Interplay between Cellular and Non-Cellular Components of the Tumour Microenvironment in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and lethal cancers worldwide. Currently, treatments available for advanced HCC provide dismal chances of survival, thus there is an urgent need to develop more effective therapeutic strategies. While much of the focus of recent decades has been on targeting malignant cells, promising results have emerged from targeting the tumour microenvironment (TME). The extracellular matrix (ECM) is the main non-cellular component of the TME and it profoundly changes during tumorigenesis to promote the growth and survival of malignant cells. Despite this, many in vitro models for drug testing fail to consider the TME leading to a high failure rate in clinical trials. Here, we present an overview of the function and properties of the ECM in the liver and how these change during malignant transformation. We also discuss the relationship between immune cells and ECM in the TME in HCC. Lastly, we present advanced, 3D culture techniques of cancer modelling and argue that the incorporation of TME components into these is essential to better recapitulate the complex interactions within the TME.

Development and Application of Patient-Derived Cancer Organoidsin Clinical Management of Gastrointestinal Cancer: A State-of-the-Art Review

Human gastrointestinal cancer (e.g., gastric cancer and colorectal cancer) has been a leading cause of cancer-related deaths worldwide and has imposed a great threat to the public health. Although early-stage gastrointestinal cancer can be effectively treated by surgery, followed by postoperative chemotherapy, patients with advanced gastrointestinal cancer often exhibit poor prognosis and cancer relapse due to the absence of effective personalized treatment strategies. Patient-derived cancer organoid technology has been rapidly developed in recent years, and its emergence has opened up an unprecedented approach to model human cancers in vitro. Patient-derived cancer organoids involve the ex vivo culture of fragments of freshly resected human tumors that retain the histological features of original tumors. This review thoroughly discussed the evolutionary process of human gastrointestinal organoids cultured since 2009, and highlighted the potentials of patient-derived cancer organoids in clinical management of gastrointestinal cancer in terms of advances achieved in cancer modelling compared with conventional modelling methods, high-throughput drug screening, and development of personalized treatment selection. Additionally, the current limitations of patient-derived cancer organoids and the potential solutions to overcome these problems were summarized.

A novel CRISPR activation mouse enables modelling of aggressive lymphoma and interrogation of venetoclax resistance.

CRISPR technologies have advanced cancer modelling in mice, but CRISPR activation (CRISPRa) methods have not been thoroughly exploited in this context. Here we establish a CRISPRa mouse (dCas9a-SAMKI/+) for inducing gene expression in vivo and in vitro. Using dCas9a-SAMKI/KI primary lymphocytes, we induced B cell restricted genes in the T cell lineage and vice versa, demonstrating the power of this system. Next, to model double hit lymphoma (DHL), we transactivated pro-survival BCL-2 in Eµ-MycT/+;dCas9a-SAMKI/+ haematopoietic stem and progenitor cells. Lethally-irradiated mice transplanted with these cells rapidly developed lymphomas expressing high BCL-2. Unlike standard Eµ-Myc lymphomas, BCL-2-expressing lymphomas were highly sensitive to the BCL-2 inhibitor venetoclax. Finally, we performed genome-wide activation screens in these lymphoma cells and found a dominant role for the BCL-2 family protein A1 in venetoclax resistance. This demonstrates the power of our CRISPRa model for mimicking disease and provides insights into potential resistance mechanisms towards targeted therapies.

Inverse Reconstruction of Cell Proliferation Laws in Cancer Invasion Modelling

The process of local cancer cell invasion of the surrounding tissue is key for the overall tumour growth and spread within the human body, the past 3 decades witnessing intense mathematical modelling efforts in these regards. However, for a deep understanding of the cancer invasion process these modelling studies require robust data assimilation approaches. While being of crucial importance in assimilating potential clinical data, the inverse problems approaches in cancer modelling are still in their early stages, with questions regarding the retrieval of the characteristics of tumour cells motility, cells mutations, and cells population proliferation, remaining widely open. This study deals with the identification and reconstruction of the usually unknown cancer cell proliferation law in cancer modelling from macroscopic tumour snapshot data collected at some later stage in the tumour evolution. Considering two basic tumour configurations, associated with the case of one cancer cells population and two cancer cells subpopulations that exercise their dynamics within the extracellular matrix, we combine Tikhonov regularisation and gaussian mollification approaches with finite element and finite differences approximations to reconstruct the proliferation laws for each of these sub-populations from both exact and noisy measurements. Our inverse problem formulation is accompanied by numerical examples for the reconstruction of several proliferation laws used in cancer growth modelling.

