Characterization of a large panel of patient-derived tumor xenografts representing the clinical heterogeneity of human colorectal cancer

Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer

Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer. We demonstrate that the utilization of patient-specific databases guided by transcriptional profiles increases the depth of human protein identification in PDX models. Our data show that human proteomes of serially passaged PDXs differ significantly from their patient-derived tumor of origin. Analysis of differentially abundant proteins revealed enrichment of distinct biological pathways with major downregulated processes including extracellular matrix organization and the immune system. Finally, we investigated the relative abundances of ovarian cancer-related proteins identified from the Cancer Gene Census across serially passaged PDXs, and found their protein levels to be unstable across PDX models. Our findings highlight features of distinct and dynamic proteomes of serially-passaged PDX models of ovarian cancer.

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.

Deciphering resistance mechanisms in cancer: final report of MATCH-R study with a focus on molecular drivers and PDX development

BACKGROUND

Understanding the resistance mechanisms of tumor is crucial for advancing cancer therapies. The prospective MATCH-R trial (NCT02517892), led by Gustave Roussy, aimed to characterize resistance mechanisms to cancer treatments through molecular analysis of fresh tumor biopsies. This report presents the genomic data analysis of the MATCH-R study conducted from 2015 to 2022 and focuses on targeted therapies.

METHODS

The study included resistant metastatic patients (pts) who accepted an image-guided tumor biopsy. After evaluation of tumor content (TC) in frozen tissue biopsies, targeted NGS (10 < TC < 30%) or Whole Exome Sequencing and RNA sequencing (TC > 30%) were performed before and/or after the anticancer therapy. Patient-derived xenografts (PDX) were established by implanting tumor fragments into NOD scid gamma mice and amplified up to five passages.

RESULTS

A total of 1,120 biopsies were collected from 857 pts with the most frequent tumor types being lung (38.8%), digestive (16.3%) and prostate (14.1%) cancer. Molecular targetable driver were identified in 30.9% (n = 265/857) of the patients, with EGFR (41.5%), FGFR2/3 (15.5%), ALK (11.7%), BRAF (6.8%), and KRAS (5.7%) being the most common altered genes. Furthermore, 66.0% (n = 175/265) had a biopsy at progression on targeted therapy. Among resistant cases, 41.1% (n = 72/175) had no identified molecular mechanism, 32.0% (n = 56/175) showed on-target resistance, and 25.1% (n = 44/175) exhibited a by-pass resistance mechanism. Molecular profiling of the 44 patients with by-pass resistance identified 51 variants, with KRAS (13.7%), PIK3CA (11.8%), PTEN (11.8%), NF2 (7.8%), AKT1 (5.9%), and NF1 (5.9%) being the most altered genes. Treatment was tailored for 45% of the patients with a resistance mechanism identified leading to an 11 months median extension of clinical benefit. A total of 341 biopsies were implanted in mice, successfully establishing 136 PDX models achieving a 39.9% success rate. PDX models are available for EGFR (n = 31), FGFR2/3 (n = 26), KRAS (n = 18), ALK (n = 16), BRAF (n = 6) and NTRK (n = 2) driven cancers. These models closely recapitulate the biology of the original tumors in term of molecular alterations and pharmacological status, and served as valuable models to validate overcoming treatment strategies.

CONCLUSION

The MATCH-R study highlights the feasibility of on purpose image guided tumor biopsies and PDX establishment to characterize resistance mechanisms and guide personalized therapies to improve outcomes in pre-treated metastatic patients.

The roles of patient-derived xenograft models and artificial intelligence toward precision medicine

Patient-derived xenografts (PDX) involve transplanting patient cells or tissues into immunodeficient mice, offering superior disease models compared with cell line xenografts and genetically engineered mice. In contrast to traditional cell-line xenografts and genetically engineered mice, PDX models harbor the molecular and biologic features from the original patient tumor and are generationally stable. This high fidelity makes PDX models particularly suitable for preclinical and coclinical drug testing, therefore better predicting therapeutic efficacy. Although PDX models are becoming more useful, the several factors influencing their reliability and predictive power are not well understood. Several existing studies have looked into the possibility that PDX models could be important in enhancing our knowledge with regard to tumor genetics, biomarker discovery, and personalized medicine; however, a number of problems still need to be addressed, such as the high cost and time-consuming processes involved, together with the variability in tumor take rates. This review addresses these gaps by detailing the methodologies to generate PDX models, their application in cancer research, and their advantages over other models. Further, it elaborates on how artificial intelligence and machine learning were incorporated into PDX studies to fast-track therapeutic evaluation. This review is an overview of the progress that has been done so far in using PDX models for cancer research and shows their potential to be further improved in improving our understanding of oncogenesis.

Clinical relevance and therapeutic predictive ability of hypoxia biomarkers in head and neck cancer tumour models

Tumour hypoxia promotes poor patient outcomes, with particularly strong evidence for head and neck squamous cell carcinoma (HNSCC). To effectively target hypoxia, therapies require selection biomarkers and preclinical models that can accurately model tumour hypoxia. We established 20 patient-derived xenograft (PDX) and cell line-derived xenograft (CDX) models of HNSCC that we characterised for their fidelity to represent clinical HNSCC in gene expression, hypoxia status and proliferation and that were evaluated for their sensitivity to hypoxia-activated prodrugs (HAPs). PDX models showed greater fidelity in gene expression to clinical HNSCC than cell lines, as did CDX models relative to their paired cell lines. PDX models were significantly more hypoxic than CDX models, as assessed by hypoxia gene signatures and pimonidazole immunohistochemistry, and showed similar hypoxia gene expression to clinical HNSCC tumours. Hypoxia or proliferation status alone could not determine HAP sensitivity across our 20 HNSCC and two non-HNSCC tumour models by either tumour growth inhibition or killing of hypoxia cells in an ex vivo clonogenic assay. In summary, our tumour models provide clinically relevant HNSCC models that are suitable for evaluating hypoxia-targeting therapies; however, additional biomarkers to hypoxia are required to accurately predict drug sensitivity.

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.

Discovery of a nitroaromatic nannocystin with potent in vivo anticancer activity against colorectal cancer by targeting AKT1

The development of targeted chemotherapeutic agents against colorectal cancer (CRC), one of the most common cancers with a high mortality rate, is in a constant need. Nannocystins are a family of myxobacterial secondary metabolites featuring a 21-membered depsipeptide ring. The in vitro anti-CRC activity of natural and synthetic nannocystins was well documented, but little is known about their in vivo efficacy and if positive, the underlying mechanism of action. In this study we synthesized a nitroaromatic nannocystin through improved preparation of a key fragment, and characterized its in vitro activity and in vivo efficacy against CRC. We first described the total synthesis of compounds 2-4 featuring Heck macrocyclization to forge their 21-membered macrocycle. In a panel of 7 cancer cell lines from different tissues, compound 4 inhibited the cell viability with IC values of 1-6 nM. In particular, compound 4 (1, 2, 4 nM) inhibited the proliferation of CRC cell lines (HCT8, HCT116 and LoVo) in both concentration and time dependent manners. Furthermore, compound 4 concentration-dependently inhibited the colony formation and migration of CRC cell lines. Moreover, compound 4 induced cell cycle arrest at sub-G1 phase, apoptosis and cellular senescence in CRC cell lines. In three patient-derived CRC organoids, compound 4 inhibited the PDO with IC values of 3.68, 28.93 and 11.81 nM, respectively. In a patient-derived xenograft mouse model, injection of compound 4 (4, 8 mg/kg, i.p.) every other day for 12 times dose-dependently inhibited the tumor growth without significant change in body weight. We conducted RNA-sequencing, molecular docking and cellular thermal shift assay to elucidate the anti-CRC mechanisms of compound 4, and revealed that it exerted its anti-CRC effect at least in part by targeting AKT1.

