An Orthotopic Patient-Derived Xenograft (PDX) Model Allows the Analysis of Metastasis-Associated Features in Colorectal Cancer

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

Establishment and Clinical Significance of the Patient-Derived Xenograft Model of Colorectal Cancer

OBJECTIVES

Patient-derived xenograft (PDX) models are widely acknowledged for their ability to reflect the heterogeneity of human cancers and can be used to improve preclinical models. In this study, we evaluated the factors affecting the tumor formation rate of the PDX colorectal cancer (CRC) model and conducted preliminary drug sensitivity tests.

METHODS

CRC patients who underwent elective surgery at Shaoxing People's Hospital from November 2019 to October 2020 were included. The tumor tissue obtained from surgery was transplanted to the back of NSG mice, and the PDX model was established and subcultured to the F3 generation. Factors that affected tumorigenicity were analyzed and compared histologically. Drug interventions included 5-fluorouracil, oxaliplatin, and propofol.

RESULTS

Sixty CRC patients were included in this study, and tumorigenesis was observed in CRC tissue derived from 37 cases (62%). The primary tumor malignancy degree (tumor stage and degree of cell differentiation), preoperative carcinoembryonic antigen level, and tumor location in CRC patients could affect the tumorigenicity of the PDX model. Histopathological analysis of CRC-PDX transplanted tumor tissue was highly consistent with the patient's tumor tissue. All four chemotherapy regimens could inhibit tumor growth and cause tumor tissue damage. Propofol could inhibit diarrhea in mice and protect intestinal mucosa.

CONCLUSIONS

The CRC-PDX model established in this study can maintain the biological characteristics of primary tumors and can be used as a reference model for the individualized treatment of CRC patients. The degree of malignancy of the primary tumor is the primary factor affecting the tumorigenesis rate of the PDX model.

Intersecting pathways: The role of hybrid E/M cells and circulating tumor cells in cancer metastasis and drug resistance

Cancer metastasis and therapy resistance are intricately linked with the dynamics of Epithelial-Mesenchymal Transition (EMT) and Circulating Tumor Cells (CTCs). EMT hybrid cells, characterized by a blend of epithelial and mesenchymal traits, have emerged as pivotal in metastasis and demonstrate remarkable plasticity, enabling transitions across cellular states crucial for intravasation, survival in circulation, and extravasation at distal sites. Concurrently, CTCs, which are detached from primary tumors and travel through the bloodstream, are crucial as potential biomarkers for cancer prognosis and therapeutic response. There is a significant interplay between EMT hybrid cells and CTCs, revealing a complex, bidirectional relationship that significantly influences metastatic progression and has a critical role in cancer drug resistance. This resistance is further influenced by the tumor microenvironment, with factors such as tumor-associated macrophages, cancer-associated fibroblasts, and hypoxic conditions driving EMT and contributing to therapeutic resistance. It is important to understand the molecular mechanisms of EMT, characteristics of EMT hybrid cells and CTCs, and their roles in both metastasis and drug resistance. This comprehensive understanding sheds light on the complexities of cancer metastasis and opens avenues for novel diagnostic approaches and targeted therapies and has significant advancements in combating cancer metastasis and overcoming drug resistance.

Preclinical evaluation of EpCAM-binding designed ankyrin repeat proteins (DARPins) as targeting moieties for bimodal near-infrared fluorescence and photoacoustic imaging of cancer

PURPOSE

Fluorescence-guided surgery (FGS) can play a key role in improving radical resection rates by assisting surgeons to gain adequate visualization of malignant tissue intraoperatively. Designed ankyrin repeat proteins (DARPins) possess optimal pharmacokinetic and other properties for in vivo imaging. This study aims to evaluate the preclinical potential of epithelial cell adhesion molecule (EpCAM)-binding DARPins as targeting moieties for near-infrared fluorescence (NIRF) and photoacoustic (PA) imaging of cancer.

METHODS

EpCAM-binding DARPins Ac2, Ec4.1, and non-binding control DARPin Off7 were conjugated to IRDye 800CW and their binding efficacy was evaluated on EpCAM-positive HT-29 and EpCAM-negative COLO-320 human colon cancer cell lines. Thereafter, NIRF and PA imaging of all three conjugates were performed in HT-29_luc2 tumor-bearing mice. At 24 h post-injection, tumors and organs were resected and tracer biodistributions were analyzed.

