A renewable tissue resource of phenotypically stable, biologically and ethnically diverse, patient-derived human breast cancer xenograft models

ALDH1A3 is the switch that determines the balance of ALDH+ and CD24-CD44+ cancer stem cells, EMT-MET, and glucose metabolism in breast cancer

Plasticity is an inherent feature of cancer stem cells (CSCs) and regulates the balance of key processes required at different stages of breast cancer progression, including epithelial-to-mesenchymal transition (EMT) versus mesenchymal-to-epithelial transition (MET), and glycolysis versus oxidative phosphorylation. Understanding the key factors that regulate the switch between these processes could lead to novel therapeutic strategies that limit tumor progression. We found that aldehyde dehydrogenase 1A3 (ALDH1A3) regulates these cancer-promoting processes and the abundance of the two distinct breast CSC populations defined by high ALDH activity and CD24-CD44+ cell surface expression. While ALDH1A3 increases ALDH+ breast cancer cells, it inversely suppresses the CD24-CD44+ population by retinoic acid signaling-mediated gene expression changes. This switch in CSC populations induced by ALDH1A3 was paired with decreased migration but increased invasion and an intermediate EMT phenotype. We also demonstrate that ALDH1A3 increases oxidative phosphorylation and decreases glycolysis and reactive oxygen species (ROS). The effects of ALDH1A3 reduction were countered with the glycolysis inhibitor 2-deoxy-D-glucose (2DG). In cell culture and tumor xenograft models, 2DG suppresses the increase in the CD24-CD44+ population and ROS induced by ALDH1A3 knockdown. Combined inhibition of ALDH1A3 and glycolysis best reduces breast tumor growth and tumor-initiating cells, suggesting that the combination of targeting ALDH1A3 and glycolysis has therapeutic potential for limiting CSCs and tumor progression. Together, these findings identify ALDH1A3 as a key regulator of processes required for breast cancer progression and depletion of ALDH1A3 makes breast cancer cells more susceptible to glycolysis inhibition.

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

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

Leveraging preclinical models of metastatic breast cancer

Women that present to the clinic with established breast cancer metastases have limited treatment options. Yet, the majority of preclinical studies are actually not directed at developing treatment regimens for established metastatic disease. In this review we will discuss the current state of preclinical macro-metastatic breast cancer models, including, but not limited to syngeneic GEMM, PDX and xenografts. Challenges within these models which are often overlooked include fluorophore-immunogenic neoantigens, differences in experimental vs spontaneous metastasis and tumor heterogeneity. Furthermore, due to cell plasticity in the tumor immune microenvironment (TIME) of the metastatic landscape, the treatment efficacy of newly approved immune checkpoint blockade (ICB) may differ in metastatic sites as compared to primary localized tumors.

Predicting Tumor Volume Doubling Time and Progression-Free Survival in Untreated Patients from Patient-Derived-Xenograft (PDX) Models: A Translational Model-Based Approach

Tumor volume doubling time (TVDT) has been shown to be a potential surrogate marker of biological tumor activity. However, its availability in clinics is strongly limited due to ethical and practical reasons, as its assessment requires at least two subsequent tumor volume measurements in untreated patients. Here, a translational modeling framework to predict TVDT distributions in untreated cancer patient populations from tumor growth data in patient-derived xenograft (PDX) mice is proposed. Eleven solid cancer types were considered. For each of them, a set of tumor growth studies in PDX mice was selected and analyzed through a mathematical model to characterize the distribution of the exponential tumor growth rate in mice. Then, assuming an exponential growth of the tumor mass in humans, the growth rates were scaled from PDX mice to humans through an allometric scaling approach and used to predict TVDTs in untreated patients. A very good agreement was found between model predicted and clinically observed TVDTs, with 91% of the predicted TVDT medians fell within 1.5-fold of observations. Further, exploiting the intrinsic relationship between tumor growth dynamics and progression free survival (PFS), the exponential growth rates in humans were used to generate the expected PFS curves in absence of anticancer treatment. Predicted curves were extremely close to published PFS data from studies involving patient cohorts treated with supportive care or low effective therapies. The proposed approach shows promise as a potential tool to increase knowledge about TVDT in humans without the need of directly measuring tumor dimensions in untreated patients, and to predict PFS curves in untreated patients, that could fill the absence of placebo-controlled arms against which to compare treaded arms during clinical trials. However, further validation and refinement are needed to fully assess its effectiveness in this regard.

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.

Anti-EGFR Antibody-Drug Conjugate Carrying an Inhibitor Targeting CDK Restricts Triple-Negative Breast Cancer Growth

PURPOSE

Anti-EGFR antibodies show limited response in breast cancer, partly due to activation of compensatory pathways. Furthermore, despite the clinical success of cyclin-dependent kinase (CDK) 4/6 inhibitors in hormone receptor-positive tumors, aggressive triple-negative breast cancers (TNBC) are largely resistant due to CDK2/cyclin E expression, whereas free CDK2 inhibitors display normal tissue toxicity, limiting their therapeutic application. A cetuximab-based antibody drug conjugate (ADC) carrying a CDK inhibitor selected based on oncogene dysregulation, alongside patient subgroup stratification, may provide EGFR-targeted delivery.

EXPERIMENTAL DESIGN

Expressions of G1/S-phase cell cycle regulators were evaluated alongside EGFR in breast cancer. We conjugated cetuximab with CDK inhibitor SNS-032, for specific delivery to EGFR-expressing cells. We assessed ADC internalization and its antitumor functions in vitro and in orthotopically grown basal-like/TNBC xenografts.

