Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models

Study on the efficacy of IFN-γ- and sPD-1-overexpressing BMSCs in enhancing immune effects for the treatment of lung adenocarcinoma

Background

Soluble programmed cell death receptor-1 (sPD-1) blocks the PD-1/PD-L1 pathway, reverses tumor immune suppression, and inhibits tumor growth. However, clinical applications are limited by its poor tissue distribution and rapid dispersion. Bone marrow-derived mesenchymal stem cells (BMSCs) are favorable carriers for tumor immunotherapy due to their capacity for external gene introduction and targeted tumor homing. However, they may inadvertently promote tumor growth. Interferon-gamma (IFN-γ) inhibits BMSC-mediated tumor growth and stimulates antigen-presenting cells to activate T lymphocytes. This study utilizes BMSCs transfected with IFN-γ as carriers for sPD-1, enabling the targeted homing of sPD-1 to tumor tissues, thereby enhancing the efficacy and sustained stability of immunotherapy.

Methods

stable IFN-γ- and sPD-1-overexpressing BMSCs were successfully constructed by lentiviral transfection. A non-contact co-culture system was established with Lewis and A549 lung adenocarcinoma cells to observe changes in the lung cancer cells after co-culture, using assays including cell migration and invasion experiments, as well as cellular senescence detection. Additionally, a subcutaneous lung adenocarcinoma model was established in C57BL/6J mice for intervention studies. Tumor volume, cellular apoptosis in tumor tissue (assessed by TUNEL assay), peripheral Treg cells (analyzed by flow cytometry), and histopathological markers (evaluated by HE staining and immunohistochemistry) were analyzed. The expression levels of BAX, BCL-2, AKT, PI3K, and PD-L1 were assessed by quantitative PCR and Western Blot.

Results

IFN-γ- and sPD-1-overexpressing BMSCs exhibited high bioactivity and genetic stability, inhibiting lung adenocarcinoma cell proliferation, accelerating cellular senescence, and reducing migration and invasion. Furthermore, they upregulate Bax expression, downregulate Bcl-2, and promote apoptosis. Additionally, these cells alleviate inflammatory damage in lung tissue of tumor-bearing mice, lower Treg cell levels to inhibit tumor immune evasion, and reduce the expression of PI3K/AKT and PD-L1.

Conclusion

IFN-γ- and sPD-1-overexpressing BMSCs effectively inhibit lung adenocarcinoma cell growth and tumor progression. The primary mechanisms include suppression of cancer cell growth, migration, and invasion; promotion of apoptosis and senescence in cancer cells; modulation of Treg cells; and inhibition of the PI3K/AKT signaling pathway and PD-1/PD-L1 pathways.

OBSERVE: guidelines for the refinement of rodent cancer models

Existing guidelines on the preparation (Planning Research and Experimental Procedures on Animals: Recommendations for Excellence (PREPARE)) and reporting (Animal Research: Reporting of In Vivo Experiments (ARRIVE)) of animal experiments do not provide a clear and standardized approach for refinement during in vivo cancer studies, resulting in the publication of generic methodological sections that poorly reflect the attempts made at accurately monitoring different pathologies. Compliance with the 3Rs guidelines has mainly focused on reduction and replacement; however, refinement has been harder to implement. The Oncology Best-practices: Signs, Endpoints and Refinements for in Vivo Experiments (OBSERVE) guidelines are the result of a European initiative supported by EurOPDX and INFRAFRONTIER, and aim to facilitate the refinement of studies using in vivo cancer models by offering robust and practical recommendations on approaches to research scientists and animal care staff. We listed cancer-specific clinical signs as a reference point and from there developed sets of guidelines for a wide variety of rodent models, including genetically engineered models and patient derived xenografts. In this Consensus Statement, we systematically and comprehensively address refinement and monitoring approaches during the design and execution of murine cancer studies. We elaborate on the appropriate preparation of tumor-initiating biologicals and the refinement of tumor-implantation methods. We describe the clinical signs to monitor associated with tumor growth, the appropriate follow-up of animals tailored to varying clinical signs and humane endpoints, and an overview of severity assessment in relation to clinical signs, implantation method and tumor characteristics. The guidelines provide oncology researchers clear and robust guidance for the refinement of in vivo cancer models.

