Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Orthotopic meningioma rat model exhibits morphological and immunohistochemical congruency and epigenetic concordance with benign primary patient-derived tumors

Meningiomas are the most common primary central nervous system tumor. Clinical trials have failed to support effective medical treatments, despite initially promising animal studies. A key issue could be that available experimental models fail to mimic the clinical situation. Hence, there is a need for meningioma models with high translational value for understanding pathophysiology and tests of possible medical treatments. Resemblance between models and clinical meningiomas should be optimized with respect to morphology, immunohistochemistry and epigenetic factors, which we aimed to do. Third passage primary patient-derived benign meningiomas were implanted intracranially in athymic nude rats. The animals were euthanized after three months. We found intra- and intertumoral variability in terms of tumor take rate (79.5% for superficially implanted cells and 25% for deeply implanted cells) and xenograft sizes. There were close resemblance between primary tumors and xenografts in morphology and immunohistochemistry. Furthermore, we performed DNA-methylation using the EPIC 850 K array on three pairs of primary tumors and xenografts. Copy number variation profiles and correlation plots on CpGs showed a high degree of similarities between primary tumors and corresponding xenografts. On differential methylation analysis, most probes were insignificant (866,074), 25 were hypermethylated, and 382 were hypomethylated, where no significant differentially methylated regions were revealed.

PDX models for functional precision oncology and discovery science

Precision oncology relies on detailed molecular analysis of how diverse tumours respond to various therapies, with the aim to optimize treatment outcomes for individual patients. Patient-derived xenograft (PDX) models have been key to preclinical validation of precision oncology approaches, enabling the analysis of each tumour's unique genomic landscape and testing therapies that are predicted to be effective based on specific mutations, gene expression patterns or signalling abnormalities. To extend these standard precision oncology approaches, the field has strived to complement the otherwise static and often descriptive measurements with functional assays, termed functional precision oncology (FPO). By utilizing diverse PDX and PDX-derived models, FPO has gained traction as an effective preclinical and clinical tool to more precisely recapitulate patient biology using in vivo and ex vivo functional assays. Here, we explore advances and limitations of PDX and PDX-derived models for precision oncology and FPO. We also examine the future of PDX models for precision oncology in the age of artificial intelligence. Integrating these two disciplines could be the key to fast, accurate and cost-effective treatment prediction, revolutionizing oncology and providing patients with cancer with the most effective, personalized treatments.

Receptor tyrosine kinase inhibition leads to regression of acral melanoma by targeting the tumor microenvironment

BACKGROUND

Acral melanoma (AM) is an aggressive melanoma variant that arises from palmar, plantar, and nail unit melanocytes. Compared to non-acral cutaneous melanoma (CM), AM is biologically distinct, has an equal incidence across genetic ancestries, typically presents in advanced stage disease, is less responsive to therapy, and has an overall worse prognosis.

METHODS

An independent analysis of published sequencing data was performed to evaluate the frequency of receptor tyrosine kinase (RTK) ligands and adapter protein gene variants and expression. To target these genetic variants, a zebrafish acral melanoma model and preclinical patient-derived xenograft (PDX) mouse models were treated with a panel of RTK inhibitors. Residual PDX tumors were evaluated for changes in proliferation, vasculature, necrosis, and ferroptosis by histology and immunohistochemistry.

RESULTS

RTK ligands and adapter proteins are frequently amplified, translocated, and/or overexpressed in AM. Dual FGFR/VEGFR inhibitors decrease acral-analogous melanocyte proliferation and migration in zebrafish, and the potent pan-FGFR/VEGFR inhibitor, Lenvatinib, uniformly induces tumor regression in AM PDX tumors but only slows tumor growth in CM models. Unlike other multi-RTK inhibitors, Lenvatinib is not directly cytotoxic to dissociated AM PDX tumor cells and instead disrupts tumor architecture and vascular networks.

CONCLUSION

Considering the great difficulty in establishing AM cell culture lines, these findings suggest that AM may be more sensitive to microenvironment perturbations than CM. In conclusion, dual FGFR/VEGFR inhibition may be a viable therapeutic strategy that targets the unique biology of AM.

Integrative ensemble modelling of cetuximab sensitivity in colorectal cancer patient-derived xenografts

Patient-derived xenografts (PDXs) are tumour fragments engrafted into mice for preclinical studies. PDXs offer clear advantages over simpler in vitro cancer models - such as cancer cell lines (CCLs) and organoids - in terms of structural complexity, heterogeneity, and stromal interactions. Here, we characterise 231 colorectal cancer PDXs at the genomic, transcriptomic, and epigenetic levels, along with their response to cetuximab, an EGFR inhibitor used clinically for metastatic colorectal cancer. After evaluating the PDXs' quality, stability, and molecular concordance with publicly available patient cohorts, we present results from training, interpreting, and validating the integrative ensemble classifier CeSta. This model takes in input the PDXs' multi-omic characterisation and predicts their sensitivity to cetuximab treatment, achieving an area under the receiver operating characteristics curve > 0.88. Our study demonstrates that large PDX collections can be leveraged to train accurate, interpretable drug sensitivity models that: (1) better capture patient-derived therapeutic biomarkers compared to models trained on CCL data, (2) can be robustly validated across independent PDX cohorts, and (3) could contribute to the development of future therapeutic biomarkers.

