Interrogating open issues in cancer precision medicine with patient-derived xenografts

The use of organoids in creating immune microenvironments and treating gynecological tumors

Owing to patient-derived tumor tissues and cells, significant advances have been made in personalized cancer treatment and precision medicine, with cancer stem cell-derived three-dimensional tumor organoids serving as crucial in vitro models that accurately replicate the structural, phenotypic, and genetic characteristics of tumors. However, despite their extensive use in drug testing, genome editing, and transplantation for facilitating personalized treatment approaches in clinical practice, the inadequate capacity of these organoids to effectively model immune cells and stromal components within the tumor microenvironment limits their potential. Additionally, effective clinical immunotherapy has led the tumor immune microenvironment to garner considerable attention, increasing the demand for simulating patient-specific tumor-immune interactions. Consequently, co-culture techniques integrating tumor organoids with immune cells and tumor microenvironment constituents have been developed to expand the possibilities for personalized drug response investigations, with recent advancements enhancing the understanding of the strengths, limitations, and applicability of the co-culture approach. Herein, the recent advancements in the field of tumor organoids have been comprehensively reviewed, specifically highlighting the tumor organoid co-culture-related developments with various immune cell models and their implications for clinical research. Furthermore, this review delineates the current state of research and application of organoid models regarding the therapeutic approaches and related challenges for gynecological tumors. This study may provide a theoretical basis for further research on the use of patient-derived organoids in tumor immunity, drug development, and precision medicine.

CTC-derived pancreatic cancer models serve as research tools and are suitable for precision medicine approaches

Pancreatic ductal adenocarcinoma (PDAC) poses significant clinical challenges, often presenting as unresectable with limited biopsy options. Here, we show that circulating tumor cells (CTCs) offer a promising alternative, serving as a "liquid biopsy" that enables the generation of in vitro 3D models and highly aggressive in vivo models for functional and molecular studies in advanced PDAC. Within the retrieved CTC pool (median 65 CTCs/5 mL), we identify a subset (median content 8.9%) of CXCR4+ CTCs displaying heightened stemness and metabolic traits, reminiscent of circulating cancer stem cells. Through comprehensive analysis, we elucidate the importance of CTC-derived models for identifying potential targets and guiding treatment strategies. Screening of stemness-targeting compounds identified stearoyl-coenzyme A desaturase (SCD1) as a promising target for advanced PDAC. These results underscore the pivotal role of CTC-derived models in uncovering therapeutic avenues and ultimately advancing personalized care in PDAC.

Extracellular matrix regulation of cell spheroid invasion in a 3D bioprinted solid tumor-on-a-chip

Tumor organoids and tumors-on-chips can be built by placing patient-derived cells within an engineered extracellular matrix (ECM) for personalized medicine. The engineered ECM influences the tumor response, and understanding the ECM-tumor relationship accelerates translating tumors-on-chips into drug discovery and development. In this work, we tuned the physical and structural characteristics of ECM in a 3D bioprinted soft-tissue sarcoma microtissue. We formed cell spheroids at a controlled size and encapsulated them into our gelatin methacryloyl (GelMA)-based bioink to make perfusable hydrogel-based microfluidic chips. We then demonstrated the scalability and customization flexibility of our hydrogel-based chip via engineering tools. A multiscale physical and structural data analysis suggested a relationship between cell invasion response and bioink characteristics. Tumor cell invasive behavior and focal adhesion properties were observed in response to varying polymer network densities of the GelMA-based bioink. Immunostaining assays and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) helped assess the bioactivity of the microtissue and measure the cell invasion. The RT-qPCR data showed higher expressions of HIF-1α, CD44, and MMP2 genes in a lower polymer density, highlighting the correlation between bioink structural porosity, ECM stiffness, and tumor spheroid response. This work is the first step in modeling STS tumor invasiveness in hydrogel-based microfluidic chips. STATEMENT OF SIGNIFICANCE: We optimized an engineering protocol for making tumor spheroids at a controlled size, embedding spheroids into a gelatin-based matrix, and constructing a perfusable microfluidic device. A higher tumor invasion was observed in a low-stiffness matrix than a high-stiffness matrix. The physical characterizations revealed how the stiffness is controlled by the density of polymer chain networks and porosity. The biological assays revealed how the structural properties of the gelatin matrix and hypoxia in tumor progression impact cell invasion. This work can contribute to personalized medicine by making more effective, tailored cancer models.

Precision Oncology and Systemic Targeted Therapy in Pseudomyxoma Peritonei

PURPOSE

Pseudomyxoma peritonei (PMP) is a rare and poorly understood malignant condition characterized by the accumulation of intra-abdominal mucin produced from peritoneal metastases. Currently, cytoreductive surgery remains the mainstay of treatment but disease recurrence and death after relapse frequently occur in patients with PMP. New therapeutic strategies are therefore urgently needed for these patients.

EXPERIMENTAL DESIGN

A total of 120 PMP samples from 50 patients were processed to generate a collection of 50 patient-derived organoid (PDO) and xenograft (PDX) models. Whole exome sequencing, immunohistochemistry analyses, and in vitro and in vivo drug efficacy studies were performed.

RESULTS

In this study, we have generated a collection of PMP preclinical models and identified druggable targets, including BRAFV600E, KRASG12C, and KRASG12D, that could also be detected in intra-abdominal mucin biopsies of patients with PMP using droplet digital PCR. Preclinical models preserved the histopathological markers from the original patient sample. The BRAFV600E inhibitor encorafenib reduced cell viability of BRAFV600E PMP-PDO models. Proof-of-concept in vivo experiments showed that a systemic treatment with encorafenib significantly reduced tumor growth and prolonged survival in subcutaneous and orthotopic BRAFV600E-PMP-PDX mouse models.

CONCLUSIONS

Our study demonstrates for the first time that systemic targeted therapies can effectively control PMP tumors. BRAF signaling pathway inhibition represents a new therapeutic opportunity for patients with BRAFV600E PMP who have a poor prognosis. Importantly, our present data and collection of preclinical models pave the way for evaluating the efficacy of other systemic targeted therapies toward extending the promise of precision oncology to patients with PMP.

Leveraging preclinical models of metastatic breast cancer

Women that present to the clinic with established breast cancer metastases have limited treatment options. Yet, the majority of preclinical studies are actually not directed at developing treatment regimens for established metastatic disease. In this review we will discuss the current state of preclinical macro-metastatic breast cancer models, including, but not limited to syngeneic GEMM, PDX and xenografts. Challenges within these models which are often overlooked include fluorophore-immunogenic neoantigens, differences in experimental vs spontaneous metastasis and tumor heterogeneity. Furthermore, due to cell plasticity in the tumor immune microenvironment (TIME) of the metastatic landscape, the treatment efficacy of newly approved immune checkpoint blockade (ICB) may differ in metastatic sites as compared to primary localized tumors.

