Interrogating open issues in cancer medicine with patient-derived xenografts

Bibliometric analysis of global research on human organoids

The emergence and rapid development of human organoids have provided the possibility to replace animal models in treating human diseases. Intelligence studies help focus on research hotspots and address key mechanistic issues. Currently, few comprehensive studies describe the characteristics of human organoid research. In this study, we extracted 8,591 original articles on organoids from the Web of Science core collection database over the past two decades and conducted intelligence analysis using CiteSpace. The number of publications in this field has experienced rapid growth in the last ten years (almost 70-fold increase since 2009). The United States, China, Germany, Netherlands, and UK have strong collaborations in publishing articles. Clevers Hans, Van Der Laan, Jason R Spence, and Sato Toshiro have made significant contributions to advancing progress in this field. Clustering and burst analysis categorized research hotspots into tissue model and functional construction, intercellular signaling, immune mechanisms, and tumor metastasis. Organoid research in highly cited articles covers four major areas: basic research (38%), involving stem cell developmental processes and cell-cell interactions; biobanking (10%), with a focus on organoid cultivation; precision medicine (16%), emphasizing cell therapy and drug development; and disease modeling (36%), including pathogen analysis and screening for disease-related genetic variations. The main obstacles currently faced in organoid research include cost and technology, vascularization of cells, immune system establishment, international standard protocols, and limited availability of high-quality clinical trial data. Future research will focus on cost-saving measures, technology sharing, development of international standards, and conducting high-level clinical trials.

Overcome Drug Resistance in Cholangiocarcinoma: New Insight Into Mechanisms and Refining the Preclinical Experiment Models

Cholangiocarcinoma (CCA) is an aggressive tumor characterized by a poor prognosis. Therapeutic options are limited in patients with advanced stage of CCA, as a result of the intrinsic or acquired resistance to currently available chemotherapeutic agents, and the lack of new drugs entering into clinical application. The challenge in translating basic research to the clinical setting, caused by preclinical models not being able to recapitulate the tumor characteristics of the patient, seems to be an important reason for the lack of effective and specific therapies for CCA. So, there seems to be two ways to improve patient outcomes. The first one is developing the combination therapies based on a better understanding of the mechanisms contributing to the resistance to currently available chemotherapeutic agents. The second one is developing novel preclinical experimental models that better recapitulate the genetic and histopathological features of the primary tumor, facilitating the screening of new drugs for CCA patients. In this review, we discussed the evidence implicating the mechanisms underlying treatment resistance to currently investigated drugs, and the development of preclinical experiment models for CCA.

Zebrafish patient-derived xenograft models predict lymph node involvement and treatment outcome in non-small cell lung cancer

Background

Accurate predictions of tumor dissemination risks and medical treatment outcomes are critical to personalize therapy. Patient-derived xenograft (PDX) models in mice have demonstrated high accuracy in predicting therapeutic outcomes, but methods for predicting tumor invasiveness and early stages of vascular/lymphatic dissemination are still lacking. Here we show that a zebrafish tumor xenograft (ZTX) platform based on implantation of PDX tissue fragments recapitulate both treatment outcome and tumor invasiveness/dissemination in patients, within an assay time of only 3 days.

Methods

Using a panel of 39 non-small cell lung cancer PDX models, we developed a combined mouse-zebrafish PDX platform based on direct implantation of cryopreserved PDX tissue fragments into zebrafish embryos, without the need for pre-culturing or expansion. Clinical proof-of-principle was established by direct implantation of tumor samples from four patients.

Results

The resulting ZTX models responded to Erlotinib and Paclitaxel, with similar potency as in mouse-PDX models and the patients themselves, and resistant tumors similarly failed to respond to these drugs in the ZTX system. Drug response was coupled to elevated expression of EGFR, Mdm2, Ptch1 and Tsc1 (Erlotinib), or Nras and Ptch1 (Paclitaxel) and reduced expression of Egfr, Erbb2 and Foxa (Paclitaxel). Importantly, ZTX models retained the invasive phenotypes of the tumors and predicted lymph node involvement of the patients with 91% sensitivity and 62% specificity, which was superior to clinically used tests. The biopsies from all four patient tested implanted successfully, and treatment outcome and dissemination were quantified for all patients in only 3 days.

