A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology

Direct visualization of emergent metastatic features within an ex vivo model of the tumor microenvironment

Ischemic conditions such as hypoxia and nutrient starvation, together with interactions with stromal cells, are critical drivers of metastasis. These conditions arise deep within tumor tissues, and thus, observing nascent metastases is exceedingly challenging. We thus developed the 3MIC-an ex vivo model of the tumor microenvironment-to study the emergence of metastatic features in tumor cells in a 3-dimensional (3D) context. Here, tumor cells spontaneously create ischemic-like conditions, allowing us to study how tumor spheroids migrate, invade, and interact with stromal cells under different metabolic conditions. Consistent with previous data, we show that ischemia increases cell migration and invasion, but the 3MIC allowed us to directly observe and perturb cells while they acquire these pro-metastatic features. Interestingly, our results indicate that medium acidification is one of the strongest pro-metastatic cues and also illustrate using the 3MIC to test anti-metastatic drugs on cells experiencing different metabolic conditions. Overall, the 3MIC can help dissecting the complexity of the tumor microenvironment for the direct observation and perturbation of tumor cells during the early metastatic process.

Combined inhibition of CDK4/6 and AKT is highly effective against the luminal androgen receptor (LAR) subtype of triple negative breast cancer

Luminal Androgen Receptor (LAR) triple-negative breast cancers (TNBC) express androgen receptors (AR), exhibit high frequency of PIK3CA mutations and intact RB. Herein, we investigated combined blockade of the CDK4/6 and PI3K signaling with palbociclib, alpelisib, and capivasertib, which inhibit CDK4/6, PI3Kα, and AKT1-3, respectively. The combination of palbociclib/capivasertib, but not palbociclib/alpelisib, synergistically inhibited proliferation of MDA-MB-453 and MFM-223 LAR cells [synergy score 7.34 (p = 5.81x10-11) and 4.78 (p = 0.012), respectively]. The AR antagonist enzalutamide was inactive against MDA-MB-453, MFM-223, and CAL148 cells and did not enhance the efficacy of either combination. Palbociclib/capivasertib inhibited growth of LAR patient-derived xenografts more potently than palbociclib/alpelisib. Treatment of LAR cells with palbociclib suppressed phosphorylated-RB and resulted in adaptive phosphorylation/activation of S473 pAKT and AKT substrates GSK3β, PRAS40, and FoxO3a. Capivasertib blocked palbociclib-induced phosphorylation of AKT substrates more potently than alpelisib. Treatment with PI3Kβ inhibitors did not block phosphorylation of AKT substrates, suggesting that PI3Kβ did not mediate the adaptive response to CDK4/6 inhibition. Phosphokinase arrays of MDA-MB-453 cells treated with palbociclib showed time-dependent upregulation of PDGFRβ, GSK3β, STAT3, and STAT6. RNA silencing of PDGFRβ in palbociclib-treated MDA-MB-453 and MFM-223 cells blocked the upregulation of S473 pAKT, suggesting that the adaptive response to CDK4/6 blockade involves PDGFRβ signaling. Finally, treatment with palbociclib and the PDGFR inhibitor CP637451 arrested growth of MDA-MB-453 and MFM-223 cells to the same degree as palbociclib/capivasertib. These findings support testing the combination of CDK4/6 and AKT inhibitors in patients with LAR TNBC, and further investigation of PDGFR antagonists in this breast cancer subtype.

A comprehensive luminal breast cancer patient-derived xenografts (PDX) library to capture tumor heterogeneity and explore the mechanisms of resistance to CDK4/6 inhibitors

Breast cancer (BC) is marked by significant genetic, morphological and clinical heterogeneity. To capture this heterogeneity and unravel the molecular mechanisms driving tumor progression and drug resistance, we established a comprehensive patient-derived xenograft (PDX) biobank, focusing particularly on luminal (estrogen receptor, ER+) and young premenopausal patients, for whom PDX models are currently scarce. Across all BC subtypes, our efforts resulted in an overall success rate of 17% (26 established PDX lines out of 151 total attempts), specifically 15% in luminal, 12% in human epidermal growth factor receptor 2 positive (HER2+) and 35% in triple negative BC. These PDX mirrored morphologic and genetic features of BC from which they originated, serving as a reliable tool to investigate drug resistance and test therapeutic strategies. We focused on understanding resistance to CDK4/6 inhibitors (CDK4/6i), which are crucial in the treatment of patients with advanced luminal BC. Treating a sensitive luminal BC PDX with the CDK4/6i palbociclib revealed that, despite initial tumor shrinkage, some tumors might eventually regrow under drug treatment. RNA sequencing, followed by gene set enrichment analyses, unveiled that these PDXs have become refractory to CDK4/6i, both at biological and molecular levels, displaying significant enrichment in proliferation pathways, such as MTORC1, E2F and MYC. Using organoids derived from these PDX (PDxO), we observed that acquisition of CDK4/6i resistance conferred cross-resistance to endocrine therapy and that targeting MTORC1 was a successful strategy to overcome CDK4/6i resistance. Considered together, these results indicate that our PDX models may serve as robust tools to elucidate the molecular basis of BC disease progression and, by providing the possibility to simultaneously test different therapies on the same tumor, to surmount treatment resistance. While this approach is of course not feasible in the clinic, its exploitation in PDX may expedite the identification and development of more successful therapies for patients with advanced luminal BC. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Establishment of matched bladder cancer PDX and PDX-derived organoid model and evaluation of anti-tumor efficacy of abemaciclib

INTRODUCTION

Bladder cancer is one of the most common malignancies of the urinary system and there's a significant unmet need for new effective therapeutics for bladder cancer. The limited number of available models to study malignant bladder tumors is one of the obstructions in developing bladder cancer therapeutics. Patient-derived xenograft (PDX) and organoid (PDO) models are more representatives of human cancer than cell lines and cell line-derived xenograft (CDX) and are likely to be more promising and efficient in predicting drug response and finding new therapeutics.

METHODS

Three pairs of patient-derived xenograft (PDX) models of bladder cancer and their corresponding PDX-derived organoids (PDXOs) were successfully established. These models were utilized to assess the efficacy of abemaciclib. The sensitivity of the drug was determined through the Cell Counting Kit-8 (CCK8) assay in PDXO cultures, corroborated by the EdU incorporation assay. Additionally, the in vivo tumor growth was monitored in the matched PDX models.

RESULTS

In vitro PDXO cultures and in vivo PDX tumor models consistently demonstrated that abemaciclib had varying degrees of inhibitory effects across different bladder cancer (BC) patients. Notably, our study further revealed that treatment with abemaciclib significantly modified the expression patterns of CyclinD1/CDK4. This was achieved by not only diminishing their expression levels but also by shifting their expression from a membrane-associated localization to the nucleus.

