Patient-Derived Xenograft Models of Breast Cancer and Their Application

Discovery and Characterization of a Chemical Probe for Cyclin-Dependent Kinase-Like 2

Acylaminoindazole-based inhibitors of CDKL2 were identified via analyses of cell-free binding and selectivity data. Compound 9 was selected as a CDKL2 chemical probe based on its potent inhibition of CDKL2 enzymatic activity, engagement of CDKL2 in cells, and excellent kinome-wide selectivity, especially when used in cells. Compound 16 was designed as a negative control to be used alongside compound 9 in experiments to interrogate CDKL2-mediated biology. A solved cocrystal structure of compound 9 bound to CDKL2 highlighted key interactions it makes within its ATP-binding site. Inhibition of downstream phosphorylation of EB2, a CDKL2 substrate, in rat primary neurons provided evidence that engagement of CDKL2 by compound 9 in cells resulted in inhibition of its activity. When used at relevant concentrations, compound 9 does not impact the viability of rat primary neurons or certain breast cancer cells nor elicit consistent changes in the expression of proteins involved in epithelial-mesenchymal transition.

Patient-Derived Organoids as Therapy Screening Platforms in Cancer Patients

Patient-derived organoids (PDOs) developed ex vivo and in vitro are increasingly used for therapeutic screening. They provide a more physiologically relevant model for drug discovery and development compared to traditional cell lines. However, several challenges remain to be addressed to fully realize the potential of PDOs in therapeutic screening. This paper summarizes recent advancements in PDO development and the enhancement of PDO culture models. This is achieved by leveraging materials engineering and microfabrication technologies, including organs-on-a-chip and droplet microfluidics. Additionally, this work discusses the application of PDOs in therapy screening to meet diverse requirements and overcome bottlenecks in cancer treatment. Furthermore, this work introduces tools for data processing and analysis of organoids, along with their microenvironment. These tools aim to achieve enhanced readouts. Finally, this work explores the challenges and future perspectives of using PDOs in drug development and personalized screening for cancer patients.

Recent advancements of hydrogels in immunotherapy: Breast cancer treatment

Breast cancer is the most prevalent cancer among women and the leading cause of cancer-related deaths in this population. Recent advances in Immunotherapy, or combined immunotherapy, offering a more targeted and less toxic approach, expand the survival rate of patients more than conventional treatment. Notably, hydrogels, a versatile platform provided promising avenues to combat breast cancer in preclinical studies and extended to clinical practices. With advantages such as the alternation of tumor microenvironment, immunomodulation, targeted delivery of therapeutic agents, and their sustained release at specific sites of interest, hydrogels can potentially be used for the treatment of breast cancer. This review highlights the advantages, mechanisms of action, stimuli-responsiveness properties, and recent advancements of hydrogels for treating breast cancer immunotherapy. Moreover, post-treatment and its clinical translations are discussed in this review. The integration of hydrogels in immunotherapy strategies may pave the way for more effective, personalized, and patient-friendly approaches to combat breast cancer, ultimately contributing to a brighter future for breast cancer patients.

Mutant RAS-driven Secretome Causes Skeletal Muscle Defects in Breast Cancer

Cancer-induced skeletal muscle defects differ in severity between individuals with the same cancer type. Cancer subtype-specific genomic aberrations are suggested to mediate these differences, but experimental validation studies are very limited. We utilized three different breast cancer patient-derived xenograft (PDX) models to correlate cancer subtype with skeletal muscle defects. PDXs were derived from brain metastasis of triple-negative breast cancer (TNBC), estrogen receptor-positive/progesterone receptor-positive (ER+/PR+) primary breast cancer from a BRCA2-mutation carrier, and pleural effusion from an ER+/PR- breast cancer. While impaired skeletal muscle function as measured through rotarod performance and reduced levels of circulating and/or skeletal muscle miR-486 were common across all three PDXs, only TNBC-derived PDX activated phospho-p38 in skeletal muscle. To further extend these results, we generated transformed variants of human primary breast epithelial cells from healthy donors using HRASG12V or PIK3CAH1047R mutant oncogenes. Mutations in RAS oncogene or its modulators are found in approximately 37% of metastatic breast cancers, which is often associated with skeletal muscle defects. Although cells transformed with both oncogenes generated adenocarcinomas in NSG mice, only HRASG12V-derived tumors caused skeletal muscle defects affecting rotarod performance, skeletal muscle contraction force, and miR-486, Pax7, pAKT, and p53 levels in skeletal muscle. Circulating levels of the chemokine CXCL1 were elevated only in animals with tumors containing HRASG12V mutation. Because RAS pathway aberrations are found in 19% of cancers, evaluating skeletal muscle defects in the context of genomic aberrations in cancers, particularly RAS pathway mutations, may accelerate development of therapeutic modalities to overcome cancer-induced systemic effects.

SIGNIFICANCE

Mutant RAS- and PIK3CA-driven breast cancers distinctly affect the function of skeletal muscle. Therefore, research and therapeutic targeting of cancer-induced systemic effects need to take aberrant cancer genome into consideration.

Discovery and Characterization of a Chemical Probe for Cyclin-Dependent Kinase-Like 2

Acylaminoindazole-based inhibitors of CDKL2 were identified via analyses of cell-free binding and selectivity data. Compound 9 was selected as a CDKL2 chemical probe based on its potent inhibition of CDKL2 enzymatic activity, engagement of CDKL2 in cells, and excellent kinome-wide selectivity, especially when used in cells. Compound 16 was designed as a negative control to be used alongside compound 9 in experiments to interrogate CDKL2-mediated biology. A solved co-crystal structure of compound 9 bound to CDKL2 highlighted key interactions it makes within its ATP-binding site. Inhibition of downstream phosphorylation of EB2, a CDKL2 substrate, in rat primary neurons provided evidence that engagement of CDKL2 by compound 9 in cells resulted in inhibition of its activity. When used at relevant concentrations, compound 9 does not impact the viability of rat primary neurons or certain breast cancer cells nor elicit consistent changes in the expression of proteins involved in epithelial-mesenchymal transition.

The combination of breast cancer PDO and mini-PDX platform for drug screening and individualized treatment

The majority of advanced breast cancers exhibit strong aggressiveness, heterogeneity, and drug resistance, and currently, the lack of effective treatment strategies is one of the main challenges that cancer research must face. Therefore, developing a feasible preclinical model to explore tailored treatments for refractory breast cancer is urgently needed. We established organoid biobanks from 17 patients with breast cancer and characterized them by immunohistochemistry (IHC) and next generation sequencing (NGS). In addition, we in the first combination of patient-derived organoids (PDOs) with mini-patient-derived xenografts (Mini-PDXs) for the rapid and precise screening of drug sensitivity. We confirmed that breast cancer organoids are a high-fidelity three-dimension (3D) model in vitro that recapitulates the original tumour's histological and genetic features. In addition, for a heavily pretreated patient with advanced drug-resistant breast cancer, we combined PDO and Mini-PDX models to identify potentially effective combinations of therapeutic agents for this patient who were alpelisib + fulvestrant. In the drug sensitivity experiment of organoids, we observed changes in the PI3K/AKT/mTOR signalling axis and oestrogen receptor (ER) protein expression levels, which further verified the reliability of the screening results. Our study demonstrates that the PDO combined with mini-PDX model offers a rapid and precise drug screening platform that holds promise for personalized medicine, improving patient outcomes and addressing the urgent need for effective therapies in advanced breast cancer.