Gastric Cancer Assembloids Derived from Patient-Derived Xenografts: A Preclinical Model for Therapeutic Drug Screening

The construction of reliable preclinical models is crucial for understanding the molecular mechanisms involved in gastric cancer and for advancing precision medicine. Currently, existing in vitro tumor models often do not accurately replicate the human gastric cancer environment and are unsuitable for high-throughput therapeutic drug screening. In this study, droplet microfluidic technology is employed to create novel gastric cancer assembloids by encapsulating patient-derived xenograft gastric cancer cells and patient stromal cells in Gelatin methacryloyl (GelMA)-Gelatin-Matrigel microgels. The usage of GelMA-Gelatin-Matrigel composite hydrogel effectively alleviated cell aggregation and sedimentation during the assembly process, allowing for the handling of large volumes of cell-laden hydrogel and the uniform generation of assembloids in a high-throughput manner. Notably, the patient-derived xenograft assembloids exhibited high consistency with primary tumors at both transcriptomic and histological levels, and can be efficiently scaled up for preclinical drug screening efforts. Furthermore, the drug screening results clearly demonstrated that the in vitro assembloid model closely mirrored in vivo drug responses. Thus, these findings suggest that gastric cancer assembloids, which effectively replicate the in vivo tumor microenvironment, show promise for enabling more precise high-throughput drug screening and predicting the clinical outcomes of various drugs.

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.

Repurposed AT9283 triggers anti-tumoral effects by targeting MKK3 oncogenic functions in Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) is the third most common type of cancer and the second leading cause of cancer-related deaths worldwide, with a survival rate near to 10% when diagnosed at an advanced stage. Hence, the identification of new molecular targets to design more selective and efficient therapies is urgently required. The Mitogen activated protein kinase kinase 3 (MKK3) is a dual-specificity threonine/tyrosine protein kinase that, activated in response to cellular stress and inflammatory stimuli, regulates a plethora of biological processes. Previous studies revealed novel MKK3 roles in supporting tumor malignancy, as its depletion induces autophagy and cell death in cancer lines of different tumor types, including CRC. Therefore, MKK3 may represent an interesting new therapeutic target in advanced CRC, however selective MKK3 inhibitors are currently not available.

METHODS

The study involved transcriptomic based drug repurposing approach and confirmatory assays with CRC lines, primary colonocytes and a subset of CRC patient-derived organoids (PDO). Investigations in vitro and in vivo were addressed.

RESULTS

The repurposing approach identified the multitargeted kinase inhibitor AT9283 as a putative compound with MKK3 depletion-mimicking activities. Indeed, AT9283 drops phospho- and total-MKK3 protein levels in tested CRC models. Likely the MKK3 silencing, AT9283 treatment: i) inhibited cell proliferation promoting autophagy and cell death in tested CRC lines and PDOs; ii) resulted well-tolerated by CCD-18Co colonocytes; iii) reduced cancer cell motility inhibiting CRC cell migration and invasion; iv) inhibited COLO205 xenograft tumor growth. Mechanistically, AT9283 abrogated MKK3 protein levels mainly through the inhibition of aurora kinase A (AURKA), impacting on MKK3/AURKA protein-protein interaction and protein stability therefore uncovering the relevance of MKK3/AURKA crosstalk in sustaining CRC malignancy in vitro and in vivo.

CONCLUSION

Overall, we demonstrated that the anti-tumoral effects triggered by AT9283 treatment recapitulated the MKK3 depletion effects in all tested CRC models in vitro and in vivo, suggesting that AT9283 is a repurposed drug. According to its good tolerance when tested with primary colonocytes (CCD-18CO), AT9283 is a promising drug for the development of novel therapeutic strategies to target MKK3 oncogenic functions in late-stage and metastatic CRC patients.

Evaluation of Combined Chemotherapy and Genomic-Driven Targeted Therapy in Patient-Derived Xenografts Identifies New Therapeutic Approaches in Squamous Non-Small-Cell Lung Cancer Patients

The combination of chemotherapy and targeted therapy has been validated in non-small-cell lung cancer (NSCLC) patients with EGFR mutations. We therefore investigated whether this type of combined approach could be more widely used by targeting other genetic alterations present in NSCLC. PDXs were generated from patients with NSCLC adenocarcinomas (ADCs) and squamous-cell carcinomas (SCCs). Targeted NGS analyses identified various molecular abnormalities in the MAPK and PI3K pathways and in the cell cycle process in our PDX panel. The antitumor efficacy of targeted therapies alone or in combination with chemotherapy was then tested in vivo. We observed that trametinib, BKM120, AZD2014 and palbociclib increased the efficacy of each chemotherapy in SCC PDXs, in contrast to a non-insignificant or slight improvement in ADCs. Furthermore, we observed high efficacy of trametinib in KRAS-, HRAS- and NRAS-mutated tumors (ADCs and SCCs), suggesting that the MEK inhibitor may be useful in a wider population of NSCLC patients, not just those with KRAS-mutated ADCs. Our results suggest that the detection of pathogenic variants by NGS should be performed in all NSCLCs, and particularly in SCCs, to offer patients a more effective combination of chemotherapy and targeted therapy.

Gastrointestinal Cancer Patient Derived Organoids at the Frontier of Personalized Medicine and Drug Screening

Cancer is a leading cause of death worldwide. Around one-third of the total global cancer incidence and mortality are related to gastrointestinal (GI) cancers. Over the past few years, rapid developments have been made in patient-derived organoid (PDO) models for gastrointestinal cancers. By closely mimicking the molecular properties of their parent tumors in vitro, PDOs have emerged as powerful tools in personalized medicine and drug discovery. Here, we review the current literature on the application of PDOs of common gastrointestinal cancers in the optimization of drug treatment strategies in the clinic and their rising importance in pre-clinical drug development. We discuss the advantages and limitations of gastrointestinal cancer PDOs and outline the microfluidics-based strategies that improve the throughput of PDO models in order to extract the maximal benefits in the personalized medicine and drug discovery process.

Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment

The development of neoplasia involves a complex and continuous interplay between malignantly transformed cells and the tumour microenvironment (TME). Cancer immunotherapies targeting the immune TME have been increasingly validated in clinical trials but response rates vary substantially between tumour histologies and are often transient, idiosyncratic and confounded by resistance. Faithful experimental models of the patient-specific tumour immune microenvironment, capable of recapitulating tumour biology and immunotherapy effects, would greatly improve patient selection, target identification and definition of resistance mechanisms for immuno-oncology therapeutics. In this Review, we discuss currently available and rapidly evolving 3D tumour organoid models that capture important immune features of the TME. We highlight diverse opportunities for organoid-based investigations of tumour immunity, drug development and precision medicine.

Tumor Cell Stemness and Stromal Cell Features Contribute to Oral Cancer Outcome Disparity in Black Americans

Black Americans (BAs) with head and neck cancer (HNC) have worse survival outcomes compared to the White patients. While HNC disparities in patient outcomes for BAs have been well recognized, the specific drivers of the inferior outcomes remain poorly understood. Here, we investigated the biologic features of patient tumor specimens obtained during the surgical treatment of oral cancers and performed a follow-up study of the patients' post-surgery recurrences and metastases with the aim to explore whether tumor biologic features could be associated with the poorer outcomes among BA patients compared with White American (WA) patients. We examined the tumor stemness traits and stromal properties as well as the post-surgery recurrence and metastasis of oral cancers among BA and WA patients. It was found that high levels of tumor self-renewal, invasion, tumorigenesis, metastasis, and tumor-promoting stromal characteristics were linked to post-surgery recurrence and metastasis. There were more BA than WA patients demonstrating high stemness traits and strong tumor-promoting stromal features in association with post-surgery tumor recurrences and metastases, although the investigated cases displayed clinically comparable TNM stages and histological grades. These findings demonstrated that the differences in tumor stemness and stromal property among cancers with comparable clinical diagnoses contribute to the outcome disparity in HNCs. More research is needed to understand the genetic and molecular basis of the biologic characteristics underlying the inferior outcomes among BA patients, so that targeting strategies can be developed to reduce HNC disparity.