Current Insights in Murine Models for Breast Cancer: Present, Past and Future

Breast cancer is an intricate disease that is increasing at a fast pace, and numerous heterogeneities within it further make it difficult to investigate. We have always used animal models to understand cancer pathology and create an in vivo microenvironment that closely resembles human cancer. They are considered an indispensable part of any clinical investigation regarding cancer. Animal models have a high potency in identifying the relevant biomarkers and genetic pathways involved in the course of disease prognosis. Researchers have previously explored a variety of organisms, including Drosophila melanogaster, zebrafish, and guinea pigs, to analyse breast cancer, but murine models have proven the most comprehensive due to their homologous nature with human chromosomes, easy availability, simple gene editing, and high adaptability. The available models have their pros and cons, and it depends on the researcher to select the one most relevant to their research question. Chemically induced models are cost-effective and simple to create. Transplantation models such as allografts and xenografts can mimic the human breast cancer environment reliably. Genetically engineered mouse models (GEMMs) help to underpin the genetic alterations involved and test novel immunotherapies. Virus-mediated models and gene knockout models have also provided new findings regarding breast cancer progression and metastasis. These mouse models have also enabled the visualization of breast cancer metastases. It is also imperative to consider the cost-effectiveness of these models. Despite loopholes, mouse models have evolved and are required for disease analysis.

Genetic Alterations of NF-κB and Its Regulators: A Rich Platform to Advance Colorectal Cancer Diagnosis and Treatment

Colorectal cancer (CRC) is the third leading cause of cancer mortality in the United States, with an estimated 52,000 deaths in 2023. Though significant progress has been made in both diagnosis and treatment of CRC in recent years, genetic heterogeneity of CRC-the culprit for possible CRC relapse and drug resistance, is still an insurmountable challenge. Thus, developing more effective therapeutics to overcome this challenge in new CRC treatment strategies is imperative. Genetic and epigenetic changes are well recognized to be responsible for the stepwise development of CRC malignancy. In this review, we focus on detailed genetic alteration information about the nuclear factor (NF)-κB signaling, including both NF-κB family members, and their regulators, such as protein arginine methyltransferase 5 (PRMT5), and outer dynein arm docking complex subunit 2 (ODAD2, also named armadillo repeat-containing 4, ARMC4), etc., in CRC patients. Moreover, we provide deep insight into different CRC research models, with a particular focus on patient-derived xenografts (PDX) and organoid models, and their potential applications in CRC research. Genetic alterations on NF-κB signaling components are estimated to be more than 50% of the overall genetic changes identified in CRC patients collected by cBioportal for Cancer Genomics; thus, emphasizing its paramount importance in CRC progression. Consequently, various genetic alterations on NF-κB signaling may hold great promise for novel therapeutic development in CRC. Future endeavors may focus on utilizing CRC models (e.g., PDX or organoids, or isogenic human embryonic stem cell (hESC)-derived colonic cells, or human pluripotent stem cells (hPSC)-derived colonic organoids, etc.) to further uncover the underpinning mechanism of these genetic alterations in NF-κB signaling in CRC progression. Moreover, establishing platforms for drug discovery in dishes, and developing Biobanks, etc., may further pave the way for the development of innovative personalized medicine to treat CRC in the future.

Prediction and prognostic potential of NR3C1 gene expression level in DLBCL patients

Objective: Diffuse Large B-Cell Lymphoma (DLBCL) is a common and frequently occurring subtype of Non-Hodgkin Lymphoma (NHL). The effective treatment and prognosis of DLBCL are still urgently needed to be explored. This article aims to shed light on the connection between DLBCL survival and NR3C1 expression levels. Methods: First, we divided the 952 DLBCL patients into an NR3C1 high-expression group and an NR3C1 low-expression group and compared the baseline characteristics of the two groups. Second, we used multivariate analysis to predict the dependent variable for age, pathology, ECOG score, lactate dehydrogenase (LDH) ratio, and NR3C1 expression level. Finally, we analyzed the progression-free survival (PFS) and overall survival rate (OS) of DLBCL patients with high or low NR3C1 expression. Results: DLBCL patients with high NR3C1 expression had a better prognosis than those with low NR3C1 expression (OS, P < 0.0001). In DLBCL patients of CHOP therapy, high NR3C1 expression was associated with a good survival prognosis in OS (OS, P = 0.028). Conclusion: In multivariate analysis, NR3C1 high expression was an independent prognostic factor that predicted a longer OS of DLBCL (OS, P = 0.0003). NR3C1 is considered an independent predictor of DLBCL patients and can be used as a biomarker for the prognosis of DLBCL.

Establishment and characterization of a non-gestational choriocarcinoma patient-derived xenograft model

BACKGROUND

Non-gestational choriocarcinoma (NGC) is a rare subtype of malignant germ cell tumour and there is no consensus on its treatment. The lack of suitable preclinical models for NGC is a challenge in drug discovery research. Patient-derived xenograft (PDX) models recapitulate the tumour microenvironment of the original cancer tissue. Therefore, they have received considerable attention for studies on rare cancer. Here, we aimed to establish a PDX model from a patient with recurrent NGC.

METHODS

Fresh NGC tumour tissue was immediately transplanted into a severely immune-deficient mouse (NOD.Cg-Prkdcscid1l2rgtm1Wjl/SzJ) and maintained for more than three in vivo passages. Subsequently, we evaluated the molecular characteristics of the PDX model using immunohistochemistry, polymerase chain reaction, and RNA sequencing. Moreover, the PDX tumours were transplanted into BALB/c nude mice, and we evaluated their sensitivity for cisplatin and methotrexate.

RESULTS

The PDX tumour maintained the morphological features of NGC. Moreover, Immunohistochemistry revealed that the human chorionic gonadotropin, cytokeratin 7, and EpCAM expression levels were similar to those in the primary tumour. Furthermore, serum human chorionic gonadotropin levels were elevated in both the primary tumour and the PDX models. Additionally, using PCR analysis with species-specific primers, we confirmed that the PDX tumour contained human genes and was derived from human tissue. Moreover, the gene expression profile of the NGC was compared with that of epithelial ovarian cancer samples and cell lines, and 568 dysregulated genes in the NGC were extracted. The expression of the dysregulated genes in PDX was significantly correlated with that in the primary tumour (R2 = 0.873, P < 0.001). Finally, we demonstrated that the PDX tumour was sensitive to cisplatin and methotrexate; therefore, its clinical response to the agents was similar to that of the primary tumour.

CONCLUSIONS

We successfully established a PDX model of NGC, to the best of our knowledge, for the first time. The established PDX retained the molecular and transcriptome characteristics of the primary tumour and can be used to predict drug effects. It may facilitate further research and the development of novel therapeutic agents for NGC.

Comparative analysis of response to treatments and molecular features of tumor-derived organoids versus cell lines and PDX derived from the same ovarian clear cell carcinoma

BACKGROUND

In the era of personalized medicine, the establishment of preclinical models of cancer that faithfully recapitulate original tumors is essential to potentially guide clinical decisions.