Interrogating Estrogen Signaling Pathways in Human ER-Positive Breast Cancer Cells Forming Bone Metastases in Mice

Breast cancer bone metastases (BMET) are incurable, primarily osteolytic, and occur most commonly in estrogen receptor-α positive (ER+) breast cancer. ER+ human breast cancer BMET modeling in mice has demonstrated an estrogen (E2)-dependent increase in tumor-associated osteolysis and bone-resorbing osteoclasts, independent of estrogenic effects on tumor proliferation or bone turnover, suggesting a possible mechanistic link between tumoral ERα-driven osteolysis and ER+ bone progression. To explore this question, inducible secretion of the osteolytic factor, parathyroid hormone-related protein (PTHrP), was utilized as an in vitro screening bioassay to query the osteolytic potential of estrogen receptor- and signaling pathway-specific ligands in BMET-forming ER+ human breast cancer cells expressing ERα, ERß, and G protein-coupled ER. After identifying genomic ERα signaling, also responsibility for estrogen's proliferative effects, as necessary and sufficient for osteolytic PTHrP secretion, in vivo effects of a genomic-only ER agonist, estetrol (E4), on osteolytic ER+ BMET progression were examined. Surprisingly, while pharmacologic effects of E4 on estrogen-dependent tissues, including bone, were evident, E4 did not support osteolytic BMET progression (vs robust E2 effects), suggesting an important role for nongenomic ER signaling in ER+ metastatic progression at this site. Because bone effects of E4 did not completely recapitulate those of E2, the relative importance of nongenomic ER signaling in tumor vs bone cannot be ascertained here. Nonetheless, these intriguing findings suggest that targeted manipulation of estrogen signaling to mitigate ER+ metastatic progression in bone may require a nuanced approach, considering genomic and nongenomic effects of ER signaling on both sides of the tumor/bone interface.

Metabolic difference between patient-derived xenograft model of pancreatic ductal adenocarcinoma and corresponding primary tumor

BACKGROUND

Patients-derived xenograft (PDX) model have been widely used for tumor biological and pathological studies. However, the metabolic similarity of PDX tumor to the primary cancer (PC) is still unknown.

METHODS

In present study, we established PDX model by engrafting primary tumor of pancreatic ductal adenocarcinoma (PDAC), and then compared the tumor metabolomics of PC, the first generation of PDX tumor (PDXG1), and the third generation of PDX tumor (PDXG3) by using 1H NMR spectroscopy. Then, we assessed the differences in response to chemotherapy between PDXG1 and PDXG3 and corresponding metabolomic differences in drug-resistant tumor tissues. To evaluate the metabolomic similarity of PDX to PC, we also compared the metabolomic difference of cell-derived xenograft (CDX) vs. PC and PDX vs. PC.

RESULTS

After engraftment, PDXG1 tumor had a low level of lactate, pyruvate, citrate and multiple amino acids (AAs) compared with PC. Metabolite sets enrichment and metabolic pathway analyses implied that glycolysis metabolisms were suppressed in PDXG1 tumor, and tricarboxylic acid cycle (TCA)-associated anaplerosis pathways, such as amino acids metabolisms, were enhanced. Then, after multiple passages of PDX, the altered glycolysis and TCA-associated anaplerosis pathways were partially recovered. Although no significant difference was observed in the response of PDXG1 and PDXG3 to chemotherapy, the difference in glycolysis and amino acids metabolism between PDXG1 and PDXG3 could still be maintained. In addition, the metabolomic difference between PC and CDX models were much larger than that of PDX model and PC, indicating that PDX model still retain more metabolic characteristics of primary tumor which is more suitable for tumor-associated metabolism research.

CONCLUSIONS

Compared with primary tumor, PDX models have obvious difference in metabolomic level. These findings can help us design in vivo tumor metabolomics research legitimately and analyze the underlying mechanism of tumor metabolic biology thoughtfully.

Current views on in vivo models for breast cancer research and related drug development

INTRODUCTION

Animal models play a crucial role in breast cancer research, in particular mice and rats, who develop mammary tumors that closely resemble their human counterparts. These models allow the study of mechanisms behind breast carcinogenesis, as well as the efficacy and safety of new, and potentially more effective and advantageous therapeutic approaches. Understanding the advantages and disadvantages of each model is crucial to select the most appropriate one for the research purpose.

AREA COVERED

This review provides a concise overview of the animal models available for breast cancer research, discussing the advantages and disadvantages of each one for searching new and more effective approaches to treatments for this type of cancer.

EXPERT OPINION

Rodent models provide valuable information on the genetic alterations of the disease, the tumor microenvironment, and allow the evaluation of the efficacy of chemotherapeutic agents. However, in vivo models have limitations, and one of them is the fact that they do not fully mimic human diseases. Choosing the most suitable model for the study purpose is crucial for the development of new therapeutic agents that provide better care for breast cancer patients.

Biomarkers and experimental models for cancer immunology investigation

The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

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

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

ABCB1 Regulates Immune Genes in Breast Cancer

Background

Resistance to standard chemotherapy is a critical problem for breast cancer patients. The ATP-binding cassette (ABC) superfamily transporters actively pump out drugs and play an important role in chemoresistance. ABCB1 (ABC subfamily B, member 1, also named as multidrug resistance protein 1, MDR1) and suppressive myeloid-derived suppressor cells (MDSCs) potentially involve in chemoresistance of breast cancer. The relationship between ABCB1 and immune genes in breast cancer has not been widely studied.

Methods

Microarray and RNA sequencing data were obtained from The Cancer Genome Atlas Breast Invasive Carcinoma in Genomic Data Commons Data Portal and Gene Expression Omnibus database. A patient-derived xenograft (PDX) model of HER2+ breast cancer was established to investigate the association between ABCB1 and immune genes in breast cancer.

Results

Expression of ABCB1 increased in doxorubicin-selected MCF-7/ADR cells. High expression of ABCB1 mRNA is correlated with lymph-node metastasis and worse overall survival in patients with breast cancer. ABCB1 is positively correlated with IL6, CSF1, CSF3, and PTGS2. In the HER2+ stage IIA breast cancer PDX model, both doxorubicin and paclitaxel suppressed growth of P2 tumors. IL6, CSF1, CSF3, and PTGS2 expression were suppressed by paclitaxel but not doxorubicin. Intrasplenic MDSCs, including CD11b+Ly6G+ and CD11b+Ly6C+ cells, were more abundant than intratumor MDSCs in PDX-carrying nude mice. Clinically, the patient developed cancer recurrence after adjuvant chemotherapy with doxorubicin-based regimen and was well controlled after paclitaxel-trastuzumab combined therapy.