CONCLUSION

Our research provided compelling evidence attesting to the reliability and potential of PDX and PDXO models in the realm of precision medicine. These models are instrumental in identifying patients who are likely to respond favorably to a specific drug treatment.

Patient-Derived Organoids: A Game-Changer in Personalized Cancer Medicine

Research on cancer therapies has benefited from predictive tools capable of simulating treatment response and other disease characteristics in a personalized manner, in particular three-dimensional cell culture models. Such models include tumor-derived spheroids, multicellular spheroids including organotypic multicellular spheroids, and tumor-derived organoids. Additionally, organoids can be grown from various cancer cell types, such as pluripotent stem cells and induced pluripotent stem cells, progenitor cells, and adult stem cells. Although patient-derived xenografts and genetically engineered mouse models replicate human disease in vivo, organoids are less expensive, less labor intensive, and less time-consuming, all-important aspects in high-throughput settings. Like in vivo models, organoids mimic the three-dimensional structure, cellular heterogeneity, and functions of primary tissues, with the advantage of representing the normal oxygen conditions of patient organs. In this review, we summarize the use of organoids in disease modeling, drug discovery, toxicity testing, and precision oncology. We also summarize the current clinical trials using organoids.

Activation of the γ-secretase/NICD-PXR/Notch pathway induces Taxol resistance in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is currently the only subtype lacking efficient targeted therapies. Taxol is the primary chemotherapeutic agent for TNBC. However, Taxol resistance often develops in the treatment of TNBC patients, which importantly contributes to high mortality and poor prognosis in TNBC patients. Recent preclinical studies have shown that the inhibition of Notch pathway by γ-secretase inhibitors can slow down the progression of TNBC. Our studies in bioinformatic analysis of breast cancer patients and TNBC/Taxol cells in vitro showed that there was high correlation between the activation of Notch pathway and Taxol resistance in TNBC. Increased γ-secretase activity (by the overexpression of catalytic core PSEN-1) significantly reduced Taxol sensitivity of TNBC cells, and enhanced biological characteristics of malignancy in vitro, and tumour growth in vivo. Mechanistically, increased γ-secretase activity led to the accumulation of NICD in the nucleus, promoting the interaction between NICD and PXR to activate PXR, which triggered the transcription of PXR downstream associated drug resistance genes. Furthermore, we showed that pharmacological inhibition of γ-secretase with γ-secretase inhibitors (Nirogacestat and DAPT) can reverse Taxol resistance in vivo and in vitro. Our results for the first time demonstrate that the activation of γ -secretase/NCD-PXR/Notch pathway is one of important mechanisms to cause Taxol resistance in TNBC, and the blockades of this pathway may represent a new therapeutic strategy for overcoming Taxol resistance in TNBC.

Modeling lung adenocarcinoma metastases using patient-derived organoids

Approximately 50% of patients with surgically resected early-stage lung cancer develop distant metastasis. At present, there is no in vivo metastasis model to investigate the biology of human lung cancer metastases. Using well-characterized lung adenocarcinoma (LUAD) patient-derived organoids (PDOs), we establish an in vivo metastasis model that preserves the biologic features of human metastases. Results of whole-genome and RNA sequencing establish that our in vivo PDO metastasis model can be used to study clonality and tumor evolution and to identify biomarkers related to organotropism. Investigation of the response of KRASG12C PDOs to sotorasib demonstrates that the model can examine the efficacy of treatments to suppress metastasis and identify mechanisms of drug resistance. Finally, our PDO model cocultured with autologous peripheral blood mononuclear cells can potentially be used to determine the optimal immune-priming strategy for individual patients with LUAD.

The SRC-family serves as a therapeutic target in triple negative breast cancer with acquired resistance to chemotherapy

BACKGROUND

Resistance to chemotherapy, combined with heterogeneity among resistant tumors, represents a significant challenge in the clinical management of triple negative breast cancer (TNBC). By dissecting molecular pathways associated with treatment resistance, we sought to define patient sub-groups and actionable targets for next-line treatment.

METHODS

Bulk RNA sequencing and reverse phase protein array profiling were performed on isogenic patient-derived xenografts (PDX) representing paclitaxel-sensitive and -resistant tumors. Pathways identified as upregulated in the resistant model were further explored as targets in PDX explants. Their clinical relevance was assessed in two distinct patient cohorts (NeoAva and MET500).

RESULTS

Increased activity in signaling pathways involving SRC-family kinases (SFKs)- and MAPK/ERK was found in treatment resistant PDX, with targeted inhibitors being significantly more potent in resistant tumors. Up-regulation of SFKs- and MAPK/ERK-pathways was also detected in a sub-group of chemoresistant patients after neoadjuvant treatment. Furthermore, High SFK expression (of either SRC, FYN and/or YES1) was detected in metastatic lesions of TNBC patients with fast progressing disease (median disease-free interval 27 vs 105 months).

CONCLUSIONS

Upregulation of SFK-signaling is found in a subset of chemoresistant tumors and is persistent in metastatic lesions. Based on pre-clinical results, these patients may respond favorably to treatment targeting SFKs.

AKT and EZH2 inhibitors kill TNBCs by hijacking mechanisms of involution

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and has the highest rate of recurrence1. The predominant standard of care for advanced TNBC is systemic chemotherapy with or without immunotherapy; however, responses are typically short lived1,2. Thus, there is an urgent need to develop more effective treatments. Components of the PI3K pathway represent plausible therapeutic targets; more than 70% of TNBCs have alterations in PIK3CA, AKT1 or PTEN3-6. However, in contrast to hormone-receptor-positive tumours, it is still unclear whether or how triple-negative disease will respond to PI3K pathway inhibitors7. Here we describe a promising AKT-inhibitor-based therapeutic combination for TNBC. Specifically, we show that AKT inhibitors synergize with agents that suppress the histone methyltransferase EZH2 and promote robust tumour regression in multiple TNBC models in vivo. AKT and EZH2 inhibitors exert these effects by first cooperatively driving basal-like TNBC cells into a more differentiated, luminal-like state, which cannot be effectively induced by either agent alone. Once TNBCs are differentiated, these agents kill them by hijacking signals that normally drive mammary gland involution. Using a machine learning approach, we developed a classifier that can be used to predict sensitivity. Together, these findings identify a promising therapeutic strategy for this highly aggressive tumour type and illustrate how deregulated epigenetic enzymes can insulate tumours from oncogenic vulnerabilities. These studies also reveal how developmental tissue-specific cell death pathways may be co-opted for therapeutic benefit.

