The fidelity of cancer cells in PDX models: Characteristics, mechanism and clinical significance

Fluorescence-Guided Spatial Drug Screening in 3D Colorectal Cancer Spheroids

The limited recapitulation of critical cancer features in 2D cultures causes poor translatability of preclinical results from in vitro assays to in vivo tumor models. This contributes to slow drug development with a low success rate. 3D cultures better recapitulate the tumor microenvironment, enabling more accurate predictions when screening drug candidates and improving the development of chemotherapeutics. Platinum (Pt) (IV) compounds are promising prodrugs designed to reduce the severe systemic toxicity of widely used Food and Drug Administration (FDA)-approved Pt(II) drugs such as cisplatin. Here, this work presents spatiotemporal evaluations in 3D colorectal cancer (CRC) spheroids of mitochondria-targeting Pt(IV) complexes. CRC spheroids provide a greater pathophysiological recapitulation of in vivo tumors than 2D cultures by a marked upregulation of the ABCG2 chemoresistance marker expression. Furthermore, new 3D-staining protocols are introduced to evaluate the real-time decrease in mitochondria membrane potential (ΔΨ) in CRC spheroids, and a Pt-sensing dye to quantify the Pt mitochondrial accumulation. Finally, this work demonstrates a correlation between in vitro results and the efficacy of the compounds in vivo. Overall, the CRC spheroids represent a fast and cost-effective model to assess the behavior of Pt compounds in vitro and predict their translational potential in CRC treatment.

Nextflow pipeline for Visium and H&E data from patient-derived xenograft samples

We designed a Nextflow DSL2-based pipeline, Spatial Transcriptomics Quantification (STQ), for simultaneous processing of 10x Genomics Visium spatial transcriptomics data and a matched hematoxylin and eosin (H&E)-stained whole-slide image (WSI), optimized for patient-derived xenograft (PDX) cancer specimens. Our pipeline enables the classification of sequenced transcripts for deconvolving the mouse and human species and mapping the transcripts to reference transcriptomes. We align the H&E WSI with the spatial layout of the Visium slide and generate imaging and quantitative morphology features for each Visium spot. The pipeline design enables multiple analysis workflows, including single or dual reference genome input and stand-alone image analysis. We show the utility of our pipeline on a dataset from Visium profiling of four melanoma PDX samples. The clustering of Visium spots and clustering of H&E imaging features reveal similar patterns arising from the two data modalities.

MCM5 is a Novel Therapeutic Target for Glioblastoma

Objective

MCM5 is a DNA licensing factor involved in cell proliferation and has been previously established as an excellent biomarker in a number of malignancies. Nevertheless, the role of MCM5 in GBM has not been fully clarified. The present study aimed to investigate the potential roles of MCM5 in the treatment of GBM and to elucidate its underlying mechanism, which is beneficial for developing new therapeutic strategies and predicting prognosis.

Methods

Firstly, we obtained transcriptomic and proteomic data from the TCGA and CPTAC databases on glioma patients. Employing the DeSeq2 R package, we then identified genes with joint differential expression in GBM tissues subjected to chemotherapy. To develop a prognostic risk score model, we performed univariate and multivariate Cox regression analyses. In vitro knockdown and overexpression of MCM5 were used to further investigate the biological functions of GBM cells. Additionally, we also delved into the upstream regulation of MCM5, revealing associations with several transcription factors. Finally, we investigated differences in immune cell infiltration and drug sensitivity across diverse risk groups identified in the prognostic risk model.

Results

In this study, the chemotherapy-treated GBM samples exhibited consistent alterations in 46 upregulated and 94 downregulated genes at both the mRNA and protein levels. Notably, MCM5 emerged as a gene with prognostic significance as well as potential therapeutic relevance. In vitro experiments subsequently validated the role of increased MCM5 expression in promoting GBM cell proliferation and resistance to TMZ. Correlations with transcription factors such as CREB1, CTCF, NFYB, NRF1, PBX1, TEAD1, and USF1 were discovered during upstream regulatory analysis, enriching our understanding of MCM5 regulatory mechanisms. The study additionally delves into immune cell infiltration and drug sensitivity, providing valuable insights for personalized treatment approaches.

Conclusion

This study identifies MCM5 as a key player in GBM, demonstrating its prognostic significance and potential therapeutic relevance by elucidating its role in promoting cell proliferation and resistance to chemotherapy.

Creation and Validation of Patient-Derived Cancer Model Using Peritoneal and Pleural Effusion in Patients with Advanced Ovarian Cancer: An Early Experience

Background: The application of personalized cancer treatment based on genetic information and surgical samples has begun in the field of cancer medicine. However, a biopsy may be painful for patients with advanced diseases that do not qualify for surgical resection. Patient-derived xenografts (PDXs) are cancer models in which patient samples are transplanted into immunodeficient mice. PDXs are expected to be useful for personalized medicine. The aim of this study was to establish a PDX from body fluid (PDX-BF), such as peritoneal and pleural effusion samples, to provide personalized medicine without surgery. Methods: PDXs-BF were created from patients with ovarian cancer who had positive cytology findings based on peritoneal and pleural effusion samples. PDXs were also prepared from each primary tumor. The pathological findings based on immunohistochemistry were compared between the primary tumor, PDX, and PDX-BF. Further, genomic profiles and gene expression were evaluated using DNA and RNA sequencing to compare primary tumors, PDXs, and PDX-BF. Results: Among the 15 patients, PDX-BF was established for 8 patients (5 high-grade serous carcinoma, 1 carcinosarcoma, 1 low-grade serous carcinoma, and 1 clear cell carcinoma); the success rate was 53%. Histologically, PDXs-BF have features similar to those of primary tumors and PDXs. In particular, PDXs-BF had similar gene mutations and expression patterns to primary tumors and PDXs. Conclusions: PDX-BF reproduced primary tumors in terms of pathological features and genomic profiles, including gene mutation and expression. Thus, PDX-BF may be a potential alternative to surgical resection for patients with advanced disease.

Orthotopic and metastatic tumour models in preclinical cancer research

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

Andrographolide inhibits Burkitt's lymphoma by binding JUN and CASP3 proteins

BACKGROUND

Burkitt's lymphoma, one of the most common subtypes of pediatric malignant lymphoma, is notorious for its swift onset, aggressive proliferation, pronounced invasiveness, and marked malignancy. The therapeutic landscape for Burkitt's lymphoma currently falls short of providing universally effective and tolerable solutions. Andrographolide, a primary active component of Andrographis paniculata, is renowned for its properties of heat-clearing, detoxification, inflammation reduction, and pain relief. It is predominantly used in treating bacterial and viral infections of the upper respiratory tract, as well as dysentery. Various reports highlight the antitumor effects of andrographolide. Yet, its specific impact and the underlying mechanism of action on Burkitt's lymphoma remain an uncharted area of research.

METHOD

We employed network pharmacology to pinpoint the targets of andrographolide's action on Burkitt's lymphoma and the associated pathways. We then evaluated the impact of andrographolide on Burkitt's lymphoma using both in vitro and in vivo patient-derived xenograft (PDX) models. Concurrently, we confirmed the molecular targets of andrographolide in Burkitt's lymphoma through immunofluorescence assays.