Conclusion

ABCB1 was a poor predictor of HER2+ LN- breast cancer. Regulation of immune genes by ABCB1 contributed to cancer recurrence and treatment effect. The PDX model was suitable for investigation the expression of target genes and expansion of immune cells.

Unlocking the potential of the tumor microenvironment for cancer therapy

The tumor microenvironment (TME) holds a crucial role in the progression of cancer. Epithelial-derived tumors share common traits in shaping the TME. The Warburg effect is a notable phenomenon wherein tumor cells exhibit resistance to apoptosis and an increased reliance on anaerobic glycolysis for energy production. Recognizing the pivotal role of the TME in controlling tumor growth and influencing responses to chemotherapy, researchers have focused on developing potential cancer treatment strategies. A wide array of therapies, including immunotherapies, antiangiogenic agents, interventions targeting cancer-associated fibroblasts (CAF), and therapies directed at the extracellular matrix, have been under investigation and have demonstrated efficacy. Additionally, innovative techniques such as tumor tissue explants, "tumor-on-a-chip" models, and multicellular tumor spheres have been explored in laboratory research. This comprehensive review aims to provide insights into the intricate cross-talk between cancer-associated signaling pathways and the TME in cancer progression, current therapeutic approaches targeting the TME, the immune landscape within solid tumors, the role of the viral TME, and cancer cell metabolism.

Engineering liquid metal-based nanozyme for enhancing microwave dynamic therapy in breast cancer PDX model

BACKGROUNDS

The novel concept of microwave dynamic therapy (MDT) solves the problem of incomplete tumor eradication caused by non-selective heating and uneven temperature distribution of microwave thermal therapy (MWTT) in clinic, but the poor delivery of microwave sensitizer and the obstacle of tumor hypoxic microenvironment limit the effectiveness of MDT.

RESULTS

Herein, we engineer a liquid metal-based nanozyme LM@ZIF@HA (LZH) with eutectic Gallium Indium (EGaIn) as the core, which is coated with CoNi-bimetallic zeolite imidazole framework (ZIF) and hyaluronic acid (HA). The flexibility of the liquid metal and the targeting of HA enable the nanozyme to be effectively endocytosed by tumor cells, solving the problem of poor delivery of microwave sensitizers. Due to the catalase-like activity, the nanozyme catalyze excess H2O2 in the tumor microenvironment to generate O2, alleviating the restriction of the tumor hypoxic microenvironment and promoting the production of ROS under microwave irradiation. In vitro cell experiments, the nanozyme has remarkable targeting effect, oxygen production capacity, and microwave dynamic effect, which effectively solves the defects of MDT. In the constructed patient-derived xenograft (PDX) model, the nanozyme achieves excellent MDT effect, despite the heterogeneity and complexity of the tumor model that is similar to the histological and pathological features of the patient. The tumor volume in the LZH + MW group is only about 1/20 of that in the control group, and the tumor inhibition rate is as high as 95%.

CONCLUSION

The synthesized nanozyme effectively solves the defects of MDT, improves the targeted delivery of microwave sensitizers while regulating the hypoxic microenvironment of tumors, and achieves excellent MDT effect in the constructed PDX model, providing a new strategy for clinical cancer treatment.

Breast Cancer Tissue Explants: An Approach to Develop Personalized Therapy in Public Health Services

Breast cancer is one of the main causes of death worldwide. Lately, there is great interest in developing methods that assess individual sensitivity and/or resistance of tumors to antineoplastics to provide personalized therapy for patients. In this study we used organotypic culture of human breast tumor slices to predict the experimental effect of antineoplastics on the viability of tumoral tissue. Samples of breast tumor were taken from 27 patients with clinically advanced breast cancer; slices were obtained and incubated separately for 48 h with paclitaxel, docetaxel, epirubicin, 5-fluorouracil, cyclophosphamide, and cell culture media (control). We determined an experimental tumor sensitivity/resistance (S/R) profile by evaluating tissue viability using the Alamar Blue® metabolic test, and by structural viability (histopathological analyses, necrosis, and inflammation). These parameters were related to immunohistochemical expression of the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. The predominant histological type found was infiltrating ductal carcinoma (85.2%), followed by lobular carcinoma (7.4%) and mixed carcinoma (7.4%). Experimental drug resistance was related to positive hormone receptor status in 83% of samples treated with cyclophosphamide (p = 0.027). Results suggest that the tumor S/R profile can help to predict personalized therapy or optimize chemotherapeutic treatments in breast cancer.

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

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

Cancer Models on Chip: Paving the Way to Large-Scale Trial Applications

Cancer kills millions of individuals every year all over the world (Global Cancer Observatory). The physiological and biomechanical processes underlying the tumor are still poorly understood, hindering researchers from creating new, effective therapies. Inconsistent results of preclinical research, in vivo testing, and clinical trials decrease drug approval rates. 3D tumor-on-a-chip (ToC) models integrate biomaterials, tissue engineering, fabrication of microarchitectures, and sensory and actuation systems in a single device, enabling reliable studies in fundamental oncology and pharmacology. This review includes a critical discussion about their ability to reproduce the tumor microenvironment (TME), the advantages and drawbacks of existing tumor models and architectures, major components and fabrication techniques. The focus is on current materials and micro/nanofabrication techniques used to manufacture reliable and reproducible microfluidic ToC models for large-scale trial applications.

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.

Inhibiting PRMT5 induces DNA damage and increases anti-proliferative activity of Niraparib, a PARP inhibitor, in models of breast and ovarian cancer

BACKGROUND

Inhibitors of Poly (ADP-Ribose) Polymerases (PARP) provide clinical benefit to patients with breast and ovarian cancers, by compromising the DNA repair activity of cancer cells. Although these agents extend progression-free survival in many patients, responses can be short lived with many patients ultimately progressing. Identification of combination partners that increase dependence of cancer cells to the DNA repair activity of PARPs may represent a strategy to increase the utility of PARP inhibitors. Protein arginine methyltransferase 5 (PRMT5) regulates DNA damage response pathways through splicing and protein modification, and inhibitors of PRMT5 have recently entered clinical trials.

METHODS

The effect of PRMT5 inhibition on the levels of DNA damage and repair markers including γH2AX, RAD51, and 53BP1 was determined using high content immunofluorescent imaging. The anti-proliferative activity of the combination of PRMT5 and PARP inhibitors was evaluated using in vitro models of breast and ovarian cancers using both cell lines and ex vivo patient derived xenografts. Finally, the combinations of PRMT5 and PARP inhibitors were evaluated in cell line xenograft models in vivo.

RESULTS

Inhibition of PRMT5 by GSK3326595 led to increased levels of markers of DNA damage. The addition of GSK3326595 to the PARP inhibitor, niraparib, resulted in increased growth inhibition of breast and ovarian cancer cell lines and patient derived spheroids. In vivo, the combination improved the partial effects on tumor growth inhibition achieved by either single agent, producing complete tumor stasis and regression.

