrogels to Engineer 3D Cell Microenvironments for Cell Constructs Formation and Precise Oncology Remodeling in Ovarian Cancer

Designer self-assembling peptides form the entangled nanofiber networks in hydrogels by ionic-complementary self-assembly. This type of hydrogel has realistic biological and physiochemical properties to serve as biomimetic extracellular matrix (ECM) for biomedical applications. The advantages and benefits are distinct from natural hydrogels and other synthetic or semisynthetic hydrogels. Designer peptides provide diverse alternatives of main building blocks to form various functional nanostructures. The entangled nanofiber networks permit essential compositional complexity and heterogeneity of engineering cell microenvironments in comparison with other hydrogels, which may reconstruct the tumor microenvironments (TMEs) in 3D cell cultures and tissue-specific modeling in vitro. Either ovarian cancer progression or recurrence and relapse are involved in the multifaceted TMEs in addition to mesothelial cells, fibroblasts, endothelial cells, pericytes, immune cells, adipocytes, and the ECM. Based on the progress in common hydrogel products, this work focuses on the diverse designer self-assembling peptide hydrogels for instructive cell constructs in tissue-specific modeling and the precise oncology remodeling for ovarian cancer, which are issued by several research aspects in a 3D context. The advantages and significance of designer peptide hydrogels are discussed, and some common approaches and coming challenges are also addressed in current complex tumor diseases.

Patient-derived explants (PDEs) as a powerful preclinical platform for anti-cancer drug and biomarker discovery

Preclinical models that can accurately predict outcomes in the clinic are much sought after in the field of cancer drug discovery and development. Existing models such as organoids and patient-derived xenografts have many advantages, but they suffer from the drawback of not contextually preserving human tumour architecture. This is a particular problem for the preclinical testing of immunotherapies, as these agents require an intact tumour human-specific microenvironment for them to be effective. In this review, we explore the potential of patient-derived explants (PDEs) for fulfilling this need. PDEs involve the ex vivo culture of fragments of freshly resected human tumours that retain the histological features of original tumours. PDE methodology for anti-cancer drug testing has been in existence for many years, but the platform has not been widely adopted in translational research facilities, despite strong evidence for its clinical predictivity. By modifying PDE endpoint analysis to include the spatial profiling of key biomarkers by using multispectral imaging, we argue that PDEs offer many advantages, including the ability to correlate drug responses with tumour pathology, tumour heterogeneity and changes in the tumour microenvironment. As such, PDEs are a powerful model of choice for cancer drug and biomarker discovery programmes.