RESULTS

Transcriptomic (6,173 primary, 27 baseline, and matched post-chemotherapy residual tumors), single-cell RNA sequencing (150,290 cells, 27 treatment-naïve tumors), and spatial transcriptomic (43 tumor sections, 22 TNBCs) analyses confirmed expression of CDK2 and its cyclin partners in basal-like/TNBCs, associated with EGFR. Spatiotemporal live-cell imaging and super-resolution confocal microscopy demonstrated ADC colocalization with late lysosomal clusters. The ADC inhibited cell cycle progression, induced cytotoxicity against high EGFR-expressing tumor cells, and bystander killing of neighboring EGFR-low tumor cells, but minimal effects on immune cells. Despite carrying a small molar fraction (1.65%) of the SNS-032 inhibitor, the ADC restricted EGFR-expressing spheroid and cell line/patient-derived xenograft tumor growth.

CONCLUSIONS

Exploiting EGFR overexpression, and dysregulated cell cycle in aggressive and treatment-refractory tumors, a cetuximab-CDK inhibitor ADC may provide selective and efficacious delivery of cell cycle-targeted agents to basal-like/TNBCs, including chemotherapy-resistant residual disease.

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

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

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

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

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.

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

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

Factors associated with engraftment success of patient-derived xenografts of breast cancer

BACKGROUND

Patient-derived xenograft (PDX) models serve as a valuable tool for the preclinical evaluation of novel therapies. They closely replicate the genetic, phenotypic, and histopathological characteristics of primary breast tumors. Despite their promise, the rate of successful PDX engraftment is various in the literature. This study aimed to identify the key factors associated with successful PDX engraftment of primary breast cancer.

METHODS

We integrated clinicopathological data with morphological attributes quantified using a trained artificial intelligence (AI) model to identify the principal factors affecting PDX engraftment.

RESULTS

Multivariate logistic regression analyses demonstrated that several factors, including a high Ki-67 labeling index (Ki-67LI) (p < 0.001), younger age at diagnosis (p = 0.032), post neoadjuvant chemotherapy (NAC) (p = 0.006), higher histologic grade (p = 0.039), larger tumor size (p = 0.029), and AI-assessed higher intratumoral necrosis (p = 0.027) and intratumoral invasive carcinoma (p = 0.040) proportions, were significant factors for successful PDX engraftment (area under the curve [AUC] 0.905). In the NAC group, a higher Ki-67LI (p < 0.001), lower Miller-Payne grade (p < 0.001), and reduced proportion of intratumoral normal breast glands as assessed by AI (p = 0.06) collectively provided excellent prediction accuracy for successful PDX engraftment (AUC 0.89).

CONCLUSIONS

We found that high Ki-67LI, younger age, post-NAC status, higher histologic grade, larger tumor size, and specific morphological attributes were significant factors for predicting successful PDX engraftment of primary breast cancer.

The impact of erythropoiesis-stimulating agents administration concomitantly with adjuvant anti-HER2 treatments on the outcomes of patients with early breast cancer: a sub-analysis of the ALTTO study

PURPOSE

To assess whether erythropoiesis-stimulating agents (ESA) administration impacts the outcomes of patients with HER2-positive early breast cancer (EBC).

METHODS

ALTTO (NCT00490139) patients were categorized by ESA use during adjuvant anti-HER2 treatment. Disease-free-survival (DFS), overall survival (OS), and time-to-distant recurrence (TTDR) were analyzed by ESA administration, with subgroup analyses according to prognostic factors. Log-rank tests and Cox modeling were performed. Adverse events (AEs) of ESA-interest were compared.

RESULTS

Among 8381 patients recruited in ALTTO, 123 (1.5%) received ESA concomitantly with study treatment. The median age of patients receiving ESA was 54 years, 39.0% premenopausal, most had tumor size > 2 cm (56.9%), node-positive (58.5%), and positive estrogen receptor expression (61.8%). Median follow-up was shorter in the ESA group [6.1 years (IQR 5.3-7.0) vs. 6.9 years (6.0-7.1); p < 0.001]. There was no DFS difference by ESA administration (log-rank p = 0.70), with 3- and 7-year DFS of 89.2% (95% CI 81.8-93.8%) and 81.6% (71.4-88.5%) in ESA group vs. 88.3% (87.6-89.0%) and 80.0% (79.1-80.9%) in No-ESA group. In subgroup analyses, the interaction of ESA administration with menopausal status was statistically significant (unadjusted p = 0.024; stratified p = 0.033), favoring premenopausal women receiving ESA. We observed no significant association of ESA administration with OS (log-rank p = 0.57; 7-year OS in ESA 88.6% vs. 90.0% in non-ESA) or TTDR. ESA-interest AEs were experienced by eight (6.5%) patients receiving ESA and 417 (5.1%) in the No-ESA group (p = 0.41).

CONCLUSION

ESA administration to patients receiving adjuvant anti-HER2 treatment for HER2-positive EBC was safe and not associated with a negative impact on survival outcomes.