RESULT

Utilizing network pharmacology, we identified 15 relevant targets, 60 interrelationships between these targets, and numerous associated signaling pathways for andrographolide's action on Burkitt's lymphoma. In vitro efficacy tests using High-throughput Drug Sensitivity Testing and in vivo PDX model evaluations revealed that andrographolide effectively curtailed the growth of Burkitt's lymphoma. Moreover, we observed a increased in the expression of JUN (c-Jun) and CASP3 (Caspase 3) proteins in Burkitt's lymphoma cells treated with andrographolide.

CONCLUSION

Andrographolide inhibits the growth of Burkitt's lymphoma by inhibiting JUN and CASP3 proteins.

Histopathologic and immunophenotypic characterization of patient-derived pediatric malignant hepatocellular tumor xenografts (PDXs)

Advances in targeted therapies for pediatric hepatocellular tumors have been limited due to a paucity of clinically relevant models. Establishment and validation of intrahepatic patient-derived xenograft (PDX) models would help bridging this gap. The aim of this study is to compare the histomorphologic and immunophenotypic fidelity of patient tumors and their corresponding intrahepatic PDX models. Murine PDX models were established by intrahepatic implantation of patient tumors. Pathology slides from both patients and their corresponding PDX models were reviewed and quantitatively assessed for various histologic components and immunophenotypic markers. Ten PDX models were successfully established from nine patients with pre- (n=3) and post- (n=6) chemotherapy samples; diagnosed of hepatoblastoma (n=8) and hepatocellular neoplasm, not otherwise specified (n=1). Two of nine (22.2%) patients showed ≥75% fetal component; however, the corresponding PDX models did not maintain this fetal differentiation. High grade histology was seen in three patients (33.3%) and overrepresented in six PDX models (60%). Within the subset of three PDXs that were further characterized, significant IHC concordance was seen in all 3 models for CK7, CK19, Ki-67, and p53; and 2 of 3 models for Sox9 and Beta-catenin. GPC-3 and GS showed variable to moderate concordance, while Hepar was the least concordant. Our study shows that in general, the PDX models appear to represent the higher-grade component of the original tumor and show significant concordance for Ki-67, making them appropriate tools for testing new therapies for the most aggressive, therapy-resistant tumors.

Rebuilding the microenvironment of primary tumors in humans: a focus on stroma

Conventional tumor models have critical shortcomings in that they lack the complexity of the human stroma. The heterogeneous stroma is a central compartment of the tumor microenvironment (TME) that must be addressed in cancer research and precision medicine. To fully model the human tumor stroma, the deconstruction and reconstruction of tumor tissues have been suggested as new approaches for in vitro tumor modeling. In this review, we summarize the heterogeneity of tumor-associated stromal cells and general deconstruction approaches used to isolate patient-specific stromal cells from tumor tissue; we also address the effect of the deconstruction procedure on the characteristics of primary cells. Finally, perspectives on the future of reconstructed tumor models are discussed, with an emphasis on the essential prerequisites for developing authentic humanized tumor models.

The generation and use of animal models of osteosarcoma in cancer research

Osteosarcoma is the most common malignant bone tumor affecting children and adolescents. Currently, the most common treatment is surgery combined with neoadjuvant chemotherapy. Although the survival rate of patients with osteosarcoma has improved in recent years, it remains poor when the tumor(s) progress and distant metastases develop. Therefore, better animal models that more accurately replicate the natural progression of the disease are needed to develop improved prognostic and diagnostic markers, as well as targeted therapies for both primary and metastatic osteosarcoma. The present review described animal models currently being used in research investigating osteosarcoma, and their characteristics, advantages, and disadvantages. These models may help elucidate the pathogenic mechanism(s) of osteosarcoma and provide evidence to support and develop clinical treatment strategies.

Methods to study xenografted human cancer in genetically diverse mice

Xenografting human cancer tissues into mice to test new cures against cancers is critical for understanding and treating the disease. However, only a few inbred strains of mice are used to study cancers, and derivatives of mainly one strain, mostly NOD/ShiLtJ, are used for therapy efficacy studies. As it has been demonstrated when human cancer cell lines or patient-derived tissues (PDX) are xenografted into mice, the neoplastic cells are human but the supporting cells that comprise the tumor (the stroma) are from the mouse. Therefore, results of studies of xenografted tissues are influenced by the host strain. We previously published that when the same neoplastic cells are xenografted into different mouse strains, the pattern of tumor growth, histology of the tumor, number of immune cells infiltrating the tumor, and types of circulating cytokines differ depending on the strain. Therefore, to better comprehend the behavior of cancer in vivo, one must xenograft multiple mouse strains. Here we describe and report a series of methods that we used to reveal the genes and proteins expressed when the same cancer cell line, MDA-MB-231, is xenografted in different hosts. First, using proteomic analysis, we show how to use the same cell line in vivo to reveal the protein changes in the neoplastic cell that help it adapt to its host. Then, we show how different hosts respond molecularly to the same cell line. We also find that using multiple strains can reveal a more suitable host than those traditionally used for a "difficult to xenograft" PDX. In addition, using complex trait genetics, we illustrate a feasible method for uncovering the alleles of the host that support tumor growth. Finally, we demonstrate that Diversity Outbred mice, the epitome of a model of mouse-strain genetic diversity, can be xenografted with human cell lines or PDX using 2-deoxy-D-glucose treatment.

Consistency between Primary Uterine Corpus Malignancies and Their Corresponding Patient-Derived Xenograft Models

Patient-derived xenograft (PDX) models retain the characteristics of tumors and are useful tools for personalized therapy and translational research. In this study, we aimed to establish PDX models for uterine corpus malignancies (UC-PDX) and analyze their similarities. Tissue fragments obtained from 92 patients with uterine corpus malignancies were transplanted subcutaneously into immunodeficient mice. Histological and immunohistochemical analyses were performed to compare tumors of patients with PDX tumors. DNA and RNA sequencing were performed to validate the genetic profile. Furthermore, the RNA in extracellular vesicles (EVs) extracted from primary and PDX tumors was analyzed. Among the 92 cases, 52 UC-PDX models were established, with a success rate of 56.5%. The success rate depended on tumor histology and staging. The pathological and immunohistochemical features of primary and PDX tumors were similar. DNA sequencing revealed similarities in gene mutations between the primary and PDX tumors. RNA sequencing showed similarities in gene expressions between primary and PDX tumors. Furthermore, the RNA profiles of the EVs obtained from primary and PDX tumors were similar. As UC-PDX retained the pathological and immunohistochemical features and gene profiles of primary tumors, they may provide a platform for developing personalized medicine and translational research.

Progress and perspective of organoid technology in breast cancer research

ABSTRACT

Breast cancer, a malignant tumor with a high incidence in women, lacks in vitro research models that can represent the biological functions of breast tumors in vivo. As a new biological tool, the organoid model has unique advantages over traditional methods, such as cell culture and patient-derived xenografts. Combining organoids with other emerging technologies, such as gene engineering and microfluidic chip technology, provides an effective method to compensate for the deficiencies in organoid models of breast cancer in vivo. The emergence of breast cancer organoids has provided new tools and research directions in precision medicine, personality therapy, and drug research. In this review, we summarized the merits and demerits of organoids compared to traditional biological models, explored the latest developments in the combination of new technologies and organoid models, and discussed the construction methods and application prospects of different breast organoid models.

