I-AbACUS: a Reliable Software Tool for the Semi-Automatic Analysis of Invasion and Migration Transwell Assays

Accurate Identification of Cancer Cells in Complex Pre-Clinical Models Using a Deep-Learning Neural Network: A Transfection-Free Approach

3D co-cultures are key tools for in vitro biomedical research as they recapitulate more closely the in vivo environment while allowing a tighter control on the culture's composition and experimental conditions. The limited technologies available for the analysis of these models, however, hamper their widespread application. The separation of the contribution of the different cell types, in particular, is a fundamental challenge. In this work, ORACLE (OvaRiAn Cancer ceLl rEcognition) is presented, a deep neural network trained to distinguish between ovarian cancer and healthy cells based on the shape of their nucleus. The extensive validation that are conducted includes multiple cell lines and patient-derived cultures to characterize the effect of all the major potential confounding factors. High accuracy and reliability are maintained throughout the analysis (F1score> 0.9 and Area under the ROC curve -ROC-AUC- score = 0.99) demonstrating ORACLE's effectiveness with this detection and classification task. ORACLE is freely available (https://github.com/MarilisaCortesi/ORACLE/tree/main) and can be used to recognize both ovarian cancer cell lines and primary patient-derived cells. This feature is unique to ORACLE and thus enables for the first time the analysis of in vitro co-cultures comprised solely of patient-derived cells.

Beyond 2D cell cultures: how 3D models are changing the in vitro study of ovarian cancer and how to make the most of them

3D cell cultures are a fundamental tool in ovarian cancer research that can enable more effective study of the main features of this lethal disease, including the high rates of recurrence and chemoresistance. A clearer, more comprehensive understanding of the biological underpinnings of these phenomena could aid the development of more effective treatments thus improving patient outcomes. Selecting the most appropriate model to investigate the different aspects of cell biology that are relevant to cancer is challenging, especially since the assays available for the study of 3D cultures are not fully established yet. To maximise the usefulness of 3D cell cultures of ovarian cancer, we undertook an in-depth review of the currently available models, taking into consideration the strengths and limitations of each approach and of the assay techniques used to evaluate the results. This integrated analysis provides insight into which model-assay pair is best suited to study different parameters of ovarian cancer biology such as cell proliferation, gene expression or treatment response. We also describe how the combined use of multiple models is likely to be the most effective strategy for the in vitro characterisation of complex behaviours.

A comparative analysis of 2D and 3D experimental data for the identification of the parameters of computational models

Computational models are becoming an increasingly valuable tool in biomedical research. Their accuracy and effectiveness, however, rely on the identification of suitable parameters and on appropriate validation of the in-silico framework. Both these steps are highly dependent on the experimental model used as a reference to acquire the data. Selecting the most appropriate experimental framework thus becomes key, together with the analysis of the effect of combining results from different experimental models, a common practice often necessary due to limited data availability. In this work, the same in-silico model of ovarian cancer cell growth and metastasis, was calibrated with datasets acquired from traditional 2D monolayers, 3D cell culture models or a combination of the two. The comparison between the parameters sets obtained in the different conditions, together with the corresponding simulated behaviours, is presented. It provides a framework for the study of the effect of the different experimental models on the development of computational systems. This work also provides a set of general guidelines for the comparative testing and selection of experimental models and protocols to be used for parameter optimization in computational models.

Berberine alkaloids inhibit the proliferation and metastasis of breast carcinoma cells involving Wnt/β-catenin signaling and EMT