Conclusions

We conclude that the ZTX platform provide a fast, accurate, and clinically relevant system for evaluation of treatment outcome and invasion/dissemination of PDX models, providing an attractive platform for combined mouse-zebrafish PDX trials and personalized medicine.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02280-x.

Functional precision oncology: Testing tumors with drugs to identify vulnerabilities and novel combinations

Functional precision medicine is a strategy whereby live tumor cells from affected individuals are directly perturbed with drugs to provide immediately translatable, personalized information to guide therapy. The heterogeneity of human cancer has led to the realization that personalized approaches are needed to improve treatment outcomes. Precision oncology has traditionally used static features of the tumor to dictate which therapies should be used. Static features can include expression of key targets or genomic analysis of mutations to identify therapeutically targetable "drivers." Although a surprisingly small proportion of individuals derive clinical benefit from the static approach, functional precision medicine can provide additional information regarding tumor vulnerabilities. We discuss emerging technologies for functional precision medicine as well as limitations and challenges in using these assays in the clinical trials that will be necessary to determine whether functional precision medicine can improve outcomes and eventually become a standard tool in clinical oncology.

Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer

Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.

Molecular phenotypes reveal heterogeneous engraftments of patient-derived hepatocellular carcinoma xenografts

Objective

Patient-derived xenograft (PDX) models provide a promising preclinical platform for hepatocellular carcinoma (HCC). However, the molecular features associated with successful engraftment of PDX models have not been revealed.

Methods

HCC tumor samples from 76 patients were implanted in immunodeficient mice. The molecular expression was evaluated by immunohistochemistry. Patient and tumor characteristics as well as tumor molecular expressions were compared for PDX engraftment using the Chi-square test. The independent prediction parameters were identified by logistic regression analyses.

Results

The engraftment rate for PDX models from patients with HCC was 39.47% (30/76). Tumors from younger patients and patients with elevated preoperative alpha-fetoprotein level had higher engraftment rates. Tumors with poor differentiation and vascular invasion were related to engraftment success. The positive expression of CK19, CD133, glypican-3 (GPC3), and Ki67 in tumor samples was associated with engraftment success. Logistic regression analyses indicated that GPC3 and Ki67 were two of the strongest predictors of PDX engraftment. Tumors with GPC3/Ki67 phenotypes showed heterogeneous engraftment rates, with 71.9% in GPC3⁺/Ki67⁺ tumors, 30.8% in GPC3⁻/Ki67⁺ tumors, 15.0% in GPC3⁺/Ki67⁻ tumors, and 0 in GPC3⁻/Ki67⁻ tumors.

Conclusions

Successful engraftment of HCC PDXs was significantly related to molecular features. Tumors with the GPC3⁺/Ki67⁺ phenotype were the most likely to successfully establish HCC PDXs.

Phase II trial of ribociclib and letrozole in patients with relapsed oestrogen receptor-positive ovarian or endometrial cancers

Objective

We describe a phase II clinical trial of the combination of ribociclib and letrozole for treatment of relapsed oestrogen receptor (ER)-positive ovarian cancer (OC) and endometrial cancer (EC). The primary endpoint was the proportion of patients alive, progression-free survival (PFS), and still on treatment at 12 weeks (PFS12), with 45% or greater considered positive.

Methods

Patients with measurable, relapsed ER-positive OC or EC (platinum-sensitive or resistant) were eligible and treated with 400 mg of oral ribociclib and 2.5 mg of oral letrozole daily. Patient-derived xenografts (PDXs) were created from imaging-guided tumour biopsies.

