Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment

Patient-derived organoids in precision cancer medicine

Organoids are three-dimensional (3D) cultures, normally derived from stem cells, that replicate the complex structure and function of human tissues. They offer a physiologically relevant model to address important questions in cancer research. The generation of patient-derived organoids (PDOs) from various human cancers allows for deeper insights into tumor heterogeneity and spatial organization. Additionally, interrogating non-tumor stromal cells increases the relevance in studying the tumor microenvironment, thereby enhancing the relevance of PDOs in personalized medicine. PDOs mark a significant advancement in cancer research and patient care, signifying a shift toward more innovative and patient-centric approaches. This review covers aspects of PDO cultures to address the modeling of the tumor microenvironment, including extracellular matrices, air-liquid interface and microfluidic cultures, and organ-on-chip. Specifically, the role of PDOs as preclinical models in gene editing, molecular profiling, drug testing, and biomarker discovery and their potential for guiding personalized treatment in clinical practice are discussed.

Cancer Patient-Derived Cell-Based Models: Applications and Challenges in Functional Precision Medicine

The field of oncology has witnessed remarkable progress in personalized cancer therapy. Functional precision medicine has emerged as a promising avenue for achieving superior treatment outcomes by integrating omics profiling and sensitivity testing of patient-derived cancer cells. This review paper provides an in-depth analysis of the evolution of cancer-directed drugs, resistance mechanisms, and the role of functional precision medicine platforms in revolutionizing individualized treatment strategies. Using two-dimensional (2D) and three-dimensional (3D) cell cultures, patient-derived xenograft (PDX) models, and advanced functional assays has significantly improved our understanding of tumor behavior and drug response. This progress will lead to identifying more effective treatments for more patients. Considering the limited eligibility of patients based on a genome-targeted approach for receiving targeted therapy, functional precision medicine provides unprecedented opportunities for customizing medical interventions according to individual patient traits and individual drug responses. This review delineates the current landscape, explores limitations, and presents future perspectives to inspire ongoing advancements in functional precision medicine for personalized cancer therapy.

Insights into metabolic heterogeneity of colorectal cancer gained from fluorescence lifetime imaging

Heterogeneity of tumor metabolism is an important, but still poorly understood aspect of tumor biology. Present work is focused on the visualization and quantification of cellular metabolic heterogeneity of colorectal cancer using fluorescence lifetime imaging (FLIM) of redox cofactor NAD(P)H. FLIM-microscopy of NAD(P)H was performed in vitro in four cancer cell lines (HT29, HCT116, CaCo2 and CT26), in vivo in the four types of colorectal tumors in mice and ex vivo in patients' tumor samples. The dispersion and bimodality of the decay parameters were evaluated to quantify the intercellular metabolic heterogeneity. Our results demonstrate that patients' colorectal tumors have significantly higher heterogeneity of energy metabolism compared with cultured cells and tumor xenografts, which was displayed as a wider and frequently bimodal distribution of a contribution of a free (glycolytic) fraction of NAD(P)H within a sample. Among patients' tumors, the dispersion was larger in the high-grade and early stage ones, without, however, any association with bimodality. These results indicate that cell-level metabolic heterogeneity assessed from NAD(P)H FLIM has a potential to become a clinical prognostic factor.

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.

A 3D Pancreatic Cancer Model with Integrated Optical Sensors for Noninvasive Metabolism Monitoring and Drug Screening

A distinct feature of pancreatic ductal adenocarcinoma (PDAC) is a prominent tumor microenvironment (TME) with remarkable cellular and spatial heterogeneity that meaningfully impacts disease biology and treatment resistance. The dynamic crosstalk between cancer cells and the dense stromal compartment leads to spatially and temporally heterogeneous metabolic alterations, such as acidic pH that contributes to drug resistance in PDAC. Thus, monitoring the extracellular pH metabolic fluctuations within the TME is crucial to predict and to quantify anticancer drug efficacy. Here, a simple and reliable alginate-based 3D PDAC model embedding ratiometric optical pH sensors and cocultures of tumor (AsPC-1) and stromal cells for simultaneously monitoring metabolic pH variations and quantify drug response is presented. By means of time-lapse confocal laser scanning microscopy (CLSM) coupled with a fully automated computational analysis, the extracellular pH metabolic variations are monitored and quantified over time during drug testing with gemcitabine, folfirinox, and paclitaxel, commonly used in PDAC therapy. In particular, the extracellular acidification is more pronounced after drugs treatment, resulting in increased antitumor effect correlated with apoptotic cell death. These findings highlight the importance of studying the influence of cellular metabolic mechanisms on tumor response to therapy in 3D tumor models, this being crucial for the development of personalized medicine approaches.

Patient-derived tumor organoids: a new avenue for preclinical research and precision medicine in oncology

Over the past decade, the emergence of patient-derived tumor organoids (PDTOs) has broadened the repertoire of preclinical models and progressively revolutionized three-dimensional cell culture in oncology. PDTO can be grown from patient tumor samples with high efficiency and faithfully recapitulates the histological and molecular characteristics of the original tumor. Therefore, PDTOs can serve as invaluable tools in oncology research, and their translation to clinical practice is exciting for the future of precision medicine in oncology. In this review, we provide an overview of methods for establishing PDTOs and their various applications in cancer research, starting with basic research and ending with the identification of new targets and preclinical validation of new anticancer compounds and precision medicine. Finally, we highlight the challenges associated with the clinical implementation of PDTO, such as its representativeness, success rate, assay speed, and lack of a tumor microenvironment. Technological developments and autologous cocultures of PDTOs and stromal cells are currently ongoing to meet these challenges and optimally exploit the full potential of these models. The use of PDTOs as standard tools in clinical oncology could lead to a new era of precision oncology in the coming decade.

Clinicopathological Factors as Predictors for Establishment of Patient Derived Head and Neck Squamous Cell Carcinoma Organoids

INTRODUCTION

Patient derived organoids (PDOs) are 3D in vitro models and have shown to better reflect patient and tumor heterogeneity than conventional 2D cell lines. To utilize PDOs in clinical settings and trials for biomarker discovery or drug response evaluation, it is valuable to determine the best way to optimize sample selection for maximum PDO establishment. In this study, we assess patient, tumor and tissue sampling factors and correlate them with successful PDO establishment in a well-documented cohort of patients with head and neck squamous cell carcinoma (HNSCC).

METHODS

Tumor and non-tumorous adjacent tissue samples were obtained from HNSCC patients during routine biopsy or resection procedures at the University Medical Center Utrecht. The tissue was subsequently processed to establish PDOs. The sample purity was determined as the presence of epithelial cells in the culture on the day of organoid isolation as visualized microscopically by the researcher. PDO establishment was recorded for all samples. Clinical data was obtained from the medical records and was correlated to PDO establishment and presence of epithelial cells.

RESULTS

Organoids could be established in 133/250 (53.2%) primary tumor site tissues. HNSCC organoid establishment tended to be more successful if patients were younger than the median age of 68 years (74/123 (60.2%) vs. 59/127 (46.5%), p = 0.03). For a subset of samples, the presence of epithelial cells in the organoid culture on the day of organoid isolation was recorded in 112/149 (75.2%) of these samples. When cultures were selected for presence of epithelial cells, organoid establishment increased to 76.8% (86/112 samples).

CONCLUSION

This study found a trend between age and successful organoid outgrowth in patients with HNSCC younger than 68 years and emphasizes the value of efficient sampling regarding PDO establishment.