Impact of genomic background and developmental state on signaling pathways and response to therapy in glioblastoma patient-derived cells

Glioblastoma (GBM) tumors represents diverse genomic epigenomic, and transcriptional landscapes, with significant intratumoral heterogeneity that challenges standard of care treatments involving radiation (RT) and the DNA-alkylating agent temozolomide (TMZ). In this study, we employed targeted proteomics to assess the response of a genomically-diverse panel of GBM patient-derived cancer stem cells (CSCs) to astrocytic differentiation, growth factor withdrawal and traditional high fetal bovine serum culture. Our findings revealed a complex crosstalk and co-activation of key oncogenic signaling in CSCs and diverse patterns of response to these external stimuli. Using RNA sequencing and DNA methylation, we observed common adaptations in response to astrocytic differentiation of CSCs across genomically distinct models, including BMP-Smad pathway activation, reduced cholesterol biosynthesis, and upregulation of extracellular matrix components. Notably, we observed that these differentiated CSC progenies retained a subset of stemness genes and the activation of cell survival pathways. We also examined the impact of differentiation state and genomic background on GBM cell sensitivity and transcriptional response to TMZ and RT. Differentiation of CSCs increased resistance to TMZ but not to RT. While transcriptional responses to these treatments were predominantly regulated by p53 in wild-type p53 GBM cells, its transcriptional activity was modulated by the differentiation status and treatment modality. Both mutant and wild-type p53 models exhibited significant activation of a DNA-damage associated interferon response in CSCs and differentiated cells, suggesting this pathway may play a wider role in GBM response to TMZ and RT. Our integrative analysis of the impact of GBM cell developmental states, in the context of genomic and molecular diversity of patient-derived models, provides valuable insights for pre-clinical studies aimed at optimizing treatment strategies.

Unveiling Therapeutic Opportunities with Melanoma Patient-derived Organoid Models

With the development of immunotherapy, there is an ongoing need to develop models that can recapitulate the tumor microenvironment of native tumors. While traditional two- and three-dimensional models can offer insights into cancer development and progression, these lack crucial aspects that hinder a faithful mimic of native tumors. An alternative model that has gained a lot of attention is the patient-derived organoid. The development of these organoids recapitulates the complex intercellular communication, tumor microenvironment, and histoarchitecture of tumors. This paper describes the protocol for establishing melanoma patient-derived organoid (MPDO) models. To validate these models, we assessed the immune cell composition, including the expression levels of T-cell activation markers, to confirm the cellular heterogeneity of the organoids. Additionally, to describe the potential utility of MPDOs in cellular therapies, we evaluated the cytotoxic capabilities of treating the organoids with γδ T-cells. In conclusion, the MPDO models offer promising avenues for understanding tumor complexity, validating therapeutic strategies, and potentially advancing personalized treatment.

Single-cell analysis of breast cancer metastasis reveals epithelial-mesenchymal plasticity signatures associated with poor outcomes

Metastasis is the leading cause of cancer-related deaths. It is unclear how intratumor heterogeneity (ITH) contributes to metastasis and how metastatic cells adapt to distant tissue environments. The study of these adaptations is challenged by the limited access to patient material and a lack of experimental models that appropriately recapitulate ITH. To investigate metastatic cell adaptations and the contribution of ITH to metastasis, we analyzed single-cell transcriptomes of matched primary tumors and metastases from patient-derived xenograft models of breast cancer. We found profound transcriptional differences between the primary tumor and metastatic cells. Primary tumors upregulated several metabolic genes, whereas motility pathway genes were upregulated in micrometastases, and stress response signaling was upregulated during progression. Additionally, we identified primary tumor gene signatures that were associated with increased metastatic potential and correlated with patient outcomes. Immune-regulatory control pathways were enriched in poorly metastatic primary tumors, whereas genes involved in epithelial-mesenchymal transition were upregulated in highly metastatic tumors. We found that ITH was dominated by epithelial-mesenchymal plasticity (EMP), which presented as a dynamic continuum with intermediate EMP cell states characterized by specific genes such as CRYAB and S100A2. Elevated expression of an intermediate EMP signature correlated with worse patient outcomes. Our findings identified inhibition of the intermediate EMP cell state as a potential therapeutic target to block metastasis.

XENTURION is a population-level multidimensional resource of xenografts and tumoroids from metastatic colorectal cancer patients

The breadth and depth at which cancer models are interrogated contribute to the successful clinical translation of drug discovery efforts. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, where experimental therapies are typically tested. Here we introduce XENTURION, an open-science resource offering a platform of 128 PDX models from patients with metastatic CRC, along with matched PDX-derived tumoroids. Multidimensional omics analyses indicate that tumoroids retain extensive molecular fidelity with parental PDXs. A tumoroid-based trial with the anti-EGFR antibody cetuximab reveals variable sensitivities that are consistent with clinical response biomarkers, mirror tumor growth changes in matched PDXs, and recapitulate EGFR genetic deletion outcomes. Inhibition of adaptive signals upregulated by EGFR blockade increases the magnitude of cetuximab response. These findings illustrate the potential of large living biobanks, providing avenues for molecularly informed preclinical research in oncology.

Clinical and pathological predictors of engraftment for patient-derived xenografts in lung adenocarcinoma

Patient-derived xenografts (PDXs) are increasingly utilized in preclinical drug efficacy studies due to their ability to retain the molecular, histological, and drug response characteristics of patient tumors. This study aimed to investigate the factors influencing the successful engraftment of PDXs. Lung adenocarcinoma PDXs were established using freshly resected tumor tissues obtained through surgery. Radiological data of pulmonary nodules from this PDX cohort were analyzed, categorizing them into solid tumors and tumors with ground-glass opacity (GGO) based on preoperative CT images. Gene mutation status was obtained from next generation sequencing data and MassARRAY panel. A total of 254 resected primary lung adenocarcinomas were utilized for PDX establishment, with successful initial engraftment in 58 cases (22.8 %); stable engraftment defined as at least three serial passages was observed in 43 cases (16.9 %). The stable engraftment rates of PDXs from solid tumors and tumors with GGO were 22.1 % (42 of 190 cases) and 1.6 % (1 of 64 cases), respectively (P < 0.001). Adenocarcinomas with advanced stage, poor differentiation, solid histologic subtype, and KRAS or TP53 gene mutations were associated with stable PDX engraftment. Avoiding tumors with GGO features could enhance the cost-effectiveness of establishing PDX models from early-stage resected lung adenocarcinomas.