Hypoxia-Responsive CAR-T Cells Exhibit Reduced Exhaustion and Enhanced Efficacy in Solid Tumors

Expanding the utility of chimeric antigen receptor (CAR)-T cells in solid tumors requires improving their efficacy and safety. Hypoxia is a feature of most solid tumors that could be used to help CAR-T cells discriminate tumors from normal tissues. In this study, we developed hypoxia-responsive CAR-T cells by engineering the CAR to be under regulation of hypoxia-responsive elements and selected the optimal structure (5H1P-CEA CAR), which can be activated in the tumor hypoxic microenvironment to induce CAR-T cells with high polyfunctionality. Hypoxia-responsive CAR T cells were in a "resting" state with low CAR expression under normoxic conditions. Compared with conventional CAR-T cells, hypoxia-responsive CAR-T cells maintained lower differentiation and displayed enhanced oxidative metabolism and proliferation during cultivation, and they sowed a capacity to alleviate the negative effects of hypoxia on T-cell proliferation and metabolism. Furthermore, 5H1P-CEA CAR-T cells exhibited decreased T-cell exhaustion and improved T-cell phenotype in vivo. In patient-derived xenograft models, hypoxia-responsive CAR-T cells induced more durable antitumor activity than their conventional counterparts. Overall, this study provides an approach to limit CAR expression to the hypoxic tumor microenvironment that could help to enhance CAR T-cell efficacy and safety in solid tumors.

SIGNIFICANCE

Engineering CAR-T cells to upregulate CAR expression under hypoxic conditions induces metabolic reprogramming, reduces differentiation, and increases proliferation to enhance their antitumor activity, providing a strategy to improve efficacy and safety.

Establishment and characterization of a recurrent malignant peripheral nerve sheath tumor cell line: RsNF

Malignant peripheral nerve sheath tumor (MPNST) is a highly aggressive and recurrent soft tissue sarcoma. It most commonly occurs secondary to neurofibromatosis type I, and it has a 5-year survival rate of only 8-13%. To better study the tumor heterogeneity of MPNST and to develop diverse treatment options, more tumor-derived cell lines are needed to obtain richer biological information. Here, we established a primary cell line of relapsed MPNST RsNF cells derived from a patient diagnosed with NF1 and detected the presence of NF1 mutations and SUZ12 somatic mutations through whole-exome sequencing(WES). Through tumor molecular marker targeted sequencing and single-cell transcriptome sequencing, it was found that chromosome 7 copy number variation (CNV) was gained in this cell line, and ZNF804B, EGFR, etc., were overexpressed on chromosome 7. Therefore, RsNF cells can be used as a useful tool in NF1-associated MPNST genomic amplification studies and to develop new therapeutic strategies.

Systems approach for congruence and selection of cancer models towards precision medicine

Cancer models are instrumental as a substitute for human studies and to expedite basic, translational, and clinical cancer research. For a given cancer type, a wide selection of models, such as cell lines, patient-derived xenografts, organoids and genetically modified murine models, are often available to researchers. However, how to quantify their congruence to human tumors and to select the most appropriate cancer model is a largely unsolved issue. Here, we present Congruence Analysis and Selection of CAncer Models (CASCAM), a statistical and machine learning framework for authenticating and selecting the most representative cancer models in a pathway-specific manner using transcriptomic data. CASCAM provides harmonization between human tumor and cancer model omics data, systematic congruence quantification, and pathway-based topological visualization to determine the most appropriate cancer model selection. The systems approach is presented using invasive lobular breast carcinoma (ILC) subtype and suggesting CAMA1 followed by UACC3133 as the most representative cell lines for ILC research. Two additional case studies for triple negative breast cancer (TNBC) and patient-derived xenograft/organoid (PDX/PDO) are further investigated. CASCAM is generalizable to any cancer subtype and will authenticate cancer models for faithful non-human preclinical research towards precision medicine.

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

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

Establishment and Thorough Characterization of Xenograft (PDX) Models Derived from Patients with Pancreatic Cancer for Molecular Analyses and Chemosensitivity Testing

Patient-derived xenograft (PDX) tumor models are essential for identifying new biomarkers, signaling pathways and novel targets, to better define key factors of therapy response and resistance mechanisms. Therefore, this study aimed at establishing pancreas carcinoma (PC) PDX models with thorough molecular characterization, and the identification of signatures defining responsiveness toward drug treatment. In total, 45 PC-PDXs were generated from 120 patient tumor specimens and the identity of PDX and corresponding patient tumors was validated. The majority of engrafted PDX models represent ductal adenocarcinomas (PDAC). The PDX growth characteristics were assessed, with great variations in doubling times (4 to 32 days). The mutational analyses revealed an individual mutational profile of the PDXs, predominantly showing alterations in the genes encoding KRAS, TP53, FAT1, KMT2D, MUC4, RNF213, ATR, MUC16, GNAS, RANBP2 and CDKN2A. Sensitivity of PDX toward standard of care (SoC) drugs gemcitabine, 5-fluorouracil, oxaliplatin and abraxane, and combinations thereof, revealed PDX models with sensitivity and resistance toward these treatments. We performed correlation analyses of drug sensitivity of these PDX models and their molecular profile to identify signatures for response and resistance. This study strongly supports the importance and value of PDX models for improvement in therapies of PC.

Synergistic effect of antagonists to KRas4B/PDE6 molecular complex in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis among all human cancers as it is highly resistant to chemotherapy. K-Ras mutations usually trigger the development and progression of PDAC. We hypothesized that compounds stabilizing the KRas4B/PDE6δ complex could serve as PDAC treatments. Using in silico approaches, we identified the small molecules C14 and P8 that reduced K-Ras activation in primary PDAC cells. Importantly, C14 and P8 significantly prevented tumor growth in patient-derived xenotransplants. Combined treatment with C14 and P8 strongly increased cytotoxicity in PDAC cell lines and primary cultures and showed strong synergistic antineoplastic effects in preclinical murine PDAC models that were superior to conventional therapeutics without causing side effects. Mechanistically, C14 and P8 reduced tumor growth by inhibiting AKT and ERK signaling downstream of K-RAS leading to apoptosis, specifically in PDAC cells. Thus, combined treatment with C14 and P8 may be a superior pharmaceutical strategy to improve the outcome of PDAC.

Exploratory study on the efficacy of bortezomib combining mitoxantrone or CD22-CAR T therapy targeting CD19-negative relapse after CD19-CAR T cell therapy with a simpler cell-line-based model

Target-negative relapse after CD19 chimeric antigen receptor engineered (CAR) T cell therapy for patients with B lineage acute lymphoblastic leukemia (B-ALL) presents limited treatment options with dismal outcomes. Although CD22-CAR T cells mediate similarly potent antineoplastic effects in patients with CD19dim or even CD19-negative relapse following CD19-directed immunotherapy, a high rate of relapse associated with diminished CD22 cell surface expression has also been observed. Therefore, it is unclear whether any other therapeutic options are available. Mitoxantrone has shown significant antineoplastic activity in patients with relapsed or refractory leukemia over the past decades, and in some cases, the addition of bortezomib to conventional chemotherapeutic agents has demonstrated improved response rates. However, whether this mitoxantrone and bortezomib combination therapy is effective for those patients who have relapsed B-ALL after receiving CD19-CAR T cell therapy remains to be elucidated. In this study, we established a cellular model system using a CD19-positive B-ALL cell line Nalm-6 to investigate the treatment options for CD19-negative relapsed B-ALL after CD19-CAR T cell therapy. In addition to CD22-CAR T therapy, we observed that the combination of bortezomib and mitoxantrone exhibited effective anti-leukemia activity in the CD19-negative Nalm-6 cell line by downregulating p-AKT and p-mTOR. These results suggest that this combination therapy is a possible option for target-negative refractory leukemia cells after CAR-T cell treatment.