Organoids for Functional Precision Medicine in Advanced Pancreatic Cancer

BACKGROUND & AIMS

Patient-derived organoids (PDOs) are promising tumor avatars that could enable ex vivo drug tests to personalize patients' treatments in the frame of functional precision oncology. However, clinical evidence remains scarce. This study aims to evaluate whether PDOs can be implemented in clinical practice to benefit patients with advanced refractory pancreatic ductal adenocarcinoma (PDAC).

METHODS

During 2021 to 2022, 87 patients were prospectively enrolled in an institutional review board-approved protocol. Inclusion criteria were histologically confirmed PDAC with the tumor site accessible. A panel of 25 approved antitumor therapies (chemogram) was tested and compared to patient responses to assess PDO predictive values and map the drug sensitivity landscape in PDAC.

RESULTS

Fifty-four PDOs were generated from 87 pretreated patients (take-on rate, 62%). The main PDO mutations were KRAS (96%), TP53 (88%), and CDKN2A/B (22%), with a 91% concordance rate with their tumor of origin. The mean turnaround time to chemogram was 6.8 weeks. In 91% of cases, ≥1 hit was identified (gemcitabine (n = 20 of 54), docetaxel (n = 18 of 54), and vinorelbine (n = 17 of 54), with a median of 3 hits/patient (range, 0-12). Our cohort included 34 evaluable patients with full clinical follow-up. We report a chemogram sensitivity of 83.3% and specificity of 92.9%. The overall response rate and progression-free survival were higher when patients received a hit treatment as compared to patients who received a nonhit drug (as part of routine management). Finally, we leveraged our PDO collection as a platform for drug validation and combo identification. We tested anti-KRASG12D (MRTX1133), alone or combined, and identified a specific synergy with anti-EGFR therapies in KRASG12D variants.

CONCLUSIONS

We report the largest prospective study aiming at implementing PDO-based functional precision oncology and identify very robust predictive values in this clinical setting. In a clinically relevant turnaround time, we identify putative hits for 91% of patients, providing unexpected potential survival benefits in this very aggressive indication. Although this remains to be confirmed in interventional precision oncology trials, PDO collection already provides powerful opportunities for drugs and combinatorial treatment development.

EUS-guided biopsies versus surgical specimens for establishing patient-derived pancreatic cancer organoids: a systematic review and meta-analysis

BACKGROUND AND AIMS

Patient-derived tumor organoids (PDTOs) are a promising new disease model in pancreatic cancer for use in personalized medicine. However, the overall success rate (SR) of establishing these cultures from EUS-guided biopsies is unknown.

METHODS

We searched relevant database publications reporting SRs of PDTO establishment from pancreatic cancer. The primary outcome was SR stratified on tissue acquisition method (EUS-guided biopsies, percutaneous biopsies, and surgical specimens).

RESULTS

Twenty-four studies were identified that included 1053 attempts at establishing PDTOs. Overall SR was 63% (95% confidence interval [CI], 54%-72%). Pooled SRs of PDTO establishment from EUS-guided biopsies, percutaneous biopsies, and surgical specimens were 60% (95% CI, 43%-76%), 36% (95% CI, 14%-61%), and 62% (95% CI, 48%-75%), respectively, and did not differ significantly (P = .1975).

CONCLUSION

The SR of PDTO establishment from EUS-guided biopsies is comparable to that from surgical specimens. Both techniques are suitable for tissue acquisition for PDTOs in clinical and research settings. (PROSPERO registration number: CRD42023425121.).

Revealing the clinical potential of high-resolution organoids

The symbiotic interplay of organoid technology and advanced imaging strategies yields innovative breakthroughs in research and clinical applications. Organoids, intricate three-dimensional cell cultures derived from pluripotent or adult stem/progenitor cells, have emerged as potent tools for in vitro modeling, reflecting in vivo organs and advancing our grasp of tissue physiology and disease. Concurrently, advanced imaging technologies such as confocal, light-sheet, and two-photon microscopy ignite fresh explorations, uncovering rich organoid information. Combined with advanced imaging technologies and the power of artificial intelligence, organoids provide new insights that bridge experimental models and real-world clinical scenarios. This review explores exemplary research that embodies this technological synergy and how organoids reshape personalized medicine and therapeutics.

Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine

Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.

Preclinical Models of Anal Cancer Combined-Modality Therapy

INTRODUCTION

There have been no significant changes in anal cancer treatment options in 4 decades. In this study, we highlight two preclinical models designed to assess anal cancer treatments.

MATERIALS AND METHODS

Transgenic K14E6/E7 mice were treated with 7, 12-dimethylbenz(a)anthracene until anal tumors developed. Mice were treated with localized radiation in addition to chemotherapy (combined-modality therapy [CMT]) and compared to no treatment control (NTC). K14E6/E7 mouse anal spheroids with and without Pik3ca mutations were isolated and treated with vehicle, LY3023414 (LY3) (a drug previously shown to be effective in cancer prevention), CMT, or CMT + LY3.

RESULTS

In the in vivo model, there was a significant increase in survival in the CMT group compared to the NTC group (P = 0.0392). In the ex vivo model, there was a significant decrease in the mean diameter of CMT and CMT + LY3-treated spheroids compared to vehicle (P ≤ 0.0001). For LY3 alone compared to vehicle, there was a statistically significant decrease in spheroid size in the K14E6/E7 group without mutation (P = 0.0004).

CONCLUSIONS

We have provided proof of concept for two preclinical anal cancer treatment models that allow for the future testing of novel therapies for anal cancer.

Endothelial cells metabolically regulate breast cancer invasion toward a microvessel

Breast cancer metastasis is initiated by invasion of tumor cells into the collagen type I-rich stroma to reach adjacent blood vessels. Prior work has identified that metabolic plasticity is a key requirement of tumor cell invasion into collagen. However, it remains largely unclear how blood vessels affect this relationship. Here, we developed a microfluidic platform to analyze how tumor cells invade collagen in the presence and absence of a microvascular channel. We demonstrate that endothelial cells secrete pro-migratory factors that direct tumor cell invasion toward the microvessel. Analysis of tumor cell metabolism using metabolic imaging, metabolomics, and computational flux balance analysis revealed that these changes are accompanied by increased rates of glycolysis and oxygen consumption caused by broad alterations of glucose metabolism. Indeed, restricting glucose availability decreased endothelial cell-induced tumor cell invasion. Our results suggest that endothelial cells promote tumor invasion into the stroma due, in part, to reprogramming tumor cell metabolism.

Quantitative Imaging of Genetically Encoded Fluorescence Lifetime Biosensors

Genetically encoded fluorescence lifetime biosensors have emerged as powerful tools for quantitative imaging, enabling precise measurement of cellular metabolites, molecular interactions, and dynamic cellular processes. This review provides an overview of the principles, applications, and advancements in quantitative imaging with genetically encoded fluorescence lifetime biosensors using fluorescence lifetime imaging microscopy (go-FLIM). We highlighted the distinct advantages of fluorescence lifetime-based measurements, including independence from expression levels, excitation power, and focus drift, resulting in robust and reliable measurements compared to intensity-based approaches. Specifically, we focus on two types of go-FLIM, namely Förster resonance energy transfer (FRET)-FLIM and single-fluorescent protein (FP)-based FLIM biosensors, and discuss their unique characteristics and benefits. This review serves as a valuable resource for researchers interested in leveraging fluorescence lifetime imaging to study molecular interactions and cellular metabolism with high precision and accuracy.