CONCLUSION

These data demonstrate that inhibition of PRMT5 induced signatures of DNA damage in models of breast and ovarian cancer. Furthermore, combination with the PARP inhibitor, Niraparib, resulted in increased anti-tumor activity in vitro and in vivo. Overall, these data suggest inhibition of PRMT5 as a mechanism to broaden and enhance the clinical application of PARP inhibitors.

Deciphering Common Traits of Breast and Ovarian Cancer Stem Cells and Possible Therapeutic Approaches

Breast cancer (BC) and ovarian cancer (OC) are among the most common and deadly cancers affecting women worldwide. Both are complex diseases with marked heterogeneity. Despite the induction of screening programs that increase the frequency of earlier diagnosis of BC, at a stage when the cancer is more likely to respond to therapy, which does not exist for OC, more than 50% of both cancers are diagnosed at an advanced stage. Initial therapy can put the cancer into remission. However, recurrences occur frequently in both BC and OC, which are highly cancer-subtype dependent. Therapy resistance is mainly attributed to a rare subpopulation of cells, named cancer stem cells (CSC) or tumor-initiating cells, as they are capable of self-renewal, tumor initiation, and regrowth of tumor bulk. In this review, we will discuss the distinctive markers and signaling pathways that characterize CSC, their interactions with the tumor microenvironment, and the strategies they employ to evade immune surveillance. Our focus will be on identifying the common features of breast cancer stem cells (BCSC) and ovarian cancer stem cells (OCSC) and suggesting potential therapeutic approaches.

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.

Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective

Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer makes finding a research model that mirrors the disparate intrinsic features challenging. With advances in multi-omics technologies, establishing parallels between the various models and human tumors is increasingly intricate. Here we review the various model systems and their relation to primary breast tumors using available omics data platforms. Among the research models reviewed here, breast cancer cell lines have the least resemblance to human tumors since they have accumulated many mutations and copy number alterations during their long use. Moreover, individual proteomic and metabolomic profiles do not overlap with the molecular landscape of breast cancer. Interestingly, omics analysis revealed that the initial subtype classification of some breast cancer cell lines was inappropriate. In cell lines the major subtypes are all well represented and share some features with primary tumors. In contrast, patient-derived xenografts (PDX) and patient-derived organoids (PDO) are superior in mirroring human breast cancers at many levels, making them suitable models for drug screening and molecular analysis. While patient derived organoids are spread across luminal, basal- and normal-like subtypes, the PDX samples were initially largely basal but other subtypes have been increasingly described. Murine models offer heterogenous tumor landscapes, inter and intra-model heterogeneity, and give rise to tumors of different phenotypes and histology. Murine models have a reduced mutational burden compared to human breast cancer but share some transcriptomic resemblance, and representation of many breast cancer subtypes can be found among the variety subtypes. To date, while mammospheres and three- dimensional cultures lack comprehensive omics data, these are excellent models for the study of stem cells, cell fate decision and differentiation, and have also been used for drug screening. Therefore, this review explores the molecular landscapes and characterization of breast cancer research models by comparing recent published multi-omics data and analysis.

Recent Advancement in Breast Cancer Research: Insights from Model Organisms-Mouse Models to Zebrafish

Animal models have been utilized for decades to investigate the causes of human diseases and provide platforms for testing novel therapies. Indeed, breakthrough advances in genetically engineered mouse (GEM) models and xenograft transplantation technologies have dramatically benefited in elucidating the mechanisms underlying the pathogenesis of multiple diseases, including cancer. The currently available GEM models have been employed to assess specific genetic changes that underlay many features of carcinogenesis, including variations in tumor cell proliferation, apoptosis, invasion, metastasis, angiogenesis, and drug resistance. In addition, mice models render it easier to locate tumor biomarkers for the recognition, prognosis, and surveillance of cancer progression and recurrence. Furthermore, the patient-derived xenograft (PDX) model, which involves the direct surgical transfer of fresh human tumor samples to immunodeficient mice, has contributed significantly to advancing the field of drug discovery and therapeutics. Here, we provide a synopsis of mouse and zebrafish models used in cancer research as well as an interdisciplinary 'Team Medicine' approach that has not only accelerated our understanding of varied aspects of carcinogenesis but has also been instrumental in developing novel therapeutic strategies.

Patient-derived models: Promising tools for accelerating the clinical translation of breast cancer research findings

Breast cancer has become the highest incidence of cancer in women. It was extensively and deeply studied by biologists and medical workers worldwide. However, the meaningful results in lab researches cannot be realized in clinical, and a part of new drugs in clinical experiments do not obtain as good results as the preclinical researches. It is urgently that promote a kind of breast cancer research models that can get study results closer to the physiological condition of the human body. Patient-derived models (PDMs) originating from clinical tumor, contain primary elements of tumor and maintain key clinical features of tumor. So they are promising research models to facilitate laboratory researches translate to clinical application, and predict the treatment outcome of patients. In this review, we summarize the establishment of PDMs of breast cancer, reviewed the application of PDMs in clinical translational researches and personalized precision medicine with breast cancer as an example, to improve the understanding of PDMs among researchers and clinician, facilitate them to use PDMs on a large scale of breast cancer researches and promote the clinical translation of laboratory research and new drug development.

Experimental mouse models for translational human cancer research

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

Discovering Synergistic Compounds with BYL-719 in PI3K Overactivated Basal-like PDXs

Basal-like triple-negative breast cancer (TNBC) tumor cells are difficult to eliminate due to resistance mechanisms that promote survival. While this breast cancer subtype has low PIK3CA mutation rates when compared to estrogen receptor-positive (ER+) breast cancers, most basal-like TNBCs have an overactive PI3K pathway due to gene amplification or high gene expression. BYL-719 is a PIK3CA inhibitor that has been found to have low drug-drug interactions, which increases the likelihood that it could be useful for combinatorial therapy. Alpelisib (BYL-719) with fulvestrant was recently approved for treating ER+ breast cancer patients whose cancer had developed resistance to ER-targeting therapy. In these studies, a set of basal-like patient-derived xenograft (PDX) models was transcriptionally defined with bulk and single-cell RNA-sequencing and clinically actionable mutation profiles defined with Oncomine mutational profiling. This information was overlaid onto therapeutic drug screening results. BYL-719-based, synergistic two-drug combinations were identified with 20 different compounds, including everolimus, afatinib, and dronedarone, which were also found to be effective at minimizing tumor growth. These data support the use of these drug combinations towards cancers with activating PIK3CA mutations/gene amplifications or PTEN deficient/PI3K overactive pathways.

Quantitative characterization of cell physiological state based on dynamical cell mechanics for drug efficacy indication

Cell mechanics is essential to cell development and function, and its dynamics evolution reflects the physiological state of cells. Here, we investigate the dynamical mechanical properties of single cells under various drug conditions, and present two mathematical approaches to quantitatively characterizing the cell physiological state. It is demonstrated that the cellular mechanical properties upon the drug action increase over time and tend to saturate, and can be mathematically characterized by a linear time-invariant dynamical model. It is shown that the transition matrices of dynamical cell systems significantly improve the classification accuracies of the cells under different drug actions. Furthermore, it is revealed that there exists a positive linear correlation between the cytoskeleton density and the cellular mechanical properties, and the physiological state of a cell in terms of its cytoskeleton density can be predicted from its mechanical properties by a linear regression model. This study builds a relationship between the cellular mechanical properties and the cellular physiological state, adding information for evaluating drug efficacy.