Development of Orthotopic Patient-Derived Xenograft Models of Pediatric Intracranial Tumors

The development of clinically relevant and reliable models of central nervous system tumors has been instrumental in advancing the field of Neuro-Oncology. The orthotopic intracranial injection is widely used to study the growth, invasion, and spread of tumors in a controlled environment. Orthotopic models are performed to examine tumor cells isolated from a specific region in a patient in the same site or location in an animal model. Orthotopic brain tumor models are also utilized for preclinical testing of therapeutics as they closely recapitulate the behavior of such cancer and the brain environment of patients. Below, we describe our experiences in the development of murine models of pediatric brain tumors including diffuse midline glioma (DMG), glioblastoma (GBM), and medulloblastoma. The method provides an overview of intracranial stereotactic injections in mice.

Generation of Orthotopic and Subcutaneous Patient-Derived Xenograft Models from Diverse Clinical Tissue Samples of Pediatric Extracranial Solid Tumors

Realistic and renewable laboratory models that accurately reflect the distinct clinical features of childhood cancers have enormous potential to speed research progress. These models help us to understand disease biology, develop new research methods, advance new therapies to clinical trial, and implement personalized medicine. This chapter describes methods to generate patient-derived xenograft models of neuroblastoma and rhabdomyosarcoma, two tumor types for which children with high-risk disease have abysmal survival outcomes and survivors have lifelong-debilitating effects from treatment. Further, this protocol addresses model development from diverse clinical tumor tissue samples, subcutaneous and orthotopic engraftment, and approaches to avoid model loss.

Engineering CD276/B7-H3-targeted antibody-drug conjugates with enhanced cancer-eradicating capability

CD276/B7-H3 represents a promising target for cancer therapy based on widespread overexpression in both cancer cells and tumor-associated stroma. In previous preclinical studies, CD276 antibody-drug conjugates (ADCs) exploiting a talirine-type pyrrolobenzodiazepine (PBD) payload showed potent activity against various solid tumors but with a narrow therapeutic index and dosing regimen higher than that tolerated in clinical trials using other antibody-talirine conjugates. Here, we describe the development of a modified talirine PBD-based fully human CD276 ADC, called m276-SL-PBD, that is cross-species (human/mouse) reactive and can eradicate large 500-1,000-mm3 triple-negative breast cancer xenografts at doses 10- to 40-fold lower than the maximum tolerated dose. By combining CD276 targeting with judicious genetic and chemical ADC engineering, improved ADC purification, and payload sensitivity screening, these studies demonstrate that the therapeutic index of ADCs can be substantially increased, providing an advanced ADC development platform for potent and selective targeting of multiple solid tumor types.

SIRT6 promotes metastasis and relapse in HER2-positive breast cancer

The histone deacetylase sirtuin 6 (SIRT6) has been endowed with anti-cancer capabilities in many tumor types. Here, we investigate the impact of SIRT6-overexpression (SIRT6-OE) in Delta16HER2 mice, which are a bona fide model of HER2-positive breast cancer. After an initial delay in the tumor onset, SIRT6-OE induces a more aggressive phenotype of Delta16HER2 tumors promoting the formation of higher number of tumor foci and metastases than controls. This phenotype of SIRT6-OE tumors is associated with cancer stem cell (CSC)-like features and tumor dormancy, and low senescence and oxidative DNA damage. Accordingly, a sub-set of HER2-positive breast cancer patients with concurrent SIRT6-OE has a significant poorer relapse-free survival (RFS) probability than patients with low expression of SIRT6. ChIP-seq, RNA-seq and RT-PCR experiments indicate that SIRT6-OE represses the expression of the T-box transcription factor 3 (Tbx3) by deacetylation of H3K9ac. Accordingly, loss-of-function mutations of TBX3 or low TBX3 expression levels are predictive of poor prognosis in HER2-positive breast cancer patients. Our work indicates that high levels of SIRT6 are indicative of poor prognosis and high risk of metastasis in HER2-positive breast cancer and suggests further investigation of TBX3 as a downstream target of SIRT6 and co-marker of poor-prognosis. Our results point to a breast cancer subtype-specific effect of SIRT6 and warrant future studies dissecting the mechanisms of SIRT6 regulation in different breast cancer subtypes.

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.

A small-molecule inhibitor of TopBP1 exerts anti-MYC activity and synergy with PARP inhibitors

We have previously identified TopBP1 (topoisomerase IIβ-binding protein 1) as a promising target for cancer therapy, given its role in the convergence of Rb, PI(3)K/Akt, and p53 pathways. Based on this, we conducted a large-scale molecular docking screening to identify a small-molecule inhibitor that specifically targets the BRCT7/8 domains of TopBP1, which we have named 5D4. Our studies show that 5D4 inhibits TopBP1 interactions with E2F1, mutant p53, and Cancerous Inhibitor of Protein Phosphatase 2A. This leads to the activation of E2F1-mediated apoptosis and the inhibition of mutant p53 gain of function. In addition, 5D4 disrupts the interaction of TopBP1 with MIZ1, which in turn allows MIZ1 to bind to its target gene promoters and repress MYC activity. Moreover, 5D4 inhibits the association of the TopBP1-PLK1 complex and prevents the formation of Rad51 foci. When combined with inhibitors of PARP1/2 or PARP14, 5D4 synergizes to effectively block cancer cell proliferation. Our animal studies have demonstrated the antitumor activity of 5D4 in breast and ovarian cancer xenograft models. Moreover, the effectiveness of 5D4 is further enhanced when combined with a PARP1/2 inhibitor talazoparib. Taken together, our findings strongly support the potential use of TopBP1-BRCT7/8 inhibitors as a targeted cancer therapy.