Genomic profiling of a multi-lineage and multi-passage patient-derived xenograft biobank reflects heterogeneity of ovarian cancer

Ovarian cancer (OC) manifests as a complex disease characterized by inter- and intra-patient heterogeneity. Despite enhanced biological and genetic insights, OC remains a recalcitrant malignancy with minimal survival improvement. Based on multi-site sampling and a multi-lineage patient-derived xenograft (PDX) establishment strategy, we present herein the establishment of a comprehensive PDX biobank from histologically and molecularly heterogeneous OC patients. Comprehensive profiling of matched PDX and patient samples demonstrates that PDXs closely recapitulate parental tumors. By leveraging multi-lineage models, we reveal that the previously reported genomic disparities of PDX could be mainly attributed to intra-patient spatial heterogeneity instead of substantial model-independent genomic evolution. Moreover, DNA damage response pathway inhibitor (DDRi) screening uncovers heterogeneous responses across models. Prolonged iterative drug exposure recapitulates acquired drug resistance in initially sensitive models. Meanwhile, interrogation of induced drug-resistant (IDR) models reveals that suppressed interferon (IFN) response and activated Wnt/β-catenin signaling contribute to acquired DDRi drug resistance.

Liensinine sensitizes colorectal cancer cells to oxaliplatin by targeting HIF-1α to inhibit autophagy

BACKGROUND

Oxaliplatin is the most common chemotherapeutic agent for patients with colorectal cancer. However, its anti-cancer efficacy is restricted by drug resistance occurring through several mechanisms, including autophagy. Liensinine exerts a considerable anti-tumor effect and can regulate autophagy. Inhibition of autophagy is a strategy to reverse resistance to oxaliplatin. The aim of this study was to check if liensinine can enhance the therapeutic efficacy of oxaliplatin in colorectal cancer and if so, elucidate its mechanism.

METHODS

Two colorectal cancer cell lines, HCT116 and LoVo, and one normal intestinal epithelial cell, NCM-460 were used for in vitro experiments. Cell Counting Kit-8 (CCK-8), colony formation, and flow cytometry assays were used to evaluate the cytotoxicity of liensinine and oxaliplatin. Network pharmacology analysis and Human XL Oncology Array were used to screen targets of liensinine. Transfections and autophagy regulators were used to confirm these targets. The relationship between the target and clinical effect of oxaliplatin was analyzed. Patient-derived xenograft (PDX) models were used to validate the effects of liensinine and oxaliplatin.

RESULTS

CCK-8 and colony formation assays both showed that the combination treatment of liensinine and oxaliplatin exerted synergistic effects. Results of the network pharmacology analysis and Human XL Oncology Array suggested that liensinine can inhibit autophagy by targeting HIF-1α/eNOS. HIF-1α was identified as the key factor modulated by liensinine in autophagy and induces resistance to oxaliplatin. HIF-1α levels in tumor cells and prognosis for FOLFOX were negatively correlated in clinical data. The results from three PDX models with different HIF-1α levels showed their association with intrinsic and acquired resistance to oxaliplatin in these models, which could be reversed by liensinine.

CONCLUSIONS

Research on the relationship between HIF-1α levels and the clinical effect of oxaliplatin is lacking, and whether liensinine regulates HIF-1α is unknown. Our findings suggest that liensinine overcomes the resistance of colorectal cancer cells to oxaliplatin by suppressing HIF-1α levels to inhibit autophagy. Our findings can contribute to improving prognosis following colorectal cancer therapy.

A Self-Assembled 3D Model Demonstrates How Stiffness Educates Tumor Cell Phenotypes and Therapy Resistance in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense and stiff extracellular matrix (ECM) associated with tumor progression and therapy resistance. To further the understanding of how stiffening of the tumor microenvironment (TME) contributes to aggressiveness, a three-dimensional (3D) self-assembling hydrogel disease model is developed based on peptide amphiphiles (PAs, PA-E3Y) designed to tailor stiffness. The model displays nanofibrous architectures reminiscent of native TME and enables the study of the invasive behavior of PDAC cells. Enhanced tuneability of stiffness is demonstrated by interacting thermally annealed aqueous solutions of PA-E3Y (PA-E3Yh) with divalent cations to create hydrogels with mechanical properties and ultrastructure similar to native tumor ECM. It is shown that stiffening of PA-E3Yh hydrogels to levels found in PDAC induces ECM deposition, promotes epithelial-to-mesenchymal transition (EMT), enriches CD133+/CXCR4+ cancer stem cells (CSCs), and subsequently enhances drug resistance. The findings reveal how a stiff 3D environment renders PDAC cells more aggressive and therefore more faithfully recapitulates in vivo tumors.

The potential of organoids in renal cell carcinoma research

Renal cell carcinoma, a leading cause of death in urological malignancies, arises from the nephron. Its characteristics include diversity in disease biology, varied clinical behaviors, different prognoses, and diverse responses to systemic therapies. The term 'organoids' is used to describe structures resembling tissues created through the three-dimensional cultivation of stem cells in vitro. These organoids, when derived from tumor tissues, can retain the diversity of the primary tumor, mirror its spatial tissue structure, and replicate similar organ-like functions. In contrast to conventional two-dimensional cell cultures and the transplantation of tumor tissues into other organisms, organoids derived from tumors maintain the complexity and microenvironment of the original tumor tissue. This fidelity makes them a more reliable model for the development of cancer drugs, potentially accelerating the translation of these drugs to clinical use and facilitating personalized treatment options for patients. This review aims to summarize the recent advancements in the use of organoids for studying renal cell carcinoma, focusing on their cultivation, potential applications, and inherent limitations.

Mouse Models for Head and Neck Squamous Cell Carcinoma

The prognosis and survival rate of head and neck squamous cell carcinoma (HNSCC) have remained unchanged for years, and the pathogenesis of HNSCC is still not fully understood, necessitating further research. An ideal animal model that accurately replicates the complex microenvironment of HNSCC is urgently needed. Among all the animal models for preclinical cancer research, tumor-bearing mouse models are the best known and widely used due to their high similarity to humans. Currently, mouse models for HNSCC can be broadly categorized into chemical-induced models, genetically engineered mouse models (GEMMs), and transplanted mouse models, each with its distinct advantages and limitations. In chemical-induced models, the carcinogen spontaneously initiates tumor formation through a multistep process. The resemblance of this model to human carcinogenesis renders it an ideal preclinical platform for studying HNSCC initiation and progression from precancerous lesions. The major drawback is that these models are time-consuming and, like human cancer, unpredictable in terms of timing, location, and number of lesions. GEMMs involve transgenic and knockout mice with gene modifications, leading to malignant transformation within a tumor microenvironment that recapitulates tumorigenesis in vivo, including their interaction with the immune system. However, most HNSCC GEMMs exhibit low tumor incidence and limited prognostic significance when translated to clinical studies. Transplanted mouse models are the most widely used in cancer research due to their consistency, availability, and efficiency. Based on the donor and recipient species matching, transplanted mouse models can be divided into xenografts and syngeneic models. In the latter, transplanted cells and host are from the same strain, making syngeneic models relevant to study functional immune system. In this review, we provide a comprehensive summary of the characteristics, establishment methods, and potential applications of these different HNSCC mouse models, aiming to assist researchers in choosing suitable animal models for their research.