RESULTS

Ac2-800CW and Ec4.1-800CW specifically bound to HT-29 cells, but not to COLO-320 cells. Next, 6 nmol and 24 h were established as the optimal in vivo dose and imaging time point for both DARPin tracers. At 24 h post-injection, mean tumor-to-background ratios of 2.60 ± 0.3 and 3.1 ± 0.3 were observed for Ac2-800CW and Ec4.1-800CW, respectively, allowing clear tumor delineation using the clinical Artemis NIRF imager. Biodistribution analyses in non-neoplastic tissue solely showed high fluorescence signal in the liver and kidney, which reflects the clearance of the DARPin tracers.

CONCLUSION

Our encouraging results show that EpCAM-binding DARPins are a promising class of targeting moieties for pan-carcinoma targeting, providing clear tumor delineation at 24 h post-injection. The work described provides the preclinical foundation for DARPin-based bimodal NIRF/PA imaging of cancer.

Orthotopic and metastatic tumour models in preclinical cancer research

Mouse models of disease play a pivotal role at all stages of cancer drug development. Cell-line derived subcutaneous tumour models are predominant in early drug discovery, but there is growing recognition of the importance of the more complex orthotopic and metastatic tumour models for understanding both target biology in the correct tissue context, and the impact of the tumour microenvironment and the immune system in responses to treatment. The aim of this review is to highlight the value that orthotopic and metastatic models bring to the study of tumour biology and drug development while pointing out those models that are most likely to be encountered in the literature. Important developments in orthotopic models, such as the increasing use of early passage patient material (PDXs, organoids) and humanised mouse models are discussed, as these approaches have the potential to increase the predictive value of preclinical studies, and ultimately improve the success rate of anticancer drugs in clinical trials.

Construction of a gene signature associated with anoikis to evaluate the prognosis and immune infiltration in patients with colorectal cancer

Background

Colorectal cancer (CRC) is characterized by a high metastasis rate, leading to poor prognosis and increased mortality. Anoikis, a physiological process, serves as a crucial barrier against metastasis. The objective of this research is to construct a prognostic model for CRC based on genes associated with anoikis.

Methods

The study involved differential analysis and univariate Cox analysis of anoikis-related genes (ARGs), resulting in the selection of 47 genes closely associated with prognosis. Subsequently, unsupervised k-means clustering analysis was conducted on all patients to identify distinct clusters. Survival analysis, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed on the different clusters to investigate associations within the clusters. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were utilized to assess metabolic pathway enrichment between the identified clusters. Furthermore, single-sample GSEA (ssGSEA) was applied to explore variations in immune infiltration. Multivariable Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were conducted to construct a risk model based on ten signatures, which enabled the grouping of all samples according to their risk scores. The prognostic value of the model was validated using receiver operating characteristic (ROC) curves, area under the curve (AUC) calculations, and survival curves. Additionally, the expression of candidate genes was validated using quantitative real-time polymerase chain reaction (qRT-PCR).

Results

Forty-seven survival-related ARGs were screened out. Somatic mutation analysis showed that these genes revealed a high mutation rate. Based on their expression, two clusters were identified. Cluster B patients exhibited a shortened overall survival and higher immune infiltration. A risk scoring model including ten genes was subsequently developed, which exhibited excellent prognostic predictive ability for CRC, as evidenced by the survival curve, ROC curve, and AUC curve. In addition, a nomogram was developed for predicting 3- and 5-year survival probabilities. The qRT-PCR results indicated the dissimilarities among the ten signatures in the tumor tissues and adjacent tissues of patients with CRC were fundamentally consistent with the analytical findings.

Conclusions

This study comprehensively evaluated the prognostic significance of ARGs in CRC. It identified two distinct anoikis-related clusters and examined their respective immune microenvironments. Furthermore, an ARGs signature was developed to effectively predict the prognosis of CRC, thereby establishing a solid foundation for investigating the clinical prognostic role of anoikis in CRC.

Advances towards the use of gastrointestinal tumor patient-derived organoids as a therapeutic decision-making tool

In December 2022 the US Food and Drug Administration (FDA) removed the requirement that drugs in development must undergo animal testing before clinical evaluation, a declaration that now demands the establishment and verification of ex vivo preclinical models that closely represent tumor complexity and that can predict therapeutic response. Fortunately, the emergence of patient-derived organoid (PDOs) culture has enabled the ex vivo mimicking of the pathophysiology of human tumors with the reassembly of tissue-specific features. These features include histopathological variability, molecular expression profiles, genetic and cellular heterogeneity of parental tissue, and furthermore growing evidence suggests the ability to predict patient therapeutic response. Concentrating on the highly lethal and heterogeneous gastrointestinal (GI) tumors, herein we present the state-of-the-art and the current methodology of PDOs. We highlight the potential additions, improvements and testing required to allow the ex vivo of study the tumor microenvironment, as well as offering commentary on the predictive value of clinical response to treatments such as chemotherapy and immunotherapy.

