Organoid cultures for cancer modeling

From Organ-on-a-Chip to Human-on-a-Chip: A Review of Research Progress and Latest Applications

Organ-on-a-Chip (OOC) technology, which emulates the physiological environment and functionality of human organs on a microfluidic chip, is undergoing significant technological advancements. Despite its rapid evolution, this technology is also facing notable challenges, such as the lack of vascularization, the development of multiorgan-on-a-chip systems, and the replication of the human body on a single chip. The progress of microfluidic technology has played a crucial role in steering OOC toward mimicking the human microenvironment, including vascularization, microenvironment replication, and the development of multiorgan microphysiological systems. Additionally, advancements in detection, analysis, and organoid imaging technologies have enhanced the functionality and efficiency of Organs-on-Chips (OOCs). In particular, the integration of artificial intelligence has revolutionized organoid imaging, significantly enhancing high-throughput drug screening. Consequently, this review covers the research progress of OOC toward Human-on-a-chip, the integration of sensors in OOCs, and the latest applications of organoid imaging technologies in the biomedical field.

OLFM4 promotes the progression of intestinal metaplasia through activation of the MYH9/GSK3β/β-catenin pathway

BACKGROUND

Intestinal metaplasia (IM) is classified into complete intestinal metaplasia (CIM) and incomplete intestinal metaplasia (IIM). Patients diagnosed with IIM face an elevated susceptibility to the development of gastric cancer, underscoring the critical need for early screening measures. In addition to the complexities associated with diagnosis, the exact mechanisms driving the progression of gastric cancer in IIM patients remain poorly understood. OLFM4 is overexpressed in several types of tumors, including colorectal, gastric, pancreatic, and ovarian cancers, and its expression has been associated with tumor progression.

METHODS

In this study, we used pathological sections from two clinical centers, biopsies of IM tissues, precancerous lesions of gastric cancer (PLGC) cell models, animal models, and organoids to explore the role of OLFM4 in IIM.

RESULTS

Our results show that OLFM4 expression is highly increased in IIM, with superior diagnostic accuracy of IIM when compared to CDX2 and MUC2. OLFM4, along with MYH9, was overexpressed in IM organoids and PLGC animal models. Furthermore, OLFM4, in combination with Myosin heavy chain 9 (MYH9), accelerated the ubiquitination of GSK3β and resulted in increased β-catenin levels through the Wnt signaling pathway, promoting the proliferation and invasion abilities of PLGC cells.

CONCLUSIONS

OLFM4 represents a novel biomarker for IIM and could be utilized as an important auxiliary means to delimit the key population for early gastric cancer screening. Finally, our study identifies cell signaling pathways involved in the progression of IM.

Vitamin D opposes multilineage cell differentiation induced by Notch inhibition and BMP4 pathway activation in human colon organoids

Understanding the mechanisms involved in colonic epithelial differentiation is key to unraveling the alterations causing inflammatory conditions and cancer. Organoid cultures provide an unique tool to address these questions but studies are scarce. We report a differentiation system toward enterocytes and goblet cells, the two major colonic epithelial cell lineages, using colon organoids generated from healthy tissue of colorectal cancer patients. Culture of these organoids in medium lacking stemness agents resulted in a modest ultrastructural differentiation phenotype with low-level expression of enterocyte (KLF4, KRT20, CA1, FABP2) and goblet cell (TFF2, TFF3, AGR2) lineage markers. BMP pathway activation through depletion of Noggin and addition of BMP4 resulted in enterocyte-biased differentiation. Contrarily, blockade of the Notch pathway using the γ-secretase inhibitor dibenzazepine (DBZ) favored goblet cell differentiation. Combination treatment with BMP4 and DBZ caused a balanced strong induction of both lineages. In contrast, colon tumor organoids responded poorly to BMP4 showing only weak signals of cell differentiation, and were unresponsive to DBZ. We also investigated the effects of 1α,25-dihydroxyvitamin D3 (calcitriol) on differentiation. Calcitriol attenuated the effects of BMP4 and DBZ on colon normal organoids, with reduced expression of differentiation genes and phenotype. Consistently, in normal organoids, calcitriol inhibited early signaling by BMP4 as assessed by reduction of the level of phospho-SMAD1/5/8. Our results show that BMP and Notch signaling play key roles in human colon stem cell differentiation to the enterocytic and goblet cell lineages and that calcitriol modulates these processes favoring stemness features.

Embracing cancer complexity: Hallmarks of systemic disease

The last 50 years have witnessed extraordinary developments in understanding mechanisms of carcinogenesis, synthesized as the hallmarks of cancer. Despite this logical framework, our understanding of the molecular basis of systemic manifestations and the underlying causes of cancer-related death remains incomplete. Looking forward, elucidating how tumors interact with distant organs and how multifaceted environmental and physiological parameters impinge on tumors and their hosts will be crucial for advances in preventing and more effectively treating human cancers. In this perspective, we discuss complexities of cancer as a systemic disease, including tumor initiation and promotion, tumor micro- and immune macro-environments, aging, metabolism and obesity, cancer cachexia, circadian rhythms, nervous system interactions, tumor-related thrombosis, and the microbiome. Model systems incorporating human genetic variation will be essential to decipher the mechanistic basis of these phenomena and unravel gene-environment interactions, providing a modern synthesis of molecular oncology that is primed to prevent cancers and improve patient quality of life and cancer outcomes.