Modelling cutaneous squamous cell carcinoma for laboratory research

Cutaneous squamous cell carcinoma (cSCC) leads to significant morbidity for patients with progression and metastases. However, the molecular underpinnings of these tumors are still poorly understood. Dissecting human cSCC pathogenesis amplifies the exigence for preclinical models that mimic invasion and nodal spread. This review discusses the currently available models, including two- and three-dimensional tissue cultures, syngeneic and transgenic mice, and cell line-derived and patient-derived xenografts. We further highlight studies that have utilized the different models, considering how they recapitulate specific hallmarks of cSCC. Finally, we discuss the advantages, limitations and future research directions.

Ultrasmall Folate Receptor Alpha Targeted Enzymatically Cleavable Silica Nanoparticle Drug Conjugates Augment Penetration and Therapeutic Efficacy in Models of Cancer

To address the key challenges in the development of next-generation drug delivery systems (DDS) with desired physicochemical properties to overcome limitations regarding safety, in vivo efficacy, and solid tumor penetration, an ultrasmall folate receptor alpha (FRα) targeted silica nanoparticle (C'Dot) drug conjugate (CDC; or folic acid CDC) was developed. A broad array of methods was employed to screen a panel of CDCs and identify a lead folic acid CDC for clinical development. These included comparing the performance against antibody-drug conjugates (ADCs) in three-dimensional tumor spheroid penetration ability, assessing in vitro/ex vivo cytotoxic efficacy, as well as in vivo therapeutic outcome in multiple cell-line-derived and patient-derived xenograft models. An ultrasmall folic acid CDC, EC112002, was identified as the lead candidate out of >500 folic acid CDC formulations evaluated. Systematic studies demonstrated that the lead formulation, EC112002, exhibited highly specific FRα targeting, multivalent binding properties that would mediate the ability to outcompete endogenous folate in vivo, enzymatic responsive payload cleavage, stability in human plasma, rapid in vivo clearance, and minimal normal organ retention organ distribution in non-tumor-bearing mice. When compared with an anti-FRα-DM4 ADC, EC112002 demonstrated deeper penetration into 3D cell-line-derived tumor spheroids and superior specific cytotoxicity in a panel of 3D patient-derived tumor spheroids, as well as enhanced efficacy in cell-line-derived and patient-derived in vivo tumor xenograft models expressing a range of low to high levels of FRα. With the growing interest in developing clinically translatable, safe, and efficacious DDSs, EC112002 has the potential to address some of the critical limitations of the current systemic drug delivery for cancer management.

Optimizing Drug Response Study Design in Patient-Derived Tumor Xenografts

Patient-derived tumor xenograft (PDX) models were used to evaluate the effectiveness of preclinical anticancer agents. A design using 1 mouse per patient per drug (1 × 1 × 1) was considered practical for large-scale drug efficacy studies. We evaluated modifiable parameters that could increase the statistical power of this design based on our consolidated PDX experiments. Real studies were used as a reference to investigate the relationship between statistical power with treatment effect size, inter-mouse variation, and tumor measurement frequencies. Our results showed that large effect sizes could be detected at a significance level of .2 or .05 under a 1 × 1 × 1 design. We found that the minimum number of mice required to achieve 80% power at an alpha level of .05 under all situations explored was 21 mice per group for a small effect size and 5 mice per group for a medium effect size.

A hitchhiker's guide to cancer models

Cancer is a complex and uniquely personal disease. More than 1.7 million people in the United States are diagnosed with cancer every year. As the burden of cancer grows, so does the need for new, more effective therapeutics and for predictive tools to identify optimal, personalized treatment options for every patient. Cancer models that recapitulate various aspects of the disease are fundamental to making advances along the continuum of cancer treatment from benchside discoveries to bedside delivery. In this review, we use a thought experiment as a vehicle to arrive at four broad categories of cancer models and explore the strengths, weaknesses, opportunities, and threats for each category in advancing our understanding of the disease and improving treatment strategies.

Patient-derived primary breast cancer cells and their potential for predicting sensitivity to chemotherapy

Chemotherapy resistance exposes patients to side effects and delays the effect of therapy in patients. So far, there are no predictive tools to predict resistance to chemotherapy and select sensitive chemotherapeutic drugs for the patient. Here, we aim to develop an in-vitro primary cell culture model from breast cancer patients to predict sensitivity to chemotherapy. We created the primary breast cancer cell medium BCMI and culture system with higher efficiency of the model establishment. Immunofluorescence staining of ERa, PR and HER2 were done to identify the primary breast cancer cell from the counterpart breast cancer patient. The killing assay showed that these primary breast cancer cells responded differently to doxorubicin and pirarubicin treatment. These results indicate that our established primary breast cancer cell model holds great promise for predicting breast cancer sensitivity to chemotherapy drugs.

A comparative study of tumour-on-chip models with patient-derived xenografts for predicting chemotherapy efficacy in colorectal cancer patients

Inter-patient and intra-tumour heterogeneity (ITH) have prompted the need for a more personalised approach to cancer therapy. Although patient-derived xenograft (PDX) models can generate drug response specific to patients, they are not sustainable in terms of cost and time and have limited scalability. Tumour Organ-on-Chip (OoC) models are in vitro alternatives that can recapitulate some aspects of the 3D tumour microenvironment and can be scaled up for drug screening. While many tumour OoC systems have been developed to date, there have been limited validation studies to ascertain whether drug responses obtained from tumour OoCs are comparable to those predicted from patient-derived xenograft (PDX) models. In this study, we established a multiplexed tumour OoC device, that consists of an 8 × 4 array (32-plex) of culture chamber coupled to a concentration gradient generator. The device enabled perfusion culture of primary PDX-derived tumour spheroids to obtain dose-dependent response of 5 distinct standard-of-care (SOC) chemotherapeutic drugs for 3 colorectal cancer (CRC) patients. The in vitro efficacies of the chemotherapeutic drugs were rank-ordered for individual patients and compared to the in vivo efficacy obtained from matched PDX models. We show that quantitative correlation analysis between the drug efficacies predicted via the microfluidic perfusion culture is predictive of response in animal PDX models. This is a first study showing a comparative framework to quantitatively correlate the drug response predictions made by a microfluidic tumour organ-on-chip (OoC) model with that of PDX animal models.

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.