Patient-derived tumor models: a suitable tool for preclinical studies on esophageal cancer

Esophageal cancer (EC) is the tenth most common cancer worldwide and has high morbidity and mortality. Its main subtypes include esophageal squamous cell carcinoma and esophageal adenocarcinoma, which are usually diagnosed during their advanced stages. The biological defects and inability of preclinical models to summarize completely the etiology of multiple factors, the complexity of the tumor microenvironment, and the genetic heterogeneity of tumors severely limit the clinical treatment of EC. Patient-derived models of EC not only retain the tissue structure, cell morphology, and differentiation characteristics of the original tumor, they also retain tumor heterogeneity. Therefore, compared with other preclinical models, they can better predict the efficacy of candidate drugs, explore novel biomarkers, combine with clinical trials, and effectively improve patient prognosis. This review discusses the methods and animals used to establish patient-derived models and genetically engineered mouse models, especially patient-derived xenograft models. It also discusses their advantages, applications, and limitations as preclinical experimental research tools to provide an important reference for the precise personalized treatment of EC and improve the prognosis of patients.

A redox-responsive nanosystem to suppress chemoresistant lung cancer through targeting STAT3

Cancer stem cells (CSCs) have been demonstrated to be involved in tumor initiation and relapse, and the presence of CSCs in the tumor tissue often leads to therapeutic failure. BBI608 has been identified to eliminate CSCs by inhibiting signal transducer and activator of transcription 3 (STAT3). In this study, we confirm that BBI608 can efficiently suppress the proliferation and migration of non-small cell lung cancer (NSCLC) cells, and specifically kill the stemness-high population in chemoresistant NSCLC cells. To improve its bioavailability and tumor accumulation, BBI608 is successfully encapsulated into redox-responsive PEGylated branched N-(2-hydroxypropyl) methacrylamide (HPMA)-deoxy cholic acid (DA) polymeric nanoparticles (BBI608-SS-NPs). The BBI608-SS-NPs can release the drug in response to high concentrations of intracellular glutathione, and exhibit cytotoxicity against lung cancer cells and CSCs comparable to the free drug BBI608. Furthermore, the BBI608-SS-NPs preferentially accumulate in tumor sites, resulting in a superior anti-tumor efficacy in both cisplatin-resistant cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models of NSCLC. Mechanistic studies demonstrate that BBI608-SS-NPs not only directly inhibit the downstream genes of the STAT3 pathway, but also indirectly inhibit the Wnt pathway. Overall, this stimuli-responsive polymeric nanoformulation of BBI608 shows great potential in the treatment of chemoresistant NSCLC by targeting CSCs.

Mapping the Single-cell Differentiation Landscape of Osteosarcoma

The genetic and intratumoral heterogeneity observed in human osteosarcomas (OS) poses challenges for drug development and the study of cell fate, plasticity, and differentiation, processes linked to tumor grade, cell metastasis, and survival. To pinpoint errors in OS differentiation, we transcriptionally profiled 31,527 cells from a tissue-engineered model that directs MSCs toward adipogenic and osteoblastic fates. Incorporating pre-existing chondrocyte data, we applied trajectory analysis and non-negative matrix factorization (NMF) to generate the first human mesenchymal differentiation atlas. This 'roadmap' served as a reference to delineate the cellular composition of morphologically complex OS tumors and quantify each cell's lineage commitment. Projecting these signatures onto a bulk RNA-seq OS dataset unveiled a correlation between a stem-like transcriptomic phenotype and poorer survival outcomes. Our study takes the critical first step in accurately quantifying OS differentiation and lineage, a prerequisite to better understanding global differentiation bottlenecks that might someday be targeted therapeutically.

Challenges and Prospects of Patient-Derived Xenografts for Cancer Research

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

Selinexor demonstrates anti-tumor efficacy in paired patient-derived xenograft models and hydrogel-embedded histoculture drug sensitivity test of penile cancer

BACKGROUND

Penile cancer is a rare malignancy with a poor prognosis, even with various treatment options. Considering the little progress in the study of the pathogenesis and treatment of penile cancer because of the lack of models that mimic the biological properties of the tumor, we have developed a patient-derived xenograft (PDX) model and paired hydrogel-embedded histoculture drug sensitivity test (HDST) to screen for drugs that can inhibit tumors. The increased expression of XPO1, as a key nuclear export protein involved in the transport of various tumor suppressors and cell cycle regulatory proteins, is associated with the prognosis of a variety of tumors [World J Uroly 27(2):141-150, 2009]. Selinexor is an inhibitor of XPO1, which can treat cancers, such as multiple myeloma, gastric cancer, triple-negative breast cancer, and non-small cell carcinoma [Transl Androl Urol 6(5):785-790, 2017; OncoTargets Therapy 13:6405-6416, 2020]. However, whether XPO1 inhibition has a role in penile cancer remains unknown. Therefore, this article used the PDX and HDST models to investigate whether the inhibition of XPO1 has an effect on penile cancer and its underlying mechanism.

METHODS

We used penile cancer tumor tissues to construct a PDX model of penile cancer and paired PDXE model and confirmed the consistency of PDX tumor tissues in source patients. Then, we assessed the ability of Selinexor to inhibit penile cancer tissues in vivo using a PDX model and in vitro by HDST. We also examined the potential mechanism of XPO1 action on penile cancer by IHC and TUNEL. Finally, we assessed the safety of the drug treatment by H&E and biochemical blood analysis.

RESULTS

Result showed that the penile cancer PDX model and patient penile cancer tissues were clinically consistent in morphological characteristics and protein expression. In addition, Selinexor could inhibit tumor growth in PDX models and HDST. We found that P53, P21 expression was upregulated; Cyclin D1 expression was downregulated, and apoptosis of tumor cells was increased in the Selinexor-treated PDX model. Moreover, it had no significant effect on liver, kidney, and cardiac function.

CONCLUSION

The PDX model of penile cancer was a powerful tool for penile cancer research and new drug development. It showed that Selinexor can effectively inhibit penile cancer in vitro and in vivo. In addition, XPO1 may affect P53, P21, and Cyclin D1 expression to regulate the growth and apoptosis of penile carcinoma.

Nextflow Pipeline for Visium and H&E Data from Patient-Derived Xenograft Samples

Highlights

We have developed an automated data processing pipeline to quantify mouse and human data from patient-derived xenograft samples assayed by Visium spatial transcriptomics with matched hematoxylin and eosin (H&E) stained image. We enable deconvolution of reads with Xenome, quantification of spatial gene expression from host and graft species with Space Ranger, extraction of B-allele frequencies, and splicing quantification with Velocyto. In the H&E image processing sub-workflow, we generate morphometric and deep learning-derived feature quantifications complementary to the Visium spots, enabling multi-modal H&E/expression comparisons. We have wrapped the pipeline into Nextflow DSL2 in a scalable, portable, and easy-to-use framework.