The microtubule cytoskeleton: A validated target for the development of 2-Aryl-1H-benzo[d]imidazole derivatives as potential anticancer agents

In this study, a series of 2-Aryl-1H-benzo[d]imidazole derivatives were developed to target intra- and extracellular microtubule networks. Compounds O-7 and O-10 showed impressive anti-proliferative activity across various tested cell lines, demonstrating selectivity indexes of 151.7 and 61.9, respectively. O-7 achieved an IC50 value of 0.236 ± 0.096 μM, while O-10 showed an IC50 value of 0.622 ± 0.13 μM against A549 cell lines. The induction of early-stage apoptosis in a dose-dependent manner further underscored the potential of O-7 and O-10 as effective anti-proliferative agents. O-7 and O-10 exhibited substantial inhibition of wound closure, with wound closure percentages decreasing from 23% at 0 μM to 0.43% and 2.62% at 20 μM, respectively. Colony formation reduction rates were impressive, with O-7 at 74.2% and O-10 at 81.2%. These results indicate that the O-7 and O-10 can impede cancer cell migration and have a high potential to curtail colony formation. The mode of action investigations for O-7 and O-10 revealed that O-7 could inhibit in vitro tubulin polymerization and disrupt the intracellular microtubule cytoskeleton. This disruption led to cell cycle arrest in the G2/M phase, indicating that O-7 exerts its anticancer activity through microtubule destabilization. However, O-10 shows a different mode of action than O-7 and requires further investigation. Overall, our study showcases the potential of the synthesized benzimidazole derivatives as novel and selective anticancer agents, motivating further exploration of their pharmacological properties and therapeutic applications.

Genetically-engineered mouse models of small cell lung cancer: the next generation

Small cell lung cancer (SCLC) remains the most fatal form of lung cancer, with patients in dire need of new and effective therapeutic approaches. Modeling SCLC in an immunocompetent host is essential for understanding SCLC pathogenesis and ultimately discovering and testing new experimental therapeutic strategies. Human SCLC is characterized by near universal genetic loss of the RB1 and TP53 tumor suppressor genes. Twenty years ago, the first genetically-engineered mouse model (GEMM) of SCLC was generated using conditional deletion of both Rb1 and Trp53 in the lungs of adult mice. Since then, several other GEMMs of SCLC have been developed coupling genomic alterations found in human SCLC with Rb1 and Trp53 deletion. Here we summarize how GEMMs of SCLC have contributed significantly to our understanding of the disease in the past two decades. We also review recent advances in modeling SCLC in mice that allow investigators to bypass limitations of the previous generation of GEMMs while studying new genes of interest in SCLC. In particular, CRISPR/Cas9-mediated somatic gene editing can accelerate how new genes of interest are functionally interrogated in SCLC tumorigenesis. Notably, the development of allograft models and precancerous precursor models from SCLC GEMMs provides complementary approaches to GEMMs to study tumor cell-immune microenvironment interactions and test new therapeutic strategies to enhance response to immunotherapy. Ultimately, the new generation of SCLC models can accelerate research and help develop new therapeutic strategies for SCLC.

Analysis of organoid and immune cell co-cultures by machine learning-empowered image cytometry

Organoids are three-dimensional (3D) structures that can be derived from stem cells or adult tissue progenitor cells and exhibit an extraordinary ability to autonomously organize and resemble the cellular composition and architectural integrity of specific tissue segments. This feature makes them a useful tool for analyzing therapeutical relevant aspects, including organ development, wound healing, immune disorders and drug discovery. Most organoid models do not contain cells that mimic the neighboring tissue’s microenvironment, which could potentially hinder deeper mechanistic studies. However, to use organoid models in mechanistic studies, which would enable us to better understand pathophysiological processes, it is necessary to emulate the in situ microenvironment. This can be accomplished by incorporating selected cells of interest from neighboring tissues into the organoid culture. Nevertheless, the detection and quantification of organoids in such co-cultures remains a major technical challenge. These imaging analysis approaches would require an accurate separation of organoids from the other cell types in the co-culture. To efficiently detect and analyze 3D organoids in co-cultures, we developed a high-throughput imaging analysis platform. This method integrates automated imaging techniques and advanced image processing tools such as grayscale conversion, contrast enhancement, membrane detection and structure separation. Based on machine learning algorithms, we were able to identify and classify 3D organoids within dense co-cultures of immune cells. This procedure allows a high-throughput analysis of organoid-associated parameters such as quantity, size, and shape. Therefore, the technology has significant potential to advance contextualized research using organoid co-cultures and their potential applications in translational medicine.

Patient-Derived Xenograft Models for Ovarian Cancer

Patient-derived xenograft (PDX) models play a crucial role for in vivo research. They maintain the original molecular characteristics of the human tumor and provide a more accurate tumor microenvironment, which cannot be replicated by in vitro models. This chapter describes four different transplantation methods, namely, intra-bursal, intrarenal capsule, intraperitoneal, and subcutaneous, to develop PDX models for ovarian cancer research.

Advances of Osteosarcoma Models for Drug Discovery and Precision Medicine

The management of osteosarcoma (OS) patients presents a significant clinical challenge. Despite progress in conventional and targeted therapies, the survival rate of OS patients remains limited largely due to therapy resistance and the high metastatic potential of the disease. OS models that accurately reflect the fundamental characteristics are vital to the innovation and validation of effective therapies. This review provides an insight into the advances and challenges in OS drug development, focusing on various preclinical models, including cell lines, 3D culture models, murine models, and canine models. The relevance, strengths, and limitations of each model in OS research are explored. In particular, we highlight a range of potential therapeutics identified through these models. These instances of successful drug development represent promising pathways for personalized OS treatment.