Results

Forty patients (20 OC and 20 EC) were enrolled. A PFS12 of 55% was observed in the EC cohort and 50% in the OC cohort. A PFS greater or equal to 24 weeks (PFS24) was seen in 20% (4/20) of the OC cohort and 35% (7/20) of the EC cohort. The greatest benefit was seen in low-grade serous OC (LGSOC) (3/3, 100% PFS24) and grades 1 and 2 EC (5/11, 45% PFS24). All three LGSOC patients obtained at least a partial response lasting for over 2 years, with two of the three patients still on treatment. PDX tumour engraftment was feasible in 45% of patients. Positive survival effects of the combination of ribociclib and letrozole were observed in two of three EC PDX models.

Conclusion

Ribociclib and letrozole have promising clinical activity in relapsed ER-positive OC and EC, particularly in LGSOC and relapsed ER-positive grade 1 and 2 EC. Generation of PDX models is feasible with positive survival effects observed in EC models.

Trial registration number

ClinicalTrials.gov registry (NCT02657928).

Personalized therapeutic strategies in HER2-driven gastric cancer

BACKGROUND

Trastuzumab is the only approved targeted therapy in patients with HER2-amplified metastatic gastric cancer (GC). Regrettably, in clinical practice, only a fraction of them achieves long-term benefit from trastuzumab-based upfront strategy. To advance precision oncology, we investigated the therapeutic efficacy of different HER2-targeted strategies, in HER2 "hyper"-amplified (≥ 8 copies) tumors.

METHODS

We undertook a prospective evaluation of HER2 targeting with monoclonal antibodies, tyrosine kinase inhibitors and antibody-drug conjugates, in a selected subgroup of HER2 "hyper"-amplified gastric patient-derived xenografts (PDXs), through the design of ad hoc preclinical trials.

RESULTS

Despite the high level of HER2 amplification, trastuzumab elicited a partial response only in 2 out of 8 PDX models. The dual-HER2 blockade with trastuzumab plus either pertuzumab or lapatinib led to complete and durable responses in 5 (62.5%) out of 8 models, including one tumor bearing a concomitant HER2 mutation. In a resistant PDX harboring KRAS amplification, the novel antibody-drug conjugate trastuzumab deruxtecan (but not trastuzumab emtansine) overcame KRAS-mediated resistance. We also identified a HGF-mediated non-cell-autonomous mechanism of secondary resistance to anti-HER2 drugs, responsive to MET co-targeting.

CONCLUSION

These preclinical randomized trials clearly indicate that in HER2-driven gastric tumors, a boosted HER2 therapeutic blockade is required for optimal efficacy, leading to complete and durable responses in most of the cases. Our results suggest that a selected subpopulation of HER2-"hyper"-amplified GC patients could strongly benefit from this strategy. Despite the negative results of clinical trials, the dual blockade should be reconsidered for patients with clearly HER2-addicted cancers.

Progress in the application of organoids to breast cancer research

Breast cancer is the most common cancer diagnosed in women. Breast cancer research is currently based mainly on animal models and traditional cell culture. However, the inherent species gap between humans and animals, as well as differences in organization between organs and cells, limits research advances. The breast cancer organoid can reproduce many of the key features of human breast cancer, thereby providing a new platform for investigating the mechanisms underlying the development, progression, metastasis and drug resistance of breast cancer. The application of organoid technology can also promote drug discovery and the design of individualized treatment strategies. Here, we discuss the latest advances in the use of organoid technology for breast cancer research.

Patient-derived xenografts (PDXs) as model systems for human cancer

Patient-derived xenografts (PDXs) are obtained by transplanting fragments of a patient's tumour into immunodeficient mice. Growth and propagation of PDXs allows correlating therapeutic response in vivo with extensive, multi-dimensional molecular annotation, leading to identification of predictive biomarkers. PDXs are increasingly recognised as clinically relevant models of cancer for several reasons, of which the main is the possibility of studying the behaviour of cancer cells in a natural microenvironment, where they interact with stromal components accrued from the mouse host. PDXs maintain close similarities with the tumour of origin, in terms of tissue architecture, molecular features and response to treatments. Indeed, preclinical trials in PDXs have been shown to match and also anticipate data obtained in patients. Exploration of more complex processes like metastatic evolution and antitumour immune responses is actively pursued with PDXs, as new generations of host models emerge on the horizon.