OrgXenomics: an integrated proteomic knowledge base for patient-derived organoid and xenograft

Patient-derived models (PDMs, particularly organoids and xenografts) are irreplaceable tools for precision medicine, from target development to lead identification, then to preclinical evaluation, and finally to clinical decision-making. So far, PDM-based proteomics has emerged to be one of the cutting-edge directions and massive data have been accumulated. However, such PDM-based proteomic data have not been provided by any of the available databases, and proteomics profiles of all proteins in proteomic study are also completely absent from existing databases. Herein, an integrated database named 'OrgXenomics' was thus developed to provide the proteomic data for PDMs, which was unique in (a) explicitly describing the establishment detail for a wide array of models, (b) systematically providing the proteomic profiles (expression/function/interaction) for all proteins in studied proteomic analysis and (c) comprehensively giving the raw data for diverse organoid/xenograft-based proteomic studies of various diseases. Our OrgXenomics was expected to server as one good complement to existing proteomic databases, and had great implication for the practice of precision medicine, which could be accessed at: https://idrblab.org/orgxenomics/.

The landscape of drug sensitivity and resistance in sarcoma

Sarcomas are rare malignancies with over 100 distinct histological subtypes. Their rarity and heterogeneity pose significant challenges to identifying effective therapies, and approved regimens show varied responses. Novel, personalized approaches to therapy are needed to improve patient outcomes. Patient-derived tumor organoids (PDTOs) model tumor behavior across an array of malignancies. We leverage PDTOs to characterize the landscape of drug resistance and sensitivity in sarcoma, collecting 194 specimens from 126 patients spanning 24 distinct sarcoma subtypes. Our high-throughput organoid screening pipeline tested single agents and combinations, with results available within a week from surgery. Drug sensitivity correlated with clinical features such as tumor subtype, treatment history, and disease trajectory. PDTO screening can facilitate optimal drug selection and mirror patient outcomes in sarcoma. We could identify at least one FDA-approved or NCCN-recommended effective regimen for 59% of the specimens, demonstrating the potential of our pipeline to provide actionable treatment information.

Human breast tissue engineering in health and disease

The human mammary gland represents a highly organized and dynamic tissue, uniquely characterized by postnatal developmental cycles. During pregnancy and lactation, it undergoes extensive hormone-stimulated architectural remodeling, culminating in the formation of specialized structures for milk production to nourish offspring. Moreover, it carries significant health implications, due to the high prevalence of breast cancer. Therefore, gaining insight into the unique biology of the mammary gland can have implications for managing breast cancer and promoting the well-being of both women and infants. Tissue engineering techniques hold promise to narrow the translational gap between existing breast models and clinical outcomes. Here, we provide an overview of the current landscape of breast tissue engineering, outline key requirements, and the challenges to overcome for achieving more predictive human breast models. We propose methods to validate breast function and highlight preclinical applications for improved understanding and targeting of breast cancer. Beyond mammary gland physiology, representative human breast models can offer new insight into stem cell biology and developmental processes that could extend to other organs and clinical contexts.

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

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

Organoids: development and applications in disease models, drug discovery, precision medicine, and regenerative medicine

Organoids are miniature, highly accurate representations of organs that capture the structure and unique functions of specific organs. Although the field of organoids has experienced exponential growth, driven by advances in artificial intelligence, gene editing, and bioinstrumentation, a comprehensive and accurate overview of organoid applications remains necessary. This review offers a detailed exploration of the historical origins and characteristics of various organoid types, their applications-including disease modeling, drug toxicity and efficacy assessments, precision medicine, and regenerative medicine-as well as the current challenges and future directions of organoid research. Organoids have proven instrumental in elucidating genetic cell fate in hereditary diseases, infectious diseases, metabolic disorders, and malignancies, as well as in the study of processes such as embryonic development, molecular mechanisms, and host-microbe interactions. Furthermore, the integration of organoid technology with artificial intelligence and microfluidics has significantly advanced large-scale, rapid, and cost-effective drug toxicity and efficacy assessments, thereby propelling progress in precision medicine. Finally, with the advent of high-performance materials, three-dimensional printing technology, and gene editing, organoids are also gaining prominence in the field of regenerative medicine. Our insights and predictions aim to provide valuable guidance to current researchers and to support the continued advancement of this rapidly developing field.

Single-cell transcriptional atlas of human breast cancers and model systems

BACKGROUND

Breast cancer's complex transcriptional landscape requires an improved understanding of cellular diversity to identify effective treatments. The study of genetic variations among breast cancer subtypes at single-cell resolution has potential to deepen our insights into cancer progression.

METHODS

In this study, we amalgamate single-cell RNA sequencing data from patient tumours and matched lymph metastasis, reduction mammoplasties, breast cancer patient-derived xenografts (PDXs), PDX-derived organoids (PDXOs), and cell lines resulting in a diverse dataset of 117 samples with 506 719 total cells. These samples encompass hormone receptor positive (HR+), human epidermal growth factor receptor 2 positive (HER2+), and triple-negative breast cancer (TNBC) subtypes, including isogenic model pairs. Herein, we delineated similarities and distinctions across models and patient samples and explore therapeutic drug efficacy based on subtype proportions.

RESULTS

PDX models more closely resemble patient samples in terms of tumour heterogeneity and cell cycle characteristics when compared with TNBC cell lines. Acquired drug resistance was associated with an increase in basal-like cell proportions within TNBC PDX tumours as defined with SCSubtype and TNBCtype cell typing predictors. All patient samples contained a mixture of subtypes; compared to primary tumours HR+ lymph node metastases had lower proportions of HER2-Enriched cells. PDXOs exhibited differences in metabolic-related transcripts compared to PDX tumours. Correlative analyses of cytotoxic drugs on PDX cells identified therapeutic efficacy was based on subtype proportion.

CONCLUSIONS

We present a substantial multimodel dataset, a dynamic approach to cell-wise sample annotation, and a comprehensive interrogation of models within systems of human breast cancer. This analysis and reference will facilitate informed decision-making in preclinical research and therapeutic development through its elucidation of model limitations, subtype-specific insights and novel targetable pathways.

KEY POINTS

Patient-derived xenografts models more closely resemble patient samples in tumour heterogeneity and cell cycle characteristics when compared with cell lines. 3D organoid models exhibit differences in metabolic profiles compared to their in vivo counterparts. A valuable multimodel reference dataset that can be useful in elucidating model differences and novel targetable pathways.