Omics-based molecular classifications empowering in precision oncology

BACKGROUND

In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

CONCLUSION

This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

Recent advances in breast cancer cell line research

Breast cancer, a formidable global health challenge, needs continuous translational research to understand the complexity of mechanisms and improve therapeutic and diagnostic strategies. Breast cancer cell lines are of paramount importance as they significantly contribute to the initial stage of research to understand cancer biology. This review provides insights into targeted therapies and immunotherapies that have emerged using in vitro models and microbiome analysis. It focuses on therapeutic development using cell lines and the limitations of tumor heterogeneity and microenvironment. We explore the evolving landscape of breast cancer cell lines from two-dimensional (2-D) cultures to patient-derived xenograft (PDX) models advancing both fundamental and translational research. Patient-derived xenografts, cell line-derived xenografts (CDX), three-dimensional (3-D) cultures, organoids, and circulating tumor cells (CTC) models provide promising alternatives that capture the intricacies of the tumor microenvironment. This review bridges the gap between traditional cell lines and newer developments exploring the therapeutic and diagnostic advancements and needs for cell lines to expedite the progress in breast cancer research and treatment.

The Transformative Role of 3D Culture Models in Triple-Negative Breast Cancer Research

Advancements in cell culturing techniques have allowed the development of three-dimensional (3D) cell culture models sourced directly from patients' tissues and tumors, faithfully replicating the native tissue environment. These models provide a more clinically relevant platform for studying disease progression and treatment responses compared to traditional two-dimensional (2D) models. Patient-derived organoids (PDOs) and patient-derived xenograft organoids (PDXOs) emerge as innovative 3D cancer models capable of accurately mimicking the tumor's unique features, enhancing our understanding of tumor complexities, and predicting clinical outcomes. Triple-negative breast cancer (TNBC) poses significant clinical challenges due to its aggressive nature, propensity for early metastasis, and limited treatment options. TNBC PDOs and PDXOs have significantly contributed to the comprehension of TNBC, providing novel insights into its underlying mechanism and identifying potential therapeutic targets. This review explores the transformative role of various 3D cancer models in elucidating TNBC pathogenesis and guiding novel therapeutic strategies. It also provides an overview of diverse 3D cell culture models, derived from cell lines and tumors, highlighting their advantages and culturing challenges. Finally, it delves into live-cell imaging techniques, endpoint assays, and alternative cell culture media and methodologies, such as scaffold-free and scaffold-based systems, essential for advancing 3D cancer model research and development.

Pancreatic cancer environment: from patient-derived models to single-cell omics

Pancreatic cancer (PC) is a highly malignant cancer characterized by poor prognosis, high heterogeneity, and intricate heterocellular systems. Selecting an appropriate experimental model for studying its progression and treatment is crucial. Patient-derived models provide a more accurate representation of tumor heterogeneity and complexity compared to cell line-derived models. This review initially presents relevant patient-derived models, including patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived explants (PDEs), which are essential for studying cell communication and pancreatic cancer progression. We have emphasized the utilization of these models in comprehending intricate intercellular communication, drug responsiveness, mechanisms underlying tumor growth, expediting drug discovery, and enabling personalized medical approaches. Additionally, we have comprehensively summarized single-cell analyses of these models to enhance comprehension of intercellular communication among tumor cells, drug response mechanisms, and individual patient sensitivities.

Patient-derived tumor-like cell clusters for personalized chemo- and immunotherapies in non-small cell lung cancer

Many patient-derived tumor models have emerged recently. However, their potential to guide personalized drug selection remains unclear. Here, we report patient-derived tumor-like cell clusters (PTCs) for non-small cell lung cancer (NSCLC), capable of conducting 100-5,000 drug tests within 10 days. We have established 283 PTC models with an 81% success rate. PTCs contain primary tumor epithelium self-assembled with endogenous stromal and immune cells and show a high degree of similarity to the original tumors in phenotypic and genotypic features. Utilizing standardized culture and drug-response assessment protocols, PTC drug-testing assays reveal 89% overall consistency in prospectively predicting clinical outcomes, with 98.1% accuracy distinguishing complete/partial response from progressive disease. Notably, PTCs enable accurate prediction of clinical outcomes for patients undergoing anti-PD1 therapy by combining cell viability and IFN-γ value assessments. These findings suggest that PTCs could serve as a valuable preclinical model for personalized medicine and basic research in NSCLC.

Patient-derived organoids in human cancer: a platform for fundamental research and precision medicine

Cancer is associated with a high degree of heterogeneity, encompassing both inter- and intra-tumor heterogeneity, along with considerable variability in clinical response to common treatments across patients. Conventional models for tumor research, such as in vitro cell cultures and in vivo animal models, demonstrate significant limitations that fall short of satisfying the research requisites. Patient-derived tumor organoids, which recapitulate the structures, specific functions, molecular characteristics, genomics alterations and expression profiles of primary tumors. They have been efficaciously implemented in illness portrayal, mechanism exploration, high-throughput drug screening and assessment, discovery of innovative therapeutic targets and potential compounds, and customized treatment regimen for cancer patients. In contrast to conventional models, tumor organoids offer an intuitive, dependable, and efficient in vitro research model by conserving the phenotypic, genetic diversity, and mutational attributes of the originating tumor. Nevertheless, the organoid technology also confronts the bottlenecks and challenges, such as how to comprehensively reflect intra-tumor heterogeneity, tumor microenvironment, tumor angiogenesis, reduce research costs, and establish standardized construction processes while retaining reliability. This review extensively examines the use of tumor organoid techniques in fundamental research and precision medicine. It emphasizes the importance of patient-derived tumor organoid biobanks for drug development, screening, safety evaluation, and personalized medicine. Additionally, it evaluates the application of organoid technology as an experimental tumor model to better understand the molecular mechanisms of tumor. The intent of this review is to explicate the significance of tumor organoids in cancer research and to present new avenues for the future of tumor research.

Simultaneous inhibition of FAK and ROS1 synergistically repressed triple-negative breast cancer by upregulating p53 signalling

BACKGROUND

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype lacking effective targeted therapies, necessitating innovative treatment approaches. While targeting ROS proto-oncogene 1 (ROS1) with crizotinib has shown promise, resistance remains a limitation. Recent evidence links focal adhesion kinase (FAK) to drug resistance, prompting our study to assess the combined impact of FAK inhibitor IN10018 and crizotinib in TNBC and elucidate the underlying mechanisms.

METHODS

We employed the Timer database to analyze FAK and ROS1 mRNA levels in TNBC and adjacent normal tissues. Furthermore, we investigated the correlation between FAK, ROS1, and TNBC clinical prognosis using the GSE database. We conducted various in vitro assays, including cell viability, colony formation, flow cytometry, EdU assays, and western blotting. Additionally, TNBC xenograft and human TNBC organoid models were established to assess the combined therapy's efficacy. To comprehensively understand the synergistic anti-tumor mechanisms, we utilized multiple techniques, such as RNA sequencing, immunofluorescence, cell flow cytometry, C11-BODIPY staining, MDA assay, and GSH assay.