Amelanotic primary cervical malignant melanoma: A case report and review of literature

BACKGROUND

Primary malignant melanoma of the cervix (PMMC) is an extremely rare disease that originates from primary cervical malignant melanoma and frequently represents a challenge in disease diagnosis due to unclarified clinical and histological presentations, particularly those without melanin.

CASE SUMMARY

Here, we report a case of amelanotic PMMC, with a history of breast cancer and thyroid carcinoma. The patient was finally diagnosed by immunohistochemical staining and staged as IB2 based on the International Federation of Gynecology and Obstetrics with reference to National Comprehensive Cancer Network guidelines and was treated with radical hysterectomy, bilateral salpingo-oophorectomy and pelvic lymphadenectomy. She then received combination therapy consisting of immunotherapy with tislelizumab and radiofrequency hyperthermia. She has remained free of disease for more than 1 year.

CONCLUSION

The differential diagnosis process reenforced the notion that immunohistochemical staining is the most reliable approach for amelanotic PMMC diagnosis. Due to the lack of established therapeutic guidelines, empirical information from limited available studies does not provide the rationale for treatment-decision making. By integrating 'omics' technologies and patient-derived xenografts or mini-patient-derived xenograft models this will help to identify selective therapeutic window(s) and screen the appropriate therapeutics for targeted therapies, immune checkpoint blockade or combination therapy strategies effectively and precisely that will ultimately improve patient survival.

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.

Assessment of Patient-Derived Xenograft Growth and Antitumor Activity: The NCI PDXNet Consensus Recommendations

Although patient-derived xenografts (PDX) are commonly used for preclinical modeling in cancer research, a standard approach to in vivo tumor growth analysis and assessment of antitumor activity is lacking, complicating the comparison of different studies and determination of whether a PDX experiment has produced evidence needed to consider a new therapy promising. We present consensus recommendations for assessment of PDX growth and antitumor activity, providing public access to a suite of tools for in vivo growth analyses. We expect that harmonizing PDX study design and analysis and assessing a suite of analytical tools will enhance information exchange and facilitate identification of promising novel therapies and biomarkers for guiding cancer therapy.

A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of >1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a range of associated genomic and transcriptomic data, clinical metadata, pathologic assessments of cell composition, and, in several cases, detailed pathologic annotations of neoplastic, stromal, and necrotic regions. The amenability of these images to deep learning was highlighted through three applications: (i) development of a classifier for neoplastic, stromal, and necrotic regions; (ii) development of a predictor of xenograft-transplant lymphoproliferative disorder; and (iii) application of a published predictor of microsatellite instability. Together, this PDX Development and Trial Centers Research Network image repository provides a valuable resource for controlled digital pathology analysis, both for the evaluation of technical issues and for the development of computational image-based methods that make clinical predictions based on PDX treatment studies. Significance: A pan-cancer repository of >1,000 patient-derived xenograft hematoxylin and eosin-stained images will facilitate cancer biology investigations through histopathologic analysis and contributes important model system data that expand existing human histology repositories.

Patient-derived melanoma models

Melanoma is a very aggressive, rapidly metastasizing tumor that has been studied intensively in the past regarding the underlying genetic and molecular mechanisms. More recently developed treatment modalities have improved response rates and overall survival of patients. However, the majority of patients suffer from secondary treatment resistance, which requires in depth analyses of the underlying mechanisms. Here, melanoma models based on patients-derived material may play an important role. Consequently, a plethora of different experimental techniques have been developed in the past years. Among these are 3D and 4D culture techniques, organotypic skin reconstructs, melanoma-on-chip models and patient-derived xenografts, Every technique has its own strengths but also weaknesses regarding throughput, reproducibility, and reflection of the human situation. Here, we provide a comprehensive overview of currently used techniques and discuss their use in different experimental settings.

Patient-Derived-Xenografts in Mice: A Preclinical Platform for Cancer Research

The use of patient-derived xenografts (PDXs) has dramatically improved drug development programs. PDXs (1) reproduce the pathological features and the genomic profile of the parental tumors more precisely than other preclinical models, and (2) more faithfully predict therapy response. However, PDXs have limitations. These include the inability to completely capture tumor heterogeneity and the role of the immune system, the low engraftment efficiency of certain tumor types, and the consequences of the human-host interactions. Recently, the use of novel mouse strains and specialized engraftment techniques has enabled the generation of "humanized" PDXs, partially overcoming such limitations. Importantly, establishing, characterizing, and maintaining PDXs is costly and requires a significant regulatory, administrative, clinical, and laboratory infrastructure. In this review, we will retrace the historical milestones that led to the implementation of PDXs for cancer research, review the most recent innovations in the field, and discuss future avenues to tackle deficiencies that still exist.

Rat Models of Hormone Receptor-Positive Breast Cancer

Hormone receptor-positive (HR+) breast cancer (BC) is the most common type of breast cancer among women worldwide, accounting for 70-80% of all invasive cases. Patients with HR+ BC are commonly treated with endocrine therapy, but intrinsic or acquired resistance is a frequent problem, making HR+ BC a focal point of intense research. Despite this, the malignancy still lacks adequate in vitro and in vivo models for the study of its initiation and progression as well as response and resistance to endocrine therapy. No mouse models that fully mimic the human disease are available, however rat mammary tumor models pose a promising alternative to overcome this limitation. Compared to mice, rats are more similar to humans in terms of mammary gland architecture, ductal origin of neoplastic lesions and hormone dependency status. Moreover, rats can develop spontaneous or induced mammary tumors that resemble human HR+ BC. To date, six different types of rat models of HR+ BC have been established. These include the spontaneous, carcinogen-induced, transplantation, hormone-induced, radiation-induced and genetically engineered rat mammary tumor models. Each model has distinct advantages, disadvantages and utility for studying HR+ BC. This review provides a comprehensive overview of all published models to date.