Kinome Reprogramming Is a Targetable Vulnerability in ESR1 Fusion-Driven Breast Cancer

Transcriptionally active ESR1 fusions (ESR1-TAF) are a potent cause of breast cancer endocrine therapy (ET) resistance. ESR1-TAFs are not directly druggable because the C-terminal estrogen/anti-estrogen-binding domain is replaced with translocated in-frame partner gene sequences that confer constitutive transactivation. To discover alternative treatments, a mass spectrometry (MS)-based kinase inhibitor pulldown assay (KIPA) was deployed to identify druggable kinases that are upregulated by diverse ESR1-TAFs. Subsequent explorations of drug sensitivity validated RET kinase as a common therapeutic vulnerability despite remarkable ESR1-TAF C-terminal sequence and structural diversity. Organoids and xenografts from a pan-ET-resistant patient-derived xenograft model that harbors the ESR1-e6>YAP1 TAF were concordantly inhibited by the selective RET inhibitor pralsetinib to a similar extent as the CDK4/6 inhibitor palbociclib. Together, these findings provide preclinical rationale for clinical evaluation of RET inhibition for the treatment of ESR1-TAF-driven ET-resistant breast cancer.

SIGNIFICANCE

Kinome analysis of ESR1 translocated and mutated breast tumors using drug bead-based mass spectrometry followed by drug-sensitivity studies nominates RET as a therapeutic target. See related commentary by Wu and Subbiah, p. 3159.

Unlocking Translational Potential: Conditionally Reprogrammed Cells in Advancing Breast Cancer Research

Preclinical in vitro models play an important role in studying cancer cell biology and facilitating translational research, especially in the identification of drug targets and drug discovery studies. This is particularly relevant in breast cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (radiotherapy, chemotherapy, immunotherapy, and/or surgery) are relatively lacking. To be clinically relevant, a model must accurately replicate the biology and cellular heterogeneity of the primary tumor. Addressing these requirements and overcoming the limitations of most existing cancer cell lines, which are typically derived from a single clone, we have recently developed conditional reprogramming (CR) technology. The CR technology refers to a co-culture system of primary human normal or tumor cells with irradiated murine fibroblasts in the presence of a Rho-associated kinase inhibitor to allow the primary cells to acquire stem cell properties and the ability to proliferate indefinitely in vitro without any exogenous gene or viral transfection. This innovative approach fulfills many of these needs and offers an alternative that surpasses the deficiencies associated with traditional cancer cell lines. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have applied CR technology to conduct breast cancer research.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

PROBABILISTIC LEARNING OF TREATMENT TREES IN CANCER

Accurate identification of synergistic treatment combinations and their underlying biological mechanisms is critical across many disease domains, especially cancer. In translational oncology research, preclinical systems such as patient-derived xenografts (PDX) have emerged as a unique study design evaluating multiple treatments administered to samples from the same human tumor implanted into genetically identical mice. In this paper, we propose a novel Bayesian probabilistic tree-based framework for PDX data to investigate the hierarchical relationships between treatments by inferring treatment cluster trees, referred to as treatment trees (Rx-tree). The framework motivates a new metric of mechanistic similarity between two or more treatments accounting for inherent uncertainty in tree estimation; treatments with a high estimated similarity have potentially high mechanistic synergy. Building upon Dirichlet Diffusion Trees, we derive a closed-form marginal likelihood encoding the tree structure, which facilitates computationally efficient posterior inference via a new two-stage algorithm. Simulation studies demonstrate superior performance of the proposed method in recovering the tree structure and treatment similarities. Our analyses of a recently collated PDX dataset produce treatment similarity estimates that show a high degree of concordance with known biological mechanisms across treatments in five different cancers. More importantly, we uncover new and potentially effective combination therapies that confer synergistic regulation of specific downstream biological pathways for future clinical investigations. Our accompanying code, data, and shiny application for visualization of results are available at: https://github.com/bayesrx/RxTree.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer

Intratumor heterogeneity associates with poor patient outcome. Stromal stiffening also accompanies cancer. Whether cancers demonstrate stiffness heterogeneity, and if this is linked to tumor cell heterogeneity remains unclear. We developed a method to measure the stiffness heterogeneity in human breast tumors that quantifies the stromal stiffness each cell experiences and permits visual registration with biomarkers of tumor progression. We present Spatially Transformed Inferential Force Map (STIFMap) which exploits computer vision to precisely automate atomic force microscopy (AFM) indentation combined with a trained convolutional neural network to predict stromal elasticity with micron-resolution using collagen morphological features and ground truth AFM data. We registered high-elasticity regions within human breast tumors colocalizing with markers of mechanical activation and an epithelial-to-mesenchymal transition (EMT). The findings highlight the utility of STIFMap to assess mechanical heterogeneity of human tumors across length scales from single cells to whole tissues and implicates stromal stiffness in tumor cell heterogeneity.

A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies

Predicting in vivo response to antineoplastics remains an elusive challenge. We performed a first-of-kind evaluation of two transcriptome-based precision cancer medicine methodologies to predict tumor sensitivity to a comprehensive repertoire of clinically relevant oncology drugs, whose mechanism of action we experimentally assessed in cognate cell lines. We enrolled patients with histologically distinct, poor-prognosis malignancies who had progressed on multiple therapies, and developed low-passage, patient-derived xenograft models that were used to validate 35 patient-specific drug predictions. Both OncoTarget, which identifies high-affinity inhibitors of individual master regulator (MR) proteins, and OncoTreat, which identifies drugs that invert the transcriptional activity of hyperconnected MR modules, produced highly significant 30-day disease control rates (68% and 91%, respectively). Moreover, of 18 OncoTreat-predicted drugs, 15 induced the predicted MR-module activity inversion in vivo. Predicted drugs significantly outperformed antineoplastic drugs selected as unpredicted controls, suggesting these methods may substantively complement existing precision cancer medicine approaches, as also illustrated by a case study.