Drosophila melanogaster: A platform for anticancer drug discovery and personalized therapies

Cancer is a complex disease whereby multiple genetic aberrations, epigenetic modifications, metabolic reprogramming, and the microenvironment contribute to the development of a tumor. In the traditional anticancer drug discovery pipeline, drug candidates are usually screened in vitro using two-dimensional or three-dimensional cell culture. However, these methods fail to accurately mimic the human disease state. This has led to the poor success rate of anticancer drugs in the preclinical stages since many drugs are abandoned due to inefficacy or toxicity when transitioned to whole-organism models. The common fruit fly, Drosophila melanogaster, has emerged as a beneficial system for modeling human cancers. Decades of fundamental research have shown the evolutionary conservation of key genes and signaling pathways between flies and humans. Moreover, Drosophila has a lower genetic redundancy in comparison to mammals. These factors, in addition to the advancement of genetic toolkits for manipulating gene expression, allow for the generation of complex Drosophila genotypes and phenotypes. Numerous studies have successfully created Drosophila models for colorectal, lung, thyroid, and brain cancers. These models were utilized in the high-throughput screening of FDA-approved drugs which led to the identification of several compounds capable of reducing proliferation and rescuing phenotypes. More noteworthy, Drosophila has also unlocked the potential for personalized therapies. Drosophila ‘avatars’ presenting the same mutations as a patient are used to screen multiple therapeutic agents targeting multiple pathways to find the most appropriate combination of drugs. The outcomes of these studies have translated to significant responses in patients with adenoid cystic carcinoma and metastatic colorectal cancers. Despite not being widely utilized, the concept of in vivo screening of drugs in Drosophila is making significant contributions to the current drug discovery pipeline. In this review, we discuss the application of Drosophila as a platform in anticancer drug discovery; with special focus on the cancer models that have been generated, drug libraries that have been screened and the status of personalized therapies. In addition, we elaborate on the biological and technical limitations of this system.

Racial disparities in breast cancer preclinical and clinical models

Breast cancer (BCa) has long been a health burden to women across the globe. However, the burden is not equally carried across races. Though the manifestation and behavior of BCa differs among racial groups, the racial representation of models used in preclinical trials and clinical trial participants lacks this heterogeneity. Women of African Ancestry (WAA) are disproportionately afflicted by having an increased risk of developing BCas that are more aggressive in nature, and consequently suffer from poorer outcomes relative to women of European ancestry (WEA). Notwithstanding this, one of the most commonly used tools in studying BCa, cell lines, exhibit a sizeable gap in cell line derivatives of WEA relative to WAA. In this review, we summarize the available BCa cell lines grouped by race by major suppliers, American Type Culture Collection (ATCC) and the European Collection of Authenticated Cell Cultures (ECACC). Next, examined the enrollment of WAA in clinical trials for BCa. Of the cell lines found provided by ATCC and ECACC, those derived from WEA constituted approximately 80% and 94%, respectively. The disparity is mirrored in clinical trial enrollment where, on average, WEA made up more than 70% of participants in trials found where ancestry information was provided. As both experimental models and clinical trial participants primarily consist of WEA, results may have poorer translatability toward other races. This highlights the need for greater racial diversity at the preclinical and clinical levels to more accurately represent the population and strengthen the translatability of results.

In vitro models for head and neck cancer: Current status and future perspective

The 5-year overall survival rate remains approximately 50% for head and neck (H&N) cancer patients, even though new cancer drugs have been approved for clinical use since 2016. Cancer drug studies are now moving toward the use of three-dimensional culture models for better emulating the unique tumor microenvironment (TME) and better predicting in vivo response to cancer treatments. Distinctive TME features, such as tumor geometry, heterogenous cellularity, and hypoxic cues, notably affect tissue aggressiveness and drug resistance. However, these features have not been fully incorporated into in vitro H&N cancer models. This review paper aims to provide a scholarly assessment of the designs, contributions, and limitations of in vitro models in H&N cancer drug research. We first review the TME features of H&N cancer that are most relevant to in vitro drug evaluation. We then evaluate a selection of advanced culture models, namely, spheroids, organotypic models, and microfluidic chips, in their applications for H&N cancer drug research. Lastly, we propose future opportunities of in vitro H&N cancer research in the prospects of high-throughput drug screening and patient-specific drug evaluation.

Challenges and opportunities in metastatic breast cancer treatments: Nano-drug combinations delivered preferentially to metastatic cells may enhance therapeutic response

Despite advances in breast cancer treatments and related 5-year survival outcomes, metastatic breast cancer cures remain elusive. The current standard of care includes a combination of surgery, radiation therapy and drug therapy. However, even the most advanced procedures and treatments do not prevent breast cancer recurrence and metastasis. Once metastasis occurs, patient prognosis is poor. Recent elucidation of the spatiotemporal transit of metastatic cancer cells from primary tumor sites to distant sites provide an opportunity to integrate knowledge of drug disposition in our effort to enhance drug localization and exposure in cancer laden tissues . Novel technologies have been developed, but could be further refined to facilitate the distribution of drugs to target cancer cells and tissues. The purpose of this review is to highlight the challenges in metastatic breast cancer treatment and focus on novel drug combination and nanotechnology approaches to overcome the challenges. With improved definition of metastatic tissue target, directed localization and retention of multiple, pharmacologically active drugs to tissues and cells of interest may overcome the limitations in breast cancer treatment that may lead to a cure for breast cancer.

Living biobank-based cancer organoids: prospects and challenges in cancer research

Biobanks bridge the gap between basic and translational research. Traditional cancer biobanks typically contain normal and tumor tissues, and matched blood. However, biospecimens in traditional biobanks are usually nonrenewable. In recent years, increased interest has focused on establishing living biobanks, including organoid biobanks, for the collection and storage of viable and functional tissues for long periods of time. The organoid model is based on a 3D in vitro cell culture system, is highly similar to primary tissues and organs in vivo, and can recapitulate the phenotypic and genetic characteristics of target organs. Publications on cancer organoids have recently increased, and many types of cancer organoids have been used for modeling cancer processes, as well as for drug discovery and screening. On the basis of the current research status, more exploration of cancer organoids through technical advancements is required to improve reproducibility and scalability. Moreover, given the natural characteristics of organoids, greater attention must be paid to ethical considerations. Here, we summarize recent advances in cancer organoid biobanking research, encompassing rectal, gastric, pancreatic, breast, and glioblastoma cancers. Living cancer biobanks that contain cancerous tissues and matched organoids with different genetic backgrounds, subtypes, and individualized characteristics will eventually contribute to the understanding of cancer and ultimately facilitate the development of innovative treatments.