Receptor tyrosine kinase inhibition leads to regression of acral melanoma by targeting the tumor microenvironment

Acral melanoma (AM) is an aggressive melanoma variant that arises from palmar, plantar, and nail unit melanocytes. Compared to non-acral cutaneous melanoma (CM), AM is biologically distinct, has an equal incidence across genetic ancestries, typically presents in advanced stage disease, is less responsive to therapy, and has an overall worse prognosis. Independent analysis of published genomic and transcriptomic sequencing identified that receptor tyrosine kinase (RTK) ligands and adapter proteins are frequently amplified, translocated, and/or overexpressed in AM. To target these unique genetic changes, a zebrafish acral melanoma model was exposed to a panel of narrow and broad spectrum multi-RTK inhibitors, revealing that dual FGFR/VEGFR inhibitors decrease acral-analogous melanocyte proliferation and migration. The potent pan-FGFR/VEGFR inhibitor, Lenvatinib, uniformly induces tumor regression in AM patient-derived xenograft (PDX) tumors but only slows tumor growth in CM models. Unlike other multi-RTK inhibitors, Lenvatinib is not directly cytotoxic to dissociated AM PDX tumor cells and instead disrupts tumor architecture and vascular networks. Considering the great difficulty in establishing AM cell culture lines, these findings suggest that AM may be more sensitive to microenvironment perturbations than CM. In conclusion, dual FGFR/VEGFR inhibition may be a viable therapeutic strategy that targets the unique biology of AM.

High efficacy of huCD20-targeted AcTaferon in humanized patient derived xenograft models of aggressive B cell lymphoma

Type I interferon (IFN) is a potent antitumoral drug, with an important history in the treatment of hematologic malignancies. However, its pleiotropic nature leads to severe dose-limiting toxicities that blunt its therapeutic potential. To achieve selective targeting of specific immune or tumor cells, AcTakines (Activity-on-Target Cytokines), i.e., immunocytokines utilizing attenuated cytokines, and clinically optimized A-Kines™ were developed. In syngeneic murine models, the CD20-targeted murine IFNα2-based AcTaferons (AFNs) have demonstrated clear antitumoral effects, with excellent tolerability. The current study explores the antitumoral potential of the humanized huCD20-Fc-AFN in 5 different humanized patient derived xenograft (PDX) models of huCD20+ aggressive B non-Hodgkin lymphomas (B-NHLs). The huCD20-Fc-AFN consists of a huCD20-specific single-domain antibody (VHH) linked through a heterodimeric 'knob-in-hole' human IgG1 Fc molecule to an attenuated huIFNα2 sequence. An in vitro targeting efficacy of up to 1.000-fold could be obtained, without detectable in vivo toxicities, except for selective (on-target) and reversible B cell depletion. Treatment with huCD20-Fc-AFN significantly increased the median overall survival (mOS) in both non-humanized (mOS 31 to 45 days; HR = 0.26; p = 0.001), and humanized NSG/NOG mice (mOS 34 to 80 days; HR = 0.37; p < 0.0001). In humanized mice, there was a trend for increased survival when compared to equimolar rituximab (mOS 49 to 80 days; HR = 0.73; p = 0.09). The antitumoral effects of huCD20-Fc-AFN were partly due to direct effects of type I IFN on the tumor cells, but additional effects via the human immune system are essential to obtain long-term remissions. To conclude, huCD20-Fc-AFN could provide a novel therapeutic strategy for huCD20-expressing aggressive B-NHLs.

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.

Defining the challenges and opportunities for using patient-derived models in prostate cancer research

BACKGROUND

There are relatively few widely used models of prostate cancer compared to other common malignancies. This impedes translational prostate cancer research because the range of models does not reflect the diversity of disease seen in clinical practice. In response to this challenge, research laboratories around the world have been developing new patient-derived models of prostate cancer, including xenografts, organoids, and tumor explants.

METHODS

In May 2023, we held a workshop at the Monash University Prato Campus for researchers with expertise in establishing and using a variety of patient-derived models of prostate cancer. This review summarizes our collective ideas on how patient-derived models are currently being used, the common challenges, and future opportunities for maximizing their usefulness in prostate cancer research.

RESULTS

An increasing number of patient-derived models for prostate cancer are being developed. Despite their individual limitations and varying success rates, these models are valuable resources for exploring new concepts in prostate cancer biology and for preclinical testing of potential treatments. Here we focus on the need for larger collections of models that represent the changing treatment landscape of prostate cancer, robust readouts for preclinical testing, improved in vitro culture conditions, and integration of the tumor microenvironment. Additional priorities include ensuring model reproducibility, standardization, and replication, and streamlining the exchange of models and data sets among research groups.

CONCLUSIONS

There are several opportunities to maximize the impact of patient-derived models on prostate cancer research. We must develop large, diverse and accessible cohorts of models and more sophisticated methods for emulating the intricacy of patient tumors. In this way, we can use the samples that are generously donated by patients to advance the outcomes of patients in the future.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

BACKGROUND

A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials.

METHODS

Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors.

RESULTS

We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components.

CONCLUSIONS

Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

The Power and Promise of Patient-Derived Xenografts of Human Breast Cancer

In 2016, a group of researchers engaged in the development of patient-derived xenografts (PDXs) of human breast cancer provided a comprehensive review of the state of the field. In that review, they summarized the clinical problem that PDXs might address, the technical approaches to their generation (including a discussion of host animals and transplant conditions tested), and presented transplantation success (take) rates across groups and across transplantation conditions. At the time, there were just over 500 unique PDX models created by these investigators representing all three clinically defined subtypes (ER+, HER2+, and TNBC). Today, many of these PDX resources have at least doubled in size, and several more PDX development groups now exist, such that there may be well upward of 1000 PDX models of human breast cancer in existence worldwide. They also presented a series of open questions for the field. Many of these questions have been addressed. However, several remain open, or only partially addressed. Herein, we revisit these questions, and recount the progress that has been made in a number of areas with respect to generation, characterization, and use of PDXs in translational research, and re-present questions that remain open. These open questions, and others, are now being addressed not only by individual investigators, but also large, well-funded consortia including the PDXNet program of the National Cancer Institute in the United States, and the EuroPDX Consortium, an organization of PDX developers across Europe. Finally, we discuss the new opportunities in PDX-based research.