SIGNIFICANCE

Complementary precision cancer medicine paradigms are needed to broaden the clinical benefit realized through genetic profiling and immunotherapy. In this first-in-class application, we introduce two transcriptome-based tumor-agnostic systems biology tools to predict drug response in vivo. OncoTarget and OncoTreat are scalable for the design of basket and umbrella clinical trials. This article is highlighted in the In This Issue feature, p. 1275.

Modeling the Tumor Microenvironment and Cancer Immunotherapy in Next-Generation Humanized Mice

Cancer immunotherapy has brought significant clinical benefits to numerous patients with malignant disease. However, only a fraction of patients experiences complete and durable responses to currently available immunotherapies. This highlights the need for more effective immunotherapies, combination treatments and predictive biomarkers. The molecular properties of a tumor, intratumor heterogeneity and the tumor immune microenvironment decisively shape tumor evolution, metastasis and therapy resistance and are therefore key targets for precision cancer medicine. Humanized mice that support the engraftment of patient-derived tumors and recapitulate the human tumor immune microenvironment of patients represent a promising preclinical model to address fundamental questions in precision immuno-oncology and cancer immunotherapy. In this review, we provide an overview of next-generation humanized mouse models suitable for the establishment and study of patient-derived tumors. Furthermore, we discuss the opportunities and challenges of modeling the tumor immune microenvironment and testing a variety of immunotherapeutic approaches using human immune system mouse models.

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

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

The Potential Effect of General Anesthetics in Cancer Surgery: Meta-Analysis of Postoperative Metastasis and Inflammatory Cytokines

Metastasis or recurrence following curative surgery is the main indicator of tumor progress and is the main cause of patient death. For more than three decades, the potential for general anesthesia to affect cancer outcomes has been a subject of concern with considerable research interest. Here, we conducted this systematic review and meta-analysis to summarize the effect of inhalational anesthesia (IHNA) vs. propofol-based total intravenous anesthesia (TIVA) on metastasis and recurrence after cancer surgery from clinical and pre-clinical studies. The relative risk for metastasis/recurrence in TIVA is 0.61 (95% confidence interval (95% CI) 0.46 to 0.82, p = 0.0009) compared to IHNA. Inflammatory cytokines have been implicated in cancer metastasis following cancer surgery, thus we analyzed inflammatory cytokines levels after surgery under IHNA or TIVA. Based on pooled analysis, a lower IL-6 level was noticed in TIVA in comparison to IHNA (standardized mean difference (SMD) = 0.77, 95% CI = 0.097 to 1.44, I² = 92%, p = 0.02) but not TNF-α or IL-10. Preclinical animal model studies show that inhalational anesthetics increase the risk of breast cancer metastasis compared to propofol. In conclusion, the current evidence suggests intravenous anesthetic propofol is associated with less metastasis/recurrence and lower postoperative IL-6 level over inhaled anesthetics in the oncological surgery. We urge more well-designed clinical and preclinical studies in this field.

[89Zr]-Atezolizumab-PET Imaging Reveals Longitudinal Alterations in PDL1 during Therapy in TNBC Preclinical Models

Triple-negative breast cancers (TNBCs) currently have limited treatment options; however, PD-L1 is an indicator of susceptibility to immunotherapy. Currently, assessment of PD-L1 is limited to biopsy samples. These limitations may be overcome with molecular imaging. In this work, we describe chemistry development and optimization, in vitro, in vivo, and dosimetry of [89Zr]-Atezolizumab for PD-L1 imaging. Atezolizumab was conjugated to DFO and radiolabeled with 89Zr. Tumor uptake and heterogeneity in TNBC xenograft and patient-derived xenograft (PDX) mouse models were quantified following [89Zr]-Atezolizumab-PET imaging. PD-L1 expression in TNBC PDX models undergoing therapy and immunohistochemistry (IHC) was used to validate imaging. SUV from PET imaging was quantified and used to identify heterogeneity. PET/CT imaging using [89Zr]-Atezolizumab identified a significant increase in tumor:muscle SUVmean 1 and 4 days after niraparib therapy and revealed an increased trend in PD-L1 expression following other cytotoxic therapies. A preliminary dosimetry study indicated the organs that will receive a higher dose are the spleen, adrenals, kidneys, and liver. [89Zr]-Atezolizumab PET/CT imaging reveals potential for the noninvasive detection of PD-L1-positive TNBC tumors and allows for quantitative and longitudinal assessment. This has potential significance for understanding tumor heterogeneity and monitoring early expression changes in PD-L1 induced by therapy.

3D cancer models: One step closer to in vitro human studies

Cancer immunotherapy is the great breakthrough in cancer treatment as it displayed prolonged progression-free survival over conventional therapies, yet, to date, in only a minority of patients. In order to broad cancer immunotherapy clinical applicability some roadblocks need to be overcome, first among all the lack of preclinical models that faithfully depict the local tumor microenvironment (TME), which is known to dramatically affect disease onset, progression and response to therapy. In this review, we provide the reader with a detailed overview of current 3D models developed to mimick the complexity and the dynamics of the TME, with a focus on understanding why the TME is a major target in anticancer therapy. We highlight the advantages and translational potentials of tumor spheroids, organoids and immune Tumor-on-a-Chip models in disease modeling and therapeutic response, while outlining pending challenges and limitations. Thinking forward, we focus on the possibility to integrate the know-hows of micro-engineers, cancer immunologists, pharmaceutical researchers and bioinformaticians to meet the needs of cancer researchers and clinicians interested in using these platforms with high fidelity for patient-tailored disease modeling and drug discovery.

Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) used. The primary goal is to determine the degree to which PDX cohort responses recapitulate patient cohort responses at the phenotypic and molecular levels, such that pre-clinical and clinical trials can inform one another. A major issue is how to manage, integrate, and analyze the abundance of data generated across both spatial and temporal scales, as well as across species. To address this issue, we are developing MIRACCL (molecular and imaging response analysis of co-clinical trials), a web-based analytical tool. For prototyping, we simulated data for a co-clinical trial in "triple-negative" breast cancer (TNBC) by pairing pre- (T0) and on-treatment (T1) magnetic resonance imaging (MRI) from the I-SPY2 trial, as well as PDX-based T0 and T1 MRI. Baseline (T0) and on-treatment (T1) RNA expression data were also simulated for TNBC and PDX. Image features derived from both datasets were cross-referenced to omic data to evaluate MIRACCL functionality for correlating and displaying MRI-based changes in tumor size, vascularity, and cellularity with changes in mRNA expression as a function of treatment.

Stabilization of E-cadherin adhesions by COX-2/GSK3β signaling is a targetable pathway in metastatic breast cancer

Metastatic progression of epithelial cancers can be associated with epithelial-mesenchymal transition (EMT) including transcriptional inhibition of E-cadherin (CDH1) expression. Recently, EM plasticity (EMP) and E-cadherin-mediated, cluster-based metastasis and treatment resistance have become more appreciated. However, the mechanisms that maintain E-cadherin expression in this context are less understood. Through studies of inflammatory breast cancer (IBC) and a 3D tumor cell "emboli" culture paradigm, we discovered that cyclooxygenase 2 (COX-2; PTGS2), a target gene of C/EBPδ (CEBPD), or its metabolite prostaglandin E2 (PGE2) promotes protein stability of E-cadherin, β-catenin, and p120 catenin through inhibition of GSK3β. The COX-2 inhibitor celecoxib downregulated E-cadherin complex proteins and caused cell death. Coexpression of E-cadherin and COX-2 was seen in breast cancer tissues from patients with poor outcome and, along with inhibitory GSK3β phosphorylation, in patient-derived xenografts (PDX) including triple negative breast cancer (TNBC).Celecoxib alone decreased E-cadherin protein expression within xenograft tumors, though CDH1 mRNA levels increased, and reduced circulating tumor cell (CTC) clusters. In combination with paclitaxel, celecoxib attenuated or regressed lung metastases. This study has uncovered a mechanism by which metastatic breast cancer cells can maintain E-cadherin-mediated cell-to-cell adhesions and cell survival, suggesting that some patients with COX-2+/E-cadherin+ breast cancer may benefit from targeting of the PGE2 signaling pathway.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

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.

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

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

A novel xenograft model of human hepatocellular carcinoma in immunocompetent mice based on the microcarrier-6

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that threaten human health; thus, the establishment of an animal model with clinical features similar to human hepatocellular carcinoma is of important practical significance.

METHODS

Taking advantage of the novel microcarrier-6, human HCC cells were injected into immunocompetent mice to establish a novel human HCC patient-derived xenograft (PDX) model. Primary HCC cells were isolated from fresh hepatocellular carcinoma tissues, which were subsequently co-cultured with microcarrier-6 to construct a three-dimensional tumor cell culture model in vitro. The HCC-microcarrier complex was implanted into mice by subcutaneous inoculation, and the tumor formation time, tumor formation rate, and pathological manifestation were recorded. Changes of immune parameters in mice were detected by flow cytometry.

RESULTS

The success rate was 60% (6/10) in the establishment of hepatocellular carcinoma PDX mouse model, and the total tumor formation rate of the tumor-forming model is 90-100%. H&E staining and immunohistochemical experiments indicate that the model well retained the characteristics of the primary tumor. Interestingly, M2 macrophages in tumor-bearing mice increased significantly, and the levels of CD4⁺ T cells were significantly reduced.

CONCLUSIONS

Through the application of the microcarrier-6 in immunocompetent mice, we successfully established a novel human HCC PDX model, which can be used to better study and further elucidate the occurrence and pathogenic mechanism of HCC, improve the predictability of toxicity and drug sensitivity in HCC.

Progress of research on tumor organoids: A bibliometric analysis of relevant publications from 2011 to 2021

Background

Research on tumor organoids has developed rapidly over the past 20 years, but a systematic analysis of current research trends is lacking. Researchers in the field need relevant references and knowledge of current research hot spots. Bibliometric analysis and visualization is a systematic method of acquiring an in-depth understanding of the status of research on tumor organoids.

Methods

CiteSpace, VOSviewer and the Bibliometric Online Analysis Platform from the Web of Science Core Collection were used to analyze and predict publishing trends and research hot spots worldwide in the field of tumor organoids.