RESULTS

The Timer database revealed higher levels of FAK and ROS1 in TNBC tissues compared to normal tissues. Analysis of GEO databases indicated that patients with high FAK and ROS1 expression had the poorest prognosis. Western blotting confirmed increased p-FAK expression in crizotinib-resistant TNBC cells. In vitro experiments showed that the combination therapy down-regulated cyclin B1, p-Cdc2, and Bcl2 while up-regulating BAX, cleaved-Caspase-3, cleaved-Caspase-9, and cleaved PARP. In TNBC xenograft models, the tumor volume in the combination therapy group was 73% smaller compared to the control group (p < 0.0001). Additionally, the combination therapy resulted in a 70% reduction in cell viability in human TNBC organoid models (p < 0.0001). RNA sequencing analysis of TNBC cells and xenograft tumor tissues highlighted enrichment in oxidative stress, glutathione metabolism, and p53 pathways. The combined group displayed a fivefold rise in the reactive oxygen species level, a 69% decrease in the GSH/GSSG ratio, and a sixfold increase in the lipid peroxidation in comparison to the control group. Western blotting demonstrated p53 upregulation and SCL7A11 and GPX4 downregulation in the combination group. The addition of a p53 inhibitor reversed these effects.

CONCLUSION

Our study demonstrates that the combination of IN10018 and crizotinib shows synergistic antitumor effects in TNBC. Mechanistically, this combination inhibits cell proliferation, enhances apoptosis, and induces ferroptosis, which is associated with increased p53 levels.

Magnetic resonance imaging-guided intracranial resection of glioblastoma tumors in patient-derived orthotopic xenografts leads to clinically relevant tumor recurrence

BACKGROUND

Preclinical in vivo cancer models are essential tools for investigating tumor progression and response to treatment prior to clinical trials. Although treatment modalities are regularly assessed in mice upon tumor growth in vivo, surgical resection remains challenging, particularly in the orthotopic site. Here, we report a successful surgical resection of glioblastoma (GBM) in patient-derived orthotopic xenografts (PDOXs).

METHODS

We derived a cohort of 46 GBM PDOX models that faithfully recapitulate human disease in mice. We assessed the detection and quantification of intracranial tumors using magnetic resonance imaging (MRI).To evaluate feasibility of surgical resection in PDOXs, we selected two models representing histopathological features of GBM tumors, including diffuse growth into the mouse brain. Surgical resection in the mouse brains was performed based on MRI-guided coordinates. Survival study followed by MRI and immunohistochemistry-based evaluation of recurrent tumors allowed for assessment of clinically relevant parameters.

RESULTS

We demonstrate the utility of MRI for the noninvasive assessment of in vivo tumor growth, preoperative programming of resection coordinates and follow-up of tumor recurrence. We report tumor detection by MRI in 90% of GBM PDOX models (36/40), of which 55% (22/40) can be reliably quantified during tumor growth. We show that a surgical resection protocol in mice carrying diffuse primary GBM tumors in the brain leads to clinically relevant outcomes. Similar to neurosurgery in patients, we achieved a near total to complete extent of tumor resection, and mice with resected tumors presented significantly increased survival. The remaining unresected GBM cells that invaded the normal mouse brain prior to surgery regrew tumors with similar histopathological features and tumor microenvironments to the primary tumors.

CONCLUSIONS

Our data positions GBM PDOXs developed in mouse brains as a valuable preclinical model for conducting therapeutic studies that involve surgical tumor resection. The high detectability of tumors by MRI across a substantial number of PDOX models in mice will allow for scalability of our approach toward specific tumor types for efficacy studies in precision medicine-oriented approaches. Additionally, these models hold promise for the development of enhanced image-guided surgery protocols.

A New Microfluidic Device to Facilitate Functional Precision Medicine Assays

Functional precision medicine (FPM) has emerged as a new approach to improve cancer treatment. Despite its potential, FPM assays present important limitations such as the number of cells and trained personnel required. To overcome these impediments, here we describe a novel microfluidic platform that can be used to perform FPM assays, optimizing the use of primary cancer cells and simplifying the process by using microfluidics to automatize the process.

A multidimensional platform of patient-derived tumors identifies drug susceptibilities for clinical lenvatinib resistance

Lenvatinib, a second-generation multi-receptor tyrosine kinase inhibitor approved by the FDA for first-line treatment of advanced liver cancer, facing limitations due to drug resistance. Here, we applied a multidimensional, high-throughput screening platform comprising patient-derived resistant liver tumor cells (PDCs), organoids (PDOs), and xenografts (PDXs) to identify drug susceptibilities for conquering lenvatinib resistance in clinically relevant settings. Expansion and passaging of PDCs and PDOs from resistant patient liver tumors retained functional fidelity to lenvatinib treatment, expediting drug repurposing screens. Pharmacological screening identified romidepsin, YM155, apitolisib, NVP-TAE684 and dasatinib as potential antitumor agents in lenvatinib-resistant PDC and PDO models. Notably, romidepsin treatment enhanced antitumor response in syngeneic mouse models by triggering immunogenic tumor cell death and blocking the EGFR signaling pathway. A combination of romidepsin and immunotherapy achieved robust and synergistic antitumor effects against lenvatinib resistance in humanized immunocompetent PDX models. Collectively, our findings suggest that patient-derived liver cancer models effectively recapitulate lenvatinib resistance observed in clinical settings and expedite drug discovery for advanced liver cancer, providing a feasible multidimensional platform for personalized medicine.

Patient-Derived Xenografts: A Valuable Preclinical Model for Drug Development and Biomarker Discovery

Patient-derived xenografts (PDXs), established by implanting patient tumor cells into immunodeficient mice, offer a platform for faithfully replicating human tumors. They closely mimic the histopathology, genomics, and drug sensitivity of patient tumors. This chapter highlights the versatile applications of PDXs, including studying tumor biology, metastasis, and chemoresistance, as well as their use in biomarker identification, drug screening, and personalized medicine. It also addresses challenges in using PDXs in cancer research, including variations in metastatic potential, lengthy establishment timelines, stromal changes, and limitations in immunocompromised models. Despite these challenges, PDXs remain invaluable tools guiding patient treatment and advancing preclinical drug development.

Engineering Heterogeneous Tumor Models for Biomedical Applications

Tumor tissue engineering holds great promise for replicating the physiological and behavioral characteristics of tumors in vitro. Advances in this field have led to new opportunities for studying the tumor microenvironment and exploring potential anti-cancer therapeutics. However, the main obstacle to the widespread adoption of tumor models is the poor understanding and insufficient reconstruction of tumor heterogeneity. In this review, the current progress of engineering heterogeneous tumor models is discussed. First, the major components of tumor heterogeneity are summarized, which encompasses various signaling pathways, cell proliferations, and spatial configurations. Then, contemporary approaches are elucidated in tumor engineering that are guided by fundamental principles of tumor biology, and the potential of a bottom-up approach in tumor engineering is highlighted. Additionally, the characterization approaches and biomedical applications of tumor models are discussed, emphasizing the significant role of engineered tumor models in scientific research and clinical trials. Lastly, the challenges of heterogeneous tumor models in promoting oncology research and tumor therapy are described and key directions for future research are provided.