Antitumor effect of toosendanin on oral squamous cell carcinoma via suppression of p-STAT3

BACKGROUND

Toosendanin (TSN) exhibits potent antitumor activity against various tumor cell lines. However, its efficacy against oral squamous cell carcinoma (OSCC) remains unknown. Here, we investigated the effects of TSN on OSCC cells in vitro and verified them in vivo using a patient-derived xenograft (PDX) model.

METHODS

The effect of TSN on OSCC cells was investigated by cytotoxicity assays and flow cytometry. The expression of proteins was detected by western blotting. An OSCC PDX model was constructed to further investigate the role of TSN in regulating the function of OSCC.

RESULTS

The cell viability of CAL27 and HN6 cells decreased as the concentration of TSN increased within the experimental range. Compared with controls, TSN at lower doses inhibited cell proliferation and induced apoptosis through S-phase cell cycle arrest. TSN inhibited OSCC cell proliferation by downregulating the STAT3 pathway through the inhibition of STAT3 phosphorylation. After successful construction of the OSCC PDX model with high pathological homology to the primary tumor and treatment with an intraperitoneal injection of TSN, we showed that TSN significantly reduced the tumor size of the PDX model mice without obvious toxicity.

CONCLUSIONS

Both in vitro and in vivo, TSN significantly inhibits the proliferation and promoted apoptosis of OSCC cells. Furthermore, TSN demonstrates potent inhibition of STAT3 phosphorylation, indicating its potential as a promising therapeutic agent for OSCC. Therefore, TSN holds great promise as a viable drug candidate for the treatment of OSCC.

CD44v6, STn & O-GD2: promising tumor associated antigens paving the way for new targeted cancer therapies

Targeted therapies are the state of the art in oncology today, and every year new Tumor-associated antigens (TAAs) are developed for preclinical research and clinical trials, but few of them really change the therapeutic scenario. Difficulties, either to find antigens that are solely expressed in tumors or the generation of good binders to these antigens, represent a major bottleneck. Specialized cellular mechanisms, such as differential splicing and glycosylation processes, are a good source of neo-antigen expression. Changes in these processes generate surface proteins that, instead of showing decreased or increased antigen expression driven by enhanced mRNA processing, are aberrant in nature and therefore more specific targets to elicit a precise anti-tumor therapy. Here, we present promising TAAs demonstrated to be potential targets for cancer monitoring, targeted therapy and the generation of new immunotherapy tools, such as recombinant antibodies and chimeric antigen receptor (CAR) T cell (CAR-T) or Chimeric Antigen Receptor-Engineered Natural Killer (CAR-NK) for specific tumor killing, in a wide variety of tumor types. Specifically, this review is a detailed update on TAAs CD44v6, STn and O-GD2, describing their origin as well as their current and potential use as disease biomarker and therapeutic target in a diversity of tumor types.

Mouse models in colon cancer, inferences, and implications

Mouse models of colorectal cancer (CRC) have been crucial in the identification of the role of genes responsible for the full range of pathology of the human disease and have proved to be dependable for testing anti-cancer drugs. Recent research points toward the relevance of tumor, angiogenic, and immune microenvironments in CRC progression to late-stage disease, as well as the treatment of it. This study examines important mouse models in CRC, discussing inherent strengths and weaknesses disclosed during their construction. It endeavors to provide both a synopsis of previous work covering how investigators have defined various models and to evaluate critically how researchers are most likely to use them in the future. Accumulated evidence regarding the metastatic process and the hope of using checkpoint inhibitors and immunological inhibitor therapies points to the need for a genetically engineered mouse model that is both immunocompetent and autochthonous.