A Case Study of a Rare Undifferentiated Spindle Cell Sarcoma of the Penis: Establishment and Characterization of Patient-Derived Models

Rare sarcomas present significant treatment challenges compared to more prevalent soft tissue sarcomas due to limited treatment options and a poor understanding of their biology. This study investigates a unique case of penile sarcoma, providing a comprehensive morphological and molecular analysis. Through the creation of experimental patient-derived models-including patient-derived xenograft (PDX), 3D, and monolayer primary cultures-we successfully replicated crucial molecular traits observed in the patient's tumor, such as smooth muscle actin and CD99 expression, along with specific mutations in genes like TSC2 and FGFR4. These models are helpful in assessing the potential for an in-depth exploration of this tumor's biology. This comprehensive approach holds promise in identifying potential therapeutic avenues for managing this exceedingly rare soft tissue sarcoma.

Humanized mouse models: A valuable platform for preclinical evaluation of human cancer

Animal models are routinely employed to assess the treatments for human cancer. However, due to significant differences in genetic backgrounds, traditional animal models are unable to meet bioresearch needs. To overcome this restriction, researchers have generated and optimized immunodeficient mice, and then engrafted human genes, cells, tissues, or organs in mice so that the responses in the model mice could provide a more reliable reference for treatments. As a bridge connecting clinical application and basic research, humanized mice are increasingly used in the preclinical evaluation of cancer treatments, particularly after gene interleukin 2 receptor gamma mutant mice were generated. Human cancer models established in humanized mice support exploration of the mechanism of cancer occurrence and provide an efficient platform for drug screening. However, it is undeniable that the further application of humanized mice still faces multiple challenges. This review summarizes the construction approaches for humanized mice and their existing limitations. We also report the latest applications of humanized mice in preclinical evaluation for the treatment of cancer and point out directions for future optimization of these models.

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.

Nanoparticle-Encapsulated Epirubicin Efficacy in the Inhibition of Growth of Orthotopic Ovarian Patient-Derived Xenograft in Immunocompromised Mice

Epirubicin hydrochloride (EPI) is an anticancer drug widely used in the treatment of many solid tumors, including ovarian cancer. Because of its anatomical location, ovarian cancer shows symptoms when it is already in an advanced stage and is thus more difficult to treat. Epirubicin hydrochloride kills cancer cells effectively, but its dose escalation is limited by its severe toxicity. By encapsulating epirubicin in dextran-based nanoparticles (POLEPI), we expected to deliver higher and thus clinically more effective doses directly to tumors, where epirubicin would be released and retained longer in the tumor. The antitumor activity of POLEPI compared to EPI was first tested ex vivo in a series of ovarian cancer patient-derived tumor xenografts (PDX). The most promising PDX was then implanted orthotopically into immunocompromised mice, and tumor growth was monitored via magnetic resonance imaging (MRI). Although we succeeded in suppressing the growth of ovarian cancer derived from a patient, in a mouse model by 70% compared to 40% via EPI in 5 days after only one injection, we could not eliminate serious side effects, and the study was terminated prematurely for humane reasons.

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.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

Background

A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials.

Methods

Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA-sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors.

Results

We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components.

Conclusions

Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

Genomic profiling of subcutaneous patient-derived xenografts reveals immune constraints on tumor evolution in childhood solid cancer

Subcutaneous patient-derived xenografts (PDXs) are an important tool for childhood cancer research. Here, we describe a resource of 68 early passage PDXs established from 65 pediatric solid tumor patients. Through genomic profiling of paired PDXs and patient tumors (PTs), we observe low mutational similarity in about 30% of the PT/PDX pairs. Clonal analysis in these pairs show an aggressive PT minor subclone seeds the major clone in the PDX. We show evidence that this subclone is more immunogenic and is likely suppressed by immune responses in the PT. These results suggest interplay between intratumoral heterogeneity and antitumor immunity may underlie the genetic disparity between PTs and PDXs. We further show that PDXs generally recapitulate PTs in copy number and transcriptomic profiles. Finally, we report a gene fusion LRPAP1-PDGFRA. In summary, we report a childhood cancer PDX resource and our study highlights the role of immune constraints on tumor evolution.

Comprehensive characterization of patient-derived xenograft models of pediatric leukemia

Patient-derived xenografts (PDX) remain valuable models for understanding the biology and for developing novel therapeutics. To expand current PDX models of childhood leukemia, we have developed new PDX models from Hispanic patients, a subgroup with a poorer overall outcome. Of 117 primary leukemia samples obtained, successful engraftment and serial passage in mice were achieved in 82 samples (70%). Hispanic patient samples engrafted at a rate (51/73, 70%) that was similar to non-Hispanic patient samples (31/45, 70%). With a new algorithm to remove mouse contamination in multi-omics datasets including methylation data, we found PDX models faithfully reflected somatic mutations, copy-number alterations, RNA expression, gene fusions, whole-genome methylation patterns, and immunophenotypes found in primary tumor (PT) samples in the first 50 reported here. This cohort of characterized PDX childhood leukemias represents a valuable resource in that germline DNA sequencing has allowed the unambiguous determination of somatic mutations in both PT and PDX.

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.