Revolutionizing digestive system tumor organoids research: Exploring the potential of tumor organoids

Digestive system tumors are the leading cause of cancer-related deaths worldwide. Despite ongoing research, our understanding of their mechanisms and treatment remain inadequate. One promising tool for clinical applications is the use of gastrointestinal tract tumor organoids, which serve as an important in vitro model. Tumor organoids exhibit a genotype similar to the patient's tumor and effectively mimic various biological processes, including tissue renewal, stem cell, and ecological niche functions, and tissue response to drugs, mutations, or injury. As such, they are valuable for drug screening, developing novel drugs, assessing patient outcomes, and supporting immunotherapy. In addition, innovative materials and techniques can be used to optimize tumor organoid culture systems. Several applications of digestive system tumor organoids have been described and have shown promising results in related aspects. In this review, we discuss the current progress, limitations, and prospects of this model for digestive system tumors.

Bioengineering Approaches for the Pancreatic Tumor Organoids Research and Application

Pancreatic cancer is a highly lethal form of digestive malignancy that poses significant health risks to individuals worldwide. Chemotherapy-based comprehensive treatment is the primary therapeutic approach for midlife and late-life patients. Nevertheless, the heterogeneity of the tumor and individual genetic backgrounds result in substantial variations in drug sensitivity among patients, rendering a single treatment regimen unsuitable for all patients. Conventional pancreatic cancer tumor organoid models are capable of emulating the biological traits of pancreatic cancer and are utilized in drug development and screening. However, these tumor organoids can still not mimic the tumor microenvironment (TME) in vivo, and the poor controllability in the preparation process hinders translation from essential drug screening to clinical pharmacological therapy. In recent years, many engineering methods with remarkable results have been used to develop pancreatic cancer organoid models, including bio-hydrogel, co-culture, microfluidic, and gene editing. Here, this work summarizes and analyzes the recent developments in engineering pancreatic tumor organoid models. In addition, the future direction of improving engineered pancreatic cancer organoids is discussed for their application prospects in clinical treatment.

Generation of Metastatic Cholangiocarcinoma Patient-Derived Xenograft Models

Cholangiocarcinoma (CCA) poses a substantial clinical hurdle as it is often detected at advanced metastatic stages with limited therapeutic options. To enhance our understanding of advanced CCA, it is imperative to establish preclinical models that faithfully recapitulate the disease's characteristics. Patient-derived xenograft (PDX) models have emerged as a valuable approach in cancer research, offering an avenue to reproduce and study the genomic, histologic, and molecular features of the original human tumors. By faithfully preserving the heterogeneity, microenvironmental interactions, and drug responses observed in human tumors, PDX models serve as highly relevant and predictive preclinical tools. Here, we present a comprehensive protocol that outlines the step-by-step process of generating and maintaining PDX models using biopsy samples from patients with advanced metastatic CCA. The protocol encompasses crucial aspects such as tissue processing, xenograft transplantation, and subsequent monitoring of the PDX models. By employing this protocol, we aim to establish a robust collection of PDX models that accurately reflect the genomic landscape, histologic diversity, and therapeutic responses observed in advanced CCA, thereby enabling improved translational research, drug development, and personalized treatment strategies for patients facing this challenging disease.

Experimental models for cancer brain metastasis

Brain metastases are a leading cause of cancer-related mortality. However, progress in their treatment has been limited over the past decade, due to an incomplete understanding of the underlying biological mechanisms. Employing accurate in vitro and in vivo models to recapitulate the complexities of brain metastasis offers the most promising approach to unravel the intricate cellular and physiological processes involved. Here, we present a comprehensive review of the currently accessible models for studying brain metastasis. We introduce a diverse array of in vitro and in vivo models, including cultured cells using the Transwell system, organoids, microfluidic models, syngeneic models, xenograft models, and genetically engineered models. We have also provided a concise summary of the merits and limitations inherent to each model while identifying the optimal contexts for their effective utilization. This review serves as a comprehensive resource, aiding researchers in making well-informed decisions regarding model selection that align with specific research questions.

Preclinical liver cancer models in the context of immunoprecision therapy: Application and perspectives

Hepatocellular carcinoma (HCC), ranking as the third leading cause of cancer-related mortality globally, continues to pose challenges in achieving optimal treatment outcomes. The complex nature of HCC, characterized by high spatiotemporal heterogeneity, invasive potential, and drug resistance, presents difficulties in its research. Consequently, an in-depth understanding and accurate simulation of the immune microenvironment of HCC are of paramount importance. This article comprehensively explores the application of preclinical models in HCC research, encompassing cell line models, patient-derived xenograft mouse models, genetically engineered mouse models, chemically induced models, humanized mouse models, organoid models, and microfluidic chip-based patient derived organotypic spheroids models. Each model possesses its distinct advantages and limitations in replicating the biological behavior and immune microenvironment of HCC. By scrutinizing the limitations of existing models, this paper aims to propel the development of next-generation cancer models, enabling more precise emulation of HCC characteristics. This will, in turn, facilitate the optimization of treatment strategies, drug efficacy prediction, and safety assessments, ultimately contributing to the realization of personalized and precision therapies. Additionally, this article also provides insights into future trends and challenges in the fields of tumor biology and preclinical research.

Use and application of organ-on-a-chip platforms in cancer research

Tumors are a major cause of death worldwide, and much effort has been made to develop appropriate anti-tumor therapies. Existing in vitro and in vivo tumor models cannot reflect the critical features of cancer. The development of organ-on-a-chip models has enabled the integration of organoids, microfluidics, tissue engineering, biomaterials research, and microfabrication, offering conditions that mimic tumor physiology. Three-dimensional in vitro human tumor models that have been established as organ-on-a-chip models contain multiple cell types and a structure that is similar to the primary tumor. These models can be applied to various foci of oncology research. Moreover, the high-throughput features of microfluidic organ-on-a-chip models offer new opportunities for achieving large-scale drug screening and developing more personalized treatments. In this review of the literature, we explore the development of organ-on-a-chip technology and discuss its use as an innovative tool in basic and clinical applications and summarize its advancement of cancer research.

Patient-derived organoids as personalized avatars and a potential immunotherapy model in cervical cancer

Cervical cancer remains a significant health issue in developing countries. However, finding a preclinical model that accurately reproduces tumor characteristics is challenging. Therefore, we established a patient-derived organoids (PDOs) biobank containing 67 cases of heterogeneous cervical cancer that mimic the histopathological and genomic characteristics of parental tumors. The in vitro response of the organoids indicated their ability to capture the radiological heterogeneity of the patients. To model individual responses to adoptive T cell therapy (ACT), we expanded tumor-infiltrating lymphocytes (TILs) ex vivo and co-cultured them with paired organoids. The PDOs-TILs co-culture system demonstrates clear responses that correspond to established immunotherapy efficiency markers like the proportion of CTLs. This study supports the potential of the PDOs platform to guide treatment in prospective interventional trials in cervical cancer.