METHODS

We established 7 models [4 cell lines, 2 Patient-Derived Tumor Organoids (PDTO) and 1 Patient-Derived Xenograft (PDX)], all derived from the same Ovarian Clear Cell Carcinoma (OCCC). To determine the relevance of each of these models, comprehensive characterization was performed based on morphological, histological, and transcriptomic analyses as well as on the evaluation of their response to the treatments received by the patient. These results were compared to the clinical data.

RESULTS

Only the PDX and PDTO models derived from the patient tumor were able to recapitulate the patient tumor heterogeneity. The patient was refractory to carboplatin, doxorubicin and gemcitabine, while tumor cell lines were sensitive to these treatments. In contrast, PDX and PDTO models displayed resistance to the 3 drugs. The transcriptomic analysis was consistent with these results since the models recapitulating faithfully the clinical response grouped together away from the other classical 2D cell culture models. We next investigated the potential of drugs that have not been used in the patient clinical management and we identified the HDAC inhibitor belinostat as a potential effective treatment based on PDTO response.

CONCLUSIONS

PDX and PDTO appear to be the most relevant models, but only PDTO seem to present all the necessary prerequisites for predictive purposes and could constitute relevant tools for therapeutic decision support in the context of these particularly aggressive cancers refractory to conventional treatments.

The search for therapeutic targets in lung cancer: Preclinical and human studies of carcinoembryonic antigen-related cell adhesion molecule 5 expression and its associated molecular landscape

OBJECTIVES

CEACAM5 is a cell-surface glycoprotein expressed on epithelial cells of some solid tumors. Tusamitamab ravtansine (SAR408701), a humanized antibody-drug conjugate targeting CEACAM5, is in clinical development for nonsquamous non-small cell lung cancer (NSQ-NSCLC) with CEACAM5 high expression (HE), defined as membranous CEACAM5 immunohistochemistry staining at ≥ 2+ intensity in ≥ 50% of tumor cells.

MATERIALS AND METHODS

We investigated correlations between CEACAM5 expression by immunohistochemistry, CEACAM5 protein expression by ELISA, and CEACAM5 RNA expression by RNA-seq in NSQ-NSCLC patient-derived xenograft (PDX) models, and tumor responses to tusamitamab ravtansine in these models. We assessed prevalence of CEACAM5 HE, clinicopathologic characteristics and molecular markers in patients with NSQ-NSCLC in clinical cohorts.

RESULTS

In a lung PDX set of 10 NSQ-NSCLC specimens, correlations between CEACAM5 by IHC, ELISA and RNA-seq ranged from 0.72 to 0.88. In a larger lung PDX set, higher H-scores were present in NSQ- (n = 93) vs SQ-NSCLC (n = 128) models, and in 12 of these NSQ-NSCLC models, more tumor responses to tusamitamab ravtansine occurred in CEACAM5 HE (5/8; 62.5%) versus moderate or negative expression (1/4; 25%), including 3 with KRAS mutations among the 6 responders. In clinical NSQ-NSCLC samples, CEACAM5 HE prevalence was (52/214; 24.3%) in primary tumors and (6/17; 35.3%) in metastases. In NSQ-NSCLC primary tumors, CEACAM5 HE prevalence was significantly higher in KRAS-altered versus wild-type (35.0% vs 19.5%; P = 0.028) and in programmed cell death ligand 1 (PD-L1) negative (tumor cells 0%)/low (1-49%) versus high (≥50%) (33.3%, 26.1%, 5.0%; P = 0.031), but not significantly different in EGFR-mutated versus wild-type (20.0% vs 25.7%, P = 0.626).

CONCLUSIONS

In NSQ-NSCLC tumors, CEACAM5 HE prevalence was 24.3% overall and was higher with KRAS altered and with PD-L1 negative/low tumors but similar regardless of EGFR mutation status. These findings support targeting CEACAM5 and the clinical development of tusamitamab ravtansine for patients with NSQ-NSCLC with CEACAM5 HE.

In Vitro and In Vivo Drug-Response Profiling Using Patient-Derived High-Grade Glioma

BACKGROUND

Genomic profiling cannot solely predict the complexity of how tumor cells behave in their in vivo microenvironment and their susceptibility to therapies. The aim of the study was to establish a functional drug prediction model utilizing patient-derived GBM tumor samples for in vitro testing of drug efficacy followed by in vivo validation to overcome the disadvantages of a strict pharmacogenomics approach.

METHODS

High-throughput in vitro pharmacologic testing of patient-derived GBM tumors cultured as 3D organoids offered a cost-effective, clinically and phenotypically relevant model, inclusive of tumor plasticity and stroma. RNAseq analysis supplemented this 128-compound screening to predict more efficacious and patient-specific drug combinations with additional tumor stemness evaluated using flow cytometry. In vivo PDX mouse models rapidly validated (50 days) and determined mutational influence alongside of drug efficacy. We present a representative GBM case of three tumors resected at initial presentation, at first recurrence without any treatment, and at a second recurrence following radiation and chemotherapy, all from the same patient.

RESULTS

Molecular and in vitro screening helped identify effective drug targets against several pathways as well as synergistic drug combinations of cobimetinib and vemurafenib for this patient, supported in part by in vivo tumor growth assessment. Each tumor iteration showed significantly varying stemness and drug resistance.

CONCLUSIONS

Our integrative model utilizing molecular, in vitro, and in vivo approaches provides direct evidence of a patient's tumor response drifting with treatment and time, as demonstrated by dynamic changes in their tumor profile, which may affect how one would address that drift pharmacologically.

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.

Patient-derived models facilitate precision medicine in liver cancer by remodeling cell-matrix interaction

Liver cancer is an aggressive tumor originating in the liver with a dismal prognosis. Current evidence suggests that liver cancer is the fifth most prevalent cancer worldwide and the second most deadly type of malignancy. Tumor heterogeneity accounts for the differences in drug responses among patients, emphasizing the importance of precision medicine. Patient-derived models of cancer are widely used preclinical models to study precision medicine since they preserve tumor heterogeneity ex vivo in the study of many cancers. Patient-derived models preserving cell-cell and cell-matrix interactions better recapitulate in vivo conditions, including patient-derived xenografts (PDXs), induced pluripotent stem cells (iPSCs), precision-cut liver slices (PCLSs), patient-derived organoids (PDOs), and patient-derived tumor spheroids (PDTSs). In this review, we provide a comprehensive overview of the different modalities used to establish preclinical models for precision medicine in liver cancer.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Experimental mouse models for translational human cancer research

The development and growth of tumors remains an important and ongoing threat to human life around the world. While advanced therapeutic strategies such as immune checkpoint therapy and CAR-T have achieved astonishing progress in the treatment of both solid and hematological malignancies, the malignant initiation and progression of cancer remains a controversial issue, and further research is urgently required. The experimental animal model not only has great advantages in simulating the occurrence, development, and malignant transformation mechanisms of tumors, but also can be used to evaluate the therapeutic effects of a diverse array of clinical interventions, gradually becoming an indispensable method for cancer research. In this paper, we have reviewed recent research progress in relation to mouse and rat models, focusing on spontaneous, induced, transgenic, and transplantable tumor models, to help guide the future study of malignant mechanisms and tumor prevention.