Meningioma animal models: a systematic review and meta-analysis

BACKGROUND

Animal models are widely used to study pathological processes and drug (side) effects in a controlled environment. There is a wide variety of methods available for establishing animal models depending on the research question. Commonly used methods in tumor research include xenografting cells (established/commercially available or primary patient-derived) or whole tumor pieces either orthotopically or heterotopically and the more recent genetically engineered models-each type with their own advantages and disadvantages. The current systematic review aimed to investigate the meningioma model types used, perform a meta-analysis on tumor take rate (TTR), and perform critical appraisal of the included studies. The study also aimed to assess reproducibility, reliability, means of validation and verification of models, alongside pros and cons and uses of the model types.

METHODS

We searched Medline, Embase, and Web of Science for all in vivo meningioma models. The primary outcome was tumor take rate. Meta-analysis was performed on tumor take rate followed by subgroup analyses on the number of cells and duration of incubation. The validity of the tumor models was assessed qualitatively. We performed critical appraisal of the methodological quality and quality of reporting for all included studies.

RESULTS

We included 114 unique records (78 using established cell line models (ECLM), 21 using primary patient-derived tumor models (PTM), 10 using genetically engineered models (GEM), and 11 using uncategorized models). TTRs for ECLM were 94% (95% CI 92-96) for orthotopic and 95% (93-96) for heterotopic. PTM showed lower TTRs [orthotopic 53% (33-72) and heterotopic 82% (73-89)] and finally GEM revealed a TTR of 34% (26-43).

CONCLUSION

This systematic review shows high consistent TTRs in established cell line models and varying TTRs in primary patient-derived models and genetically engineered models. However, we identified several issues regarding the quality of reporting and the methodological approach that reduce the validity, transparency, and reproducibility of studies and suggest a high risk of publication bias. Finally, each tumor model type has specific roles in research based on their advantages (and disadvantages).

SYSTEMATIC REVIEW REGISTRATION

PROSPERO-ID CRD42022308833.

A biobank of pediatric patient-derived-xenograft models in cancer precision medicine trial MAPPYACTS for relapsed and refractory tumors

Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient's tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Pediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and treatments development in advanced pediatric malignancies.

Establishment of a high-fidelity patient-derived xenograft model for cervical cancer enables the evaluation of patient's response to conventional and novel therapies

BACKGROUND

Recurrent or metastatic cervical cancer (r/m CC) often has poor prognosis owing to its limited treatment options. The development of novel therapeutic strategies has been hindered by the lack of preclinical models that accurately reflect the biological and genomic heterogeneity of cervical cancer (CC). Herein, we aimed to establish a large patient-derived xenograft (PDX) biobank for CC, evaluate the consistency of the biologic indicators between PDX and primary tumor tissues of patients, and explore its utility for assessing patient's response to conventional and novel therapies.

METHODS

Sixty-nine fresh CC tumor tissues were implanted directly into immunodeficient mice to establish PDX models. The concordance of the PDX models with their corresponding primary tumors (PTs) was compared based on the clinical pathological features, protein biomarker levels, and genomic features through hematoxylin & eosin staining, immunohistochemistry, and whole exome sequencing, respectively. Moreover, the clinical information of CC patients, RNA transcriptome and immune phenotyping of primary tumors were integrated to identify the potential parameters that could affect the success of xenograft engraftment. Subsequently, PDX model was evaluated for its capacity to mirror patient's response to chemotherapy. Finally, PDX model and PDX-derived organoid (PDXO) were utilized to evaluate the therapeutic efficacy of neratinib and adoptive cell therapy (ACT) combination strategy for CC patients with human epidermal growth factor receptor 2 (HER2) mutation.

RESULTS

We established a PDX biobank for CC with a success rate of 63.8% (44/69). The primary features of established PDX tumors, including clinicopathological features, the expression levels of protein biomarkers including Ki67, α-smooth muscle actin, and p16, and genomics, were highly consistent with their PTs. Furthermore, xenograft engraftment was likely influenced by the primary tumor size, the presence of follicular helper T cells and the expression of cell adhesion-related genes in primary tumor tissue. The CC derived PDX models were capable of recapitulating the patient's response to chemotherapy. In a PDX model, a novel therapeutic strategy, the combination of ACT and neratinib, was shown to effectively inhibit the growth of PDX tumors derived from CC patients with HER2-mutation.

CONCLUSIONS

We established by far the largest PDX biobank with a high engraftment rate for CC that preserves the histopathological and genetic characteristics of patient's biopsy samples, recapitulates patient's response to conventional therapy, and is capable of evaluating the efficacy of novel therapeutic modalities for CC.

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.

Establishment and characterization of two novel patient-derived lines from canine high-grade glioma

High-grade glioma is an aggressive cancer that occurs naturally in pet dogs. Canine high-grade glioma (cHGG) is treated with radiation, chemotherapy or surgery, but has no curative treatment. Within the past eight years, there have been advances in our imaging and histopathology standards as well as genetic charactereization of cHGG. However, there are only three cHGG cell lines publicly available, all of which were derived from astrocytoma and established using methods involving expansion of tumour cells in vitro on plastic dishes. In order to provide more clinically relevant cell lines for studying cHGG in vitro, the goal of this study was to establish cHGG patient-derived lines, whereby cancer cells are expanded in vivo by injecting cells into immunocompromized laboratory mice. The cells are then harvested from mice and used for in vitro studies. This method is the standard in the human field and has been shown to minimize the acquisition of genetic alterations and gene expression changes from the original tumour. Through a multi-institutional collaboration, we describe our methods for establishing two novel cHGG patient-derived lines, Boo-HA and Mo-HO, from a high-grade astrocytoma and a high-grade oligodendroglioma, respectively. We compare our novel lines to G06-A, J3T-Bg, and SDT-3G (traditional cHGG cell lines) in terms of proliferation and sensitivity to radiation. We also perform whole genome sequencing and identify an NF1 truncating mutation in Mo-HO. We report the characterization and availability of these novel patient-derived lines for use by the veterinary community.