Patient Characteristics Associated with Growth of Patient-Derived Tumor Implants in Mice (Patient-Derived Xenografts)

Background: patient-derived xenografts (PDXs) have defined the field of translational cancer research in recent years, becoming one of the most-used tools in early drug development. The process of establishing cancer models in mice has turned out to be challenging, since little research focuses on evaluating which factors impact engraftment success. We sought to determine the clinical, pathological, or molecular factors which may predict better engraftment rates in PDXs. Methods: between March 2017 and January 2021, tumor samples obtained from patients with primary or metastatic cancer were implanted into athymic nude mice. A full comprehensive evaluation of baseline factors associated with the patients and patients' tumors was performed, with the goal of potentially identifying predictive markers of engraftment. We focused on clinical (patient factors) pathological (patients' tumor samples) and molecular (patients' tumor samples) characteristics, analyzed either by immunohistochemistry (IHC) or next-generation sequencing (NGS), which were associated with the likelihood of final engraftment, as well as with tumor growth rates in xenografts. Results: a total of 585 tumor samples were collected and implanted. Twenty-one failed to engraft, due to lack of malignant cells. Of 564 tumor-positive samples, 187 (33.2%) grew at time of analysis. The study was able to find correlation and predictive value for engraftment for the following: the use of systemic antibiotics by the patient within 2 weeks of sampling (38.1% (72/189) antibiotics- group vs. 30.7% (115/375) no-antibiotics) (p = 0.048), and the administration of systemic steroids to the patients within 2 weeks of sampling (41.5% (34/48) steroids vs. 31.7% (153/329), no-steroids) (p = 0.049). Regarding patient's baseline tests, we found certain markers could help predict final engraftment success: for lactate dehydrogenase (LDH) levels, 34.1% (140/411) of tumors derived from patients with baseline blood LDH levels above the upper limit of normality (ULN) achieved growth, against 30.7% (47/153) with normal LDH (p = 0.047). Histological tumor characteristics, such as grade of differentiation, were also correlated. Grade 1: 25.4% (47/187), grade 2: 34.8% (65/187) and grade 3: 40.1% (75/187) tumors achieved successful growth (p = 0.043), suggesting the higher the grade, the higher the likelihood of success. Similarly, higher ki67 levels were also correlated with better engraftment rates: low (Ki67 < 15%): 8.9% (9/45) achieved growth vs. high (Ki67 ≥ 15%): 31% (35/113) (p: 0.002). Other markers of aggressiveness such as the presence of lymphovascular invasion in tumor sample of origin was also predictive: 42.2% (97/230) with lymphovascular vs. 26.9% (90/334) of samples with no invasion (p = 0.0001). From the molecular standpoint, mismatch-repair-deficient (MMRd) tumors showed better engraftment rates: 62.1% (18/29) achieved growth vs. 40.8% (75/184) of proficient tumors (p = 0.026). A total of 84 PDX were breast models, among which 57.9% (11/19) ER-negative models grew, vs. 15.4% (10/65) of ER-positive models (p = 0.0001), also consonant with ER-negative tumors being more aggressive. BRAFmut cancers are more likely to achieve engraftment during the development of PDX models. Lastly, tumor growth rates during first passages can help establish a cutoff point for the decision-making process during PDX development, since the higher the tumor grades, the higher the likelihood of success. Conclusions: tumors with higher grade and Ki67 protein expression, lymphovascular and/or perineural invasion, with dMMR and are negative for ER expression have a higher probability of achieving growth in the process of PDX development. The use of steroids and/or antibiotics in the patient prior to sampling can also impact the likelihood of success in PDX development. Lastly, establishing a cutoff point for tumor growth rates could guide the decision-making process during PDX development.

LINC00665 activating Wnt3a/β-catenin signaling by bond with YBX1 promotes gastric cancer proliferation and metastasis

Long noncoding RNAs (lncRNAs) play a key role in human cancer development; nevertheless, the effect of lncRNA LINC00665 on the progression of gastric cancer (GC) still unclear. In this study, we found that LINC00665 expression is upregulated in GC than normal gastric mucosa tissues and higher LINC00665 expression is associated with a poor prognosis in GC patients. Downregulated LINC00665 inhibited GC cells proliferation, invasion, and migration in vitro. Pulmonary metastasis animal models showed that downregulated LINC00665 could reduce the lung metastasis of GC in vivo. Tumor organoids were generated from human malignant GC tissues, downregulated LINC00665 could inhibit the growth of the organoids of GC tissues. Mechanistically, downregulated LINC00665 could inhibit GC cells EMT. RNA pulldown, RIP, and RIP-seq studies found that LINC00665 can bind to the transcription factor YBX1 and form a positive feed-forward loop. The luciferase reporter and CHIP results showed that YBX1 could regulate the transcriptional activity of Wnt3a, and downregulation of LINC00665 could block the activation of Wnt/β-catenin signaling. In conclusion, our results identified a feedback loop between LINC00665 and YBX1 that activates Wnt/β-catenin signaling, and it may be a potential therapeutic approach to suppress GC progression.

Preclinical glioma models in neuro-oncology: enhancing translational research

PURPOSE OF REVIEW

Gliomas represent approximately 25% of all primary brain and other central nervous system (CNS) tumors and 81% of malignant tumors. Unfortunately, standard treatment approaches for most CNS cancers have shown limited improvement in patient survival rates.

RECENT FINDINGS

The current drug development process has been plagued by high failure rates, leading to a shift towards human disease models in biomedical research. Unfortunately, suitable preclinical models for brain tumors have been lacking, hampering our understanding of tumor initiation processes and the discovery of effective treatments. In this review, we will explore the diverse preclinical models employed in neuro-oncology research and their contributions to translational science.

SUMMARY

By utilizing a combination of these preclinical models and fostering interdisciplinary collaborations, researchers can deepen their understanding of glioma brain tumors and develop novel therapeutic strategies to combat these devastating diseases. These models offer promising prospects for personalized and efficacious treatments for these challenging malignancies. Although it is unrealistic to fully replicate the complexity of the human body in vitro, the ultimate goal should be to achieve the closest possible resemblance to the clinical context.

Collagen 1-mediated CXCL1 secretion in tumor cells activates fibroblasts to promote radioresistance of esophageal cancer

Esophageal squamous-cell carcinoma (ESCC) is commonly treated with radiotherapy; however, radioresistance hinders its clinical effectiveness, and the underlying mechanism remains elusive. Here, we develop patient-derived xenografts (PDXs) from 19 patients with ESCC to investigate the mechanisms driving radioresistance. Using RNA sequencing, cytokine arrays, and single-cell RNA sequencing, we reveal an enrichment of cancer-associated fibroblast (CAF)-derived collagen type 1 (Col1) and tumor-cell-derived CXCL1 in non-responsive PDXs. Col1 not only promotes radioresistance by augmenting DNA repair capacity but also induces CXCL1 secretion in tumor cells. Additionally, CXCL1 further activates CAFs via the CXCR2-STAT3 pathway, establishing a positive feedback loop. Directly interfering with tumor-cell-derived CXCL1 or inhibiting the CXCL1-CXCR2 pathway effectively restores the radiosensitivity of radioresistant xenografts in vivo. Collectively, our study provides a comprehensive understanding of the molecular mechanisms underlying radioresistance and identifies potential targets to improve the efficacy of radiotherapy for ESCC.

A preclinical platform for assessing long-term drug efficacy exploiting mechanically tunable scaffolds colonized by a three-dimensional tumor microenvironment

BACKGROUND

Long-term drug evaluation heavily relies upon rodent models. Drug discovery methods to reduce animal models in oncology may include three-dimensional (3D) cellular systems that take into account tumor microenvironment (TME) cell types and biomechanical properties.

METHODS

In this study we reconstructed a 3D tumor using an elastic polymer (acrylate-endcapped urethane-based poly(ethylene glycol) (AUPPEG)) with clinical relevant stiffness. Single cell suspensions from low-grade serous ovarian cancer (LGSOC) patient-derived early passage cultures of cancer cells and cancer-associated fibroblasts (CAF) embedded in a collagen gel were introduced to the AUPPEG scaffold. After self-organization in to a 3D tumor, this model was evaluated by a long-term (> 40 days) exposure to a drug combination of MEK and HSP90 inhibitors. The drug-response results from this long-term in vitro model are compared with drug responses in an orthotopic LGSOC xenograft mouse model.