Metabolic Imaging as a Tool to Characterize Chemoresistance and Guide Therapy in Triple-Negative Breast Cancer (TNBC)

After an initial response to chemotherapy, tumor relapse is frequent. This event is reflective of both the spatiotemporal heterogeneities of the tumor microenvironment as well as the evolutionary propensity of cancer cell populations to adapt to variable conditions. Because the cause of this adaptation could be genetic or epigenetic, studying phenotypic properties such as tumor metabolism is useful as it reflects molecular, cellular, and tissue-level dynamics. In triple-negative breast cancer (TNBC), the characteristic metabolic phenotype is a highly fermentative state. However, during treatment, the spatial and temporal dynamics of the metabolic landscape are highly unstable, with surviving populations taking on a variety of metabolic states. Thus, longitudinally imaging tumor metabolism provides a promising approach to inform therapeutic strategies, and to monitor treatment responses to understand and mitigate recurrence. Here we summarize some examples of the metabolic plasticity reported in TNBC following chemotherapy and review the current metabolic imaging techniques available in monitoring chemotherapy responses clinically and preclinically. The ensemble of imaging technologies we describe has distinct attributes that make them uniquely suited for a particular length scale, biological model, and/or features that can be captured. We focus on TNBC to highlight the potential of each of these technological advances in understanding evolution-based therapeutic resistance.

Probing organoid metabolism using fluorescence lifetime imaging microscopy (FLIM): The next frontier of drug discovery and disease understanding

Organoid models have been used to address important questions in developmental and cancer biology, tissue repair, advanced modelling of disease and therapies, among other bioengineering applications. Such 3D microenvironmental models can investigate the regulation of cell metabolism, and provide key insights into the mechanisms at the basis of cell growth, differentiation, communication, interactions with the environment and cell death. Their accessibility and complexity, based on 3D spatial and temporal heterogeneity, make organoids suitable for the application of novel, dynamic imaging microscopy methods, such as fluorescence lifetime imaging microscopy (FLIM) and related decay time-assessing readouts. Several biomarkers and assays have been proposed to study cell metabolism by FLIM in various organoid models. Herein, we present an expert-opinion discussion on the principles of FLIM and PLIM, instrumentation and data collection and analysis protocols, and general and emerging biosensor-based approaches, to highlight the pioneering work being performed in this field.

In vivo label-free optical signatures of chemotherapy response in human pancreatic ductal adenocarcinoma patient-derived xenografts

Pancreatic cancer is a devastating disease often detected at later stages, necessitating swift and effective chemotherapy treatment. However, chemoresistance is common and its mechanisms are poorly understood. Here, label-free multi-modal nonlinear optical microscopy was applied to study microstructural and functional features of pancreatic tumors in vivo to monitor inter- and intra-tumor heterogeneity and treatment response. Patient-derived xenografts with human pancreatic ductal adenocarcinoma were implanted into mice and characterized over five weeks of intraperitoneal chemotherapy (FIRINOX or Gem/NabP) with known responsiveness/resistance. Resistant and responsive tumors exhibited a similar initial metabolic response, but by week 5 the resistant tumor deviated significantly from the responsive tumor, indicating that a representative response may take up to five weeks to appear. This biphasic metabolic response in a chemoresistant tumor reveals the possibility of intra-tumor spatiotemporal heterogeneity of drug responsiveness. These results, though limited by small sample size, suggest the possibility for further work characterizing chemoresistance mechanisms using nonlinear optical microscopy.

Mini-organs with big impact: Organoids in liver cancer studies

Hepatocellular carcinoma, the most common primary liver cancer and a leading cause of death, is a difficult disease to treat due to its heterogeneous nature. Traditional models, such as 2D culture and patient-derived xenografts, have not proven effective. However, the development of 3D culture techniques, such as organoids, which can mimic the tumor microenvironment (TME) and preserve heterogeneity and pathophysiological properties of tumor cells, offers new opportunities for treatment and research. Organoids also have the potential for biomarker detection and personalized medication, as well as genome editing using CRISPR/Cas9 to study the behavior of certain genes and therapeutic interventions. This review explores to-the-date development of organoids with a focus on TME modeling in 3D organoid cultures. Further, it discusses gene editing using CRISPR/Cas9 in organoids, the challenges faced, and the prospects in the field of organoids.

Light-sheet autofluorescence lifetime imaging with a single-photon avalanche diode array

Significance

Fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzyme nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] is a popular method to monitor single-cell metabolism within unperturbed, living 3D systems. However, FLIM of NAD(P)H has not been performed in a light-sheet geometry, which is advantageous for rapid imaging of cells within live 3D samples.

Aim

We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM.

Approach

A single-photon avalanche diode camera was integrated into a light-sheet microscope to achieve optical sectioning and limit out-of-focus contributions for NAD(P)H FLIM of single cells.

Results

An NAD(P)H light-sheet FLIM system was built and validated with fluorescence lifetime standards and with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times. NAD(P)H light-sheet FLIM in vivo was demonstrated with live neutrophil imaging in a larval zebrafish tail wound also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light-sheet geometries, indicating a 30 × to 6 × acquisition speed advantage for the light sheet compared to the laser scanning geometry.

Conclusions

FLIM of NAD(P)H is feasible in a light-sheet geometry and is attractive for 3D live cell imaging applications, such as monitoring immune cell metabolism and migration within an organism.

Irbesartan overcomes gemcitabine resistance in pancreatic cancer by suppressing stemness and iron metabolism via inhibition of the Hippo/YAP1/c-Jun axis

BACKGROUND

Chemoresistance is the main reason for the poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Thus, there is an urgent need to screen out new targets and compounds to reverse chemotherapeutic resistance.

METHODS

We established a bio-bank of human PDAC organoid models, covering a representative range of PDAC tumor subtypes. We screened a library of 1304 FDA-approved compounds to identify candidates efficiently overcoming chemotherapy resistance. The effects of the compounds were evaluated with a CellTiter-Glo-3D assay, organoid apoptosis assay and in vivo patient-derived xenograft (PDX), patient-derived organoid (PDO) and LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx1-Cre (KPC) genetically engineered mouse models. RNA-sequencing, genome editing, sphere formation assays, iron assays and luciferase assays were conducted to elucidate the mechanism.

RESULTS

High-throughput drug screening of chemotherapy-resistant PDOs identified irbesartan, an angiotensin ‖ type 1 (AT1) receptor antagonist, which could synergistically enhance the ability of chemotherapy to kill PDAC cells. In vitro and in vivo validation using PDO, PDX and KPC mouse models showed that irbesartan efficiently sensitized PDAC tumors to chemotherapy. Mechanistically, we found that irbesartan decreased c-Jun expression by inhibiting the Hippo/YAP1 pathway and further overcame chemotherapy resistance in PDAC. We also explored c-Jun, a potential target of irbesartan, which can transcriptionally upregulate the expression of key genes involved in stemness maintenance (SOX9/SOX2/OCT4) and iron metabolism (FTH1/FTL/TFRC). More importantly, we observed that PDAC patients with high levels of c-Jun expression demonstrated poor responses to the current standard chemotherapy regimen (gemcitabine plus nab-paclitaxel). Moreover, patients with PDAC had significant survival benefits from treatment with irbesartan plus a standard chemotherapy regimen in two-center retrospective clinical cohorts and patients with high c-Jun expression exhibited a better response to combination chemotherapy.