A comparative analysis of preclinical computed tomography radiomics using cone-beam and micro-computed tomography scanners

Background and purpose

Radiomics analysis extracts quantitative data (features) from medical images. These features could potentially reflect biological characteristics and act as imaging biomarkers within precision medicine. However, there is a lack of cross-comparison and validation of radiomics outputs which is paramount for clinical implementation. In this study, we compared radiomics outputs across two computed tomography (CT)-based preclinical scanners.

Materials and methods

Cone beam CT (CBCT) and µCT scans were acquired using different preclinical CT imaging platforms. The reproducibility of radiomics features on each scanner was assessed using a phantom across imaging energies (40 & 60 kVp) and segmentation volumes (44-238 mm3). Retrospective mouse scans were used to compare feature reliability across varying tissue densities (lung, heart, bone), scanners and after voxel size harmonisation. Reliable features had an intraclass correlation coefficient (ICC) > 0.8.

Results

First order and GLCM features were the most reliable on both scanners across different volumes. There was an inverse relationship between tissue density and feature reliability, with the highest number of features in lung (CBCT=580, µCT=734) and lowest in bone (CBCT=110, µCT=560). Comparable features for lung and heart tissues increased when voxel sizes were harmonised. We have identified tissue-specific preclinical radiomics signatures in mice for the lung (133), heart (35), and bone (15).

Conclusions

Preclinical CBCT and µCT scans can be used for radiomics analysis to support the development of meaningful radiomics signatures. This study demonstrates the importance of standardisation and emphasises the need for multi-centre studies.

A clinically relevant computed tomography (CT) radiomics strategy for intracranial rodent brain tumour monitoring

Here, we establish a CT-radiomics based method for application in invasive, orthotopic rodent brain tumour models. Twenty four NOD/SCID mice were implanted with U87R-Luc2 GBM cells and longitudinally imaged via contrast enhanced (CE-CT) imaging. Pyradiomics was employed to extract CT-radiomic features from the tumour-implanted hemisphere and non-tumour-implanted hemisphere of acquired CT-scans. Inter-correlated features were removed (Spearman correlation > 0.85) and remaining features underwent predictive analysis (recursive feature elimination or Boruta algorithm). An area under the curve of the receiver operating characteristic curve was implemented to evaluate radiomic features for their capacity to predict defined outcomes. Firstly, we identified a subset of radiomic features which distinguish the tumour-implanted hemisphere and non- tumour-implanted hemisphere (i.e, tumour presence from normal tissue). Secondly, we successfully translate preclinical CT-radiomic pipelines to GBM patient CT scans (n = 10), identifying similar trends in tumour-specific feature intensities (E.g. 'glszm Zone Entropy'), thereby suggesting a mouse-to-human species conservation (a conservation of radiomic features across species). Thirdly, comparison of features across timepoints identify features which support preclinical tumour detection earlier than is possible by visual assessment of CT scans. This work establishes robust, preclinical CT-radiomic pipelines and describes the application of CE-CT for in-depth orthotopic brain tumour monitoring. Overall we provide evidence for the role of pre-clinical 'discovery' radiomics in the neuro-oncology space.

The identification of BCL-XL and MCL-1 as key anti-apoptotic proteins in medulloblastoma that mediate distinct roles in chemotherapy resistance

Medulloblastoma is the most common malignant paediatric brain tumour, representing 20% of all paediatric intercranial tumours. Current aggressive treatment protocols and the use of radiation therapy in particular are associated with high levels of toxicity and significant adverse effects, and long-term sequelae can be severe. Therefore, improving chemotherapy efficacy could reduce the current reliance on radiation therapy. Here, we demonstrated that systems-level analysis of basal apoptosis protein expression and their signalling interactions can differentiate between medulloblastoma cell lines that undergo apoptosis in response to chemotherapy, and those that do not. Combining computational predictions with experimental BH3 profiling, we identified a therapeutically-exploitable dependence of medulloblastoma cells on BCL-XL, and experimentally validated that BCL-XL targeting, and not targeting of BCL-2 or MCL-1, can potentiate cisplatin-induced cytotoxicity in medulloblastoma cell lines with low sensitivity to cisplatin treatment. Finally, we identified MCL-1 as an anti-apoptotic mediator whose targeting is required for BCL-XL inhibitor-induced apoptosis. Collectively, our study identifies that BCL-XL and MCL-1 are the key anti-apoptotic proteins in medulloblastoma, which mediate distinct protective roles. While BCL-XL has a first-line role in protecting cells from apoptosis basally, MCL-1 represents a second line of defence that compensates for BCL-XL upon its inhibition. We provide rationale for the further evaluation of BCL-XL and MCL-1 inhibitors in the treatment of medulloblastoma, and together with current efforts to improve the cancer-specificity of BCL-2 family inhibitors, these novel treatment strategies have the potential to improve the future clinical management of medulloblastoma.