Implementing Patient-Derived Xenografts to Assess the Effectiveness of Cyclin-Dependent Kinase Inhibitors in Glioblastoma

Glioblastoma (GBM) is the most common primary brain tumor with no available cure. As previously described, seliciclib, a first-generation cyclin-dependent kinase (CDK) inhibitor, down-regulates the anti-apoptotic protein, Mcl-1, in GBM, thereby sensitizing GBM cells to the apoptosis-inducing effects of the death receptor ligand, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). Here, we have assessed the efficacy of seliciclib when delivered in combination with the antibody against human death receptor 5, drozitumab, in clinically relevant patient-derived xenograft (PDX) models of GBM. A reduction in viability and significant levels of apoptosis were observed in vitro in human GBM neurospheres following treatment with seliciclib plus drozitumab. While the co-treatment strategy induced a similar effect in PDX models, the dosing regimen required to observe seliciclib-targeted responses in the brain, resulted in lethal toxicity in 45% of animals. Additional studies showed that the second-generation CDK inhibitor, CYC065, with improved potency in comparison to seliciclib, induced a significant decrease in the size of human GBM neurospheres in vitro and was well tolerated in vivo, upon administration at clinically relevant doses. This study highlights the continued need for robust pre-clinical assessment of promising treatment approaches using clinically relevant models.

Keeping the Engine Running: The Relevance and Predictive Value of Preclinical Models for CAR-T Cell Development

The cellular immunotherapy field has achieved important milestones in the last 30 years towards the treatment of a variety of cancers due to improvements in ex-vivo T cell manufacturing processes, the invention of synthetic T cell receptors, and advances in cellular engineering. Here, we discuss major preclinical models that have been useful for the validation of chimeric antigen receptor (CAR)-T cell therapies and also promising new models that will fuel future investigations towards success. However, multiple unanswered questions in the CAR-T cell field remain to be addressed that will require innovative preclinical models. Key challenges facing the field include premature immune rejection of universal CAR-T cells and the immune suppressive tumor microenvironment. Immune competent models that accurately recapitulate tumor heterogeneity, the hostile tumor microenvironment, and barriers to CAR-T cell homing, toxicity, and persistence are needed for further advancement of the field.

Implementation of the Chick Chorioallantoic Membrane (CAM) Model in Radiation Biology and Experimental Radiation Oncology Research

Radiotherapy (RT) is part of standard cancer treatment. Innovations in treatment planning and increased precision in dose delivery have significantly improved the therapeutic gain of radiotherapy but are reaching their limits due to biologic constraints. Thus, a better understanding of the complex local and systemic responses to RT and of the biological mechanisms causing treatment success or failure is required if we aim to define novel targets for biological therapy optimization. Moreover, optimal treatment schedules and prognostic biomarkers have to be defined for assigning patients to the best treatment option. The complexity of the tumor environment and of the radiation response requires extensive in vivo experiments for the validation of such treatments. So far in vivo investigations have mostly been performed in time- and cost-intensive murine models. Here we propose the implementation of the chick chorioallantoic membrane (CAM) model as a fast, cost-efficient model for semi high-throughput preclinical in vivo screening of the modulation of the radiation effects by molecularly targeted drugs. This review provides a comprehensive overview on the application spectrum, advantages and limitations of the CAM assay and summarizes current knowledge of its applicability for cancer research with special focus on research in radiation biology and experimental radiation oncology.

Cancer metabolism gets physical

Patient-derived culture models enable assessment of drug sensitivity and can connect personalized genomics with therapeutic options. However, their clinical translation is constrained by limited fidelity. We outline how the physical microenvironment regulates cell metabolism and describe how engineered culture systems could enhance the predictive power for precision medicine.