Patient-Derived Organoids as a Promising Tool for Multimodal Management of Sarcomas

The management of sarcomas, a diverse group of cancers arising from connective tissues, presents significant challenges due to their heterogeneity and limited treatment options. Patient-derived sarcoma organoids (PDSOs) have emerged as a promising tool in the multimodal management of sarcomas, offering unprecedented opportunities for personalized medicine and improved treatment strategies. This review aims to explore the potential of PDSOs as a promising tool for multimodal management of sarcomas. We discuss the establishment and characterization of PDSOs, which realistically recapitulate the complexity and heterogeneity of the original tumor, providing a platform for genetic and molecular fidelity, histological resemblance, and functional characterization. Additionally, we discuss the applications of PDSOs in pathological and genetic evaluation, treatment screening and development, and personalized multimodal management. One significant advancement of PDSOs lies in their ability to guide personalized treatment decisions, enabling clinicians to assess the response and efficacy of different therapies in a patient-specific manner. Through continued research and development, PDSOs hold the potential to revolutionize sarcoma management and drive advancements in personalized medicine, biomarker discovery, preclinical modeling, and therapy optimization. The integration of PDSOs into clinical practice can ultimately improve patient outcomes and significantly impact the field of sarcoma treatment.

Pan-glioma analyses reveal species- and tumor-specific regulation of neuron-glioma synapse genes by lncRNAs

Gliomas are highly heterogeneous and aggressive. Malignant cells in gliomas can contact normal neurons through a synapse-like structure (called neuron-to-glioma synapse, NGS) to promote their proliferation, but it is unclear whether NGS gene expression and regulation show species- and tumor-specificity. This question is important in that many anti-cancer drugs are developed upon mouse models. To address this question, we conducted a pan-glioma analysis using nine scRNA-seq datasets from humans and mice. We also experimentally validated the key element of our methods and verified a key result using TCGA datasets of the same glioma types. Our analyses revealed that NGS gene expression and regulation by lncRNAs are highly species- and tumor-specific. Importantly, simian-specific lncRNAs are more involved in NGS gene regulation than lncRNAs conserved in mammals, and transgenic mouse gliomas have little in common with PDX mouse models and human gliomas in terms of NGS gene regulation. The analyses suggest that simian-specific lncRNAs are a new and rich class of potential targets for tumor-specific glioma treatment, and provide pertinent data for further experimentally and clinically exmining the targets.

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.

The challenge of making the right choice: patient avatars in the era of cancer immunotherapies

Immunotherapies are a key therapeutic strategy to fight cancer. Diverse approaches are used to activate tumor-directed immunity and to overcome tumor immune escape. The dynamic interplay between tumor cells and their tumor(immune)microenvironment (T(I)ME) poses a major challenge to create appropriate model systems. However, those model systems are needed to gain novel insights into tumor (immune) biology and a prerequisite to accurately develop and test immunotherapeutic approaches which can be successfully translated into clinical application. Several model systems have been established and advanced into so-called patient avatars to mimic the patient´s tumor biology. All models have their advantages but also disadvantages underscoring the necessity to pay attention in defining the rationale and requirements for which the patient avatar will be used. Here, we briefly outline the current state of tumor model systems used for tumor (immune)biological analysis as well as evaluation of immunotherapeutic agents. Finally, we provide a recommendation for further development to make patient avatars a complementary tool for testing and predicting immunotherapeutic strategies for personalization of tumor therapies.

Intergenic CircRNA Circ_0007379 Inhibits Colorectal Cancer Progression by Modulating miR-320a Biogenesis in a KSRP-Dependent Manner

Circular RNAs (circRNAs) are covalently closed RNA structures that play multiple roles in tumorigenesis and progression. Compared with exon‒intron circRNAs, the biological functions and implications of intergenic circRNAs in human cancer are still poorly understood. Here, we performed circRNA microarray analysis and identified an intergenic circRNA, circ_0007379, that was significantly downregulated in patients with colorectal cancer (CRC). The biogenesis of circ_0007379 was mediated by reverse complementary matches (RCMs) and was negatively regulated by the RNA helicase DHX9. Functionally, circ_0007379 suppressed CRC cell growth and metastasis in cell culture as well as in patient-derived organoid and xenograft models. Mechanistically, circ_0007379 acted as a scaffold to facilitate the processing of both pri-miR-320a and pre-miR-320a in a KSRP-dependent manner, leading to miR-320a maturation and subsequent repression of transcription factor RUNX1 expression. Thus, our findings establish a previously unrecognized function of circRNA in inhibiting CRC progression.

Imagine beyond: recent breakthroughs and next challenges in mammary gland biology and breast cancer research

On 8 December 2022 the organizing committee of the European Network for Breast Development and Cancer labs (ENBDC) held its fifth annual Think Tank meeting in Amsterdam, the Netherlands. Here, we embraced the opportunity to look back to identify the most prominent breakthroughs of the past ten years and to reflect on the main challenges that lie ahead for our field in the years to come. The outcomes of these discussions are presented in this position paper, in the hope that it will serve as a summary of the current state of affairs in mammary gland biology and breast cancer research for early career researchers and other newcomers in the field, and as inspiration for scientists and clinicians to move the field forward.

Combined proteomics and CRISPR‒Cas9 screens in PDX identify ADAM10 as essential for leukemia in vivo

BACKGROUND

Acute leukemias represent deadly malignancies that require better treatment. As a challenge, treatment is counteracted by a microenvironment protecting dormant leukemia stem cells.

METHODS

To identify responsible surface proteins, we performed deep proteome profiling on minute numbers of dormant patient-derived xenograft (PDX) leukemia stem cells isolated from mice. Candidates were functionally screened by establishing a comprehensive CRISPR‒Cas9 pipeline in PDX models in vivo.