The Use of Patient-Derived Organoids in the Study of Molecular Metabolic Adaptation in Breast Cancer

Around 13% of women will likely develop breast cancer during their lifetime. Advances in cancer metabolism research have identified a range of metabolic reprogramming events, such as altered glucose and amino acid uptake, increased reliance on glycolysis, and interactions with the tumor microenvironment (TME), all of which present new opportunities for targeted therapies. However, studying these metabolic networks is challenging in traditional 2D cell cultures, which often fail to replicate the three-dimensional architecture and dynamic interactions of real tumors. To address this, organoid models have emerged as powerful tools. Tumor organoids are 3D cultures, often derived from patient tissue, that more accurately mimic the structural and functional properties of actual tumor tissues in vivo, offering a more realistic model for investigating cancer metabolism. This review explores the unique metabolic adaptations of breast cancer and discusses how organoid models can provide deeper insights into these processes. We evaluate the most advanced tools for studying cancer metabolism in three-dimensional culture models, including optical metabolic imaging (OMI), matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), and recent advances in conventional techniques applied to 3D cultures. Finally, we explore the progress made in identifying and targeting potential therapeutic targets in breast cancer metabolism.

Divergent iron regulatory states contribute to heterogeneity in breast cancer aggressiveness

Contact with dense collagen I (Col1) can induce collective invasion of triple negative breast cancer (TNBC) cells and transcriptional signatures linked to poor patient prognosis. However, this response is heterogeneous and not well understood. Using phenotype-guided sequencing analysis of invasive vs. noninvasive subpopulations, we show that these two phenotypes represent opposite sides of the iron response protein 1 (IRP1)-mediated response to cytoplasmic labile iron pool (cLIP) levels. Invasive cells upregulate iron uptake and utilization machinery characteristic of a low cLIP response, which includes contractility regulating genes that drive migration. Non-invasive cells upregulate iron sequestration machinery characteristic of a high cLIP response, which is accompanied by upregulation of actin sequestration genes. These divergent IRP1 responses result from Col1-induced transient expression of heme oxygenase I (HO-1), which cleaves heme and releases iron. These findings lend insight into the emerging theory that heme and iron fluxes regulate TNBC aggressiveness.

Mcam stabilizes a luminal progenitor-like breast cancer cell state via Ck2 control and Src/Akt/Stat3 attenuation

Cell state control is crucial for normal tissue development and cancer cell mimicry of stem/progenitor states, contributing to tumor heterogeneity, therapy resistance, and progression. Here, we demonstrate that the cell surface glycoprotein Mcam maintains the tumorigenic luminal progenitor (LP)-like epithelial cell state, leading to Basal-like mammary cancers. In the Py230 mouse mammary carcinoma model, Mcam knockdown (KD) destabilized the LP state by deregulating the Ck2/Stat3 axis, causing a switch to alveolar and basal states, loss of an estrogen-sensing subpopulation, and resistance to tamoxifen-an effect reversed by Ck2 and Stat3 inhibitors. In vivo, Mcam KD blocked generation of Basal-like tumors and Sox10+Krt14+ cells. In human tumors, MCAM loss was largely exclusive of the Basal-like subtype, linked instead to proliferative Luminal subtypes, including often endocrine-resistant Luminal B cancers. This study has implications for developing therapies targeting MCAM, CK2, and STAT3 and their likely effective contexts.

DrugMAP 2.0: molecular atlas and pharma-information of all drugs

The escalating costs and high failure rates have decelerated the pace of drug development, which amplifies the research interests in developing combinatorial/repurposed drugs and understanding off-target adverse drug reaction (ADR). In other words, it is demanded to delineate the molecular atlas and pharma-information for the combinatorial/repurposed drugs and off-target interactions. However, such invaluable data were inadequately covered by existing databases. In this study, a major update was thus conducted to the DrugMAP, which accumulated (a) 20831 combinatorial drugs and their interacting atlas involving 1583 pharmacologically important molecules; (b) 842 repurposed drugs and their interacting atlas with 795 molecules; (c) 3260 off-targets relevant to the ADRs of 2731 drugs and (d) various types of pharmaceutical information, including diverse ADMET properties, versatile diseases, and various ADRs/off-targets. With the growing demands for discovering combinatorial/repurposed therapies and the rapidly emerging interest in AI-based drug discovery, DrugMAP was highly expected to act as an indispensable supplement to existing databases facilitating drug discovery, which was accessible at: https://idrblab.org/drugmap/.

Three-dimensional analysis of mitochondria in a patient-derived xenograft model of triple negative breast cancer reveals mitochondrial network remodeling following chemotherapy treatments

Mitochondria are hubs of metabolism and signaling and play an important role in tumorigenesis, therapeutic resistance, and metastasis in many cancer types. Various laboratory models of cancer demonstrate the extraordinary dynamics of mitochondrial structure, but little is known about the role of mitochondrial structure in resistance to anticancer therapy. We previously demonstrated the importance of mitochondrial structure and oxidative phosphorylation in the survival of chemotherapy-refractory triple negative breast cancer (TNBC) cells. As TNBC is a highly aggressive breast cancer subtype with few targeted therapy options, conventional chemotherapies remain the backbone of early TNBC treatment. Unfortunately, approximately 45% of TNBC patients retain substantial residual tumor burden following chemotherapy, associated with abysmal prognoses. Using an orthotopic patient-derived xenograft mouse model of human TNBC, we compared mitochondrial structures between treatment-naïve tumors and residual tumors after conventional chemotherapeutics were administered singly or in combination. We reconstructed 1,750 mitochondria in three dimensions from serial block-face scanning electron micrographs, providing unprecedented insights into the complexity and intra-tumoral heterogeneity of mitochondria in TNBC. Following exposure to carboplatin or docetaxel given individually, residual tumor mitochondria exhibited significant increases in mitochondrial complexity index, area, volume, perimeter, width, and length relative to treatment-naïve tumor mitochondria. In contrast, residual tumors exposed to those chemotherapies given in combination exhibited diminished mitochondrial structure changes. Further, we document extensive intra-tumoral heterogeneity of mitochondrial structure, especially prior to chemotherapeutic exposure. These results highlight the potential for structure-based monitoring of chemotherapeutic responses and reveal potential molecular mechanisms that underlie chemotherapeutic resistance in TNBC.

HIV-protease inhibitors potentiate the activity of carfilzomib in triple-negative breast cancer

BACKGROUND

Resistance to chemotherapy is a major problem in the treatment of patients with triple-negative breast cancer (TNBC). Preclinical data suggest that TNBC is dependent on proteasomes; however, clinical observations indicate that the efficacy of proteasome inhibitors in TNBC may be limited, suggesting the need for combination therapies.