CONCLUSIONS

Irbesartan could be used in combination with chemotherapy to improve the therapeutic efficacy in PDAC patients with high levels of c-Jun expression. Irbesartan effectively inhibited chemotherapy resistance by suppressing the Hippo/YAP1/c-Jun/stemness/iron metabolism axis. Based on our findings, we are designing an investigator-initiated phase II clinical trial on the efficacy and safety of irbesartan plus a standard gemcitabine/nab-paclitaxel regimen in the treatment of patients with advanced III/IV staged PDAC and are hopeful that we will observe patient benefits.

Tumor heterogeneity: preclinical models, emerging technologies, and future applications

Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.

Replacement, Reduction, and Refinement of Animal Experiments in Anticancer Drug Development: The Contribution of 3D In Vitro Cancer Models in the Drug Efficacy Assessment

In the last decades three-dimensional (3D) in vitro cancer models have been proposed as a bridge between bidimensional (2D) cell cultures and in vivo animal models, the gold standards in the preclinical assessment of anticancer drug efficacy. 3D in vitro cancer models can be generated through a multitude of techniques, from both immortalized cancer cell lines and primary patient-derived tumor tissue. Among them, spheroids and organoids represent the most versatile and promising models, as they faithfully recapitulate the complexity and heterogeneity of human cancers. Although their recent applications include drug screening programs and personalized medicine, 3D in vitro cancer models have not yet been established as preclinical tools for studying anticancer drug efficacy and supporting preclinical-to-clinical translation, which remains mainly based on animal experimentation. In this review, we describe the state-of-the-art of 3D in vitro cancer models for the efficacy evaluation of anticancer agents, focusing on their potential contribution to replace, reduce and refine animal experimentations, highlighting their strength and weakness, and discussing possible perspectives to overcome current challenges.

Development of a 3D Tumor Spheroid Model from the Patient's Glioblastoma Cells and Its Study by Metabolic Fluorescence Lifetime Imaging

Patient-specific in vitro tumor models are a promising platform for studying the mechanisms of oncogenesis and personalized selection of drugs. In case of glial brain tumors, development and use of such models is particularly relevant as the effectiveness of such tumor treatment remains extremely unsatisfactory. The aim of the study was to develop a model of a 3D tumor glioblastoma spheroid based on a patient's surgical material and to study its metabolic characteristics by means of fluorescence lifetime imaging microscopy of metabolic coenzymes.

Materials and Methods

The study was conducted with tumor samples from patients diagnosed with glioblastoma (Grade IV). To create spheroids, primary cultures were isolated from tumor tissue samples; the said cultures were characterized morphologically and immunocytochemically, and then planted into round-bottom ultra low-adhesion plates. The number of cells for planting was chosen empirically. The characteristics of the growth of cell cultures were compared with spheroids from glioblastomas of patients with U373 MG stable line of human glioblastoma. Visualization of autofluorescence of metabolic coenzymes of nicotinamide adenine dinucleotide (phosphate) NAD(P)H and flavin adenine dinucleotide (FAD) in spheroids was performed by means of an LSM 880 laser scanning microscope (Carl Zeiss, Germany) with a FLIM module (Becker & Hickl GmbH, Germany). The autofluorescence decay parameters were studied under normoxic and hypoxic conditions (3.5% О₂).

Results

An original protocol for 3D glioblastoma spheroids cultivation was developed. Primary glial cultures from surgical material of patients were obtained and characterized. The isolated glioblastoma cells had a spindle-shaped morphology with numerous processes and a pronounced granularity of cytoplasm. All cultures expressed glial fibrillary acidic protein (GFAP). The optimal seeding dose of 2000 cells per well was specified; its application results in formation of spheroids with a dense structure and stable growth during 7 days. The FLIM method helped to establish that spheroid cells from the patient material had a generally similar metabolism to spheroids from the stable line, however, they demonstrated more pronounced metabolic heterogeneity. Cultivation of spheroids under hypoxic conditions revealed a transition to a more glycolytic type of metabolism, which is expressed in an increase in the contribution of the free form of NAD(P)H to fluorescence decay.

Conclusion

The developed model of tumor spheroids from patients' glioblastomas in combination with the FLIM can serve as a tool to study characteristics of tumor metabolism and develop predictive tests to evaluate the effectiveness of antitumor therapy.

Single cell metabolic imaging of tumor and immune cells in vivo in melanoma bearing mice

Introduction

Metabolic reprogramming of cancer and immune cells occurs during tumorigenesis and has a significant impact on cancer progression. Unfortunately, current techniques to measure tumor and immune cell metabolism require sample destruction and/or cell isolations that remove the spatial context. Two-photon fluorescence lifetime imaging microscopy (FLIM) of the autofluorescent metabolic coenzymes nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD) provides in vivo images of cell metabolism at a single cell level.

Methods

Here, we report an immunocompetent mCherry reporter mouse model for immune cells that express CD4 either during differentiation or CD4 and/or CD8 in their mature state and perform in vivo imaging of immune and cancer cells within a syngeneic B78 melanoma model. We also report an algorithm for single cell segmentation of mCherry-expressing immune cells within in vivo images.

Results

We found that immune cells within B78 tumors exhibited decreased FAD mean lifetime and an increased proportion of bound FAD compared to immune cells within spleens. Tumor infiltrating immune cell size also increased compared to immune cells from spleens. These changes are consistent with a shift towards increased activation and proliferation in tumor infiltrating immune cells compared to immune cells from spleens. Tumor infiltrating immune cells exhibited increased FAD mean lifetime and increased protein-bound FAD lifetime compared to B78 tumor cells within the same tumor. Single cell metabolic heterogeneity was observed in both immune and tumor cells in vivo.

Discussion

This approach can be used to monitor single cell metabolic heterogeneity in tumor cells and immune cells to study promising treatments for cancer in the native in vivo context.

Pancreatic Cancer Organoids: An Emerging Platform for Precision Medicine?

Despite recent therapeutic advances, pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive malignancies, with remarkable resistance to treatment, poor prognosis, and poor clinical outcome. More efficient therapeutic approaches are urgently needed to improve patients' survival. Recently, the development of organoid culture systems has gained substantial attention as an emerging preclinical research model. PDAC organoids have been developed to study pancreatic cancer biology, progression, and treatment response, filling the translational gap between in vitro and in vivo models. Here, we review the rapidly evolving field of PDAC organoids and their potential as powerful preclinical tools that could pave the way towards precision medicine for pancreatic cancer.

S100 family proteins are linked to organoid morphology and EMT in pancreatic cancer

Epithelial-mesenchymal transition (EMT) is a continuum that includes epithelial, partial EMT, and mesenchymal states, each of which is associated with cancer progression, invasive capabilities, and ultimately, metastasis. We used a lineage-traced sporadic model of pancreatic cancer to generate a murine organoid biobank from primary and secondary tumors, including sublines that underwent partial EMT and complete EMT. Using an unbiased proteomics approach, we found that organoid morphology predicts the EMT state, and the solid organoids are associated with a partial EMT signature. We also observed that exogenous TGFβ1 induces solid organoid morphology that is associated with changes in the S100 family, complete EMT, and the formation of high-grade tumors. S100A4 may be a useful biomarker for predicting EMT state, disease progression, and outcome in patients with pancreatic cancer.