Cancer-associated fibroblasts are the main contributors to epithelial-to-mesenchymal signatures in the tumor microenvironment

Epithelial-to-mesenchymal transition (EMT) is associated with tumor initiation, metastasis, and drug resistance. However, the mechanisms underlying these associations are largely unknown. We studied several tumor types to identify the source of EMT gene expression signals and a potential mechanism of resistance to immuno-oncology treatment. Across tumor types, EMT-related gene expression was strongly associated with expression of stroma-related genes. Based on RNA sequencing of multiple patient-derived xenograft models, EMT-related gene expression was enriched in the stroma versus parenchyma. EMT-related markers were predominantly expressed by cancer-associated fibroblasts (CAFs), cells of mesenchymal origin which produce a variety of matrix proteins and growth factors. Scores derived from a 3-gene CAF transcriptional signature (COL1A1, COL1A2, COL3A1) were sufficient to reproduce association between EMT-related markers and disease prognosis. Our results suggest that CAFs are the primary source of EMT signaling and have potential roles as biomarkers and targets for immuno-oncology therapies.

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

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

Patient-derived organoids (PDOs) and PDO-derived xenografts (PDOXs): New opportunities in establishing faithful pre-clinical cancer models

One of the major bottlenecks in advancing basic cancer research and developing novel cancer therapies is the lack of in vitro pre-clinical models that faithfully recapitulate tumor properties in the patients. Monolayer cultures of cancer cell lines usually lose the heterogeneity of the parental tumors, while patient-derived xenograft (PDX) suffers from its time- and resource-intensive nature. The emergence of organoid culture system and its application in cancer research provides a unique opportunity to develop novel in vitro cancer pre-clinical models. Here we review the recent advances in utilizing organoids culture system and other related three-dimensional culture systems in studying cancer biology, performing drug screening, and developing cancer therapies. In particular, we discuss the advantages of applying xenograft initiated from patient-derived organoids (PDOs) as a faithful cancer pre-clinical model in basic cancer research and precision medicine.

Recent advances in the development of transplanted colorectal cancer mouse models

Despite progress in prevention and treatment, colorectal cancer (CRC) remains the third most common malignancy worldwide and the second most common cause of cancer death in 2020. To evaluate various characteristics of human CRC, a variety of mouse models have been established. Transplant mouse models have distinct advantages in studying the clinical behavior and therapeutic progress of CRC. Host, xenograft, and transplantation routes are the basis of transplant mouse models. As the effects of the tumor microenvironment and the systemic environment on cancer cells are gradually revealed, 3 key elements of transplanted CRC mouse models have been revolutionized. This has led to the development of humanized mice, patient-derived xenografts, and orthotopic transplants that reflect the human systemic environment, patient's tumor of origin, and tumor growth microenvironments in immunodeficient mice, respectively. These milestone events have allowed for great progress in tumor biology and the treatment of CRC. This article reviews the evolution of these events and points out their strengths and weaknesses as innovative and useful preclinical tools to study CRC progression and metastasis and to exploit novel treatment schedules by establishing a testing platform. This review article depicts the optimal transplanted CRC mouse models and emphasizes the significance of surgical models in the study of CRC behavior and treatment response.

Cell clusters adopt a collective amoeboid mode of migration in confined nonadhesive environments

Cell migration is essential to living organisms and deregulated in cancer. Single cell's migration ranges from traction-dependent mesenchymal motility to contractility-driven propulsive amoeboid locomotion, but collective cell migration has only been described as a focal adhesion-dependent and traction-dependent process. Here, we show that cancer cell clusters, from patients and cell lines, migrate without focal adhesions when confined into nonadhesive microfabricated channels. Clusters coordinate and behave like giant super cells, mobilizing their actomyosin contractility at the rear to power their migration. This polarized cortex does not sustain persistent retrograde flows, of cells or actin, like in the other modes of migration but rather harnesses fluctuating cell deformations, or jiggling. Theoretical physical modeling shows this is sufficient to create a gradient of friction forces and trigger directed cluster motion. This collective amoeboid mode of migration could foster metastatic spread by enabling cells to cross a wide spectrum of environments.

Targeting RAS Mutant Colorectal Cancer with Dual Inhibition of MEK and CDK4/6

KRAS and NRAS mutations occur in 45% of colorectal cancers, with combined MAPK pathway and CDK4/6 inhibition identified as a potential therapeutic strategy. In the current study, this combinatorial treatment approach was evaluated in a co-clinical trial in patient-derived xenografts (PDX), and safety was established in a clinical trial of binimetinib and palbociclib in patients with metastatic colorectal cancer with RAS mutations. Across 18 PDX models undergoing dual inhibition of MEK and CDK4/6, 60% of tumors regressed, meeting the co-clinical trial primary endpoint. Prolonged duration of response occurred predominantly in TP53 wild-type models. Clinical evaluation of binimetinib and palbociclib in a safety lead-in confirmed safety and provided preliminary evidence of activity. Prolonged treatment in PDX models resulted in feedback activation of receptor tyrosine kinases and acquired resistance, which was reversed with a SHP2 inhibitor. These results highlight the clinical potential of this combination in colorectal cancer, along with the utility of PDX-based co-clinical trial platforms for drug development.

SIGNIFICANCE

This co-clinical trial of combined MEK-CDK4/6 inhibition in RAS mutant colorectal cancer demonstrates therapeutic efficacy in patient-derived xenografts and safety in patients, identifies biomarkers of response, and uncovers targetable mechanisms of resistance.

Critical evaluation of an autologous peripheral blood mononuclear cell-based humanized cancer model

The use of humanized mouse models for oncology is rapidly expanding. Autologous patient-derived systems are particularly attractive as they can model the human cancer's heterogeneity and immune microenvironment. In this study, we developed an autologous humanized mouse cancer model by engrafting NSG mice with patient-derived xenografts and infused matched peripheral blood mononuclear cells (PBMCs). We first defined the time course of xenogeneic graft-versus-host-disease (xGVHD) and determined that only minimal xGVHD was observed for up to 8 weeks. Next, colorectal and pancreatic cancer patient-derived xenograft bearing NSG mice were infused with 5x106 human PBMCS for development of the humanized cancer models (iPDX). Early after infusion of human PBMCs, iPDX mice demonstrated engraftment of human CD4+ and CD8+ T cells in the blood of both colorectal and pancreatic cancer patient-derived models that persisted for up to 8 weeks. At the end of the experiment, iPDX xenografts maintained the features of the primary human tumor including tumor grade and cell type. The iPDX tumors demonstrated infiltration of human CD3+ cells with high PD-1 expression although we observed significant intra and inter- model variability. In summary, the iPDX models reproduced key features of the corresponding human tumor. The observed variability and high PD-1 expression are important considerations that need to be addressed in order to develop a reproducible model system.

