The promises and challenges of patient-derived tumor organoids in drug development and precision oncology

Patient-derived tumor models in cancer research: Evaluation of the oncostatic effects of melatonin

The development of new anticancer therapies tends to be very slow. Although their impact on potential candidates is confirmed in preclinical studies, ∼95 % of these new therapies are not approved when tested in clinical trials. One of the main reasons for this is the lack of accurate preclinical models. In this context, there are different patient-derived models, which have emerged as a powerful oncological tool: patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived cells (PDCs). Although all these models are widely applied, PDXs, which are created by engraftment of patient tumor tissues into mice, is considered more reliable. In fundamental research, the PDX model is used to evaluate drug-sensitive markers and, in clinical practice, to select a personalized therapeutic strategy. Melatonin is of particular importance in the development of innovative cancer treatments due to its oncostatic impact and lack of adverse effects. However, the literature regarding the oncostatic effect of melatonin in patient-derived tumor models is scant. This review aims to describe the important role of patient-derived models in the development of anticancer treatments, focusing, in particular, on PDX models, as well as their use in cancer research. This review also summarizes the existing literature on the anti-tumoral effect of melatonin in patient-derived models in order to propose future anti-neoplastic clinical applications.

Breast cancer organoids derived from patients: A platform for tailored drug screening

Breast cancer stands as the most prevalent and heterogeneous malignancy affecting women globally, posing a substantial health concern. Enhanced comprehension of tumor pathology and the development of novel therapeutics are pivotal for advancing breast cancer treatment. Contemporary breast cancer investigation heavily leans on in vivo models and conventional cell culture techniques. Nonetheless, these approaches often encounter high failure rates in clinical trials due to species disparities and tissue structure variations. To address this, three-dimensional cultivation of organoids, resembling organ-like structures, has emerged as a promising alternative. Organoids represent innovative in vitro models that mirror in vivo tissue microenvironments. They retain the original tumor's diversity and facilitate the expansion of tumor samples from diverse origins, facilitating the representation of varying tumor stages. Optimized breast cancer organoid models, under precise culture conditions, offer benefits including convenient sample acquisition, abbreviated cultivation durations, and genetic stability. These attributes ensure a faithful replication of in vivo traits of breast cancer cells. As intricate cellular entities boasting spatial arrangements, breast cancer organoid models harbor substantial potential in precision medicine, organ transplantation, modeling intricate diseases, gene therapy, and drug innovation. This review delivers an overview of organoid culture techniques and outlines future prospects for organoid modeling.

Recreating the extracellular matrix: novel 3D cell culture platforms in cancer research

Cancer initiation and progression heavily rely on microenvironmental cues derived from various components of the niche including the extracellular matrix (ECM). ECM is a complex macromolecular network that governs cell functionality. Although the two-dimensional (2D) cell culture systems provide useful information at the molecular level and preclinical testing, they could not accurately represent the in vivo matrix microenvironmental architecture. Hence, it is no surprise that researchers in the last decade have focussed their efforts on establishing novel advanced in vitro culture models that mimic tumour and tissue-specific niches and interactions. These numerous three-dimensional (3D) culture systems that are now widely available, as well as those still under development, grant researchers with new, improved tools to study cancer progression and to explore innovative therapeutic options. Herein, we report on the emerging methods and cutting-edge technologies in 3D cell culture platforms and discuss their potential use in unveiling tumour microenvironmental cues, drug screening and personalized treatment.