METHODS

We compared bortezomib and carfilzomib and their combinations with nelfinavir and lopinavir in TNBC cell lines and primary cells with regard to their cytotoxic activity, functional proteasome inhibition, and induction of the unfolded protein response (UPR). Furthermore, we evaluated the involvement of sXBP1, ABCB1, and ABCG2 in the cytotoxic activity of drug combinations.

RESULTS

Carfilzomib, via proteasome β5 + β2 inhibition, is more cytotoxic in TNBC than bortezomib, which inhibits β5 + β1 proteasome subunits. The cytotoxicity of carfilzomib was significantly potentiated by nelfinavir or lopinavir. Carfilzomib with lopinavir induced endoplasmic reticulum stress and pro-apoptotic UPR through the accumulation of excess proteasomal substrate protein in TNBC in vitro. Moreover, lopinavir increased the intracellular availability of carfilzomib by inhibiting carfilzomib export from cells that express high levels and activity of ABCB1, but not ABCG2.

CONCLUSION

Proteasome inhibition by carfilzomib combined with nelfinavir/lopinavir represents a potential treatment option for TNBC, warranting further investigation.

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.

Gastric Cancer Assembloids Derived from Patient-Derived Xenografts: A Preclinical Model for Therapeutic Drug Screening

The construction of reliable preclinical models is crucial for understanding the molecular mechanisms involved in gastric cancer and for advancing precision medicine. Currently, existing in vitro tumor models often do not accurately replicate the human gastric cancer environment and are unsuitable for high-throughput therapeutic drug screening. In this study, droplet microfluidic technology is employed to create novel gastric cancer assembloids by encapsulating patient-derived xenograft gastric cancer cells and patient stromal cells in Gelatin methacryloyl (GelMA)-Gelatin-Matrigel microgels. The usage of GelMA-Gelatin-Matrigel composite hydrogel effectively alleviated cell aggregation and sedimentation during the assembly process, allowing for the handling of large volumes of cell-laden hydrogel and the uniform generation of assembloids in a high-throughput manner. Notably, the patient-derived xenograft assembloids exhibited high consistency with primary tumors at both transcriptomic and histological levels, and can be efficiently scaled up for preclinical drug screening efforts. Furthermore, the drug screening results clearly demonstrated that the in vitro assembloid model closely mirrored in vivo drug responses. Thus, these findings suggest that gastric cancer assembloids, which effectively replicate the in vivo tumor microenvironment, show promise for enabling more precise high-throughput drug screening and predicting the clinical outcomes of various drugs.

OBSERVE: guidelines for the refinement of rodent cancer models

Existing guidelines on the preparation (Planning Research and Experimental Procedures on Animals: Recommendations for Excellence (PREPARE)) and reporting (Animal Research: Reporting of In Vivo Experiments (ARRIVE)) of animal experiments do not provide a clear and standardized approach for refinement during in vivo cancer studies, resulting in the publication of generic methodological sections that poorly reflect the attempts made at accurately monitoring different pathologies. Compliance with the 3Rs guidelines has mainly focused on reduction and replacement; however, refinement has been harder to implement. The Oncology Best-practices: Signs, Endpoints and Refinements for in Vivo Experiments (OBSERVE) guidelines are the result of a European initiative supported by EurOPDX and INFRAFRONTIER, and aim to facilitate the refinement of studies using in vivo cancer models by offering robust and practical recommendations on approaches to research scientists and animal care staff. We listed cancer-specific clinical signs as a reference point and from there developed sets of guidelines for a wide variety of rodent models, including genetically engineered models and patient derived xenografts. In this Consensus Statement, we systematically and comprehensively address refinement and monitoring approaches during the design and execution of murine cancer studies. We elaborate on the appropriate preparation of tumor-initiating biologicals and the refinement of tumor-implantation methods. We describe the clinical signs to monitor associated with tumor growth, the appropriate follow-up of animals tailored to varying clinical signs and humane endpoints, and an overview of severity assessment in relation to clinical signs, implantation method and tumor characteristics. The guidelines provide oncology researchers clear and robust guidance for the refinement of in vivo cancer models.

Precision oncology: current and future platforms for treatment selection

Genomic profiling of hundreds of cancer-associated genes is now a component of routine cancer care. DNA sequencing can identify mutations, mutational signatures, and structural alterations predictive of therapy response and assess for heritable cancer risk, but it has been less useful for identifying predictive biomarkers of sensitivity to cytotoxic chemotherapies, antibody drug conjugates, and immunotherapies. The clinical adoption of molecular profiling platforms such as RNA sequencing better suited to identifying those patients most likely to respond to immunotherapies and drug combinations will be critical to expanding the benefits of precision oncology. This review discusses the potential advantages of innovative molecular and functional profiling platforms designed to replace or complement targeted DNA sequencing and the major hurdles to their clinical adoption.

XENTURION is a population-level multidimensional resource of xenografts and tumoroids from metastatic colorectal cancer patients

The breadth and depth at which cancer models are interrogated contribute to the successful clinical translation of drug discovery efforts. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, where experimental therapies are typically tested. Here we introduce XENTURION, an open-science resource offering a platform of 128 PDX models from patients with metastatic CRC, along with matched PDX-derived tumoroids. Multidimensional omics analyses indicate that tumoroids retain extensive molecular fidelity with parental PDXs. A tumoroid-based trial with the anti-EGFR antibody cetuximab reveals variable sensitivities that are consistent with clinical response biomarkers, mirror tumor growth changes in matched PDXs, and recapitulate EGFR genetic deletion outcomes. Inhibition of adaptive signals upregulated by EGFR blockade increases the magnitude of cetuximab response. These findings illustrate the potential of large living biobanks, providing avenues for molecularly informed preclinical research in oncology.

Application and prospect of organoid technology in breast cancer

Breast cancer is the most common malignant tumor in women. Due to the high heterogeneity of breast cancer cells, traditional in vitro research models still have major limitations. Therefore, it is urgent to establish an experimental model that can accurately simulate the characteristics of human breast cancer. Breast cancer organoid technology emerged as the times required, that is, to construct tissue analogs with organ characteristics by using a patient's tumor tissue through 3D culture in vitro. Since the breast cancer organoid can fully preserve the histology and genetic characteristics of the original tumor, it provides a reliable model for preclinical drug screening, establishment of breast cancer organoid biobanks, research into the mechanisms of tumor development, and determination of cancer targets. It has promoted personalized treatment for clinical breast cancer patients. This article mainly focuses on recent research progress and applications of organoid technology in breast cancer, discussing the current limitations and prospects of breast cancer organoid technology.