Results

A total of 3,666 publications on tumor organoids were retrieved, and 2,939 eligible articles were included in the final analysis. The number of publications has grown significantly, with the United States of America as the leading country for research on tumor organoids. Among journals, Cancers published the largest number of articles. Harvard Medical School published the highest number of articles among all institutions. The Chinese Academy of Sciences was ranked highest among all contributing institutions on the importance of their publications. A trend in multi-disciplinary collaboration was observed in studies on tumor organoids. Keywords indicated that the current research largely concentrated on optimizing the construction of organoid models to use for medication development and screening in the clinical setting, and to provide patients with individualized treatment for gastric cancer and colorectal cancer, which are newly emerging research hotspots. Gastric and colorectal cancers were the top two tumors that have received increasing attention and have become the focal points of recent studies.

Conclusion

This study analyzed 2,939 publications covering the topic of tumor organoids. Although optimizing the construction of organoid models has always been a hot topic in this field, the application of tumor organoids to the development of medications and screenings will foster individualized treatment for patients, which is another emerging hot spot in this field of research.

Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach

Although systemic chemotherapy remains the standard of care for TNBC, even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC PDXs to identify biomarkers of response. To demonstrate their ability to function as a preclinical cohort, PDXs were characterized using DNA sequencing, transcriptomics, and proteomics to show consistency with clinical samples. We then developed a network-based approach (CTD/WGCNA) to identify biomarkers of response to carboplatin (MSI1, TMSB15A, ARHGDIB, GGT1, SV2A, SEC14L2, SERPINI1, ADAMTS20, DGKQ) and docetaxel (c, MAGED4, CERS1, ST8SIA2, KIF24, PARPBP). CTD/WGCNA multigene biomarkers are predictive in PDX datasets (RNAseq and Affymetrix) for both taxane- (docetaxel or paclitaxel) and platinum-based (carboplatin or cisplatin) response, thereby demonstrating cross-expression platform and cross-drug class robustness. These biomarkers were also predictive in clinical datasets, thus demonstrating translational potential.

Extracellular Matrix Glycation and Crosslinking in Mammary Tumor Progression

Breast cancer progression is accompanied by profound extracellular matrix (ECM) remodeling. A greater abundance of aligned fibrillar collagen is characteristic of invasive and aggressive breast cancers and has been associated with elevated activity of collagen crosslinking enzymes, such as lysyl oxidase (LOX) and lysyl hydroxylases (LH) and the formation of more mature collagen matrix crosslinks. Aligned collagen fibers can facilitate metastatic dissemination of tumor cells, and LOX inhibitors have been used to inhibit tumor progression and metastasis in experimental models. Thus, a better understanding of how matrix crosslinking alters tumor cell phenotypes, and behaviors would improve our ability to effectively treat aggressive metastatic breast cancer. Herein described is an experimental approach to glycate and crosslink a collagen-I/basement membrane extract ECM to study the impact of ECM crosslinking on mammary tumor progression in vivo. Moreover, glycation of collagen by sugars to form advanced glycation end products naturally occurs during aging, extending the potential relevance of this approach to research on mechanisms of aging involved in disease progression.

Quaternary nanoparticles enable sustained release of bortezomib for hepatocellular carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) represents the third leading cause of cancer-related mortality in the world. Over the past two decades, there has been minimal improvement in therapies as well as clinical outcomes for patients with Barcelona Clinic Liver Cancer (BCLC)-B. These patients are treated with local interventions, including transarterial chemoembolization. Current methodologies only allow sustained intratumoral release measured in hours. Methodologies to allow sustained local release of the drug cargo over days to weeks are acutely needed. We hypothesize that tumor response as well as outcomes of patients with BCLC-B can be improved through utilization of a highly cytotoxic agent delivered with a sustained release platform.

APPROACH AND RESULTS

High-throughput drug screening across 40 HCC patient-derived organoids identified bortezomib (BTZ) as a highly cytotoxic small molecule for HCC. We designed and manufactured sustained release BTZ nanoparticles (BTZ-NP) using a flash nanocomplexation/nanoprecipitation process. We quantified the release profile and tested the anti-tumoral effects in vivo. The BTZ-NP formulation demonstrated a sustained release of BTZ of 30 days. This BTZ-NP formulation was highly effective in controlling tumor size and improved survival in vivo in three animal models of HCC, including when delivered via the hepatic artery, as we envision its delivery in patients. In addition, the BTZ-NP formulation was superior to treatment with doxorubicin-drug eluting beads.

CONCLUSIONS

The BTZ-NP formulation provides a potent and safe treatment of HCC via a localized delivery approach. These results warrant additional preclinical studies to advance this technology to human clinical trials.

Emerging photodynamic/sonodynamic therapies for urological cancers: progress and challenges

Photodynamic therapy (PDT), and sonodynamic therapy (SDT) that developed from PDT, have been studied for decades to treat solid tumors. Compared with other deep tumors, the accessibility of urological tumors (e.g., bladder tumor and prostate tumor) makes them more suitable for PDT/SDT that requires exogenous stimulation. Due to the introduction of nanobiotechnology, emerging photo/sonosensitizers modified with different functional components and improved physicochemical properties have many outstanding advantages in cancer treatment compared with traditional photo/sonosensitizers, such as alleviating hypoxia to improve quantum yield, passive/active tumor targeting to increase drug accumulation, and combination with other therapeutic modalities (e.g., chemotherapy, immunotherapy and targeted therapy) to achieve synergistic therapy. As WST11 (TOOKAD® soluble) is currently clinically approved for the treatment of prostate cancer, emerging photo/sonosensitizers have great potential for clinical translation, which requires multidisciplinary participation and extensive clinical trials. Herein, the latest research advances of newly developed photo/sonosensitizers for the treatment of urological cancers, and the efficacy, as well as potential biological effects, are highlighted. In addition, the clinical status of PDT/SDT for urological cancers is presented, and the optimization of the photo/sonosensitizer development procedure for clinical translation is discussed.