Engineered colorectal cancer tissue recapitulates key attributes of a patient-derived xenograft tumor line

The development of physiologically relevantin vitrocolorectal cancer (CRC) models is vital for advancing understanding of tumor biology. Although CRC patient-derived xenografts (PDXs) recapitulate key patient tumor characteristics and demonstrate high concordance with clinical outcomes, the use of thisin vivomodel is costly and low-throughput. Here we report the establishment and in-depth characterization of anin vitrotissue-engineered CRC model using PDX cells. To form the 3D engineered CRC-PDX (3D-eCRC-PDX) tissues, CRC PDX tumors were expandedin vivo, dissociated, and the isolated cells encapsulated within PEG-fibrinogen hydrogels. Following PEG-fibrinogen encapsulation, cells remain viable and proliferate within 3D-eCRC-PDX tissues. Tumor cell subpopulations, including human cancer and mouse stromal cells, are maintained in long-term culture (29 days); cellular subpopulations increase ratiometrically over time. The 3D-eCRC-PDX tissues mimic the mechanical stiffness of originating tumors. Extracellular matrix protein production by cells in the 3D-eCRC-PDX tissues resulted in approximately 57% of proteins observed in the CRC-PDX tumors also being present in the 3D-eCRC-PDX tissues on day 22. Furthermore, we show congruence in enriched gene ontology molecular functions and Hallmark gene sets in 3D-eCRC-PDX tissues and CRC-PDX tumors compared to normal colon tissue, while prognostic Kaplan-Meier plots for overall and relapse free survival did not reveal significant differences between CRC-PDX tumors and 3D-eCRC-PDX tissues. Our results demonstrate high batch-to-batch consistency and strong correlation between ourin vitrotissue-engineered PDX-CRC model and the originatingin vivoPDX tumors, providing a foundation for future studies of disease progression and tumorigenic mechanisms.

Palbociclib in combination with sunitinib exerts a synergistic anti-cancer effect in patient-derived xenograft models of various human cancers types

The efficacy/safety of combining palbociclib (a CDK4/6 inhibitor) and sunitinib (a multi-targeted receptor tyrosine kinase inhibitor) was evaluated, using patient-derived xenograft (PDX) models. Twenty-three PDX mice models were developed from patients with various solid tumors. The mice were randomized to 4 groups (5-6 mice in each): control/palbociclib (100 mg/kg)/sunitinib (50 mg/kg)/combination. Drugs were administered orally, 5 days/week. In 17/23 PDX models (74%), the combination demonstrated a synergistic inhibitory effect vs the monotherapies ("responder" models) with no unexpected toxicities. In 13/17 responder models, where standard-of-care (SOC) was an additional comparator, the combination was more effective than SOC in 7 models, as effective in 4, and less effective in 2. The mean ± SEM experiment duration in 15/17 responder models (2/17 were excluded due to technical issues) was 86 ± 12 and 31 ± 5 days for the combination and control groups, respectively (p = 0.0002). The effect of the combination was dose-dependent. Cell-viability experiments in A549/MDA-MB-231/HT-29 cell lines and experiments using tumor-derived primary cell spheroids supported the PDX findings. In conclusion, combination of palbociclib and sunitinib exerts a synergistic anti-tumor effect without adding unexpected toxicity. A clinical trial assessing this combination is underway.

Emerging drug targets for triple-negative breast cancer: A guided tour of the preclinical landscape

INTRODUCTION

Triple-negative breast cancer (TNBC) is the most fatal molecular subtype of breast cancer because of its aggressiveness and resistance to chemotherapy. FDA-approved therapies for TNBC are limited to poly(ADP-ribose) polymerase inhibitors, immune checkpoint inhibitors, and trophoblast cell surface antigen 2-targeted antibody-drug conjugate. Therefore, developing a novel effective targeted therapy for TNBC is an urgent unmet need.

AREAS COVERED

In this narrative review, we discuss emerging targets for TNBC treatment discovered in early translational studies. We focus on cancer cell membrane molecules, hyperactive intracellular signaling pathways, and the tumor microenvironment (TME) based on their druggability, therapeutic potency, specificity to TNBC, and application in immunotherapy.

EXPERT OPINION

The significant challenges in the identification and validation of TNBC-associated targets are 1) application of appropriate genetic, molecular, and immunological approaches for modulating the target, 2) establishment of a proper mouse model that accurately represents the human immune TME, 3) TNBC molecular heterogeneity, and 4) failure translation of preclinical findings to clinical practice. To overcome those difficulties, future research needs to apply novel technology, such as single-cell RNA sequencing, thermostable group II intron reverse transcriptase sequencing, and humanized mouse models. Further, combination treatment targeting multiple pathways in both the TNBC tumor and its TME is essential for effective disease control.

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

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

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

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

Three-Dimensional Silk Fibroin/Chitosan Based Microscaffold for Anticancer Drug Screening

Traditional monolayer cell cultures often fail to accurately predict the anticancer activity of drug candidates, as they do not recapitulate the natural microenvironment. Recently, three-dimensional (3D) culture systems have been increasingly applied to cancer research and drug screening. Materials with good biocompatibility are crucial to create a 3D tumor microenvironment involved in such systems. In this study, natural silk fibroin (SF) and chitosan (CS) were selected as the raw materials to fabricate 3D microscaffolds; Besides, sodium tripolyphosphate (TPP), and 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) were used as cross-linking agents. The physicochemical properties of obtained scaffolds were characterized with kinds of testing methods, including emission scanning electron microscopy, x-ray photoelectron spectroscopy, fourier transform infrared spectroscopy, water absorption, and swelling ratio analysis. Cancer cell lines (LoVo and MDA-MB-231) were then seeded on scaffolds for biocompatibility examination and drug sensitivity tests. SEM results showed that EDC cross-linked scaffolds had smaller and more uniform pores with great interconnection than the TPP cross-linked scaffolds, and the EDC cross-linked scaffold exhibited a water absorption ratio around 1000% and a swelling ratio of about 72%. These spatial structures and physical properties could provide more adhesion sites and sufficient nutrients for cell growth. Moreover, both LoVo and MDA-MB-231 cells cultured on the EDC cross-linked scaffold exhibited good adhesion and spreading. CCK8 results showed that increased chemotherapeutic drug sensitivity was observed in 3D culture compared with 2D culture, particularly in the condition of low drug dose (<1  μ M). The proposed SF/CS microscaffold can provide a promising in vitro platform for the efficacy prediction and sensitivity screening of anticancer drugs.

A Three-Dimensional Organoid Model of Primary Breast Cancer to Investigate the Effects of Oncolytic Virotherapy

Background: Although several oncolytic viruses have already been tested in early-stage clinical studies of breast cancer, there is still an urgent need to develop patient-derived experimental systems that mimic the response of breast cancer to oncolytic agents in preparation of testing different oncolytic viruses in clinical trials. We addressed this need by developing a protocol to study the effects of oncolytic viruses in stable organoid cell cultures derived from breast cancer tissue.

Methods: We used an established three-dimensional organoid model derived from tissue of 10 patients with primary breast cancer. We developed an experimental protocol for infecting organoid cultures with oncolytic viruses and compared the oncolytic effects of a measles vaccine virus (MeV) and a vaccinia virus (GLV) genetically engineered to express either green fluorescent protein (MeV-GFP) and red fluorescent protein (GLV-0b347), respectively, or a suicide gene encoding a fusion of cytosine deaminase with uracil phosphoribosyltransferase (MeV-SCD and GLV-1h94, respectively), thereby enabling enzymatic conversion of the prodrug 5-fluorocytosine (5-FC) into cytotoxic compounds 5-fluorouracil (5-FU) and 5-fluorouridine monophosphate (5-FUMP).