Summary

We designed a Nextflow DSL2-based pipeline, Spatial Transcriptomics Quantification (STQ), for simultaneous processing of 10x Genomics Visium spatial transcriptomics data and a matched hematoxylin and eosin (H&E)-stained whole slide image (WSI), optimized for Patient-Derived Xenograft (PDX) cancer specimens. Our pipeline enables the classification of sequenced transcripts for deconvolving the mouse and human species and mapping the transcripts to reference transcriptomes. We align the H&E WSI with the spatial layout of the Visium slide and generate imaging and quantitative morphology features for each Visium spot. The pipeline design enables multiple analysis workflows, including single or dual reference genomes input and stand-alone image analysis. We showed the utility of our pipeline on a dataset from Visium profiling of four melanoma PDX samples. The clustering of Visium spots and clustering of imaging features of H&E data reveal similar patterns arising from the two data modalities.

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

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

Experimental Murine Models for Colorectal Cancer Research

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

A new intronic quantitative PCR method led to the discovery of transformation from human ascites to murine malignancy in a mouse model

Purpose

To establish a fast and accurate detection method for interspecies contaminations in the patient-derived xenograft (PDX) models and cell lines, and to elucidate possible mechanisms if interspecies oncogenic transformation is detected.

Methods

A fast and highly sensitive intronic qPCR method detecting Gapdh intronic genomic copies was developed to quantify if cells were human or murine or a mixture. By this method, we documented that murine stromal cells were abundant in the PDXs; we also authenticated our cell lines to be human or murine.

Results

In one mouse model, GA0825-PDX transformed murine stromal cells into a malignant tumorigenic murine P0825 cell line. We traced the timeline of this transformation and discovered three subpopulations descended from the same GA0825-PDX model: epithelium-like human H0825, fibroblast-like murine M0825, and main passaged murine P0825 displayed differences in tumorigenic capability in vivo. P0825 was the most aggressive and H0825 was weakly tumorigenic. Immunofluorescence (IF) staining revealed that P0825 cells highly expressed several oncogenic and cancer stem cell markers. Whole exosome sequencing (WES) analysis revealed that TP53 mutation in the human ascites IP116-generated GA0825-PDX may have played a role in the human-to-murine oncogenic transformation.

Conclusion

This intronic qPCR is able to quantify human/mouse genomic copies with high sensitivity and within a time frame of a few hours. We are the first to use intronic genomic qPCR for authentication and quantification of biosamples. Human ascites transformed murine stroma into malignancy in a PDX model.

Targeting SMYD2 inhibits angiogenesis and increases the efficiency of apatinib by suppressing EGFL7 in colorectal cancer

Angiogenesis is an essential factor affecting the occurrence and development of solid tumors. SET And MYND Domain Containing 2 (SMYD2) serves as an oncogene in various cancers. However, whether SMYD2 is involved in tumor angiogenesis remains unclear. Here, we report that SMYD2 expression is associated with microvessel density in colorectal cancer (CRC) tissues. SMYD2 promotes CRC angiogenesis in vitro and in vivo. Mechanistically, SMYD2 physically interacts with HNRNPK and mediates lysine monomethylation at K422 of HNRNPK, which substantially increases RNA binding activity. HNRNPK acts by binding and stabilizing EGFL7 mRNA. As an angiogenic stimulant, EGFL7 enhances CRC angiogenesis. H3K4me3 maintained by PHF8 mediates the abnormal overexpression of SMYD2 in CRC. Moreover, targeting SMYD2 blocks CRC angiogenesis in tumor xenografts. Treatment with BAY-598, a functional inhibitor of SMYD2, can also synergize with apatinib in patient-derived xenografts. Overall, our findings reveal a new regulatory axis of CRC angiogenesis and provide a potential strategy for antiangiogenic therapy.

Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes

The increasing number of available anti-cancer drugs presents a challenge for oncologists, who must choose the most effective treatment for the patient. Precision cancer medicine relies on matching a drug with a tumor's molecular profile to optimize the therapeutic benefit. However, current precision medicine approaches do not fully account for intra-tumoral heterogeneity. Different mutation profiles and cell behaviors within a single heterogeneous tumor can significantly impact therapy response and patient outcomes. Patient-derived avatar models recapitulate a patient's tumor in an animal or dish and provide the means to functionally assess heterogeneity's impact on drug response. Mouse xenograft and organoid avatars are well-established, but the time required to generate these models is not practical for clinical decision-making. Zebrafish are emerging as a time-efficient and cost-effective cancer avatar model. In this review, we highlight recent developments in zebrafish cancer avatar models and discuss the unique features of zebrafish that make them ideal for the interrogation of cancer heterogeneity and as part of precision cancer medicine pipelines.

Integrative Multi-OMICs Identifies Therapeutic Response Biomarkers and Confirms Fidelity of Clinically Annotated, Serially Passaged Patient-Derived Xenografts Established from Primary and Metastatic Pediatric and AYA Solid Tumors

Establishment of clinically annotated, molecularly characterized, patient-derived xenografts (PDXs) from treatment-naïve and pretreated patients provides a platform to test precision genomics-guided therapies. An integrated multi-OMICS pipeline was developed to identify cancer-associated pathways and evaluate stability of molecular signatures in a panel of pediatric and AYA PDXs following serial passaging in mice. Original solid tumor samples and their corresponding PDXs were evaluated by whole-genome sequencing, RNA-seq, immunoblotting, pathway enrichment analyses, and the drug−gene interaction database to identify as well as cross-validate actionable targets in patients with sarcomas or Wilms tumors. While some divergence between original tumor and the respective PDX was evident, majority of alterations were not functionally impactful, and oncogenic pathway activation was maintained following serial passaging. CDK4/6 and BETs were prioritized as biomarkers of therapeutic response in osteosarcoma PDXs with pertinent molecular signatures. Inhibition of CDK4/6 or BETs decreased osteosarcoma PDX growth (two-way ANOVA, p < 0.05) confirming mechanistic involvement in growth. Linking patient treatment history with molecular and efficacy data in PDX will provide a strong rationale for targeted therapy and improve our understanding of which therapy is most beneficial in patients at diagnosis and in those already exposed to therapy.

AKR1C2 Promotes Metastasis and Regulates the Molecular Features of Luminal Androgen Receptor Subtype in Triple Negative Breast Cancer Cells

PURPOSE

Patients with triple-negative breast cancer (TNBC) have an increased risk of distant metastasis compared to those with other subtypes. In this study, we aimed to identify the genes associated with distant metastasis in TNBC and their underlying mechanisms.

METHODS

We established patient-derived xenograft (PDX) models using surgically resected breast cancer tissues from 31 patients with TNBC. Among these, 15 patients subsequently developed distant metastases. Candidate metastasis-associated genes were identified using RNA sequencing. In vitro wound healing, proliferation, migration, and invasion assays and in vivo tumor xenograft and metastasis assays were performed to determine the functional importance of aldo-keto reductase family 1 member C2 (AKR1C2). Additionally, we used the METABRIC dataset to investigate the potential role of AKR1C2 in regulating TNBC subtypes and their downstream signaling activities.

RESULTS

RNA sequencing of primary and PDX tumors showed that genes involved in steroid hormone biosynthesis, including AKR1C2, were significantly upregulated in patients who subsequently developed metastasis. In vitro and in vivo assays showed that silencing of AKR1C2 resulted in reduced cell proliferation, migration, invasion, tumor growth, and incidence of lung metastasis. AKR1C2 was upregulated in the luminal androgen receptor (LAR) subtype of TNBC in the METABRIC dataset, and AKR1C2 silencing resulted in the downregulation of LAR classifier genes in TNBC cell lines. The androgen receptor (AR) gene was a downstream mediator of AKR1C2-associated phenotypes in TNBC cells. AKR1C2 expression was associated with gene expression pathways that regulate AR expression, including JAK-STAT signaling or interleukin 6 (IL-6). The levels of phospho-signal transducer and activator of transcription and IL-6, along with secreted IL-6, were significantly downregulated in AKR1C2-silenced TNBC cells.