Establishment and Culture of Patient-Derived Breast Organoids

Breast cancer is a complex disease that has been classified into several different histological and molecular subtypes. Patient-derived breast tumor organoids developed in our laboratory consist of a mix of multiple tumor-derived cell populations, and thus represent a better approximation of tumor cell diversity and milieu than the established 2D cancer cell lines. Organoids serve as an ideal in vitro model, allowing for cell-extracellular matrix interactions, known to play an important role in cell-cell interactions and cancer progression. Patient-derived organoids also have advantages over mouse models as they are of human origin. Furthermore, they have been shown to recapitulate the genomic, transcriptomic as well as metabolic heterogeneity of patient tumors; thus, they are capable of representing tumor complexity as well as patient diversity. As a result, they are poised to provide more accurate insights into target discovery and validation and drug sensitivity assays. In this protocol, we provide a detailed demonstration of how patient-derived breast organoids are established from resected breast tumors (cancer organoids) or reductive mammoplasty-derived breast tissue (normal organoids). This is followed by a comprehensive account of 3D organoid culture, expansion, passaging, freezing, as well as thawing of patient-derived breast organoid cultures.

Light sheet autofluorescence lifetime imaging with a single photon avalanche diode array

Single photon avalanche diode (SPAD) array sensors can increase the imaging speed for fluorescence lifetime imaging microscopy (FLIM) by transitioning from laser scanning to widefield geometries. While a SPAD camera in epi-fluorescence geometry enables widefield FLIM of fluorescently labeled samples, label-free imaging of single-cell autofluorescence is not feasible in an epi-fluorescence geometry because background fluorescence from out-of-focus features masks weak cell autofluorescence and biases lifetime measurements. Here, we address this problem by integrating the SPAD camera in a light sheet illumination geometry to achieve optical sectioning and limit out-of-focus contributions, enabling fast label-free FLIM of single-cell NAD(P)H autofluorescence. The feasibility of this NAD(P)H light sheet FLIM system was confirmed with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times, and in vivo NAD(P)H light sheet FLIM was demonstrated with live neutrophil imaging in a zebrafish tail wound, also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light sheet geometries, indicating a 30X to 6X frame rate advantage for the light sheet compared to the laser scanning geometry. This light sheet system provides faster frame rates for 3D NAD(P)H FLIM for live cell imaging applications such as monitoring single cell metabolism and immune cell migration throughout an entire living organism.

Spatial Alignment of Organoids Tracking Subclonal Chemotherapy Resistance in Pancreatic and Ampullary Cancer

Pancreatic and ampullary cancers remain highly morbid diseases for which accurate clinical predictions are needed for precise therapeutic predictions. Patient-derived cancer organoids have been widely adopted; however, prior work has focused on well-level therapeutic sensitivity. To characterize individual oligoclonal units of therapeutic response, we introduce a low-volume screening assay, including an automated alignment algorithm. The oligoclonal growth response was compared against validated markers of response, including well-level viability and markers of single-cell viability. Line-specific sensitivities were compared with clinical outcomes. Automated alignment algorithms were generated to match organoids across time using coordinates across a single projection of Z-stacked images. After screening for baseline size (50 μm) and circularity (>0.4), the match efficiency was found to be optimized by accepting the diffusion thresholded with the root mean standard deviation of 75 μm. Validated well-level viability showed a limited correlation with the mean organoid size (R = 0.408), and a normalized growth assayed by normalized changes in area (R = 0.474) and area (R = 0.486). Subclonal populations were defined by both residual growth and the failure to induce apoptosis and necrosis. For a culture with clinical resistance to gemcitabine and nab-paclitaxel, while a therapeutic challenge induced a robust effect in inhibiting cell growth (GΔ = 1.53), residual oligoclonal populations were able to limit the effect on the ability to induce apoptosis (GΔ = 0.52) and cell necrosis (GΔ = 1.07). Bioengineered approaches are feasible to capture oligoclonal heterogeneity in organotypic cultures, integrating ongoing efforts for utilizing organoids across cancer types as integral biomarkers and in novel therapeutic development.

Single-cell technologies uncover intra-tumor heterogeneity in childhood cancers

Childhood cancer is the second leading cause of death in children aged 1 to 14. Although survival rates have vastly improved over the past 40 years, cancer resistance and relapse remain a significant challenge. Advances in single-cell technologies enable dissection of tumors to unprecedented resolution. This facilitates unraveling the heterogeneity of childhood cancers to identify cell subtypes that are prone to treatment resistance. The rapid accumulation of single-cell data from different modalities necessitates the development of novel computational approaches for processing, visualizing, and analyzing single-cell data. Here, we review single-cell approaches utilized or under development in the context of childhood cancers. We review computational methods for analyzing single-cell data and discuss best practices for their application. Finally, we review the impact of several studies of childhood tumors analyzed with these approaches and future directions to implement single-cell studies into translational cancer research in pediatric oncology.

Patient-derived organoids (PDOs) and PDO-derived xenografts (PDOXs): New opportunities in establishing faithful pre-clinical cancer models

One of the major bottlenecks in advancing basic cancer research and developing novel cancer therapies is the lack of in vitro pre-clinical models that faithfully recapitulate tumor properties in the patients. Monolayer cultures of cancer cell lines usually lose the heterogeneity of the parental tumors, while patient-derived xenograft (PDX) suffers from its time- and resource-intensive nature. The emergence of organoid culture system and its application in cancer research provides a unique opportunity to develop novel in vitro cancer pre-clinical models. Here we review the recent advances in utilizing organoids culture system and other related three-dimensional culture systems in studying cancer biology, performing drug screening, and developing cancer therapies. In particular, we discuss the advantages of applying xenograft initiated from patient-derived organoids (PDOs) as a faithful cancer pre-clinical model in basic cancer research and precision medicine.

Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism

BACKGROUND

Epithelial ovarian cancer (OC) is the most lethal gynecological malignancy and patients present with significant metastatic burden, particularly to the adipose-rich microenvironment of the omentum. Recent evidence has highlighted the importance of metabolic adaptations in enabling this metastasis, leading to significant interest in evolving the arsenal of tools used to study OC metabolism. In this study, we demonstrate the capability of genetically encoded fluorescent biosensors to study OC, with a focus on 3D organoid models that better recapitulate in vivo tumor microenvironments.

MATERIALS AND METHODS

Plasmids encoding the metabolic biosensors HyPer, iNap, Peredox, and Perceval were transfected into 15 ovarian cancer cell lines to assay oxidative stress, NADPH/NADP+, NADH/NAD+, and ATP/ADP, respectively. Fluorescence readings were used to assay dynamic metabolic responses to omental conditioned media (OCM) and 100 μM carboplatin treatment. SKOV3 cells expressing HyPer were imaged as 2D monolayers, 3D organoids, and as in vivo metastases via an intravital omental window. We further established organoids from ascites collected from Stage III/IV OC patients with carboplatin-resistant or carboplatin-sensitive tumors (n = 8 total). These patient-derived organoids (PDOs) were engineered to express HyPer, and metabolic readings of oxidative stress were performed during treatment with 100 μM carboplatin.

RESULTS

Exposure to OCM or carboplatin induced heterogenous metabolic changes in 15 OC cell lines, as measured using metabolic sensors. Oxidative stress of in vivo omental metastases, measured via intravital imaging of metastasizing SKOV3-HyPer cells, was more closely recapitulated by SKOV3-HyPer organoids than by 2D monolayers. Finally, carboplatin treatment of HyPer-expressing PDOs induced higher oxidative stress in organoids derived from carboplatin-resistant patients than from those derived from carboplatin-sensitive patients.