CRISPR Cas System: an efficient tool for cancer modelling

The Clustered Regularly Interspaced Short Palindromic Repeats–Cas-9 (CRISPR-Cas9) system has been a revolutionising tool in the field of molecular genetics, which provides a versatile range of editing potentials. Researchers can produce breaks or alter genomes with ease using the system. Cancer is one of the multi-gene diseases whose genes need to be studied in detail. The CRISPR-Cas9 technology may also provide a promising potential in the field of cancer genetics. The current narrative review comprised 50 research articles which were keenly analysed and the applications and outcomes of CRISPR-Cas9 system in cancer genetics were comprehensively and critically discussed. It was concluded that application of the system had great potential to help understand cancer biology of various types and could be used for its genetic modelling. However, much work is still needed to be done to apply the technology for understanding...Continuous...

Impact of Force Function Formulations on the Numerical Simulation of Centre-Based Models

Centre-based or cell-centre models are a framework for the computational study of multicellular systems with widespread use in cancer modelling and computational developmental biology. At the core of these models are the numerical method used to update cell positions and the force functions that encode the pairwise mechanical interactions of cells. For the latter, there are multiple choices that could potentially affect both the biological behaviour captured, and the robustness and efficiency of simulation. For example, available open-source software implementations of centre-based models rely on different force functions for their default behaviour and it is not straightforward for a modeller to know if these are interchangeable. Our study addresses this problem and contributes to the understanding of the potential and limitations of three popular force functions from a numerical perspective. We show empirically that choosing the force parameters such that the relaxation time for two cells after cell division is consistent between different force functions results in good agreement of the population radius of a two-dimensional monolayer relaxing mechanically after intense cell proliferation. Furthermore, we report that numerical stability is not sufficient to prevent unphysical cell trajectories following cell division, and consequently, that too large time steps can cause geometrical differences at the population level.

Impact of force function formulations on the numerical simulation of centre-based models

Centre-based, or cell-centre models are a framework for the computational study of multicellular systems with widespread use in cancer modelling and computational developmental biology. At the core of these models are the numerical method used to update cell positions and the force functions that encode the pairwise mechanical interactions of cells. For the latter there are multiple choices that could potentially affect both the biological behaviour captured, and the robustness and efficiency of simulation. For example, available open-source software implementations of centre-based models rely on different force functions for their default behaviour and it is not straightforward for a modeler to know if these are interchangeable. Our study addresses this problem and contributes to the understanding of the potential and limitations of three popular force functions from a numerical perspective. We show empirically that choosing the force parameters such that the relaxation time for two cells after cell division is consistent between different force functions results in good agreement of the population radius of a growing monolayer. Furthermore, we report that numerical stability is not sufficient to prevent unphysical cell trajectories following cell division, and consequently, that too large time steps can cause geometrical differences at the population level.

Decellularised scaffolds: just a framework? Current knowledge and future directions

The use of decellularised matrices as scaffolds offers the advantage of great similarity with the tissue to be replaced. Moreover, decellularised tissues and organs can be repopulated with the patient’s own cells to produce bespoke therapies. Great progress has been made in research and development of decellularised scaffolds, and more recently, these materials are being used in exciting new areas like hydrogels and bioinks. However, much effort is still needed towards preserving the original extracellular matrix composition, especially its minor components, assessing its functionality and scaling up for large tissues and organs. Emphasis should also be placed on developing new decellularisation methods and establishing minimal criteria for assessing the success of the decellularisation process. The aim of this review is to critically review the existing literature on decellularised scaffolds, especially on the preparation of these matrices, and point out areas for improvement, finishing with alternative uses of decellularised scaffolds other than tissue and organ reconstruction. Such uses include three-dimensional ex vivo platforms for idiopathic diseases and cancer modelling.