CONCLUSION

Our data indicate that AKR1C2 is an important regulator of cancer growth and metastasis in TNBC and may be a critical determinant of LAR subtype features.

Leonurine suppresses prostate cancer growth in vitro and in vivo by regulating miR-18a-5p/SLC40A1 axis

Prostate cancer is a leading cause of cancer-associated death in males. Leonurine (Leo) is a pleiotropic anti-tumor agent isolated from traditional Chinese herb that was used in gynecologic treatments. However, its pharmacological effect against prostate cancer progression remains unclear. Here, we showed that Leo dose dependently inhibited prostate cancer cell proliferation, promoted cell apoptosis, and induced cell cycle arrest. Moreover, we noticed that miR-18a-5p was downregulated and the solute carrier family 40 member 1 (SLC40A1) is upregulated by Leo treatment. SLC40A1 knockdown by siRNA abrogated the inhibitory effect of Leo on prostate cancer progression. Notably, Leo also significantly inhibited prostate cancer progression in a subcutaneous xenograft tumor mouse model in vivo. This study further unveiled the mechanism by which Leo inhibited prostate cancer progression, which provides a promising potential for its future clinical application.

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.

Genetically diverse mouse platform to xenograft cancer cells

The lack of genetically diverse preclinical animal models in basic biology and efficacy testing has been cited as a potential cause of failure in clinical trials. We developed and characterized five diverse RAG1 null mouse strains as models that allow xenografts to grow. In these strains, we characterized the growth of breast cancer, leukemia and glioma cell lines. We found a wide range of growth characteristics that were far more dependent on strain than tumor type. For the breast cancer cell line, we characterized the spectrum of xenograft/tumor growth at structural, histological, cellular and molecular levels across each strain, and found that each strain captures unique structural components of the stroma. Furthermore, we showed that the increase in tumor-infiltrating myeloid CD45+ cells and the amount of circulating cytokine IL-6 and chemokine KC (also known as CXCL1) is associated with a higher tumor size in different strains. This resource is available to study established human xenografts, as well as difficult-to-xenograft tumors and growth of hematopoietic stems cells, and to decipher the role of myeloid cells in the development of spontaneous cancers.

Assessing the performance of different outcomes for tumor growth studies with animal models

The consistency of reporting results for patient‐derived xenograft (PDX) studies is an area of concern. The PDX method commonly starts by implanting a derivative of a human tumor into a mouse, then comparing the tumor growth under different treatment conditions. Currently, a wide array of statistical methods (e.g., t‐test, regression, chi‐squared test) are used to analyze these data, which ultimately depend on the outcome chosen (e.g., tumor volume, relative growth, categorical growth). In this simulation study, we provide empirical evidence for the outcome selection process by comparing the performance of both commonly used outcomes and novel variations of common outcomes used in PDX studies. Data were simulated to mimic tumor growth under multiple scenarios, then each outcome of interest was evaluated for 10 000 iterations. Comparisons between different outcomes were made with respect to average bias, variance, type‐1 error, and power. A total of 18 continuous, categorical, and time‐to‐event outcomes were evaluated, with ultimately 2 outcomes outperforming the others: final tumor volume and change in tumor volume from baseline. Notably, the novel variations of the tumor growth inhibition index (TGII)—a commonly used outcome in PDX studies—was found to perform poorly in several scenarios with inflated type‐1 error rates and a relatively large bias. Finally, all outcomes of interest were applied to a real‐world dataset.

Identification and Validation of Three Hub Genes Involved in Cell Proliferation and Prognosis of Castration-Resistant Prostate Cancer

Background

The acquisition of castration resistance is lethal and inevitable in most prostate cancer patients under hormone therapy. However, effective biomarkers and therapeutic targets for castration-resistant prostate cancer remain to be defined.

Methods

Comprehensive bioinformatics tools were used to screen hub genes in castration-resistant prostate cancer and were verified in androgen-dependent prostate cancer and castration-resistant prostate cancer in TCGA and the SU2C/PCF Dream Team database, respectively. Gene set enrichment analysis and in vitro experiments were performed to determine the potential functions of hub genes involved in castration-resistant prostate cancer progression.

Results

Three hub genes were screened out by bioinformatics analysis: MCM4, CENPI, and KNTC1. These hub genes were upregulated in castration-resistant prostate cancer and showed high diagnostic and prognostic value. Moreover, the expression levels of the hub genes were positively correlated with neuroendocrine prostate cancer scores, which represent the degree of castration-resistant prostate cancer aggression. Meanwhile, in vitro experiments confirmed that hub gene expression was increased in castration-resistant prostate cancer cell lines and that inhibition of hub genes hindered cell cycle transition, resulting in suppression of castration-resistant prostate cancer cell proliferation, which confirmed the gene set enrichment analysis results.

Conclusions

MCM4, CENPI, and KNTC1 could serve as candidate diagnostic and prognostic biomarkers of castration-resistant prostate cancer and may provide potential preventive and therapeutic targets.

Patient-derived cancer models: Valuable platforms for anticancer drug testing

Molecularly targeted treatments and immunotherapy are cornerstones in oncology, with demonstrated efficacy across different tumor types. Nevertheless, the overwhelming majority metastatic disease is incurable due to the onset of drug resistance. Preclinical models including genetically engineered mouse models, patient-derived xenografts and two- and three-dimensional cell cultures have emerged as a useful resource to study mechanisms of cancer progression and predict efficacy of anticancer drugs. However, variables including tumor heterogeneity and the complexities of the microenvironment can impair the faithfulness of these platforms. Here, we will discuss advantages and limitations of these preclinical models, their applicability for drug testing and in co-clinical trials and potential strategies to increase their reliability in predicting responsiveness to anticancer medications.

Evaluating Translational Methods for Personalized Medicine—A Scoping Review

The introduction of personalized medicine, through the increasing multi-omics characterization of disease, brings new challenges to disease modeling. The scope of this review was a broad evaluation of the relevance, validity, and predictive value of the current preclinical methodologies applied in stratified medicine approaches. Two case models were chosen: oncology and brain disorders. We conducted a scoping review, following the Joanna Briggs Institute guidelines, and searched PubMed, EMBASE, and relevant databases for reports describing preclinical models applied in personalized medicine approaches. A total of 1292 and 1516 records were identified from the oncology and brain disorders search, respectively. Quantitative and qualitative synthesis was performed on a final total of 63 oncology and 94 brain disorder studies. The complexity of personalized approaches highlights the need for more sophisticated biological systems to assess the integrated mechanisms of response. Despite the progress in developing innovative and complex preclinical model systems, the currently available methods need to be further developed and validated before their potential in personalized medicine endeavors can be realized. More importantly, we identified underlying gaps in preclinical research relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. To achieve a broad implementation of predictive translational models in personalized medicine, these fundamental deficits must be addressed.