Current Advances and Future Strategies for BCL-2 Inhibitors: Potent Weapons against Cancers

Targeting the intrinsic apoptotic pathway regulated by B-cell lymphoma-2 (BCL-2) antiapoptotic proteins can overcome the evasion of apoptosis in cancer cells. BCL-2 inhibitors have evolved into an important means of treating cancers by inducing tumor cell apoptosis. As the most extensively investigated BCL-2 inhibitor, venetoclax is highly selective for BCL-2 and can effectively inhibit tumor survival. Its emergence and development have significantly influenced the therapeutic landscape of hematological malignancies, especially in chronic lymphocytic leukemia and acute myeloid leukemia, in which it has been clearly incorporated into the recommended treatment regimens. In addition, the considerable efficacy of venetoclax in combination with other agents has been demonstrated in relapsed and refractory multiple myeloma and certain lymphomas. Although venetoclax plays a prominent antitumor role in preclinical experiments and clinical trials, large individual differences in treatment outcomes have been characterized in real-world patient populations, and reduced drug sensitivity will lead to disease recurrence or progression. The therapeutic efficacy may vary widely in patients with different molecular characteristics, and key genetic mutations potentially result in differential sensitivities to venetoclax. The identification and validation of more novel biomarkers are required to accurately predict the effectiveness of BCL-2 inhibition therapy. Furthermore, we summarize the recent research progress relating to the use of BCL-2 inhibitors in solid tumor treatment and demonstrate that a wealth of preclinical models have shown promising results through combination therapies. The applications of venetoclax in solid tumors warrant further clinical investigation to define its prospects.

Development and optimisation of a preclinical cone beam computed tomography-based radiomics workflow for radiation oncology research

Background and purpose

Radiomics features derived from medical images have the potential to act as imaging biomarkers to improve diagnosis and predict treatment response in oncology. However, the complex relationships between radiomics features and the biological characteristics of tumours are yet to be fully determined. In this study, we developed a preclinical cone beam computed tomography (CBCT) radiomics workflow with the aim to use in vivo models to further develop radiomics signatures.

Materials and methods

CBCT scans of a mouse phantom were acquired using onboard imaging from a small animal radiotherapy research platform (SARRP, Xstrahl). The repeatability and reproducibility of radiomics outputs were compared across different imaging protocols, segmentation sizes, pre-processing parameters and materials. Robust features were identified and used to compare scans of two xenograft mouse tumour models (A549 and H460).

Results

Changes to the radiomics workflow significantly impact feature robustness. Preclinical CBCT radiomics analysis is feasible with 119 stable features identified from scans imaged at 60 kV, 25 bin width and 0.26 mm slice thickness. Large variation in segmentation volumes reduced the number of reliable radiomics features for analysis. Standardization in imaging and analysis parameters is essential in preclinical radiomics analysis to improve accuracy of outputs, leading to more consistent and reproducible findings.

Conclusions

We present the first optimised workflow for preclinical CBCT radiomics to identify imaging biomarkers. Preclinical radiomics has the potential to maximise the quantity of data captured in in vivo experiments and could provide key information supporting the wider application of radiomics.

Patient-derived xenograft model in colorectal cancer basic and translational research

Colorectal cancer (CRC) is one of the most popular malignancies globally, with 930 000 deaths in 2020. The evaluation of CRC-related pathogenesis and the discovery of potential therapeutic targets will be meaningful and helpful for improving CRC treatment. With huge efforts made in past decades, the systematic treatment regimens have been applied to improve the prognosis of CRC patients. However, the sensitivity of CRC to chemotherapy and targeted therapy is different from person to person, which is an important cause of treatment failure. The emergence of patient-derived xenograft (PDX) models shows great potential to alleviate the straits. PDX models possess similar genetic and pathological characteristics as the features of primary tumors. Moreover, PDX has the ability to mimic the tumor microenvironment of the original tumor. Thus, the PDX model is an important tool to screen precise drugs for individualized treatment, seek predictive biomarkers for prognosis supervision, and evaluate the unknown mechanism in basic research. This paper reviews the recent advances in constructed methods and applications of the CRC PDX model, aiming to provide new knowledge for CRC basic research and therapeutics.