Clinical efficacy of tumor organoid-guided cancer therapy for locally advanced unresectable or metastatic breast cancer

Patient-derived organoids (PDOs) may facilitate treatment selection. This retrospective cohort study evaluated the feasibility and clinical benefit of using PDOs to guide personalized treatment in metastatic breast cancer (MBC). Patients diagnosed with MBC were recruited between January 2019 and August 2022. PDOs were established and the efficacy of customized drug panels was determined by measuring cell mortality after drug exposure. Patients receiving organoid-guided treatment (OGT) were matched 1:2 by nearest neighbor propensity scores with patients receiving treatment of physician's choice (TPC). The primary outcome was progression-free survival. Secondary outcomes included objective response rate and disease control rate. Targeted gene sequencing and pathway enrichment analysis were performed. Forty-six PDOs (46 of 51, 90.2%) were generated from 45 MBC patients. PDO drug screening showed an accuracy of 78.4% (95% CI 64.9%-91.9%) in predicting clinical responses. Thirty-six OGT patients were matched to 69 TPC patients. OGT was associated with prolonged median progression-free survival (11.0 months vs. 5.0 months; hazard ratio 0.53 [95% CI 0.33-0.85]; p = .01) and improved disease control (88.9% vs. 63.8%; odd ratio 4.26 [1.44-18.62]) compared with TPC. The objective response rate of both groups was similar. Pathway enrichment analysis in hormone receptor-positive, human epidermal growth factor receptor 2-negative patients demonstrated differentially modulated pathways implicated in DNA repair and transcriptional regulation in those with reduced response to capecitabine/gemcitabine, and pathways associated with cell cycle regulation in those with reduced response to palbociclib. Our study shows that PDO-based functional precision medicine is a feasible and effective strategy for MBC treatment optimization and customization.

DSBSO-Based XL-MS Analysis of Breast Cancer PDX Tissues to Delineate Protein Interaction Network in Clinical Samples

Protein-protein interactions (PPIs) are fundamental to understanding biological systems as protein complexes are the active molecular modules critical for carrying out cellular functions. Dysfunctional PPIs have been associated with various diseases including cancer. Systems-wide PPI analysis not only sheds light on pathological mechanisms, but also represents a paradigm in identifying potential therapeutic targets. In recent years, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for defining endogenous PPIs of cellular networks. While proteome-wide studies have been performed in cell lysates, intact cells and tissues, applications of XL-MS in clinical samples have not been reported. In this study, we adopted a DSBSO-based in vivo XL-MS platform to map interaction landscapes from two breast cancer patient-derived xenograft (PDX) models. As a result, we have generated a PDX interaction network comprising 2,557 human proteins and identified interactions unique to breast cancer subtypes. Interestingly, most of the observed differences in PPIs correlated well with protein abundance changes determined by TMT-based proteome quantitation. Collectively, this work has demonstrated the feasibility of XL-MS analysis in clinical samples, and established an analytical workflow for tissue cross-linking that can be generalized for mapping PPIs from patient samples in the future to dissect disease-relevant cellular networks.

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.

In vitro co-culture models for studying organoids-macrophages interaction: the golden technology of cancer immunotherapy

Macrophages, as the largest immune cell group in tumour tissues, play a crucial role in influencing various malignant behaviours of tumour cells and tumour immune evasion. As the research on macrophages and cancer immunotherapy develops, the importance of appropriate research models becomes increasingly evident. The development of organoids has bridged the gap between traditional two-dimensional (2D) cultures and animal experiments. Recent studies have demonstrated that organoids exhibit similar physiological characteristics to the source tissue and closely resemble the in vivo genome and molecular markers of the source tissue or organ. However, organoids still lack an immune component. Developing a co-culture model of organoids and macrophages is crucial for studying the interaction and mechanisms between tumour cells and macrophages. This paper presents an overview of the establishment of co-culture models, the current research status of organoid macrophage interactions, and the current status of immunotherapy. In addition, the application prospects and shortcomings of the model are explained. Ultimately, it is hoped that the co-culture model will offer a preclinical testing platform for maximising a precise cancer immunotherapy strategy.

O-GlcNAcylation of MITF regulates its activity and CDK4/6 inhibitor resistance in breast cancer

Cyclin-dependent kinases 4 and 6 (CDK4/6) play a pivotal role in cell cycle and cancer development. Targeting CDK4/6 has demonstrated promising effects against breast cancer. However, resistance to CDK4/6 inhibitors (CDK4/6i), such as palbociclib, remains a substantial challenge in clinical settings. Using high-throughput combinatorial drug screening and genomic sequencing, we find that the microphthalmia-associated transcription factor (MITF) is activated via O-GlcNAcylation by O-GlcNAc transferase (OGT) in palbociclib-resistant breast cancer cells and tumors. Mechanistically, O-GlcNAcylation of MITF at Serine 49 enhances its interaction with importin α/β, thus promoting its translocation to nuclei, where it suppresses palbociclib-induced senescence. Inhibition of MITF or its O-GlcNAcylation re-sensitizes resistant cells to palbociclib. Moreover, clinical studies confirm the activation of MITF in tumors from patients who are palbociclib-resistant or undergoing palbociclib treatment. Collectively, our studies shed light on the mechanism regulating palbociclib resistance and present clinical evidence for developing therapeutic approaches to treat CDK4/6i-resistant breast cancer patients.

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.

Organoid Cultures for the Study of Mammary Biology and Breast Cancer: The Promise and Challenges

During the last decade, biomedical research has experienced a resurgence in the use of three-dimensional culture models for studies of normal and cancer biology. This resurgence has been driven by the development of models in which primary cells are grown in tissue-mimicking media and extracellular matrices to create organoid or organotypic cultures that more faithfully replicate the complex architecture and physiology of normal tissues and tumors. In addition, patient-derived tumor organoids preserve the three-dimensional organization and characteristics of the patient tumors ex vivo, becoming excellent preclinical models to supplement studies of tumor xenografts transplanted into immunocompromised mice. In this perspective, we provide an overview of how organoids are being used to investigate normal mammary biology and as preclinical models of breast cancer and discuss improvements that would enhance their utility and relevance to the field.

TOWARDS Study: Patient-Derived Xenograft Engraftment Predicts Poor Survival in Patients With Newly Diagnosed Triple-Negative Breast Cancer

PURPOSE

Assessing risk of recurrence for nonmetastatic triple-negative breast cancer (TNBC) is a key determinant of therapeutic strategy. The best predictor of recurrence risk is failure to achieve a pathologic complete response after preoperative chemotherapy, but it imperfectly correlates with the definitive end points of relapse-free and overall survival (OS). The inability to accurately predict recurrence has led to increasingly toxic treatment regimens for patients with early-stage TNBC. Better assays for recurrence risk are needed to tailor aggressive therapy for patients who need it and avoid overtreatment and unnecessary toxicity for those at low risk. The purpose of this study was to determine if patient-derived xenograft (PDX) engraftment of newly diagnosed breast tumors can serve as an accurate predictor of recurrence and death from breast cancer.