Establishment and Identification of Patient-Derived Xenograft Model for Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma is the most common head and neck malignancy with high morbidity and mortality. Currently, platinum-based chemotherapy is the conventional chemotherapy regimen for patients with oral squamous cell carcinoma. However, due to the heterogeneity of tumors and individual differences of patients, chemotherapy regimens lacking individualized evaluation of tumor patients are often less effective. Therefore, personalized tumor chemotherapy is one of the effective methods for the future treatment of malignant tumors. The patient-derived xenograft model is a relatively new tumor xenograft model that relies on immunodeficient mice. This model can better maintain various histological characteristics of primary tumor grafts, such as pathological structural features, molecular diversity, and gene expression profiles. Therefore, the patient-derived xenograft model combined with drug screening technology to explore new tumor chemotherapy is the critical research direction for future tumor treatment. This study successfully established the patient-derived xenograft model of oral squamous cell carcinoma. It was verified by hematoxylin-eosin staining and immunohistochemistry that the constructed patient-derived xenograft model retained the pathological and molecular biological characteristics of primary tumors. Our patient-derived xenograft model can be used further to study the oncological characteristics of oral squamous carcinoma and can also be applied to personalize the treatment of oral squamous carcinoma patients, providing a practical resource for screening chemotherapy drugs.

The cell-line-derived subcutaneous tumor model in preclinical cancer research

Tumor-bearing experimental animals are essential for preclinical cancer drug development. A broad range of tumor models is available, with the simplest and most widely used involving a tumor of mouse or human origin growing beneath the skin of a mouse: the subcutaneous tumor model. Here, we outline the different types of in vivo tumor model, including some of their advantages and disadvantages and how they fit into the drug-development process. We then describe in more detail the subcutaneous tumor model and key steps needed to establish it in the laboratory, namely: choosing the mouse strain and tumor cells; cell culture, preparation and injection of tumor cells; determining tumor volume; mouse welfare; and an appropriate experimental end point. The protocol leads to subcutaneous tumor growth usually within 1-3 weeks of cell injection and is suitable for those with experience in tissue culture and mouse experimentation.

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

Metastasis is the primary cause of death in patients with colorectal cancer (CRC), urging the need for preclinical models that recapitulate the metastatic process at the individual patient level. We used an orthotopic patient-derived xenograft (PDX) obtained through the direct implantation of freshly dissociated CRC cells in the colon of immunocompromised mice to model the metastatic process. Ortho-PDX engraftment was associated to a specific set of molecular features of the parental tumor, such as epithelial-to-mesenchymal transition (EMT), TGF-β pathway activation, increased expression of stemness-associated factors and higher numbers of circulating tumor cells (CTCs) clusters expressing the metastatic marker CD44v6. A parallel analysis of orthotopic/metastatic xenografts and organoids showed that tumor cells underwent mesenchymal-to-epithelial transition at the metastatic site and that metastasis-derived organoids had increased chemotherapy resistance. These observations support the usefulness of ortho-PDX as a preclinical model to study metastasis-related features and provide preliminary evidence that EMT/stemness properties of primary colorectal tumors may be crucial for orthotopic tumor engraftment.

Patient-derived organoids identify an apico-basolateral polarity switch associated with survival in colorectal cancer

The metastatic progression of cancer remains a major issue in patient treatment. Yet, the molecular and cellular mechanisms underlying this process remains unclear. Here, we use primary explants and organoids from patients harboring mucinous colorectal carcinoma (MUC CRC), a poor prognosis histological form of digestive cancers, to study the architecture, invasive behavior and chemoresistance of tumor cell intermediates. We report that these tumors maintain a robust apico-basolateral polarity as they spread in the peritumoral stroma or organotypic collagen-I gels. We identified two distinct topologies: MUC CRCs either display a conventional "apical-in" polarity or, more frequently, harbor an inverted "apical-out" topology. Transcriptomic analyses combined with interference experiments on organoids showed that TGFb and focal adhesion signaling pathways are the main drivers of polarity orientation. Finally, this apical-out topology is associated with increased resistance to chemotherapeutic treatments in organoids and decreased patient survival in the clinic. Thus, patient-derived organoids have the potential to bridge histological, cellular and molecular analyses to decrypt onco-morphogenic programs and stratify cancer patients.

In Vivo Modeling of Human Breast Cancer Using Cell Line and Patient-Derived Xenografts

Historically, human breast cancer has been modeled largely in vitro using long-established cell lines primarily in two-dimensional culture, but also in three-dimensional cultures of varying cellular and molecular complexities. A subset of cell line models has also been used in vivo as cell line-derived xenografts (CDX). While outstanding for conducting detailed molecular analysis of regulatory mechanisms that may function in vivo, results of drug response studies using long-established cell lines have largely failed to translate clinically. In an attempt to address this shortcoming, many laboratories have succeeded in developing clinically annotated patient-derived xenograft (PDX) models of human cancers, including breast, in a variety of host systems. While immunocompromised mice are the predominant host, the immunocompromised rat and pig, zebrafish, as well as the chicken egg chorioallantoic membrane (CAM) have also emerged as potential host platforms to help address perceived shortcomings of immunocompromised mice. With any modeling platform, the two main issues to be resolved are criteria for "credentialing" the models as valid models to represent human cancer, and utility with respect to the ability to generate clinically relevant translational research data. Such data are beginning to emerge, particularly with the activities of PDX consortia such as the NCI PDXNet Program, EuroPDX, and the International Breast Cancer Consortium, as well as a host of pharmaceutical companies and contract research organizations (CRO). This review focuses primarily on these important aspects of PDX-related research, with a focus on breast cancer.

Patient-derived xenograft (PDX) models, applications and challenges in cancer research

The establishing of the first cancer models created a new perspective on the identification and evaluation of new anti-cancer therapies in preclinical studies. Patient-derived xenograft models are created by tumor tissue engraftment. These models accurately represent the biology and heterogeneity of different cancers and recapitulate tumor microenvironment. These features have made it a reliable model along with the development of humanized models. Therefore, they are used in many studies, such as the development of anti-cancer drugs, co-clinical trials, personalized medicine, immunotherapy, and PDX biobanks. This review summarizes patient-derived xenograft models development procedures, drug development applications in various cancers, challenges and limitations.

Magnesium galvanic cells produce hydrogen and modulate the tumor microenvironment to inhibit cancer growth

Hydrogen can be used as an anti-cancer treatment. However, the continuous generation of H₂ molecules within the tumor is challenging. Magnesium (Mg) and its alloys have been extensively used in the clinic as implantable metals. Here we develop, by decorating platinum on the surface of Mg rods, a Mg-based galvanic cell (MgG), which allows the continuous generation of H₂ in an aqueous environment due to galvanic-cell-accelerated water etching of Mg. By implanting MgG rods into a tumor, H₂ molecules can be generated within the tumor, which induces mitochondrial dysfunction and intracellular redox homeostasis destruction. Meanwhile, the Mg(OH)₂ residue can neutralize the acidic tumor microenvironment (TME). Such MgG rods with the micro-galvanic cell structure enable hydrogen therapy to inhibit the growth of tumors, including murine tumor models, patient-derived xenografts (PDX), as well as VX₂ tumors in rabbits. Our research suggests that the galvanic cells for hydrogen therapy based on implantable metals may be a safe and effective cancer treatment.

The production of hydrogen inside cells can stimulate cell death. Here, the authors made magnesium galvanic rods that continuously produce hydrogen and result in tumor inhibition in vitro and in vivo.