Strategies to mitigate the on- and off-target toxicities of recombinant immunotoxins: an antibody engineering perspective

Targeted cancer therapies using immunotoxins has achieved remarkable efficacies in hematological malignancies. However, the clinical development of immunotoxins is also faced with many challenges like anti-drug antibodies and dose-limiting toxicity issues. Such a poor efficacy/safety ratio is also the major hurdle in the research and development of antibody-drug conjugates. From an antibody engineering perspective, various strategies were summarized/proposed to tackle the notorious on target off tumor toxicity issues, including passive strategy (XTENylation of immunotoxins) and active strategies (modulating the affinity and valency of the targeting moiety of immunotoxins, conditionally activating immunotoxins in the tumor microenvironments and reconstituting split toxin to reduce systemic toxicity etc.). By modulating the functional characteristics of the targeting moiety and the toxic moiety of immunotoxins, selective tumor targeting can be augmented while sparing the healthy cells in normal tissues expressing the same target of interest. If successful, the improved therapeutic index will likely help to address the dose-limiting toxicities commonly observed in the clinical trials of various immunotoxins.

Correlation between Patient-Derived Xenograft Modeling and Prognosis in Osteosarcoma

Objective

To retrospectively analyze and compare the relationship between the success rate of patient‐derived xenograft (PDX) modeling of osteosarcoma and prognosis (3‐year overall survival rate and disease‐free survival rate) and incidence of lung metastasis.

Methods

The sample group consisted of 57 osteosarcoma patients with definite pathological diagnoses from Shanghai General Hospital from 2015–2017. PDX models in 57 patients were analyzed by retrospective analyses. Among the patients currently inoculated, 20 were tumorigenic in the PDX model, and 37 were nontumorigenic. According to the tumorigenicity of PDXs, the corresponding osteosarcoma patients were divided into two groups. The effects of clinically related indicators on the model were retrospectively compared. The patients were followed, and the 3‐year survival, 3‐year disease‐free survival (DFS), and lung metastasis rates were collected. The relationship between the modeling success and patient prognosis was investigated.

Results

In the chemotherapy‐treated group, the PDX modeling success rate was 17.4%, and in the nonchemotherapy group, the success rate was 47.1%. The success of PDX modeling was related to whether patients received chemotherapy. The success rate of PDX modeling is significantly reduced after receiving chemotherapy. The 3‐year overall survival rate of the PDX‐grafted group was 49.23%, and that of the PDX‐nongrafted group was 65.71%. There was a significant difference between the two groups, showing a strong negative correlation between the 3‐year survival rate and the success rate of the PDX model. The 3‐year disease‐free survival rate of the PDX‐grafted group was 29.54%. The 3‐year DFS of the PDX‐nongrafted group was 50.34%. There was a significant difference between the two groups. Lower grafted rates indicate a higher DFS rate. The incidence of lung metastasis in the PDX‐grafted group was 32.4%, and that in the nongrafted group was 13.1%. There was a significant difference between the two groups. The successful establishment of the PDX model indicates that patients are more likely to have lung metastases.

Conclusions

The success of PDX modeling often indicates poor prognosis (low 3‐year overall survival rate and disease‐free survival rate) and a greater possibility of lung metastasis. Therefore, PDX modeling in osteosarcoma patients can accurately predict the prognosis of patients and the risk of lung metastasis in advance to help us develop better therapeutic strategies.

Patient-Derived Xenotransplant of CNS Neoplasms in Zebrafish: A Systematic Review

Glioblastoma and neuroblastoma are the most common central nervous system malignant tumors in adult and pediatric populations. Both are associated with poor survival. These tumors are highly heterogeneous, having complex interactions among different cells within the tumor and with the tumor microenvironment. One of the main challenges in the neuro-oncology field is achieving optimal conditions to evaluate a tumor’s molecular genotype and phenotype. In this respect, the zebrafish biological model is becoming an excellent alternative for studying carcinogenic processes and discovering new treatments. This review aimed to describe the results of xenotransplantation of patient-derived CNS tumors in zebrafish models. The reviewed studies show that it is possible to maintain glioblastoma and neuroblastoma primary cell cultures and transplant the cells into zebrafish embryos. The zebrafish is a suitable biological model for understanding tumor progression and the effects of different treatments. This model offers new perspectives in providing personalized care and improving outcomes for patients living with central nervous system tumors.

Clinically relevant orthotopic xenograft models of patient-derived glioblastoma in zebrafish

An accurate prediction of the intracranial infiltration tendency and drug response of individual glioblastoma (GBM) cells is essential for personalized prognosis and treatment for this disease. However, the clinical utility of mouse patient-derived orthotopic xenograft (PDOX) models remains limited given current technical constraints, including difficulty in generating sufficient sample numbers from small tissue samples and a long latency period for results. To overcome these issues, we established zebrafish GBM xenografts of diverse origin, which can tolerate intracranial engraftment and maintain their unique histological features. Subsequent single-cell RNA-sequencing (scRNA-seq) analysis confirmed significant transcriptional identity to that of invading GBM microtumors observed in the proportionally larger brains of model animals and humans. Endothelial scRNA-seq confirmed that the zebrafish blood–brain barrier is homologous to the mammalian blood–brain barrier. Finally, we established a rapid and efficient zebrafish PDOX (zPDOX) model, which can predict long-term outcomes of GBM patients within 20 days. The zPDOX model provides a novel avenue for precision medicine of GBM, especially for the evaluation of intracranial infiltration tendency and prediction of individual drug sensitivity.

Editor's choice: We established zebrafish glioblastoma (GBM) xenograft models that can be used to perform genetic and biological analysis of GBMs, identify blood–brain barrier-penetrating drugs and predict clinical sensitivity to temozolomide in GBM patients.

A Comparative Study of Patient-Derived Tumor Models of Pancreatic Ductal Adenocarcinoma Involving Orthotopic Implantation

BACKGROUND

Pancreatic ductal adenocarcinoma (PDA) is associated with very poor prognoses. Therefore, new therapies and preclinical models are urgently needed. In the present study, we sought to develop more realistic experimental models for use in PDA research.

METHODS

We developed patient-derived xenografts (PDXs), established PDX-derived cell lines (PDCLs), and generated cell line-derived xenografts (CDXs), which we integrated to create 13 matched "trios" - i.e., patient-derived tumor models of PDA. We then compared and contrasted histological and molecular alterations between these three model systems.

RESULTS

Orthotopic implantation (OI) of the PDCLs resulted in tumorigenesis and metastases to the liver and peritoneum. Morphological comparisons of OI-CDXs and OI-PDXs with passaged tumors revealed that the histopathological features of the original tumor were maintained in both models. Molecular alterations in PDX tumors (including those to KRAS, TP53, SMAD4, and CDKN2A) were similar to those in the respective PDCLs and CDX tumors. When gene expression levels in the PDCLs, ectopic tumors, and OI tumors were compared, the distant metastasis-promoting gene CXCR4 was specifically upregulated in OI tumors, whose immunohistochemical profiles suggested epithelial-mesenchymal transition and adeno-squamous trans-differentiation.

CONCLUSION

These patient-derived tumor models provide useful tools for monitoring responses to antineoplastic agents and for studying PDA biology.

Opportunities and challenges of patient-derived models in cancer research: patient-derived xenografts, patient-derived organoid and patient-derived cells

Background

As reported, preclinical animal models differ greatly from the human body. The evaluation model may be the colossal obstacle for scientific research and anticancer drug development. Therefore, it is essential to propose efficient evaluation systems similar to clinical practice for cancer research.

Main body

While it has emerged for decades, the development of patient-derived xenografts, patient-derived organoid and patient-derived cell used to be limited. As the requirements for anticancer drug evaluation increases, patient-derived models developed rapidly recently, which is widely applied in basic research, drug development, and clinical application and achieved remarkable progress. However, there still lack systematic comparison and summarize reports for patient-derived models. In the current review, the development, applications, strengths, and challenges of patient-derived models in cancer research were characterized.