METHODS

This study was a blinded noninterventional trial comprising 80 patients with newly diagnosed, nonmetastatic, estrogen receptor (ER)-negative or ER-low breast cancer.

RESULTS

PDX engraftment was strongly associated with relapse in 1 year: 8 of 18 (44.4%) patients whose tumors engrafted relapsed versus 1 of 62 (1.6%) patients whose tumors did not engraft (P < .0001). Patients whose tumors engrafted had a hazard ratio (HR) for relapse of 17.5. HRs for OS and breast cancer-specific survival in PDX+ patients were 21.1 and 39.5, respectively.

CONCLUSION

We report that the ability of a tumor to engraft as a PDX predicts early recurrence by serving as a functional readout of aggressiveness and prospectively identifies the most devastating tumors. This provides new opportunity to develop surrogate assays, such as biomarkers of engraftment, which will extend the clinical feasibility of this finding.

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.

Advances in Organoid Technology: A Focus on Corneal Limbal Organoids

Organoid technology provides a versatile platform for simulating organogenesis, investigating disease pathogenesis, and exploring therapeutic interventions. Among various types of organoids that have been developed, corneal limbal organoids, the three-dimensional miniaturized corneas which are derived from either pluripotent stem cells or limbal epithelial stem cells, are particularly promising for clinical translation. This narrative review summarized the state-of-the-art in corneal limbal organoids research including the cultivation methods, clinical relevance and its limitations and challenges. The potential of corneal limbal organoids in mimicking corneal development, disease modelling, drug screening, and regenerative medicine was discussed. Technical improvements in cultivation techniques, imaging modalities, and gene editing tools are anticipated to overcome current limitations and further promote its clinical potential. Despite challenges and difficulties, the development of corneal limbal organoids opens a new era of regenerative medicine and provides a potential source of stem cell replacement therapies for challenging corneal diseases with the establishment of an in vitro corneal limbal organoid bank.

Current trends and research topics regarding organoids: A bibliometric analysis of global research from 2000 to 2023

The use of animal models for biological experiments is no longer sufficient for research related to human life and disease. The development of organ tissues has replaced animal models by mimicking the structure, function, development and homeostasis of natural organs. This provides more opportunities to study human diseases such as cancer, infectious diseases and genetic disorders. In this study, bibliometric methods were used to analyze organoid-related articles published over the last 20+ years to identify emerging trends and frontiers in organoid research. A total of 13,143 articles from 4125 institutions in 86 countries or regions were included in the analysis. The number of papers increased steadily over the 20-year period. The United States was the leading country in terms of number of papers and citations. Harvard Medical School had the highest number of papers published. Keyword analysis revealed research trends and focus areas such as organ tissues, stem cells, 3D culture and tissue engineering. In conclusion, this study used bibliometric and visualization methods to explore the field of organoid research and found that organ tissues are receiving increasing attention in areas such as cancer, drug discovery, personalized medicine, genetic disease modelling and gene repair, making them a current research hotspot and a future research trend.

Rat Models of Hormone Receptor-Positive Breast Cancer

Hormone receptor-positive (HR+) breast cancer (BC) is the most common type of breast cancer among women worldwide, accounting for 70-80% of all invasive cases. Patients with HR+ BC are commonly treated with endocrine therapy, but intrinsic or acquired resistance is a frequent problem, making HR+ BC a focal point of intense research. Despite this, the malignancy still lacks adequate in vitro and in vivo models for the study of its initiation and progression as well as response and resistance to endocrine therapy. No mouse models that fully mimic the human disease are available, however rat mammary tumor models pose a promising alternative to overcome this limitation. Compared to mice, rats are more similar to humans in terms of mammary gland architecture, ductal origin of neoplastic lesions and hormone dependency status. Moreover, rats can develop spontaneous or induced mammary tumors that resemble human HR+ BC. To date, six different types of rat models of HR+ BC have been established. These include the spontaneous, carcinogen-induced, transplantation, hormone-induced, radiation-induced and genetically engineered rat mammary tumor models. Each model has distinct advantages, disadvantages and utility for studying HR+ BC. This review provides a comprehensive overview of all published models to date.

Phase 2 study of neoadjuvant enzalutamide and paclitaxel for luminal androgen receptor-enriched TNBC: Trial results and insights into "ARness"

Luminal androgen receptor (LAR)-enriched triple-negative breast cancer (TNBC) is a distinct subtype. The efficacy of AR inhibitors and the relevant biomarkers in neoadjuvant therapy (NAT) are yet to be determined. We tested the combination of the AR inhibitor enzalutamide (120 mg daily by mouth) and paclitaxel (80 mg/m2 weekly intravenously) (ZT) for 12 weeks as NAT for LAR-enriched TNBC. Eligibility criteria included a percentage of cells expressing nuclear AR by immunohistochemistry (iAR) of at least 10% and a reduction in sonographic volume of less than 70% after four cycles of doxorubicin and cyclophosphamide. Twenty-four patients were enrolled. Ten achieved a pathologic complete response or residual cancer burden-I. ZT was safe, with no unexpected side effects. An iAR of at least 70% had a positive predictive value of 0.92 and a negative predictive value of 0.97 in predicting LAR-enriched TNBC according to RNA-based assays. Our data support future trials of AR blockade in early-stage LAR-enriched TNBC.

A co-culture system of macrophages with breast cancer tumoroids to study cell interactions and therapeutic responses

3D tumoroids have revolutionized in vitro/ex vivo cancer biology by recapitulating the complex diversity of tumors. While tumoroids provide new insights into cancer development and treatment response, several limitations remain. As the tumor microenvironment, especially the immune system, strongly influences tumor development, the absence of immune cells in tumoroids may lead to inappropriate conclusions. Macrophages, key players in tumor progression, are particularly challenging to integrate into the tumoroids. In this study, we established three optimized and standardized methods for co-culturing human macrophages with breast cancer tumoroids: a semi-liquid model and two matrix-embedded models tailored for specific applications. We then tracked interactions and macrophage infiltration in these systems using flow cytometry and light sheet microscopy and showed that macrophages influenced not only tumoroid molecular profiles but also chemotherapy response. This underscores the importance of increasing the complexity of 3D models to more accurately reflect in vivo conditions.