Immunologically "cold" triple negative breast cancers engraft at a higher rate in patient derived xenografts

TNBC is a heterogeneous subtype of breast cancer, and only a subset of TNBC can be established as PDXs. Here, we show that there is an engraftment bias toward TNBC with low levels of immune cell infiltration. Additionally, TNBC that failed to engraft show gene expression consistent with a cancer-promoting immunological state, leading us to hypothesize that the immunological state of the tumor and possibly the state of the immune system of the host may be essential for engraftment.

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

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

Genomic and epigenomic BRCA alterations predict adaptive resistance and response to platinum-based therapy in patients with triple-negative breast and ovarian carcinomas

Triple-negative breast cancer (TNBC) and ovarian carcinomas (OvCas) with BRCA1 promoter methylation ( BRCA1 meth) respond more poorly to alkylating agents compared to those bearing mutations in BRCA1 and BRCA2 ( BRCA mut). This is a conundrum given the biologically equivalent homologous recombination deficiency (HRD) induced by these genetic and epigenetic BRCA perturbations. We dissected this problem through detailed genomic analyses of TNBC and OvCa cohorts and experimentation with patient-derived xenografts and genetically engineered cell lines. We found that despite identical downstream genomic mutational signatures associated with BRCA1 meth and BRCA mut states, BRCA1 meth uniformly associates with poor outcomes. Exposure of BRCA1 meth TNBCs to platinum chemotherapy, either as clinical treatment of a patient or as experimental in vivo exposure of preclinical patient derived xenografts, resulted in allelic loss of BRCA1 methylation and increased BRCA1 expression and platinum resistance. These data suggest that, unlike BRCA mut cancers, where BRCA loss is a genetically “fixed” deficiency state, BRCA1 meth cancers are highly adaptive to genotoxin exposure and, through reversal of promoter methylation, recover BRCA1 expression and become resistant to therapy. We further found a specific augmented immune transcriptional signal associated with enhanced response to platinum chemotherapy but only in patients with BRCA-proficient cancers. We showed how integrating both this cancer immune signature and the presence of BRCA mutations results in more accurate predictions of patient response when compared to either HRD status or BRCA status alone. This underscores the importance of defining BRCA heterogeneity in optimizing the predictive precision of assigning response probabilities in TNBC and OvCa.

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.

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

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

Screening of organoids derived from patients with breast cancer implicates the repressor NCOR2 in cytotoxic stress response and antitumor immunity

Resistance to antitumor treatment contributes to patient mortality. Functional proteomic screening of organoids derived from chemotherapy-treated patients with breast cancer identified nuclear receptor corepressor 2 (NCOR2) histone deacetylase as an inhibitor of cytotoxic stress response and antitumor immunity. High NCOR2 in the tumors of patients with breast cancer predicted chemotherapy refractoriness, tumor recurrence and poor prognosis. Molecular studies revealed that NCOR2 inhibits antitumor treatment by regulating histone deacetylase 3 (HDAC3) to repress interferon regulatory factor 1 (IRF-1)-dependent gene expression and interferon (IFN) signaling. Reducing NCOR2 or impeding its epigenetic activity by modifying its interaction with HDAC3 enhanced chemotherapy responsiveness and restored antitumor immunity. An adeno-associated viral NCOR2-HDAC3 competitor potentiated chemotherapy and immune checkpoint therapy in culture and in vivo by permitting transcription of IRF-1-regulated proapoptosis and inflammatory genes to increase IFN-γ signaling. The findings illustrate the utility of patient-derived organoids for drug discovery and suggest that targeting stress and inflammatory-repressor complexes such as NCOR2-HDAC3 could overcome treatment resistance and improve the outcome of patients with cancer.

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

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

PHGDH heterogeneity potentiates cancer cell dissemination and metastasis

Cancer metastasis requires the transient activation of cellular programs enabling dissemination and seeding in distant organs1. Genetic, transcriptional and translational heterogeneity contributes to this dynamic process2,3. Metabolic heterogeneity has also been observed4, yet its role in cancer progression is less explored. Here we find that the loss of phosphoglycerate dehydrogenase (PHGDH) potentiates metastatic dissemination. Specifically, we find that heterogeneous or low PHGDH expression in primary tumours of patients with breast cancer is associated with decreased metastasis-free survival time. In mice, circulating tumour cells and early metastatic lesions are enriched with Phgdhlow cancer cells, and silencing Phgdh in primary tumours increases metastasis formation. Mechanistically, Phgdh interacts with the glycolytic enzyme phosphofructokinase, and the loss of this interaction activates the hexosamine-sialic acid pathway, which provides precursors for protein glycosylation. As a consequence, aberrant protein glycosylation occurs, including increased sialylation of integrin αvβ3, which potentiates cell migration and invasion. Inhibition of sialylation counteracts the metastatic ability of Phgdhlow cancer cells. In conclusion, although the catalytic activity of PHGDH supports cancer cell proliferation, low PHGDH protein expression non-catalytically potentiates cancer dissemination and metastasis formation. Thus, the presence of PHDGH heterogeneity in primary tumours could be considered a sign of tumour aggressiveness.