The role of Jagged1 as a dynamic switch of cancer cell plasticity in PDAC assembloids

Factors Influencing the Diagnostic Performance of Repeat Endoscopic Ultrasound-Guided Fine-Needle Aspiration/Biopsy after the First Inconclusive Diagnosis of Pancreatic Solid Lesions

Background/Aims

Endoscopic ultrasound-guided fine-needle aspiration/biopsy (EUS-FNA/B) is essential in diagnosing solid pancreatic lesions (SPLs), but without rapid on-site evaluation (ROSE), a repeat EUS-FNA/B is crucial for clarifying an inconclusive diagnosis. We aimed to evaluate factors associated with improved diagnostic performance of repeat EUS-FNA/B for initially inconclusive SPL diagnoses without ROSE.

Methods

Of 5,894 patients subjected to EUS-FNA/B, 237 (4.0%) with an initially inconclusive diagnosis of SPLs were retrospectively enrolled from five tertiary medical centers between January 2016 and June 2021. Diagnostic performance and procedural factors of EUS-FNA/B were analyzed.

Results

The diagnostic accuracies of first and repeat EUS-FNA/B were 96.2% and 67.6%, respectively. Of 237 patients with an inconclusive diagnosis from initial EUS-FNA/B, 150 were pathologically diagnosed after repeat EUS-FNA/B. In multivariate analysis of repeat EUS-FNA/B, tumor location (body/tail vs head: odds ratio [OR], 3.74; 95% confidence interval [CI], 1.48 to 9.46), number of needle passes (≥4 vs ≤3: OR, 4.80; 95% CI, 1.44 to 15.99), needle type (FNB vs FNA: OR, 3.26; 95% CI, 1.44 to 7.36), needle size (22 gauge vs 19/20 gauge: OR, 2.35; 95% CI, 1.19 to 4.62), and suction method (suction vs others: OR, 5.19; 95% CI, 1.30 to 20.75) were associated with a significantly improved diagnostic performance.

Conclusions

Repeat EUS-FNA/B is essential for patients with an inconclusive EUS-FNA/B without ROSE. To improve the diagnostic performance of repeated EUS-FNA/B, it is recommended that 22-gauge FNB needles, ≥4 needle passes, and suction methods are used.

Construction of tumor organoids and their application to cancer research and therapy

Cancer remains a severe public health burden worldwide. One of the challenges hampering effective cancer therapy is that the existing cancer models hardly recapitulate the tumor microenvironment of human patients. Over the past decade, tumor organoids have emerged as an in vitro 3D tumor model to mimic the pathophysiological characteristics of parental tumors. Various techniques have been developed to construct tumor organoids, such as matrix-based methods, hanging drop, spinner or rotating flask, nonadhesive surface, organ-on-a-chip, 3D bioprinting, and genetic engineering. This review elaborated on cell components and fabrication methods for establishing tumor organoid models. Furthermore, we discussed the application of tumor organoids to cancer modeling, basic cancer research, and anticancer therapy. Finally, we discussed current limitations and future directions in employing tumor organoids for more extensive applications.

Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid-Based 3D In Vitro Models

Modeling the heterogeneity of the tumor microenvironment (TME) in vitro is essential to investigating fundamental cancer biology and developing novel treatment strategies that holistically address the factors affecting tumor progression and therapeutic response. Thus, the development of new tools for both in vitro modeling, such as patient-derived organoids (PDOs) and complex 3D in vitro models, and single cell omics analysis, such as single-cell RNA-sequencing, represents a new frontier for investigating tumor heterogeneity. Specifically, the integration of PDO-based 3D in vitro models and single cell analysis offers a unique opportunity to explore the intersecting effects of interpatient, microenvironmental, and tumor cell heterogeneity on cell phenotypes in the TME. In this review, the current use of PDOs in complex 3D in vitro models of the TME is discussed and the emerging directions in the development of these models are highlighted. Next, work that has successfully applied single cell analysis to PDO-based models is examined and important experimental considerations are identified for this approach. Finally, open questions are highlighted that may be amenable to exploration using the integration of PDO-based models and single cell analysis. Ultimately, such investigations may facilitate the identification of novel therapeutic targets for cancer that address the significant influence of tumor-TME interactions.

The third dimension of tumor microenvironment-The importance of tumor stroma in 3D cancer models

Recent advances in the three-dimensional (3D) cancer models give rise to a plethora of new possibilities in the development of anti-cancer drug therapies and bring us closer to personalized medicine. Three-dimensional models are undoubtedly more authentic than traditional two-dimensional (2D) cell cultures. Nowadays, they are becoming preferentially used in most cancer research fields due to their more accurate biomimetic characteristics. On the contrary, they still lack the cellular and matrix complexity of the native tumor microenvironment (TME). This review focuses on the description of existing 3D models, the incorporation of TME and fluidics into these models, and their perspective in the future research. It is clear that such an improvement would need not only biological but also technical progress. Therefore, the modern approach to anti-cancer drug discovery should involve various fields.

Gene expression in organoids: an expanding horizon

Recent development of human three-dimensional organoid cultures has opened new doors and opportunities ranging from modelling human development in vitro to personalised cancer therapies. These new in vitro systems are opening new horizons to the classic understanding of human development and disease. However, the complexity and heterogeneity of these models requires cutting-edge techniques to capture and trace global changes in gene expression to enable identification of key players and uncover the underlying molecular mechanisms. Rapid development of sequencing approaches made possible global transcriptome analyses and epigenetic profiling. Despite challenges in organoid culture and handling, these techniques are now being adapted to embrace organoids derived from a wide range of human tissues. Here, we review current state-of-the-art multi-omics technologies, such as single-cell transcriptomics and chromatin accessibility assays, employed to study organoids as a model for development and a platform for precision medicine.

The application of pancreatic cancer organoids for novel drug discovery

INTRODUCTION

Pancreatic ductal adenocarcinoma presents with a dismal prognosis. Personalized therapy is urgently warranted to overcome the treatment limitations of the "one-size-fits-all" scheme. Organoids have emerged as fundamental novel tools to study tumor biology and heterogeneity, hence overcoming limitations of other model systems by better-reflecting tissue heterogeneity and recapitulating in-vivo processes. Besides their crucial role in basic research, they have evolved as tools for translational drug discovery and patient stratification.

AREAS COVERED

This review highlights the achievements of an organoid-based drug investigation and discovery. The authors present an overview of studies using organoids for drug testing. Further, they pinpoint studies correlating the in vitro prediction of organoids to the actual patient`s response. Furthermore, the authors describe novel model systems and take a thorough overlook of microfluidic chips, synthetic matrices, multicellular systems, bioprinting, and stem cell-derived pancreatic organoid systems.

EXPERT OPINION

Organoid systems promise great potential for future clinical applications. Indeed, they may be implemented into informed decision-making for guiding therapies. However, validation by randomized trials is mandatory. Additionally, organoids in combination with other cellular compartments may be exploited for drug discovery by studying niche-tumor interaction. Yet, several precautions must be kept in mind, such as standardization and reproducibility.