RESULTS

A disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) was identified as an essential vulnerability required for the survival and growth of different types of acute leukemias in vivo, and reconstitution assays in PDX models confirmed the relevance of its sheddase activity. Of translational importance, molecular or pharmacological targeting of ADAM10 reduced PDX leukemia burden, cell homing to the murine bone marrow and stem cell frequency, and increased leukemia response to conventional chemotherapy in vivo.

CONCLUSIONS

These findings identify ADAM10 as an attractive therapeutic target for the future treatment of acute leukemias.

Stratification of Tamoxifen Synergistic Combinations for the Treatment of ER+ Breast Cancer

Breast cancer alone accounts for the majority of cancer deaths among women, with the most commonly diagnosed subtype being estrogen receptor positive (ER+). Survival has greatly improved for patients with ER+ breast cancer, due in part to the development of antiestrogen compounds, such as tamoxifen. While treatment of the primary disease is often successful, as many as 30% of patients will experience recurrence and metastasis, mainly due to developed endocrine therapy resistance. In this study, we discovered two tamoxifen combination therapies, with simeprevir and VX-680, that reduce the tumor burden in animal models of ER+ breast cancer more than either compound or tamoxifen alone. Additionally, these tamoxifen combinations reduced the expression of HER2, a hallmark of tamoxifen treatment, which can facilitate acquisition of a treatment-resistant phenotype. These combinations could provide clinical benefit by potentiating tamoxifen treatment in ER+ breast cancer.

The future of patient-derived xenografts in prostate cancer research

Patient-derived xenografts (PDXs) are generated by engrafting human tumours into mice. Serially transplantable PDXs are used to study tumour biology and test therapeutics, linking the laboratory to the clinic. Although few prostate cancer PDXs are available in large repositories, over 330 prostate cancer PDXs have been established, spanning broad clinical stages, genotypes and phenotypes. Nevertheless, more PDXs are needed to reflect patient diversity, and to study new treatments and emerging mechanisms of resistance. We can maximize the use of PDXs by exchanging models and datasets, and by depositing PDXs into biorepositories, but we must address the impediments to accessing PDXs, such as institutional, ethical and legal agreements. Through collaboration, researchers will gain greater access to PDXs representing diverse features of prostate cancer.

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.

A new tumorgraft panel to accelerate precision medicine in prostate cancer

Background

Despite the significant advances in the management of advanced prostate cancer (PCa), metastatic PCa is currently considered incurable. For further investigations in precision treatment, the development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.

Methods

Fresh tumor samples along with normal corresponding tissues were obtained directly from patients at surgery. To ensure that the established models reproduce the main features of patient's tumor, both PDX tumors at multiple passages and patient's primary tumors, were processed for histological characteristics. STR profile analyses were also performed to confirm patient identity. Finally, the responses of the PDX models to androgen deprivation, PARP inhibitors and chemotherapy were also evaluated.

Results

In this study, we described the development and characterization of 5 new PDX models of PCa. Within this collection, hormone-naïve, androgen-sensitive and castration-resistant (CRPC) primary tumors as well as prostate carcinoma with neuroendocrine differentiation (CRPC-NE) were represented. Interestingly, the comprehensive genomic characterization of the models identified recurrent cancer driver alterations in androgen signaling, DNA repair and PI3K, among others. Results were supported by expression patterns highlighting new potential targets among gene drivers and the metabolic pathway. In addition, in vivo results showed heterogeneity of response to androgen deprivation and chemotherapy, like the responses of patients to these treatments. Importantly, the neuroendocrine model has been shown to be responsive to PARP inhibitor.

Conclusion

We have developed a biobank of 5 PDX models from hormone-naïve, androgen-sensitive to CRPC primary tumors and CRPC-NE. Increased copy-number alterations and accumulation of mutations within cancer driver genes as well as the metabolism shift are consistent with the increased resistance mechanisms to treatment. The pharmacological characterization suggested that the CRPC-NE could benefit from the PARP inhibitor treatment. Given the difficulties in developing such models, this relevant panel of PDX models of PCa will provide the scientific community with an additional resource for the further development of PDAC research.

The role of tumor microenvironment in drug resistance: emerging technologies to unravel breast cancer heterogeneity

Breast cancer is a highly heterogeneous disease, at both inter- and intra-tumor levels, and this heterogeneity is a crucial determinant of malignant progression and response to treatments. In addition to genetic diversity and plasticity of cancer cells, the tumor microenvironment contributes to tumor heterogeneity shaping the physical and biological surroundings of the tumor. The activity of certain types of immune, endothelial or mesenchymal cells in the microenvironment can change the effectiveness of cancer therapies via a plethora of different mechanisms. Therefore, deciphering the interactions between the distinct cell types, their spatial organization and their specific contribution to tumor growth and drug sensitivity is still a major challenge. Dissecting intra-tumor heterogeneity is currently an urgent need to better define breast cancer biology and to develop therapeutic strategies targeting the microenvironment as helpful tools for combined and personalized treatment. In this review, we analyze the mechanisms by which the tumor microenvironment affects the characteristics of tumor heterogeneity that ultimately result in drug resistance, and we outline state of the art preclinical models and emerging technologies that will be instrumental in unraveling the impact of the tumor microenvironment on resistance to therapies.

Dissecting metastasis using preclinical models and methods

Metastasis has long been understood to lead to the overwhelming majority of cancer-related deaths. However, our understanding of the metastatic process, and thus our ability to prevent or eliminate metastases, remains frustratingly limited. This is largely due to the complexity of metastasis, which is a multistep process that likely differs across cancer types and is greatly influenced by many aspects of the in vivo microenvironment. In this Review, we discuss the key variables to consider when designing assays to study metastasis: which source of metastatic cancer cells to use and where to introduce them into mice to address different questions of metastasis biology. We also examine methods that are being used to interrogate specific steps of the metastatic cascade in mouse models, as well as emerging techniques that may shed new light on previously inscrutable aspects of metastasis. Finally, we explore approaches for developing and using anti-metastatic therapies, and how mouse models can be used to test them.