CONCLUSIONS

Our study showed that biosensors provide a useful method of studying dynamic metabolic changes in preclinical models of OC, including 3D organoids and intravital imaging. As 3D models of OC continue to evolve, the repertoire of biosensors will likely serve as valuable tools to probe the metabolic changes of clinical importance in OC.

Three-Dimensional in Vitro Models: A Promising Tool To Scale-Up Breast Cancer Research

Common models used in breast cancer studies, including two-dimensional (2D) cultures and animal models, do not precisely model all aspects of breast tumors. These models do not well simulate the cell-cell and cell-stromal interactions required for normal tumor growth in the body and lake tumor like microenvironment. Three-dimensional (3D) cell culture models are novel approaches to studying breast cancer. They do not have the restrictions of these conventional models and are able to recapitulate the structural architecture, complexity, and specific function of breast tumors and provide similar in vivo responses to therapeutic regimens. These models can be a link between former traditional 2D culture and in vivo models and are necessary for further studies in cancer. This review attempts to summarize the most common 3D in vitro models used in breast cancer studies, including scaffold-free (spheroid and organoid), scaffold-based, and chip-based models, particularly focused on the basic and translational application of these 3D models in drug screening and the tumor microenvironment in breast cancer.

Immune organoids: from tumor modeling to precision oncology

Cancer immunotherapies, particularly immune checkpoint inhibitors, are rapidly becoming standard-of-care for many cancers. The ascendance of immune checkpoint inhibitor treatment and limitations in the accurate prediction of clinical response thereof have provided significant impetus to develop preclinical models that can guide therapeutic intervention. Traditional organoid culture methods that exclusively grow tumor epithelium as patient-derived organoids are under investigation as a personalized platform for drug discovery and for predicting clinical efficacy of chemotherapies and targeted agents. Recently, the patient-derived tumor organoid platform has evolved to contain more complex stromal and immune compartments needed to assess immunotherapeutic efficacy. We review the different methodologies for developing a more holistic patient-derived tumor organoid platform and for modeling the native immune tumor microenvironment.

The roles of intratumour heterogeneity in the biology and treatment of pancreatic ductal adenocarcinoma

Intratumour heterogeneity (ITH) has become an important focus of cancer research in recent years. ITH describes the cellular variation that enables tumour evolution, including tumour progression, metastasis and resistance to treatment. The selection and expansion of genetically distinct treatment-resistant cancer cell clones provides one explanation for treatment failure. However, tumour cell variation need not be genetically encoded. In pancreatic ductal adenocarcinoma (PDAC) in particular, the complex tumour microenvironment as well as crosstalk between tumour and stromal cells result in exceptionally variable tumour cell phenotypes that are also highly adaptable. In this review we discuss four different types of phenotypic heterogeneity within PDAC, from morphological to metabolic heterogeneity. We suggest that these different types of ITH are not independent, but, rather, can inform one another. Lastly, we highlight recent findings that suggest how therapeutic efforts may halt PDAC progression by constraining cellular heterogeneity.

Metabolic-imaging of human glioblastoma live tumors: A new precision-medicine approach to predict tumor treatment response early

Background

Glioblastoma (GB) is the most severe form of brain cancer, with a 12-15 month median survival. Surgical resection, temozolomide (TMZ) treatment, and radiotherapy remain the primary therapeutic options for GB, and no new therapies have been introduced in recent years. This therapeutic standstill is primarily due to preclinical approaches that do not fully respect the complexity of GB cell biology and fail to test efficiently anti-cancer treatments. Therefore, better treatment screening approaches are needed. In this study, we have developed a novel functional precision medicine approach to test the response to anticancer treatments in organoids derived from the resected tumors of glioblastoma patients.

Methods

GB organoids were grown for a short period of time to prevent any genetic and morphological evolution and divergence from the tumor of origin. We chose metabolic imaging by NAD(P)H fluorescence lifetime imaging microscopy (FLIM) to predict early and non-invasively ex-vivo anti-cancer treatment responses of GB organoids. TMZ was used as the benchmark drug to validate the approach. Whole-transcriptome and whole-exome analyses were performed to characterize tumor cases stratification.

Results

Our functional precision medicine approach was completed within one week after surgery and two groups of TMZ Responder and Non-Responder tumors were identified. FLIM-based metabolic tumor stratification was well reflected at the molecular level, confirming the validity of our approach, highlighting also new target genes associated with TMZ treatment and identifying a new 17-gene molecular signature associated with survival. The number of MGMT gene promoter methylated tumors was higher in the responsive group, as expected, however, some non-methylated tumor cases turned out to be nevertheless responsive to TMZ, suggesting that our procedure could be synergistic with the classical MGMT methylation biomarker.

Conclusions

For the first time, FLIM-based metabolic imaging was used on live glioblastoma organoids. Unlike other approaches, ex-vivo patient-tailored drug response is performed at an early stage of tumor culturing with no animal involvement and with minimal tampering with the original tumor cytoarchitecture. This functional precision medicine approach can be exploited in a range of clinical and laboratory settings to improve the clinical management of GB patients and implemented on other cancers as well.

Functional Precision Oncology: The Next Frontier to Improve Glioblastoma Outcome?

Glioblastoma remains the most malignant and intrinsically resistant brain tumour in adults. Despite intensive research over the past few decades, through which numerous potentially druggable targets have been identified, virtually all clinical trials of the past 20 years have failed to improve the outcome for the vast majority of GBM patients. The observation that small subgroups of patients displayed a therapeutic response across several unsuccessful clinical trials suggests that the GBM patient population probably consists of multiple subgroups that probably all require a distinct therapeutic approach. Due to extensive inter- and intratumoral heterogeneity, assigning the right therapy to each patient remains a major challenge. Classically, bulk genetic profiling would be used to identify suitable therapies, although the success of this approach remains limited due to tumor heterogeneity and the absence of direct relationships between mutations and therapy responses in GBM. An attractive novel strategy aims at implementing methods for functional precision oncology, which refers to the evaluation of treatment efficacies and vulnerabilities of (ex vivo) living tumor cells in a highly personalized way. Such approaches are currently being implemented for other cancer types by providing rapid, translatable information to guide patient-tailored therapeutic selections. In this review, we discuss the current state of the art of transforming technologies, tools and challenges for functional precision oncology and how these could improve therapy selection for GBM patients.

Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical Treatment Response

PURPOSE

Patient-derived organoids (PDO) are a promising technology to support precision medicine initiatives for patients with pancreatic ductal adenocarcinoma (PDAC). PDOs may improve clinical next-generation sequencing (NGS) and enable rapid ex vivo chemotherapeutic screening (pharmacotyping).

EXPERIMENTAL DESIGN

PDOs were derived from tissues obtained during surgical resection and endoscopic biopsies and studied with NGS and pharmacotyping. PDO-specific pharmacotype is assessed prospectively as a predictive biomarker of clinical therapeutic response by leveraging data from a randomized controlled clinical trial.

RESULTS

Clinical sequencing pipelines often fail to detect PDAC-associated somatic mutations in surgical specimens that demonstrate a good pathologic response to previously administered chemotherapy. Sequencing the PDOs derived from these surgical specimens, after biomass expansion, improves the detection of somatic mutations and enables quantification of copy number variants. The detection of clinically relevant mutations and structural variants is improved following PDO biomass expansion. On clinical trial, PDOs were derived from biopsies of treatment-naïve patients prior to treatment with FOLFIRINOX (FFX). Ex vivo PDO pharmacotyping with FFX components predicted clinical therapeutic response in these patients with borderline resectable or locally advanced PDAC treated in a neoadjuvant or induction paradigm. PDO pharmacotypes suggesting sensitivity to FFX components were associated with longitudinal declines of tumor marker, carbohydrate-antigen 19-9 (CA-19-9), and favorable RECIST imaging response.