Morphological Characterization of Human Lung Cancer Organoids Cultured in Type I Collagen Hydrogels: A Histological Approach

The malignity of lung cancer is conditioned by the tumor microenvironment (TME), in which cancer-associated fibroblasts (CAFs) are relevant. In this work, we generated organoids by combining A549 cells with CAFs and normal fibroblasts (NF) isolated from adenocarcinoma tumors. We optimized the conditions for their manufacture in a short time. We evaluated the morphology of organoids using confocal microscopy analysis of F-actin, vimentin and pankeratin. We determined the ultrastructure of the cells in the organoids via transmission electron microscopy and the expression of CDH1, CDH2 and VIM via RT-PCR. The addition of stromal cells induces the self-organization of the organoids, which acquired a bowl morphology, as well as their growth and the generation of cell processes. They also influenced the expression of genes related to epithelial mesenchymal transition (EMT). CAFs potentiated these changes. All cells acquired a characteristic secretory phenotype, with cohesive cells appearing inside the organoids. In the periphery, many cells acquired a migratory phenotype, especially in organoids that incorporated CAFs. The deposit of abundant extracellular matrix could also be observed. The results presented here reinforce the role of CAFs in the progression of lung tumors and could lay the foundation for a useful in vitro pharmacological model.

Spatial Proteomics for the Molecular Characterization of Breast Cancer

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

Immersion bioprinting of hyaluronan and collagen bioink-supported 3D patient-derived brain tumor organoids

Organoids, and in particular patient-derived organoids, have emerged as crucial tools for cancer research. Our organoid platform, which has supported patient-derived tumor organoids (PTOs) from a variety of tumor types, has been based on the use of hyaluronic acid (HA) and collagen, or gelatin, hydrogel bioinks. One hurdle to high throughput PTO biofabrication is that as high-throughput multi-well plates, bioprinted volumes have increased risk of contacting the sides of wells. When this happens, surface tension causes bioinks to fall flat, resulting in 2D cultures. To address this problem, we developed an organoid immersion bioprinting method-inspired by the FRESH printing method-in which organoids are bioprinted into support baths in well plates. The bath-in this case an HA solution-shields organoids from the well walls, preventing deformation. Here we describe an improvement to our approach, based on rheological assessment of previous gelatin baths versus newer HA support baths, combined with morphological assessment of immersion bioprinted organoids. HA print baths enabled more consistent organoid volumes and geometries. We optimized the printing parameters of this approach using a cell line. Finally, we deployed our optimized immersion bioprinting approach into a drug screening application, using PTOs derived from glioma biospecimens, and a lung adenocarcinoma brain metastasis. In these studies, we showed a general dose dependent response to an experimental p53 activator compound and temozolomide (TMZ), the drug most commonly given to brain tumor patients. Responses to the p53 activator compound were effective across all PTO sets, while TMZ responses were observed, but less pronounced, potentially explained by genetic and epigenetic states of the originating tumors. The studies presented herein showcase a bioprinting methodology that we hope can be used in increased throughput settings to help automate biofabrication of PTOs for drug development-based screening studies and precision medicine applications.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine

Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

Advances in bioengineering pancreatic tumor-stroma physiomimetic Biomodels

Pancreatic cancer exhibits a unique bioarchitecture and desmoplastic cancer-stoma interplay that governs disease progression, multi-resistance, and metastasis. Emulating the biological features and microenvironment heterogeneity of pancreatic cancer stroma in vitro is remarkably complex, yet highly desirable for advancing the discovery of innovative therapeutics. Diverse bioengineering approaches exploiting patient-derived organoids, cancer-on-a-chip platforms, and 3D bioprinted living constructs have been rapidly emerging in an endeavor to seamlessly recapitulate major tumor-stroma biodynamic interactions in a preclinical setting. Gathering on this, herein we showcase and discuss the most recent advances in bio-assembling pancreatic tumor-stroma models that mimic key disease hallmarks and its desmoplastic biosignature. A reverse engineering perspective of pancreatic tumor-stroma key elementary units is also provided and complemented by a detailed description of biodesign guidelines that are to be considered for improving 3D models physiomimetic features. This overview provides valuable examples and starting guidelines for researchers envisioning to engineer and characterize stroma-rich biomimetic tumor models. All in all, leveraging advanced bioengineering tools for capturing stromal heterogeneity and dynamics, opens new avenues toward generating more predictive and patient-personalized organotypic 3D in vitro platforms for screening transformative therapeutics targeting the tumor-stroma interplay.