Berberine alkaloids belong to the class of isoquinoline alkaloids that have been shown to possess anticancer potential, berberine exhibits inhibitory effects on breast cancer development. However, the exact mechanisms of action for anti-breast carcinoma of the alkaloids, including epiberberine, berberrubine and dihydroberberine are still unclear. MTT assay, colony formation, wound healing and transwell invasion assays detected these alkaloids suppressed proliferation, migration and invasion of breast cancer cells. Hoechst and Annexin V-FITC/PI staining were used to analyze the apoptosis of breast cancer cells. Western blotting investigated the changes noted in the expression levels of the key proteins involved in the Wnt/β-catenin signaling pathway and epithelial to mesenchymal transition (EMT). The results showed that inhibited the proliferation of breast cancer cells. Berberine alkaloids inhibited the cell cycle at G2/M phase in MCF-7 cells, but in MDA-MB-231 cells berberine alkaloids arrested the cell cycle in G0/G1 and G2/M phases. By decreasing β-catenin expression, increasing GSK-3β expression and decreasing N-cadherin expression, increasing E-cadherin expression, which proved that epiberberine, berberrubine and dihydroberberine inhibited of metastasis of breast cancer cells through Wnt signaling pathway and reversed EMT except berberine. Furthermore, berberine alkaloids exert their anti-breast cancer effects through the synergistic action of intrinsic and extrinsic pathways of apoptosis. These findings highlight the different effects of different berberine alkaloids on breast cancer cells and confirm that berberine alkaloids may be potentially used in the treatment of breast cancer.

Non-destructive monitoring of 3D cell cultures: new technologies and applications

3D cell cultures are becoming the new standard for cell-based in vitro research, due to their higher transferrability toward in vivo biology. The lack of established techniques for the non-destructive quantification of relevant variables, however, constitutes a major barrier to the adoption of these technologies, as it increases the resources needed for the experimentation and reduces its accuracy. In this review, we aim at addressing this limitation by providing an overview of different non-destructive approaches for the evaluation of biological features commonly quantified in a number of studies and applications. In this regard, we will cover cell viability, gene expression, population distribution, cell morphology and interactions between the cells and the environment. This analysis is expected to promote the use of the showcased technologies, together with the further development of these and other monitoring methods for 3D cell cultures. Overall, an extensive technology shift is required, in order for monolayer cultures to be superseded, but the potential benefit derived from an increased accuracy of in vitro studies, justifies the effort and the investment.

A brief very-low oxygen tension regimen is sufficient for the early chondrogenic commitment of human adipose-derived mesenchymal stem cells

PURPOSE

The aim of this study was to evaluate the effects exerted over chondrogenic commitment of human adipose-derived mesenchymal stem cells (ADSCs) by a very low oxygen tension (<1% pO₂).

MATERIALS/METHODS

Cell morphology, mRNA levels of chondrocyte-specific marker genes and the involvement of p38 MAPK signalling were monitored in human ADSCs under a very low oxygen tension.

RESULTS

Cell morphology was significantly changed after two days of hypoxic preconditioning when they featured as elongated spindle-shaped cells. SRY-box containing gene 9, aggrecan and collagen type II mRNA levels were enhanced under severe hypoxic culture conditions. Moreover, the inhibition of p38 MAPK resulted in a substantial reduction in transcription of the above-mentioned specific genes, proving the pivotal role of this pathway in the transcriptional regulation of chondrogenesis.

CONCLUSIONS

Here, we propose a protocol showing the early commitment of stem cells towards the chondrogenic phenotype in only 2 days of culture via a very low hypoxic environment, in the absence of growth factors added in the culture medium.

Perfusion Flow Enhances Viability and Migratory Phenotype in 3D-Cultured Breast Cancer Cells

Conventional 2D cell culture, a traditional tool in pre-clinical studies, can hardly be regarded as a representation of a natural cell microenvironment. In this respect, it might result in altered cellular behaviors. To overcome such a limitation, different approaches have been tested to conduct more representative in vitro studies. In particular, the use of 3D cell culture introduces variables, such as cell-cell and cell-extracellular matrix interactions; cell features such as survival, proliferation and migration are consequently influenced. For an example, an enhanced drug resistance and increased invasiveness are shown by cancer cells when cultured in 3D versus 2D conventional culture models. In this setting however, non-uniform cell distribution and biological behaviors appear throughout the scaffold, due to reduced diffusion of oxygen and nutrients. Perfusion in bioreactor systems can be used to improve medium transport. In this line of reasoning, this study proposes a breast cancer cell culture model sustained by an integrated approach that couples a 3D environment and a fluid perfusion. This model improves viability and uniformness of cell distribution, while inducing morphological, functional and molecular cancer cell remodeling.