Breast organoid suspension cultures maintain long-term estrogen receptor expression and responsiveness

Organoid cultures offer a powerful technology to investigate many different aspects of development, physiology, and pathology of diverse tissues. Unlike standard tissue culture of primary breast epithelial cells, breast organoids preserve the epithelial lineages and architecture of the normal tissue. However, existing organoid culture methods are tedious, difficult to scale, and do not robustly retain estrogen receptor (ER) expression and responsiveness in long-term culture. Here, we describe a modified culture method to generate and maintain organoids as suspension cultures in reconstituted basement membrane (™Matrigel). This method improves organoid growth and uniformity compared to the conventional Matrigel dome embedding method, while maintaining the fidelity of the three major epithelial lineages. Using this adopted method, we are able to culture and passage purified hormone sensing (HS) cells that retain ER responsiveness upon estrogen stimulation in long-term culture. This culture system presents a valuable platform to study the events involved in initiation and evolution of ER-positive breast cancer.

Early Changes in Tumor-Naive Cell-Free Methylomes and Fragmentomes Predict Outcomes in Pembrolizumab-Treated Solid Tumors

Early kinetics of circulating tumor DNA (ctDNA) in plasma predict response to pembrolizumab but typically requires sequencing of matched tumor tissue or fixed gene panels. We analyzed genome-wide methylation and fragment-length profiles using cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq) in 204 plasma samples from 87 patients before and during treatment with pembrolizumab from a pan-cancer phase II investigator-initiated trial (INSPIRE). We trained a pan-cancer methylation signature using independent methylation array data from The Cancer Genome Atlas to quantify cancer-specific methylation (CSM) and fragment-length score (FLS) for each sample. CSM and FLS are strongly correlated with tumor-informed ctDNA levels. Early kinetics of CSM predict overall survival and progression-free survival, independently of tumor type, PD-L1, and tumor mutation burden. Early kinetics of FLS are associated with overall survival independently of CSM. Our tumor-naïve mutation-agnostic ctDNA approach integrating methylomics and fragmentomics could predict outcomes in patients treated with pembrolizumab.

SIGNIFICANCE

Analysis of methylation and fragment length in plasma using cfMeDIP-seq provides a tumor-naive approach to measure ctDNA with results comparable with a tumor-informed bespoke ctDNA. Early kinetics within the first weeks of treatment in methylation and fragment quantity can predict outcomes with pembrolizumab in patients with various advanced solid tumors. This article is featured in Selected Articles from This Issue, p. 897.

Exploring tumor organoids for cancer treatment

As a life-threatening chronic disease, cancer is characterized by tumor heterogeneity. This heterogeneity is associated with factors that lead to treatment failure and poor prognosis, including drug resistance, relapse, and metastasis. Therefore, precision medicine urgently needs personalized tumor models that accurately reflect the tumor heterogeneity. Currently, tumor organoid technologies are used to generate in vitro 3D tissues, which have been shown to precisely recapitulate structure, tumor microenvironment, expression profiles, functions, molecular signatures, and genomic alterations in primary tumors. Tumor organoid models are important for identifying potential therapeutic targets, characterizing the effects of anticancer drugs, and exploring novel diagnostic and therapeutic options. In this review, we describe how tumor organoids can be cultured and summarize how researchers can use them as an excellent tool for exploring cancer therapies. In addition, we discuss tumor organoids that have been applied in cancer therapy research and highlight the potential of tumor organoids to guide preclinical research.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

Methylation of the chromatin modifier KMT2D by SMYD2 contributes to therapeutic response in hormone-dependent breast cancer

Activating mutations in PIK3CA are frequently found in estrogen-receptor-positive (ER+) breast cancer, and the combination of the phosphatidylinositol 3-kinase (PI3K) inhibitor alpelisib with anti-ER inhibitors is approved for therapy. We have previously demonstrated that the PI3K pathway regulates ER activity through phosphorylation of the chromatin modifier KMT2D. Here, we discovered a methylation site on KMT2D, at K1330 directly adjacent to S1331, catalyzed by the lysine methyltransferase SMYD2. SMYD2 loss attenuates alpelisib-induced KMT2D chromatin binding and alpelisib-mediated changes in gene expression, including ER-dependent transcription. Knockdown or pharmacological inhibition of SMYD2 sensitizes breast cancer cells, patient-derived organoids, and tumors to PI3K/AKT inhibition and endocrine therapy in part through KMT2D K1330 methylation. Together, our findings uncover a regulatory crosstalk between post-translational modifications that fine-tunes KMT2D function at the chromatin. This provides a rationale for the use of SMYD2 inhibitors in combination with PI3Kα/AKT inhibitors in the treatment of ER+/PIK3CA mutant breast cancer.

Advances in the study of gastric organoids as disease models

Gastric organoids are models created in the laboratory using stem cells and sophisticated three-dimensional cell culture techniques. These models have shown great promise in providing valuable insights into gastric physiology and advanced disease research. This review comprehensively summarizes and analyzes the research advances in culture methods and techniques for adult stem cells and induced pluripotent stem cell-derived organoids, and patient-derived organoids. The potential value of gastric organoids in studying the pathogenesis of stomach-related diseases and facilitating drug screening is initially discussed. The construction of gastric organoids involves several key steps, including cell extraction and culture, three-dimensional structure formation, and functional expression. Simulating the structure and function of the human stomach by disease modeling with gastric organoids provides a platform to study the mechanism of gastric cancer induction by Helicobacter pylori. In addition, in drug screening and development, gastric organoids can be used as a key tool to evaluate drug efficacy and toxicity in preclinical trials. They can also be used for precision medicine according to the specific conditions of patients with gastric cancer, to assess drug resistance, and to predict the possibility of adverse reactions. However, despite the impressive progress in the field of gastric organoids, there are still many unknowns that need to be addressed, especially in the field of regenerative medicine. Meanwhile, the reproducibility and consistency of organoid cultures are major challenges that must be overcome. These challenges have had a significant impact on the development of gastric organoids. Nonetheless, as technology continues to advance, we can foresee more comprehensive research in the construction of gastric organoids. Such research will provide better solutions for the treatment of stomach-related diseases and personalized medicine.

Digital droplet PCR analysis of organoids generated from mouse mammary tumors demonstrates proof-of-concept capture of tumor heterogeneity

Breast cancer metastases exhibit many different genetic alterations, including copy number amplifications (CNA). CNA are genetic alterations that are increasingly becoming relevant to breast oncology clinical practice. Here we identify CNA in metastatic breast tumor samples using publicly available datasets and characterize their expression and function using a metastatic mouse model of breast cancer. Our findings demonstrate that our organoid generation can be implemented to study clinically relevant features that reflect the genetic heterogeneity of individual tumors.