CONCLUSIONS

PDOs established from tissues obtained from patients previously receiving cytotoxic chemotherapies can be accomplished in a clinically certified laboratory. Sequencing PDOs following biomass expansion improves clinical sequencing quality. High in vitro sensitivity to standard-of-care chemotherapeutics predicts good clinical response to systemic chemotherapy in PDAC. See related commentary by Zhang et al., p. 3176.

Patient-Specific Sarcoma Organoids for Personalized Translational Research: Unification of the Operating Room with Rare Cancer Research and Clinical Implications

INTRODUCTION

Sarcoma clinical outcomes have been stagnant for decades due to heterogeneity of primaries, lack of comprehensive preclinical models, and rarity of disease. We hypothesized that engineering hydrogel-based sarcoma organoids directly from the patient without xenogeneic extracellular matrices (ECMs) or growth factors is routinely feasible and allows rare tumors to remain viable as avatars for personalized research.

METHODS

Surgically resected sarcomas (angiosarcomas, leiomyosarcoma, gastrointestinal stromal tumor, liposarcoma, myxofibrosarcoma, dermatofibrosarcoma protuberans [DFSP], and pleiomorphic abdominal sarcoma) were dissociated and incorporated into a hyaluronic acid and collagen-based ECM hydrogel and screened for chemotherapy efficacy. A subset of organoids was enriched with a patient-matched immune system for screening of immunotherapy efficacy (iPTOs). Response to treatment was assessed using LIVE/DEAD staining and metabolic assays.

RESULTS

Sixteen sarcomas were biofabricated into three-dimensional (3D) patient-specific sarcoma organoids with a 100% success rate. Average time from organoid development to initiation of drug testing was 7 days. Enrichment of organoids with immune system components derived from either peripheral blood mononuclear cells or lymph node cells was performed in 10/16 (62.5%) patients; 4/12 (33%) organoids did not respond to chemotherapy, while response to immunotherapy was observed in 2/10 (20%) iPTOs.

CONCLUSIONS

A large subset of sarcoma organoids does not exhibit response to chemotherapy or immunotherapy, as currently seen in clinical practice. Routine development of sarcoma hydrogel-based organoids directly from the operating room is a feasible platform, allowing for such rare tumors to remain viable for personalized translational research.

Data-Driven Identification of Biomarkers for In Situ Monitoring of Drug Treatment in Bladder Cancer Organoids

Three-dimensional (3D) organoid culture recapitulating patient-specific histopathological and molecular diversity offers great promise for precision medicine in cancer. In this study, we established label-free imaging procedures, including Raman microspectroscopy (RMS) and fluorescence lifetime imaging microscopy (FLIM), for in situ cellular analysis and metabolic monitoring of drug treatment efficacy. Primary tumor and urine specimens were utilized to generate bladder cancer organoids, which were further treated with various concentrations of pharmaceutical agents relevant for the treatment of bladder cancer (i.e., cisplatin, venetoclax). Direct cellular response upon drug treatment was monitored by RMS. Raman spectra of treated and untreated bladder cancer organoids were compared using multivariate data analysis to monitor the impact of drugs on subcellular structures such as nuclei and mitochondria based on shifts and intensity changes of specific molecular vibrations. The effects of different drugs on cell metabolism were assessed by the local autofluorophore environment of NADH and FAD, determined by multiexponential fitting of lifetime decays. Data-driven neural network and data validation analyses (k-means clustering) were performed to retrieve additional and non-biased biomarkers for the classification of drug-specific responsiveness. Together, FLIM and RMS allowed for non-invasive and molecular-sensitive monitoring of tumor-drug interactions, providing the potential to determine and optimize patient-specific treatment efficacy.

Technologies to Assess Drug Response and Heterogeneity in Patient-Derived Cancer Organoids

Patient-derived cancer organoids (PDCOs) are organotypic 3D cultures grown from patient tumor samples. PDCOs provide an exciting opportunity to study drug response and heterogeneity within and between patients. This research can guide new drug development and inform clinical treatment planning. We review technologies to assess PDCO drug response and heterogeneity, discuss best practices for clinically relevant drug screens, and assert the importance of quantifying single-cell and organoid heterogeneity to characterize response. Autofluorescence imaging of PDCO growth and metabolic activity is highlighted as a compelling method to monitor single-cell and single-organoid response robustly and reproducibly. We also speculate on the future of PDCOs in clinical practice and drug discovery.Future development will require standardization of assessment methods for both morphology and function in PDCOs, increased throughput for new drug development, prospective validation with patient outcomes, and robust classification algorithms.

Label-Free Vibrational and Quantitative Phase Microscopy Reveals Remarkable Pathogen-Induced Morphomolecular Divergence in Tumor-Derived Cells

Delineating the molecular and morphological changes that cancer cells undergo in response to extracellular stimuli is crucial for identifying factors that promote tumor progression. Label-free optical imaging offers a potentially promising route for retrieving such single-cell information by generating detailed visualization of the morphology and determining alterations in biomolecular composition. The potential of such nonperturbative morphomolecular microscopy for analyzing microbiota-cancer cell interactions has been surprisingly underappreciated, despite the growing evidence of the critical role of dysbiosis in malignant transformations. Here, using a model system of breast cancer cells, we show that label-free Raman microspectroscopy and quantitative phase microscopy can detect biomolecular and morphological changes in single cells exposed to Bacteroides fragilis toxin (BFT), a toxin secreted by enterotoxigenicB. fragilis. Remarkably, using machine learning to elucidate subtle, but consistent, cellular differences, we found that the morphomolecular differences between BFT-exposed and control breast cancer cells became more accentuated after in vivo passage, corroborating our findings that a short-term BFT exposure imparts a long-term effect on cancer cells and promotes a more invasive phenotype. Complementing more classical labeling techniques, our label-free platform offers a global detection approach with measurements representative of the overall cellular phenotype, paving the way for further investigations into the multifaceted interactions between the cancer cell and the microbiota.

Functional genomics and the future of iPSCs in disease modeling

Induced pluripotent stem cells (iPSCs) are valuable in disease modeling because of their potential to expand and differentiate into virtually any cell type and recapitulate key aspects of human biology. Functional genomics are genome-wide studies that aim to discover genotype-phenotype relationships, thereby revealing the impact of human genetic diversity on normal and pathophysiology. In this review, we make the case that human iPSCs (hiPSCs) are a powerful tool for functional genomics, since they provide an in vitro platform for the study of population genetics. We describe cutting-edge tools and strategies now available to researchers, including multi-omics technologies, advances in hiPSC culture techniques, and innovations in drug development. Functional genomics approaches based on hiPSCs hold great promise for advancing drug discovery, disease etiology, and the impact of genetic variation on human biology.

Inhibition of B-cell lymphoma 2 family proteins alters optical redox ratio, mitochondrial polarization, and cell energetics independent of cell state

SIGNIFICANCE

The optical redox ratio (ORR) [autofluorescence intensity of the reduced form of nicotinamide adenine dinucleotide (phosphate) (NAD(P)H)/flavin adenine dinucleotide (FAD)] provides a label-free method to quantify cellular metabolism. However, it is unclear whether changes in the ORR with B-cell lymphoma 2 (Bcl-2) family protein inhibition are due to metabolic stress alone or compromised cell viability.