Evaluating Translational Methods for Personalized Medicine—A Scoping Review

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

Progressing Towards a Human-Centric Approach in Cancer Research

Despite the advancement in research methodologies and technologies for cancer research, there is a high rate of anti-cancer drug attrition. In this review, we discuss different conventional and modern approaches in cancer research and how human-centric models can improve on the voids conferred by more traditional animal-centric models, thereby offering a more reliable platform for drug discovery. Advanced three-dimensional cell culture methodologies, along with in silico computational analysis form the core of human-centric cancer research. This can provide a holistic understanding of the research problems and help design specific and accurate experiments that could lead to the development of better cancer therapeutics. Here, we propose a new human-centric research roadmap that promises to provide a better platform for cancer research and drug discovery.

Informatics in Medical Product Regulation: The Right Drug at the Right Dose for the Right Patient

This chapter describes the role of regulatory medical product review in furthering precision medicine. Efficient data processing and appropriate analyses are needed to synthesize information and provide directions for use in a medical product label. We describe opportunities and challenges in outcome assessment through informatics, as bioengineered therapeutics are increasingly developed for the unmet needs of molecularly defined diseases. Data submission requirements and analytic principles are outlined, and regulatory resources and foundational law and statute are cited for the reader.

Comparative molecular genomic analyses of a spontaneous rhesus macaque model of mismatch repair-deficient colorectal cancer

Colorectal cancer (CRC) remains the third most common cancer in the US with 15% of cases displaying Microsatellite Instability (MSI) secondary to Lynch Syndrome (LS) or somatic hypermethylation of the MLH1 promoter. A cohort of rhesus macaques from our institution developed spontaneous mismatch repair deficient (MMRd) CRC with a notable fraction harboring a pathogenic germline mutation in MLH1 (c.1029C Collapse

Key Words Collapse

MESH Headings

• Animals
• Colonic Neoplasms/genetics
• Colorectal Neoplasms/genetics
• Colorectal Neoplasms/pathology
• Colorectal Neoplasms, Hereditary Nonpolyposis/genetics
• Colorectal Neoplasms, Hereditary Nonpolyposis/pathology
• DNA Methylation/genetics
• DNA Mismatch Repair/genetics
• Genomics
• Humans
• Macaca mulatta/genetics
• Mice
• Microsatellite Instability
• MutL Protein Homolog 1/genetics

Collapse

Grants

• P30 CA016672 NCI NIH HHS
• R24 OD011173 NIH HHS
• Feinberg Family Foundation
• MDACC Institutional Research Grant Program
• Cattleman for Cancer Research
• National Institutes of Health
• National Cancer Institute

Collapse

Affiliation(s)

Nejla Ozirmak Lermi Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America School of Health Professions, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Stanton B. Gray Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Charles M. Bowen Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Laura Reyes-Uribe Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Beth K. Dray Charles River Laboratories, Ashland, Ohio, United States of America
Nan Deng Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
R. Alan Harris Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America
Muthuswamy Raveendran Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America
Fernando Benavides Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Carolyn L. Hodo Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Melissa W. Taggart Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Karen Colbert Maresso Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Krishna M. Sinha Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
Jeffrey Rogers Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America
Eduardo Vilar Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America Clinical Cancer Genetics Program, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America

Collapse

Role, molecular mechanism and the potential target of breast cancer stem cells in breast cancer development