Novel Ex Vivo Models of Epithelial Ovarian Cancer: The Future of Biomarker and Therapeutic Research

Epithelial ovarian cancer (EOC) is a heterogenous disease associated with variations in presentation, pathology and prognosis. Advanced EOC is typified by frequent relapse and a historical 5-year survival of less than 30% despite improvements in surgical and systemic treatment. The advent of next generation sequencing has led to notable advances in the field of personalised medicine for many cancer types. Success in achieving cure in advanced EOC has however been limited, although significant prolongation of survival has been demonstrated. Development of novel research platforms is therefore necessary to address the rapidly advancing field of early diagnostics and therapeutics, whilst also acknowledging the significant tumour heterogeneity associated with EOC. Within available tumour models, patient-derived organoids (PDO) and explant tumour slices have demonstrated particular promise as novel ex vivo systems to model different cancer types including ovarian cancer. PDOs are organ specific 3D tumour cultures that can accurately represent the histology and genomics of their native tumour, as well as offer the possibility as models for pharmaceutical drug testing platforms, offering timing advantages and potential use as prospective personalised models to guide clinical decision-making. Such applications could maximise the benefit of drug treatments to patients on an individual level whilst minimising use of less effective, yet toxic, therapies. PDOs are likely to play a greater role in both academic research and drug development in the future and have the potential to revolutionise future patient treatment and clinical trial pathways. Similarly, ex vivo tumour slices or explants have also shown recent renewed promise in their ability to provide a fast, specific, platform for drug testing that accurately represents in vivo tumour response. Tumour explants retain tissue architecture, and thus incorporate the majority of tumour microenvironment making them an attractive method to re-capitulate in vivo conditions, again with significant timing and personalisation of treatment advantages for patients. This review will discuss the current treatment landscape and research models for EOC, their development and new advances towards the discovery of novel biomarkers or combinational therapeutic strategies to increase treatment options for women with ovarian cancer.

Organotypic Epithelial Raft Cultures as a Three-Dimensional In Vitro Model of Merkel Cell Carcinoma

Merkel cell carcinoma (MCC) is a rare type of skin cancer for which an in vitro model is still lacking. MCC tumorigenesis is associated either with the integration of Merkel cell polyomavirus into the host genome, or with the accumulation of somatic mutations upon chronic exposure to UV light. Transgenic animals expressing the viral oncoproteins, which are constitutively expressed in virus-related MCC, do not fully recapitulate MCC. Although cell-line-derived xenografts have been established for the two subtypes of MCC, they still present certain limitations. Here, we generated organotypic epithelial raft cultures (OERCs) of MCC by using primary human keratinocytes and both virus-positive and virus-negative MCC cell lines. The primary human keratinocytes and the tumor cells were grown on top of a dermal equivalent. Histological and immunohistochemical examination of the rafts confirmed the growth of MCC cells. Furthermore, gene expression analysis revealed differences in the expression profiles of the distinct tumor cells and the keratinocytes at the transcriptional level. In summary, considering the limited availability of patient samples, OERCs of MCC may constitute a suitable model for evaluating the efficacy and selectivity of new drug candidates against MCC; moreover, they are a potential tool to study the oncogenic mechanisms of this malignancy.

Orthotopic Xenografts of Colorectal Cancer Stem Cells

Cancer stem cells (CSCs) are responsible for the initiation of primary tumors and for metastasis seeding at distant organs. Therefore, they represent crucial targets for the study and preclinical testing of new antimetastatic approaches. We recently generated a molecularly characterized biobank of colorectal CSCs, isolated from individual patients and cultured in serum-free medium as multicellular spheroids. Here, we describe in detail the generation of a metastatic model of colorectal cancer based on the orthotopic injection of CSCs into the cecum serosa of immunodeficient mice. Such a model represents an excellent experimental system to investigate the cellular and molecular mechanisms involved in colorectal cancer metastasis, to analyze rare premetastatic elements such as circulating and disseminated tumor cells, and for the preclinical testing of new agents with potential antimetastatic activity.

Evaluation of two in vitro assays for tumorigenicity assessment of CRISPR-Cas9 genome-edited cells

Off-target editing is one of the main safety concerns for the use of CRISPR-Cas9 genome editing in gene therapy. These unwanted modifications could lead to malignant transformation, which renders tumorigenicity assessment of gene therapy products indispensable. In this study, we established two in vitro transformation assays, the soft agar colony-forming assay (SACF) and the growth in low attachment assay (GILA) as alternative methods for tumorigenicity evaluation of genome-edited cells. Using a CRISPR-Cas9-based approach to transform immortalized MCF10A cells, we identified PTPN12, a known tumor suppressor, as a valid positive control in GILA and SACF. Next, we measured the limit of detection for both assays and proved that SACF is more sensitive than GILA (0.8% versus 3.1% transformed cells). We further validated SACF and GILA by identifying a set of positive and negative controls and by testing the suitability of another cell line (THLE-2). Moreover, in contrast to SACF and GILA, an in vivo tumorigenicity study failed to detect the known tumorigenic potential of PTPN12 deletion, demonstrating the relevance of GILA and SACF in tumorigenicity testing. In conclusion, SACF and GILA are both attractive and valuable additions to preclinical safety assessment of gene therapy products.

Longitudinal evaluation of five nasopharyngeal carcinoma animal models on the microPET/MR platform

PURPOSE

We longitudinally evaluated the tumour growth and metabolic activity of three nasopharyngeal carcinoma (NPC) cell line models (C666-1, C17 and NPC43) and two xenograft models (Xeno76 and Xeno23) using a micropositron emission tomography and magnetic resonance (microPET/MR). With a better understanding of the interplay between tumour growth and metabolic characteristics of these NPC models, we aim to provide insights for the selection of appropriate NPC cell line/xenograft models to assist novel drug discovery and evaluation.

METHODS

Mice were imaged by ¹⁸F-deoxyglucose ([¹⁸F]FDG) microPET/MR twice a week for consecutive 3-7 weeks. [¹⁸F]FDG uptake was quantified by standardized uptake value (SUV) and presented as SUVmean tumour-to-liver ratio (SUVRmean). Longitudinal tumour growth patterns and metabolic patterns were recorded. SUVRmean and histological characteristics were compared across the five NPC models. Cisplatin was administrated to one selected optimal tumour model, C17, to evaluate our imaging platform.

RESULTS

We found variable tumour growth and metabolic patterns across different NPC tumour types. C17 has an optimal growth rate and higher tumour metabolic activity compared with C666-1. C666-1 has a fast growth rate but is low in SUVRmean at endpoint due to necrosis as confirmed by H&E. NPC43 and Xeno76 have relatively slow growth rates and are low in SUVRmean, due to severe necrosis. Xeno23 has the slowest growth rate, and a relative high SUVRmean. Cisplatin showed the expected therapeutic effect in the C17 model in marked reduction of tumour size and metabolism.

CONCLUSION

Our study establishes an imaging platform that characterizes the growth and metabolic patterns of different NPC models, and the platform is well able to demonstrate drug treatment outcome supporting its use in novel drug discovery and evaluation for NPC.

A novel PDX modeling strategy and its application in metabolomics study for malignant pleural mesothelioma

BACKGROUND

Malignant pleural mesothelioma (MPM) is a rare and aggressive carcinoma located in pleural cavity. Due to lack of effective diagnostic biomarkers and therapeutic targets in MPM, the prognosis is extremely poor. Because of difficulties in sample extraction, and the high rate of misdiagnosis, MPM is rarely studied. Therefore, novel modeling methodology is crucially needed to facilitate MPM research.