Results: The method demonstrated that all oncolytic viruses significantly inhibited cell viability in organoid cultures derived from breast cancer tissue. The oncolytic effects of the oncolytic viruses expressing suicide genes (MeV-SCD and GLV-1h94) were further enhanced by virus-triggered conversion of the prodrug 5-FC to toxic 5-FU and toxic 5-FUMP.

Conclusions: We were able to develop a protocol to assess the effects of two different types of oncolytic viruses in stable organoid cell cultures derived from breast cancer tissue. The greatest oncolytic effects were observed when the oncolytic viruses were engineered to express a suicide gene (MeV-SCD and GLV-1h94) in the presence of the prodrug 5-FC. The model therefore provides a promising in vitro method to help further testing and engineering of new generations of virotherapeutic vectors for in vivo use.

Defining and Targeting Esophagogastric Cancer Genomic Subsets With Patient-Derived Xenografts

PURPOSE

Comprehensive genomic profiling has defined key oncogenic drivers and distinct molecular subtypes in esophagogastric cancer; however, the number of clinically actionable alterations remains limited. To establish preclinical models for testing genomically driven therapeutic strategies, we generated and characterized a large collection of esophagogastric cancer patient-derived xenografts (PDXs).

MATERIALS AND METHODS

We established a biobank of 98 esophagogastric cancer PDX models derived from primary tumors and metastases. Clinicopathologic features of each PDX and the corresponding patient sample were annotated, including stage at diagnosis, treatment history, histology, and biomarker profile. To identify oncogenic DNA alterations, we analyzed and compared targeted sequencing performed on PDX and parent tumor pairs. We conducted xenotrials in genomically defined models with oncogenic drivers.

RESULTS

From April 2010 to June 2019, we implanted 276 patient tumors, of which 98 successfully engrafted (35.5%). This collection is enriched for PDXs derived from patients with human epidermal growth factor receptor 2-positive esophagogastric adenocarcinoma (62 models, 63%), the majority of which were refractory to standard therapies including trastuzumab. Factors positively correlating with engraftment included advanced stage, metastatic origin, intestinal-type histology, and human epidermal growth factor receptor 2-positivity. Mutations in TP53 and alterations in receptor tyrosine kinases (ERBB2 and EGFR), RAS/PI3K pathway genes, cell-cycle mediators (CDKN2A and CCNE1), and CDH1 were the predominant oncogenic drivers, recapitulating clinical tumor sequencing. We observed antitumor activity with rational combination strategies in models established from treatment-refractory disease.

CONCLUSION

The Memorial Sloan Kettering Cancer Center PDX collection recapitulates the heterogeneity of esophagogastric cancer and is a powerful resource to investigate mechanisms driving tumor progression, identify predictive biomarkers, and develop therapeutic strategies for molecularly defined subsets of esophagogastric cancer.

Paclitaxel resistance is mediated by NF-κB on mesenchymal primary breast cancer cells

Paclitaxel has been used widely to treat breast cancer and other types of cancer. However, resistance is a major cause of failure for treatment and results in cancer progression. The present study investigated the association between paclitaxel resistance and the mesenchymal phenotype, using a model of primary breast cancer cells and employing four different cultures, two with an epithelial phenotype (MBCDF and MBCD17) and two with a mesenchymal phenotype (MBCDF-D5 and MBCD3). Epithelial-mesenchymal markers were evaluated by western blotting; MBCDF and MBCD17 cells expressed E-cadherin, SNAIL, Slug, and Twist, low levels of N-cadherin, but not vimentin. MBCDF-D5 and MBCD3 cells expressed N-cadherin, vimentin, and higher levels of SNAIL, and low levels of E-cadherin, Slug, and Twist. Cell viability was evaluated using a crystal violet assay after paclitaxel treatment; primary breast cancer cells with mesenchymal phenotype were resistant to paclitaxel compared with the epithelial primary breast cancer cells. Furthermore, using western blotting, it was revealed that mesenchymal cells had elevated levels of nuclear factor-κΒ (NF-κB) p65 and IκB kinase (IKK). Additionally, it was demonstrated that paclitaxel-induced degradation of the inhibitor of NF-κB, activation of NF-κB in a dose-dependent manner, and Bcl-2 and Bcl-xL upregulation. Finally, employing western blotting and crystal violet assays, the effects of the proteasome inhibitor ALLN were assessed. ALLN inhibited paclitaxel-induced NF-κB activation and restored the sensitivity to paclitaxel. Together, these data suggest that targeting the NF-κB/IKK axis might be a promising strategy to overcome paclitaxel resistance.

Progress of oncolytic virotherapy for neuroblastoma

As a neuroendocrine tumor derived from the neural crest, neuroblastoma (NB) is the most common extracranial solid tumor in children. The prognosis in patients with low- and intermediate-risk NB is favorable while that in high-risk patients is often detrimental. However, the management of the considerably large proportion of high-risk patients remains challenging in clinical practice. Among various new approaches, oncolytic virus (OV) therapy offers great advantages in tumor treatment, especially for high-risk NB. Genetic modified OVs can target NB specifically without affecting normal tissue and avoid the widespread drug resistance issue in anticancer monotherapy. Meanwhile, its safety profile provides great potential in combination therapy with chemo-, radio-, and immunotherapy. The therapeutic efficacy of OV for NB is impressive from bench to bedside. The effectiveness and safety of OVs have been demonstrated and reported in studies on children with NB. Furthermore, clinical trials on some OVs (Celyvir, Pexa-Vec (JX-594) and Seneca Valley Virus (NTX-010)) have reported great results. This review summarizes the latest evidence in the therapeutic application of OVs in NB, including those generated in cell lines, animal models and clinical trials.

Microfluidic Biosensor-Based Devices for Rapid Diagnosis and Effective Anti-cancer Therapeutic Monitoring for Breast Cancer Metastasis

Breast cancer with unpredictable metastatic recurrence is the leading cause of cancer-related mortality. Early cancer detection and optimized therapy are the principal determining factors for increased survival rate. Worldwide, researchers and clinicians are in search of efficient strategies for the timely management of cancer progression. Efficient preclinical models provide information on cancer initiation, malignancy progression, relapse, and drug efficacy. The distinct histopathological features and clinical heterogeneity allows no single model to mimic breast tumor. However, engineering three-dimensional (3D) in vitro models incorporating cells and biophysical cues using a combination of organoid culture, 3D printing, and microfluidic technology could recapitulate the tumor microenvironment. These models serve to be preferable predictive models bridging the translational research gap in drug development. Microfluidic device is a cost-effective advanced in vitro model for cancer research, diagnosis, and drug assay under physiologically relevant conditions. Integrating a biosensor with microfluidics allows rapid real-time analytical validation to provide highly sensitive, specific, reproducible, and reliable outcomes. In this manner, the multi-system approach in identifying biomarkers associated with cancer facilitates early detection, therapeutic window optimization, and post-treatment evaluation.This chapter showcases the advancements related to in vitro breast cancer metastasis models focusing on microfluidic devices. The chapter aims to provide an overview of microfluidic biosensor-based devices for cancer detection and high-throughput chemotherapeutic drug screening.