RESULTS

The in vitro 3D scaffold LGSOC model mimics the growth ratio and spatial organization of the LGSOC. The AUPPEG scaffold approach allows to test new targeted treatments and monitor long-term drug responses. The results correlate with those of the orthotopic LGSOC xenograft mouse model.

CONCLUSIONS

The mechanically-tunable scaffolds colonized by a three-dimensional LGSOC allow long-term drug evaluation and can be considered as a valid alternative to reduce, replace and refine animal models in drug discovery.

Progress in building clinically relevant patient-derived tumor xenograft models for cancer research

Patient-derived tumor xenograft (PDX) models, a method involving the surgical extraction of tumor tissues from cancer patients and subsequent transplantation into immunodeficient mice, have emerged as a pivotal approach in translational research, particularly in advancing precision medicine. As the first stage of PDX development, the patient-derived orthotopic xenograft (PDOX) models implant tumor tissue in mice in the corresponding anatomical locations of the patient. The PDOX models have several advantages, including high fidelity to the original tumor, heightened drug sensitivity, and an elevated rate of successful transplantation. However, the PDOX models present significant challenges, requiring advanced surgical techniques and resource-intensive imaging technologies, which limit its application. And then, the humanized mouse models, as well as the zebrafish models, were developed. Humanized mouse models contain a human immune environment resembling the tumor and immune system interplay. The humanized mouse models are a hot topic in PDX model research. Regarding zebrafish patient-derived tumor xenografts (zPDX) and patient-derived organoids (PDO) as promising models for studying cancer and drug discovery, zPDX models are used to transplant tumors into zebrafish as novel personalized medical animal models with the advantage of reducing patient waiting time. PDO models provide a cost-effective approach for drug testing that replicates the in vivo environment and preserves important tumor-related information for patients. The present review highlights the functional characteristics of each new phase of PDX and provides insights into the challenges and prospective developments in this rapidly evolving field.

Can Organoid Model Reveal a Key Role of Extracellular Vesicles in Tumors? A Comprehensive Review of the Literature

Extracellular vesicles (EVs) are small membrane-bound vesicles that are released by cells into the extracellular environment. The role of EVs in tumors has been extensively studied, and they have been shown to play a crucial role in tumor growth, progression, and metastasis. Past research has mainly used 2D-cultured cell line models to investigate the role of EVs in tumors, which poorly simulate the tumor microenvironment. Organoid technology has gradually matured in recent years. Organoids are similar in composition and behavior to physiological cells and have the potential to recapitulate the architecture and function of the original tissue. It has been widely used in organogenesis, drug screening, gene editing, precision medicine and other fields. The integration of EVs and organoids has the potential to revolutionize the field of cancer research and represents a promising avenue for advancing our understanding of cancer biology and the development of novel therapeutic strategies. Here, we aimed to present a comprehensive overview of studies using organoids to study EVs in tumors.

Gastrointestinal organs and organoids-on-a-chip: advances and translation into the clinics

Microfluidic organs and organoids-on-a-chip models of human gastrointestinal systems have been established to recreate adequate microenvironments to study physiology and pathophysiology. In the effort to find more emulating systems and less costly models for drugs screening or fundamental studies, gastrointestinal system organoids-on-a-chip have arisen as promising pre-clinicalin vitromodel. This progress has been built on the latest developments of several technologies such as bioprinting, microfluidics, and organoid research. In this review, we will focus on healthy and disease models of: human microbiome-on-a-chip and its rising correlation with gastro pathophysiology; stomach-on-a-chip; liver-on-a-chip; pancreas-on-a-chip; inflammation models, small intestine, colon and colorectal cancer organoids-on-a-chip and multi-organoids-on-a-chip. The current developments related to the design, ability to hold one or more 'organs' and its challenges, microfluidic features, cell sources and whether they are used to test drugs are overviewed herein. Importantly, their contribution in terms of drug development and eminent clinical translation in precision medicine field, Food and Drug Administration approved models, and the impact of organoid-on-chip technology in terms of pharmaceutical research and development costs are also discussed by the authors.

Humanized mouse models for anti-cancer therapy

Patient-derived xenograft (PDX) models are the golden standard for preclinical oncology as they can recapitulate the genotypic and phenotypic complexity of human tumors, thus enabling the development of effective therapeutic strategies. PDX models are typically established in immunocompromised animals that allow efficient growth of the xenografted tumor. Given the recent success of immune therapies in different tumors however, the establishment of humanized PDX models is critical to evaluate immune oncology drugs and/or combinations thereof. Here, we describe the detailed methods to obtain humanized PDX models for anti-cancer therapy testing.

eIF3f Mediates SGOC Pathway Reprogramming by Enhancing Deubiquitinating Activity in Colorectal Cancer

Numerous studies have demonstrated that individual proteins can moonlight. Eukaryotic Initiation translation factor 3, f subunit (eIF3f) is involved in critical biological functions; however, its role independent of protein translation in regulating colorectal cancer (CRC) is not characterized. Here, it is demonstrated that eIF3f is upregulated in CRC tumor tissues and that both Wnt and EGF signaling pathways are participating in eIF3f's oncogenic impact on targeting phosphoglycerate dehydrogenase (PHGDH) during CRC development. Mechanistically, EGF blocks FBXW7β-mediated PHGDH ubiquitination through GSK3β deactivation, and eIF3f antagonizes FBXW7β-mediated PHGDH ubiquitination through its deubiquitinating activity. Additionally, Wnt signals transcriptionally activate the expression of eIF3f, which also exerts its deubiquitinating activity toward MYC, thereby increasing MYC-mediated PHGDH transcription. Thereby, both impacts allow eIF3f to elevate the expression of PHGDH, enhancing Serine-Glycine-One-Carbon (SGOC) signaling pathway to facilitate CRC development. In summary, the study uncovers the intrinsic role and underlying molecular mechanism of eIF3f in SGOC signaling, providing novel insight into the strategies to target eIF3f-PHGDH axis in CRC.

Challenges and Prospects of Patient-Derived Xenografts for Cancer Research

We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.

Progress in construction of mouse models to investigate the pathogenesis and immune therapy of human hematological malignancy

Hematological malignancy is a disease arisen by complicate reasons that seriously endangers human health. The research on its pathogenesis and therapies depends on the usage of animal models. Conventional animal model cannot faithfully mirror some characteristics of human features due to the evolutionary divergence, whereas the mouse models hosting human hematological malignancy are more and more applied in basic as well as translational investigations in recent years. According to the construction methods, they can be divided into different types (e.g. cell-derived xenograft (CDX) and patient-derived xenograft model (PDX) model) that have diverse characteristics and application values. In addition, a variety of strategies have been developed to improve human hematological malignant cell engraftment and differentiation in vivo. Moreover, the humanized mouse model with both functional human immune system and autologous human hematological malignancy provides a unique tool for the evaluation of the efficacy of novel immunotherapeutic drugs/approaches. Herein, we first review the evolution of the mouse model of human hematological malignancy; Then, we analyze the characteristics of different types of models and summarize the ways to improve the models; Finally, the way and value of humanized mouse model of human immune system in the immunotherapy of human hematological malignancy are discussed.