METHODS

A novel patient-derived xenograft (PDX) modeling strategy was designed, which included preliminary screening of patients with pleural thickening using computerized tomography (CT) scan, further reviewing history of disease and imaging by a senior sonographer as well as histopathological analysis by a senior pathologist, and PDX model construction using ultrasound-guided pleural biopsy from MPM patients. Gas chromatography-mass spectrometry-based metabolomics was further utilized for investigating circulating metabolic features of the PDX models. Univariate and multivariate analysis, and pathway analysis were performed to explore the differential metabolites, enriched metabolism pathways and potential metabolic targets.

RESULTS

After screening using our strategy, 5 out of 116 patients were confirmed to be MPM, and their specimens were used for modeling. Two PDX models were established successfully. Metabolomics analysis revealed significant metabolic shifts in PDX models, such as dysregulations in amino acid metabolism, TCA cycle and glycolysis, and nucleotide metabolism.

CONCLUSIONS

To sum up, we suggested a novel modeling strategy that may facilitate specimen availability for MM research, and by applying metabolomics in this model, several metabolic features were identified, whereas future studies with large sample size are needed.

Preclinical Solid Tumor Models to Study Novel Therapeutics in Brain Metastases

Metastases are the most common malignancy of the adult central nervous system and are becoming an increasingly troubling problem in oncology largely due to the lack of successful therapeutic options. The limited selection of treatments is a result of the currently poor understanding of the biological mechanisms of metastatic development, which in turn is difficult to achieve because of limited preclinical models that can accurately represent the clinical progression of metastasis. Described in this article are in vitro and in vivo model systems that are used to enhance the understanding of metastasis and to identify new therapies for the treatment of brain metastasis. © 2021 Wiley Periodicals LLC.

Benefits of functional assays in personalized cancer medicine: more than just a proof-of-concept

As complex and heterogeneous diseases, cancers require a more tailored therapeutic management than most pathologies. Recent advances in anticancer drug development, including the immuno-oncology revolution, have been too often plagued by unsatisfying patient response rates and survivals. In reaction to this, cancer care has fully transitioned to the “personalized medicine” concept. Numerous tools are now available tools to better adapt treatments to the profile of each patient. They encompass a large array of diagnostic assays, based on biomarkers relevant to targetable molecular pathways. As a subfamily of such so-called companion diagnostics, chemosensitivity and resistance assays represent an attractive, yet insufficiently understood, approach to individualize treatments. They rely on the assessment of a composite biomarker, the ex vivo functional response of cancer cells to drugs, to predict a patient's outcome. Systemic treatments, such as chemotherapies, as well as targeted treatments, whose efficacy cannot be fully predicted yet by other diagnostic tests, may be assessed through these means. The results can provide helpful information to assist clinicians in their decision-making process. We explore here the most advanced functional assays across oncology indications, with an emphasis on tests already displaying a convincing clinical demonstration. We then recapitulate the main technical obstacles faced by researchers and clinicians to produce more accurate, and thus more predictive, models and the recent advances that have been developed to circumvent them. Finally, we summarize the regulatory and quality frameworks surrounding functional assays to ensure their safe and performant clinical implementation. Functional assays are valuable in vitro diagnostic tools that already stand beyond the “proof-of-concept” stage. Clinical studies show they have a major role to play by themselves but also in conjunction with molecular diagnostics. They now need a final lift to fully integrate the common armament used against cancers, and thus make their way into the clinical routine.

Patient-Derived Explants of Colorectal Cancer: Histopathological and Molecular Analysis of Long-Term Cultures

Simple Summary

Colorectal cancer is the third most common cancer type among men and women. Prescription of medical treatments for cancer often relies on a process of trial and potential error, more recently guided by patient stratification based on biomarkers. Nonetheless, available biomarkers do not accurately predict patient response and there is a need for predictive and translational models to provide proper clinical information on treatment guidance. Herein, we developed an ex vivo model of colorectal cancer, using fresh tumour samples to establish explant cultures, taking advantage of agitation-based culture systems. We performed a thorough characterisation over one month in culture and observed preservation of original tumour genetic features and partial preservation of architecture and non-malignant cells that compose the tumour microenvironment. Our findings highlight the importance of detailed model characterisation and support the applicability of our model in pre- and co-clinical settings.

Abstract

Colorectal cancer (CRC) is one of the most common cancers worldwide. Although short-term cultures of tumour sections and xenotransplants have been used to determine drug efficacy, the results frequently fail to confer clinically useful information. Biomarker discovery has changed the paradigm for advanced CRC, though the presence of a biomarker does not necessarily translate into therapeutic success. To improve clinical outcomes, translational models predictive of drug response are needed. We describe a simple method for the fast establishment of CRC patient-derived explant (CRC-PDE) cultures from different carcinogenesis pathways, employing agitation-based platforms. A total of 26 CRC-PDE were established and a subset was evaluated for viability (n = 23), morphology and genetic key alterations (n = 21). CRC-PDE retained partial tumor glandular architecture and microenvironment features were partially lost over 4 weeks of culture. Key proteins (p53 and Mismatch repair) and oncogenic driver mutations of the original tumours were sustained throughout the culture. Drug challenge (n = 5) revealed differential drug response from distinct CRC-PDE cases. These findings suggest an adequate representation of the original tumour and highlight the importance of detailed model characterisation. The preservation of key aspects of the CRC microenvironment and genetics supports CRC-PDE potential applicability in pre- and co-clinical settings, as long as temporal dynamics are considered.

Engineered in vitro tumor models for cell-based immunotherapy

Tumor immunotherapy is rapidly evolving as one of the major pillars of cancer treatment. Cell-based immunotherapies, which utilize patient's own immune cells to eliminate cancer cells, have shown great promise in treating a range of malignancies, especially those of hematopoietic origins. However, their performance on a broader spectrum of solid tumor types still fall short of expectations in the clinical stage despite promising preclinical assessments. In this review, we briefly introduce cell-based immunotherapies and the inhibitory mechanisms in tumor microenvironments that may have contributed to this discrepancy. Specifically, a major obstacle to the clinical translation of cell-based immunotherapies is in the lack of preclinical models that can accurately assess the efficacies and mechanisms of these therapies in a (patho-)physiologically relevant manner. Lately, tissue engineering and organ-on-a-chip tools and microphysiological models have allowed for more faithful recapitulation of the tumor microenvironments, by incorporating crucial tumor tissue features such as cellular phenotypes, tissue architecture, extracellular matrix, physical parameters, and their dynamic interactions. This review summarizes the existing engineered tumor models with a focus on tumor immunology and cell-based immunotherapy. We also discuss some key considerations for the future development of engineered tumor models for immunotherapeutics. STATEMENT OF SIGNIFICANCE: Cell-based immunotherapies have shown great promise in treating hematological malignancies and some epithelial tumors. However, their performance on a broader spectrum of solid tumor types still fall short of expectations. Major obstacles include the inhibitory mechanisms in tumor microenvironments (TME) and the lack of preclinical models that can accurately assess the efficacies and mechanisms of cellular therapies in a (patho-)physiologically relevant manner. In this review, we introduce recent progress in tissue engineering and microphysiological models for more faithful recapitulation of TME for cell-based immunotherapies, and some key considerations for the future development of engineered tumor models. This overview will provide a better understanding on the role of engineered models in accelerating immunotherapeutic discoveries and clinical translations.