Conclusion

Patient-derived models are an indispensable approach for cancer research and human health.

OncoVee™-MiniPDX-Guided Anticancer Treatment for Gastric Cancer Patients With Synchronous Liver Metastases: A Retrospective Cohort Analysis

Background

It is estimated that 35% of gastric cancer patients appear with synchronous distant metastases—the vast majority of patients presenting with metastatic hepatic disease. How to choose the most appropriate drugs or regimens is crucial to improve the prognosis of patients. We conducted this retrospective cohort analysis to evaluate the efficacy of OncoVee™-MiniPDX-guided treatment for these patients.

Methods

Gastric cancer patients with liver metastases (GCLM) were enrolled. Patients were divided into MiniPDX and control group according to their wishes. In the observation group, the OncoVee™-MiniPDX model was conducted to screen the most sensitive drug or regimens to determine the clinical administration. Meanwhile, patients were treated with regular medications in the control group according to the guidelines without the MiniPDX model. The primary endpoint was overall survival (OS), and the secondary outcomes included objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS).

Results

A total of 68 patients with GCLM were included, with the observation and control groups of 21 and 47 patients, respectively. The baseline characteristics of patients were balanced between these two groups. MiniPDX drug sensitivity tests were associated with the increased use of targeted drugs when compared with the control group (33.3 vs. 0%, p=0.032). Median OS was estimated to be 9.4 (95% CI, 7.9–11.2) months and 7.9 (95% CI, 7.2–8.7) months in the observation and control group, respectively. Both univariate (control group vs. MiniPDX group: HR=2.586, 95% CI= 1.362–4.908, p=0.004) and multivariate regression analyses (Control group vs. MiniPDX group: adjusted HR (aHR)=4.288, 95% CI= 1.452–12.671, p=0.008) showed the superiority of the observation group on OS. Similarly, MiniPDX-based regiments significantly improve the PFS of these cases (median PFS 6.7 months vs. 4.2 months, aHR=2.773, 95% CI=1.532–3.983, p=0.029). ORR and DCR were also improved in MiniPDX group comparing with control group (ORR, 57.14 vs. 25.53%, p=0.029; DCR: 85.71 vs. 68.08%, p=0.035).

Conclusion

OncoVee™-MiniPDX model, which was used to select drugs to guide antitumor treatment, was promising to prolong survival and improve the response rate of patients with GCLM. Further well-designed studies are needed to confirm the clinical benefits of MiniPDX.

Challenging Cutaneous T-Cell Lymphoma: What Animal Models Tell us So Far

Cutaneous T-cell lymphomas are characterized by heterogeneity of clinical variants, further complicated by genomic and microenvironmental variables. Furthermore, in vitro experiments are hampered by the low culture efficiency of these malignant cells. Animal models are essential for understanding the pathogenetic mechanisms underlying malignancy and for discovering new anticancer treatments. They are divided into two main categories: those in which tumors arise in the host owing to genetic modifications and those that use tumor cell transplantation. In this review, we summarize the attempts to decipher the complexity of the pathogenesis of cutaneous T-cell lymphoma by exploiting genetically modified and xenograft models.

A transcriptional biosensor to monitor single cancer cell therapeutic responses by bioluminescence microscopy

When several life-prolonging drugs are indicated for cancer treatment, predictive drug-response tumor biomarkers are essential to guide management. Most conventional biomarkers are based on bulk tissue analysis, which cannot address the complexity of single-cell heterogeneity responsible for drug resistance. Therefore, there is a need to develop alternative drug response predictive biomarker approaches that could directly interrogate single-cell and whole population cancer cell drug sensitivity. In this study, we report a novel method exploiting bioluminescence microscopy to detect single prostate cancer (PCa) cell response to androgen receptor (AR)-axis-targeted therapies (ARAT) and predict cell population sensitivity.

Methods: We have generated a new adenovirus-delivered biosensor, PCA3-Cre-PSEBC-ITSTA, which combines an integrated two-step transcriptional amplification system (ITSTA) and the activities of the prostate cancer antigen 3 (PCA3) and modified prostate-specific antigen (PSEBC) gene promoters as a single output driving the firefly luciferase reporter gene. This system was tested on PCa cell lines and on primary PCa cells. Single cells, exposed or not to ARAT, were dynamically imaged by bioluminescence microscopy. A linear discriminant analysis (LDA)-based method was used to determine cell population sensitivities to ARAT.

Results: We show that the PCA3-Cre-PSEBC-ITSTA biosensor is PCa-specific and can dynamically monitor single-cell AR transcriptional activity before and after ARAT by bioluminescence microscopy. After biosensor transduction and bioluminescence microscopy single-cell luminescence dynamic quantification, LDA analysis could discriminate the cell populations overall ARAT sensitivity despite heterogeneous single-cell responses. Indeed, the biosensor could detect a significant decrease in AR activity following exposure to conventional ARAT in hormone-naive primary PCa cells, while in castration-resistant PCa patients, treatment response correlated with the observed clinical ARAT resistance.

Conclusion: The exploitation of bioluminescence microscopy and multi-promoter transcriptionally-regulated biosensors can aptly define the overall treatment response of patients by monitoring live single cell drug response from primary cancer tissue. This approach can be used to develop predictive biomarkers for drug response in order to help clinicians select the best drug combinations or sequences for each patient.

Challenges in genomic analysis of model systems and primary tumors of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is characterized by aggressive tumor behavior and poor prognosis. Recent next-generation sequencing (NGS)-based genomic studies have provided novel treatment modes for pancreatic cancer via the identification of cancer driver variants and molecular subtypes in PDAC. Genome-wide approaches have been extended to model systems such as patient-derived xenografts (PDXs), organoids, and cell lines for pre-clinical purposes. However, the genomic characteristics vary in the model systems, which is mainly attributed to the clonal evolution of cancer cells during their construction and culture. Moreover, fundamental limitations such as low tumor cellularity and the complex tumor microenvironment of PDAC hinder the confirmation of genomic features in the primary tumor and model systems. The occurrence of these phenomena and their associated complexities may lead to false insights into the understanding of mechanisms and dynamics in tumor tissues of patients. In this review, we describe various model systems and discuss differences in the results based on genomics and transcriptomics between primary tumors and model systems. Finally, we introduce practical strategies to improve the accuracy of genomic analysis of primary tissues and model systems.

An avian embryo patient-derived xenograft model for preclinical studies of human breast cancers

Lack of preclinical patient-derived xenograft cancer models in which to conduct large-scale molecular studies seriously impairs the development of effective personalized therapies. We report here an in vivo concept consisting of implanting human tumor cells in targeted tissues of an avian embryo, delivering therapeutics, evaluating their efficacy by measuring tumors using light sheet confocal microscopy, and conducting large-scale RNA-seq analysis to characterize therapeutic-induced changes in gene expression. The model was established to recapitulate triple-negative breast cancer (TNBC) and validated using TNBC standards of care and an investigational therapeutic agent.

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Human TNBC cells implanted in the avian embryo survive and efficiently form tumors

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Anti-tumoral therapies intravenously injected are assessed by 3D imaging

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Post-graft large-scale analyses allow studying the mechanism of action of drugs

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The AVI-PDX allows preclinical evaluation of therapies and patient stratification