A Three-dimensional Ex Vivo Viability Assay Reveals a Strong Correlation Between Response to Targeted Inhibitors and Mutation Status in Melanoma Lymph Node Metastases

Although clinical management of melanoma has changed considerably in recent years, intrinsic treatment resistance remains a severe problem and strategies to design personal treatment regimens are highly warranted. We have applied a three-dimensional (3D) ex vivo drug efficacy assay, exposing disaggregated cells from 38 freshly harvested melanoma lymph node metastases and 21 patient derived xenografts (PDXs) to clinical relevant drugs for 7 days, and examined its potential to evaluate therapy response. A strong association between Vemurafenib response and BRAF mutation status was achieved (P < .0001), while enhanced viability was seen in some NRAS mutated tumors. BRAF and NRAS mutated tumors responded comparably to the MEK inhibitor Cobimetinib. Based on the ex vivo results, two tumors diagnosed as BRAF wild-type by routine pathology examinations had to be re-evaluated; one was subsequently found to have a complex V600E mutation, the other a double BRAF mutation (V600E/K601 N). No BRAF inhibitor resistance mechanisms were identified, but PIK3CA and NF1 mutations were identified in two highly responsive tumors. Concordance between ex vivo drug responses using tissue from PDXs and corresponding patient tumors demonstrate that PDX models represent an indefinite source of tumor material that may allow ex vivo evaluation of numerous drugs and combinations, as well as studies of underlying molecular mechanisms. In conclusion, we have established a rapid and low cost ex vivo drug efficacy assay applicable on tumor tissue from patient biopsies. The 3D/spheroid format, limiting the influence from normal adjacent cells and allowing assessment of drug sensitivity to numerous drugs in one week, confirms its potential as a supplement to guide clinical decision, in particular in identifying non-responding patients.

Organoid technology and applications in cancer research

During the past decade, the three-dimensional organoid technology has sprung up and become more and more popular among researchers. Organoids are the miniatures of in vivo tissues and organs, and faithfully recapitulate the architectures and distinctive functions of a specific organ.

These amazing three-dimensional constructs represent a promising, near-physiological model for human cancers, and tremendously support diverse potential applications in cancer research. Up to now, highly efficient establishment of organoids can be achieved from both normal and malignant tissues of patients. Using this bioengineered platform, the links of infection-cancer progression and mutation-carcinogenesis are feasible to be modeled. Another potential application is that organoid technology facilitates drug testing and guides personalized therapy. Although organoids still fail to model immune system accurately, co-cultures of organoids and lymphocytes have been reported in several studies, bringing hope for further application of this technology in immunotherapy. In addition, the potential value in regeneration medicine might be another paramount branch of organoid technology, which might refine current transplantation therapy through the replacement of irreversibly progressively diseased organs with isogenic healthy organoids.

In conclusion, organoids represent an excellent preclinical model for human tumors, promoting the translation from basic cancer research to clinical practice. In this review, we outline organoid technology and summarize its applications in cancer research.

Anti-angiogenic drug scheduling optimisation with application to colorectal cancer

Bevacizumab (bvz) is a first choice anti-angiogenic drug in oncology and is primarily administered in combination with chemotherapy. It has been hypothesized that anti-angiogenic drugs enhance efficacy of cytotoxic drugs by "normalizing" abnormal tumor vessels and improving drug penetration. Nevertheless, the clinical relevance of this phenomenon is still unclear with several studies over recent years suggesting an opposing relationship. Herein, we sought to develop a new computational tool to interrogate anti-angiogenic drug scheduling with particular application in the setting of colorectal cancer (CRC). Specifically, we have employed a mathematical model of vascular tumour growth which interrogates the impact of anti-angiogenic treatment and chemotherapeutic treatment on tumour volume. Model predictions were validated using CRC xenografts which underwent treatment with a clinically relevant combinatorial anti-angiogenic regimen. Bayesian model selection revealed the most appropriate term for capturing the effect of treatments on the tumour size, and provided insights into a switch-like dependence of FOLFOX delivery on the tumour vasculature. Our experimental data and mathematical model suggest that delivering chemotherapy prior to bvz may be optimal in the colorectal cancer setting.