Targeting OLFML3 in Colorectal Cancer Suppresses Tumor Growth and Angiogenesis, and Increases the Efficacy of Anti-PD1 Based Immunotherapy

The role of the proangiogenic factor olfactomedin-like 3 (OLFML3) in cancer is unclear. To characterize OLFML3 expression in human cancer and its role during tumor development, we undertook tissue expression studies, gene expression analyses of patient tumor samples, in vivo studies in mouse cancer models, and in vitro coculture experiments. OLFML3 was expressed at high levels, mainly in blood vessels, in multiple human cancers. We focused on colorectal cancer (CRC), as elevated expression of OLFML3 mRNA correlated with shorter relapse-free survival, higher tumor grade, and angiogenic microsatellite stable consensus molecular subtype 4 (CMS4). Treatment of multiple in vivo tumor models with OLFML3-blocking antibodies and deletion of the Olfml3 gene from mice decreased lymphangiogenesis, pericyte coverage, and tumor growth. Antibody-mediated blockade of OLFML3 and deletion of host Olfml3 decreased the recruitment of tumor-promoting tumor-associated macrophages and increased infiltration of the tumor microenvironment by NKT cells. Importantly, targeting OLFML3 increased the antitumor efficacy of anti-PD-1 checkpoint inhibitor therapy. Taken together, the results demonstrate that OLFML3 is a promising candidate therapeutic target for CRC.

Functional genomics approaches to improve pre-clinical drug screening and biomarker discovery

Advances in sequencing technology have enabled the genomic and transcriptomic characterization of human malignancies with unprecedented detail. However, this wealth of information has been slow to translate into clinically meaningful outcomes. Different models to study human cancers have been established and extensively characterized. Using these models, functional genomic screens and pre-clinical drug screening platforms have identified genetic dependencies that can be exploited with drug therapy. These genetic dependencies can also be used as biomarkers to predict response to treatment. For many cancers, the identification of such biomarkers remains elusive. In this review, we discuss the development and characterization of models used to study human cancers, RNA interference and CRISPR screens to identify genetic dependencies, large-scale pharmacogenomics studies and drug screening approaches to improve pre-clinical drug screening and biomarker discovery.

Engineering strategies to capture the biological and biophysical tumor microenvironment in vitro

Despite decades of research and advancements in diagnostic and treatment modalities, cancer remains a major global healthcare challenge. This is due in part to a lack of model systems that allow investigating the mechanisms underlying tumor development, progression, and therapy resistance under relevant conditions in vitro. Tumor cell interactions with their surroundings influence all stages of tumorigenesis and are shaped by both biological and biophysical cues including cell-cell and cell-extracellular matrix (ECM) interactions, tissue architecture and mechanics, and mass transport. Engineered tumor models provide promising platforms to elucidate the individual and combined contributions of these cues to tumor malignancy under controlled and physiologically relevant conditions. This review will summarize current knowledge of the biological and biophysical microenvironmental cues that influence tumor development and progression, present examples of in vitro model systems that are presently used to study these interactions and highlight advancements in tumor engineering approaches to further improve these technologies.

Drug discovery oncology in a mouse: concepts, models and limitations

The utilization of suitable mouse models is a critical step in the drug discovery oncology workflow as their generation and use are important for target identification and validation as well as toxicity and efficacy assessments. Current murine models have been instrumental in furthering insights into the mode of action of drugs before transitioning into the clinic. Recent advancements in genome editing with the development of the CRISPR/Cas9 system and the possibility of applying such technology directly in vivo have expanded the toolkit of preclinical models available. In this review, a brief presentation of the current models used in drug discovery will be provided with a particular emphasis on the novel CRISPR/Cas9 models.

Exploring the Biological Activity and Mechanism of Xenoestrogens and Phytoestrogens in Cancers: Emerging Methods and Concepts

Xenoestrogens and phytoestrogens are referred to as "foreign estrogens" that are produced outside of the human body and have been shown to exert estrogen-like activity. Xenoestrogens are synthetic industrial chemicals, whereas phytoestrogens are chemicals present in the plant. Considering that these environmental estrogen mimics potentially promote hormone-related cancers, an understanding of how they interact with estrogenic pathways in human cells is crucial to resolve their possible impacts in cancer. Here, we conducted an extensive literature evaluation on the origins of these chemicals, emerging research techniques, updated molecular mechanisms, and ongoing clinical studies of estrogen mimics in human cancers. In this review, we describe new applications of patient-derived xenograft (PDX) models and single-cell RNA sequencing (scRNA-seq) techniques in shaping the current knowledge. At the molecular and cellular levels, we provide comprehensive and up-to-date insights into the mechanism of xenoestrogens and phytoestrogens in modulating the hallmarks of cancer. At the systemic level, we bring the emerging concept of window of susceptibility (WOS) into focus. WOS is the critical timing during the female lifespan that includes the prenatal, pubertal, pregnancy, and menopausal transition periods, during which the mammary glands are more sensitive to environmental exposures. Lastly, we reviewed 18 clinical trials on the application of phytoestrogens in the prevention or treatment of different cancers, conducted from 2002 to the present, and provide evidence-based perspectives on the clinical applications of phytoestrogens in cancers. Further research with carefully thought-through concepts and advanced methods on environmental estrogens will help to improve understanding for the identification of environmental influences, as well as provide novel mechanisms to guide the development of prevention and therapeutic approaches for human cancers.

Cancer stem cell-targeted chimeric antigen receptor (CAR)-T cell therapy: Challenges and prospects

Cancer stem cells (CSCs) with their self-renewal ability are accepted as cells which initiate tumors. CSCs are regarded as interesting targets for novel anticancer therapeutic agents because of their association with tumor recurrence and resistance to conventional therapies, including radiotherapy and chemotherapy. Chimeric antigen receptor (CAR)-T cells are engineered T cells which express an artificial receptor specific for tumor associated antigens (TAAs) by which they accurately target and kill cancer cells. In recent years, CAR-T cell therapy has shown more efficiency in cancer treatment, particularly regarding blood cancers. The expression of specific markers such as TAAs on CSCs in varied cancer types makes them as potent tools for CAR-T cell therapy. Here we review the CSC markers that have been previously targeted with CAR-T cells, as well as the CSC markers that may be used as possible targets for CAR-T cell therapy in the future. Furthermore, we will detail the most important obstacles against CAR-T cell therapy and suggest solutions.

Molecular mechanisms underpinning sarcomas and implications for current and future therapy

Sarcomas are complex mesenchymal neoplasms with a poor prognosis. Their clinical management is highly challenging due to their heterogeneity and insensitivity to current treatments. Although there have been advances in understanding specific genomic alterations and genetic mutations driving sarcomagenesis, the underlying molecular mechanisms, which are likely to be unique for each sarcoma subtype, are not fully understood. This is in part due to a lack of consensus on the cells of origin, but there is now mounting evidence that they originate from mesenchymal stromal/stem cells (MSCs). To identify novel treatment strategies for sarcomas, research in recent years has adopted a mechanism-based search for molecular markers for targeted therapy which has included recapitulating sarcomagenesis using in vitro and in vivo MSC models. This review provides a comprehensive up to date overview of the molecular mechanisms that underpin sarcomagenesis, the contribution of MSCs to modelling sarcomagenesis in vivo, as well as novel topics such as the role of epithelial-to-mesenchymal-transition (EMT)/mesenchymal-to-epithelial-transition (MET) plasticity, exosomes, and microRNAs in sarcomagenesis. It also reviews current therapeutic options including ongoing pre-clinical and clinical studies for targeted sarcoma therapy and discusses new therapeutic avenues such as targeting recently identified molecular pathways and key transcription factors.