Modeling the Tumor Microenvironment and Cancer Immunotherapy in Next-Generation Humanized Mice

Cancer immunotherapy has brought significant clinical benefits to numerous patients with malignant disease. However, only a fraction of patients experiences complete and durable responses to currently available immunotherapies. This highlights the need for more effective immunotherapies, combination treatments and predictive biomarkers. The molecular properties of a tumor, intratumor heterogeneity and the tumor immune microenvironment decisively shape tumor evolution, metastasis and therapy resistance and are therefore key targets for precision cancer medicine. Humanized mice that support the engraftment of patient-derived tumors and recapitulate the human tumor immune microenvironment of patients represent a promising preclinical model to address fundamental questions in precision immuno-oncology and cancer immunotherapy. In this review, we provide an overview of next-generation humanized mouse models suitable for the establishment and study of patient-derived tumors. Furthermore, we discuss the opportunities and challenges of modeling the tumor immune microenvironment and testing a variety of immunotherapeutic approaches using human immune system mouse models.

Genomic and Transcriptomic Analyses of Malignant Pleural Mesothelioma (MPM) Samples Reveal Crucial Insights for Preclinical Testing

Cell lines are extensively used to study cancer biology. However, the use of highly passaged commercial cell lines has to be questioned, as they do not closely resemble the originating tumor. To understand the reliability of preclinical models for Malignant pleural mesothelioma (MPM) studies, we have performed whole transcriptome and whole exome analyses of fresh frozen MPM tumors and compared them to cell lines generated from these tumors, as well as commercial cell lines and a preclinical MPM mouse model. Patient-derived cell lines were generated from digested fresh tumors and whole exome sequencing was performed on DNA isolated from formalin-fixed, paraffin-embedded (FFPE) tumor samples, corresponding patient-derived cell lines, and normal tissue. RNA sequencing libraries were prepared from 10 fresh frozen tumor samples, the 10 corresponding patient-derived cell lines, and 7 commercial cell lines. Our results identified alterations in tumor suppressor genes such as FBXW7, CDKN2A, CDKN2B, and MTAP, all known to drive MPM tumorigenesis. Patient-derived cell lines correlate to a high degree with their originating tumor. Gene expressions involved in multiple pathways such as EMT, apoptosis, myogenesis, and angiogenesis are upregulated in tumor samples when compared to patient-derived cell lines; however, they are downregulated in commercial cell lines compared to patient-derived cell lines, indicating significant differences between the two model systems. Our results show that the genome and transcriptome of tumors correlate to a higher degree with patient-derived cell lines rather than commercial cell lines. These results are of major relevance for the scientific community in regard to using cell lines as an appropriate model, resembling the pathway of interest to avoid misleading results for clinical applications.

Experimental Murine Models for Colorectal Cancer Research

Colorectal cancer (CRC) is the third most prevalent malignancy worldwide and in both sexes. Numerous animal models for CRC have been established to study its biology, namely carcinogen-induced models (CIMs) and genetically engineered mouse models (GEMMs). CIMs are valuable for assessing colitis-related carcinogenesis and studying chemoprevention. On the other hand, CRC GEMMs have proven to be useful for evaluating the tumor microenvironment and systemic immune responses, which have contributed to the discovery of novel therapeutic approaches. Although metastatic disease can be induced by orthotopic injection of CRC cell lines, the resulting models are not representative of the full genetic diversity of the disease due to the limited number of cell lines suitable for this purpose. On the other hand, patient-derived xenografts (PDX) are the most reliable for preclinical drug development due to their ability to retain pathological and molecular characteristics. In this review, the authors discuss the various murine CRC models with a focus on their clinical relevance, benefits, and drawbacks. From all models discussed, murine CRC models will continue to be an important tool in advancing our understanding and treatment of this disease, but additional research is required to find a model that can correctly reflect the pathophysiology of CRC.

3D cancer models: One step closer to in vitro human studies

Cancer immunotherapy is the great breakthrough in cancer treatment as it displayed prolonged progression-free survival over conventional therapies, yet, to date, in only a minority of patients. In order to broad cancer immunotherapy clinical applicability some roadblocks need to be overcome, first among all the lack of preclinical models that faithfully depict the local tumor microenvironment (TME), which is known to dramatically affect disease onset, progression and response to therapy. In this review, we provide the reader with a detailed overview of current 3D models developed to mimick the complexity and the dynamics of the TME, with a focus on understanding why the TME is a major target in anticancer therapy. We highlight the advantages and translational potentials of tumor spheroids, organoids and immune Tumor-on-a-Chip models in disease modeling and therapeutic response, while outlining pending challenges and limitations. Thinking forward, we focus on the possibility to integrate the know-hows of micro-engineers, cancer immunologists, pharmaceutical researchers and bioinformaticians to meet the needs of cancer researchers and clinicians interested in using these platforms with high fidelity for patient-tailored disease modeling and drug discovery.