AIM

Determine whether ABT-263 (navitoclax, Bcl-2 family inhibitor) changes the ORR due to changes in mitochondrial function that are independent of changes in cell viability.

APPROACH

SW48 colon cancer cells were used to investigate changes in ORR, mitochondrial membrane potential, oxygen consumption rates, and cell state (cell growth, viability, proliferation, apoptosis, autophagy, and senescence) with ABT-263, TAK-228 [sapanisertib, mammalian target of rapamycin complex 1/2 (mTORC 1/2) inhibitor], and their combination at 24 h.

RESULTS

Changes in the ORR with Bcl-2 inhibition are driven by increases in both NAD(P)H and FAD autofluorescence, corresponding with increased basal metabolic rate and increased mitochondrial polarization. ABT-263 treatment does not change cell viability or induce autophagy but does induce a senescent phenotype. The metabolic changes seen with ABT-263 treatment are mitigated by combination with mTORC1/2 inhibition.

CONCLUSIONS

The ORR is sensitive to increases in mitochondrial polarization, energetic state, and cell senescence, which can change independently from cell viability.

Combination strategies to target metabolic flexibility in cancer

Therapeutically interfering with metabolic pathways has great merit to curtail tumor growth because the demand for copious amounts of energy for growth-supporting biomass production is common to all cancer entities. A major impediment to a straight implementation of metabolic cancer therapy is the metabolic flexibility and plasticity of cancer cells (and their microenvironment) resulting in therapy resistance and evasion. Metabolic combination therapies, therefore, are promising as they are designed to target several energetic routes simultaneously and thereby diminish the availability of alternative substrates. Thus, dietary restrictions, specific nutrient limitations, and/or pharmacological interventions impinging on metabolic pathways can be combined to improve cancer treatment efficacy, to overcome therapy resistance, or even act as a preventive measure. Here, we review the most recent developments in metabolic combination therapies particularly highlighting in vivo reports of synergistic effects and available clinical data. We close with identifying the challenges of the field (metabolic tumor heterogeneity, immune cell interactions, inter-patient variabilities) and suggest a "metabo-typing" strategy to tailor evidence-based metabolic combination therapies to the energetic requirements of the tumors and the patient's nutritional habits and status.

Impact of baseline culture conditions of cancer organoids when determining therapeutic response and tumor heterogeneity

Representative models are needed to screen new therapies for patients with cancer. Cancer organoids are a leap forward as a culture model that faithfully represents the disease. Mouse-derived cancer organoids (MDCOs) are becoming increasingly popular, however there has yet to be a standardized method to assess therapeutic response and identify subpopulation heterogeneity. There are multiple factors unique to organoid culture that could affect how therapeutic response and MDCO heterogeneity are assessed. Here we describe an analysis of nearly 3500 individual MDCOs where individual organoid morphologic tracking was performed. Change in MDCO diameter was assessed in the presence of control media or targeted therapies. Individual organoid tracking was identified to be more sensitive to treatment response than well-level assessment. The impact of different generations of mice of the same genotype, different regions of the colon, and organoid specific characteristics including baseline size, passage number, plating density, and location within the matrix were examined. Only the starting size of the MDCO altered the subsequent growth. These results were corroborated using ~ 1700 patient-derived cancer organoids (PDCOs) isolated from 19 patients. Here we establish organoid culture parameters for individual organoid morphologic tracking to determine therapeutic response and growth/response heterogeneity for translational studies.

Present Application and Perspectives of Organoid Imaging Technology

An organoid is a miniaturized and simplified in vitro model with a similar structure and function to a real organ. In recent years, the use of organoids has increased explosively in the field of growth and development, disease simulation, drug screening, cell therapy, etc. In order to obtain necessary information, such as morphological structure, cell function and dynamic signals, it is necessary and important to directly monitor the culture process of organoids. Among different detection technologies, imaging technology is a simple and convenient choice and can realize direct observation and quantitative research. In this review, the principle, advantages and disadvantages of imaging technologies that have been applied in organoids research are introduced. We also offer an overview of prospective technologies for organoid imaging. This review aims to help biologists find appropriate imaging techniques for different areas of organoid research, and also contribute to the development of organoid imaging systems.

Label-free sensing of cells with fluorescence lifetime imaging: The quest for metabolic heterogeneity

Molecular, morphological, and physiological heterogeneity is the inherent property of cells which governs differences in their response to external influence. Tumor cell metabolic heterogeneity is of a special interest due to its clinical relevance to tumor progression and therapeutic outcomes. Rapid, sensitive, and noninvasive assessment of metabolic heterogeneity of cells is a great demand for biomedical sciences. Fluorescence lifetime imaging (FLIM), which is an all-optical technique, is an emerging tool for sensing and quantifying cellular metabolism by measuring fluorescence decay parameters of endogenous fluorophores, such as NAD(P)H. To achieve accurate discrimination between metabolically diverse cellular subpopulations, appropriate approaches to FLIM data collection and analysis are needed. In this paper, the unique capability of FLIM to attain the overarching goal of discriminating metabolic heterogeneity is demonstrated. This has been achieved using an approach to data analysis based on the nonparametric analysis, which revealed a much better sensitivity to the presence of metabolically distinct subpopulations compared to more traditional approaches of FLIM measurements and analysis. The approach was further validated for imaging cultured cancer cells treated with chemotherapy. These results pave the way for accurate detection and quantification of cellular metabolic heterogeneity using FLIM, which will be valuable for assessing therapeutic vulnerabilities and predicting clinical outcomes.

Pancreatic Cancer Organoids in the Field of Precision Medicine: A Review of Literature and Experience on Drug Sensitivity Testing with Multiple Readouts and Synergy Scoring

Simple Summary

New treatments are urgently needed for pancreatic ductal adenocarcinoma because it is one of the most aggressive and lethal cancers, detected too late and resistant to conventional chemotherapy. Tumors in most patients feature a similar set of core mutations but so far it has not been possible to design a one-fits-all treatment strategy. Instead, efforts are underway to personalize the therapies. To find the treatments that might work the best for each patient, entirely new experimental platforms based on living miniature tumors, organoids, have been developed. We review here the latest international findings in designing personalized treatments pancreatic cancer patients using organoids as testing beds. Our own work adds important clues about how such testing could, and perhaps should, be conducted.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a silent killer, often diagnosed late. However, it is also dishearteningly resistant to nearly all forms of treatment. New therapies are urgently needed, and with the advent of organoid culture for pancreatic cancer, an increasing number of innovative approaches are being tested. Organoids can be derived within a short enough time window to allow testing of several anticancer agents, which opens up the possibility for functional precision medicine for pancreatic cancer. At the same time, organoid model systems are being refined to better mimic the cancer, for example, by incorporation of components of the tumor microenvironment. We review some of the latest developments in pancreatic cancer organoid research and in novel treatment design. We also summarize our own current experiences with pancreatic cancer organoid drug sensitivity and resistance testing (DSRT) in 14 organoids from 11 PDAC patients. Our data show that it may be necessary to include a cell death read-out in ex vivo DSRT assays, as metabolic viability quantitation does not capture actual organoid killing. We also successfully adapted the organoid platform for drug combination synergy discovery. Lastly, live organoid culture 3D confocal microscopy can help identify individual surviving tumor cells escaping cell death even during harsh combination treatments. Taken together, the organoid technology allows the development of novel precision medicine approaches for PDAC, which paves the way for clinical trials and much needed new treatment options for pancreatic cancer patients.