Breast cancer (BC) is one of the most common malignant tumors in women globally, and its occurrence has surpassed lung cancer and become the biggest threat for women. At present, breast cancer treatment includes surgical resection or postoperative chemotherapy and radiotherapy. However, tumor relapse and metastasis usually lead to current therapy failure thanks to breast cancer stem cells (BCSCs)-mediated tumorigenicity and drug resistance. Drug resistance is mainly due to the long-term quiescent G0 phase, strong DNA repairability, and high expression of ABC transporter, and the tumorigenicity is reflected in the activation of various proliferation pathways related to BCSCs. Therefore, understanding the characteristics of BCSCs and their intracellular and extracellular molecular mechanisms is crucial for the development of targeted drugs for BCSCs. To this end, we discussed the latest developments in BCSCs research, focusing on the analysis of specific markers, critical signaling pathways that maintain the stemness of BCSCs，such as NOTCH, Wnt/β-catenin, STAT3, Hedgehog, and Hippo-YAP signaling, immunomicroenviroment and summarizes targeting therapy strategies for stemness maintenance and differentiation, which provides a theoretical basis for further exploration of treating breast cancer and preventing relapse derived from BCSCs.

Tumor organoids: synergistic applications, current challenges, and future prospects in cancer therapy

Patient-derived cancer cells (PDCs) and patient-derived xenografts (PDXs) are often used as tumor models, but have many shortcomings. PDCs not only lack diversity in terms of cell type, spatial organization, and microenvironment but also have adverse effects in stem cell cultures, whereas PDX are expensive with a low transplantation success rate and require a long culture time. In recent years, advances in three-dimensional (3D) organoid culture technology have led to the development of novel physiological systems that model the tissues of origin more precisely than traditional culture methods. Patient-derived cancer organoids bridge the conventional gaps in PDC and PDX models and closely reflect the pathophysiological features of natural tumorigenesis and metastasis, and have led to new patient-specific drug screening techniques, development of individualized treatment regimens, and discovery of prognostic biomarkers and mechanisms of resistance. Synergistic combinations of cancer organoids with other technologies, for example, organ-on-a-chip, 3D bio-printing, and CRISPR-Cas9-mediated homology-independent organoid transgenesis, and with treatments, such as immunotherapy, have been useful in overcoming their limitations and led to the development of more suitable model systems that recapitulate the complex stroma of cancer, inter-organ and intra-organ communications, and potentially multiorgan metastasis. In this review, we discuss various methods for the creation of organ-specific cancer organoids and summarize organ-specific advances and applications, synergistic technologies, and treatments as well as current limitations and future prospects for cancer organoids. Further advances will bring this novel 3D organoid culture technique closer to clinical practice in the future.

Biomarkers and cell-based models to predict the outcome of neoadjuvant therapy for rectal cancer patients

Rectal cancer constitutes approximately one-third of all colorectal cancers and contributes to considerable mortality globally. In contrast to colon cancer, the standard treatment for localized rectal cancer often involves neoadjuvant chemoradiotherapy. Tumour response rates to treatment show substantial inter-patient heterogeneity, indicating a need for treatment stratification. Consequently researchers have attempted to establish new means for predicting tumour response in order to assist in treatment decisions. In this review we have summarized published findings regarding potential biomarkers to predict neoadjuvant treatment response for rectal cancer tumours. In addition, we describe cell-based models that can be utilized both for treatment prediction and for studying the complex mechanisms involved.

Volumetric growth tracking of patient-derived cancer organoids using optical coherence tomography

Patient-derived cancer organoids (PCOs) are in vitro organotypic models that reflect in vivo drug response, thus PCOs are an accessible model for cancer drug screening in a clinically relevant timeframe. However, current methods to assess the response of PCOs are limited. Here, a custom swept-source optical coherence tomography (OCT) system was used to rapidly evaluate volumetric growth and drug response in PCOs. This system was optimized for an inverted imaging geometry to enable high-throughput imaging of PCOs. An automated image analysis framework was developed to perform 3D single-organoid tracking of PCOs across multiple time points over 48 hours. Metabolic inhibitors and cancer therapies decreased PCOs volumetric growth rate compared to control PCOs. Single-organoid tracking improved sensitivity to drug treatment compared to a pooled analysis of changes in organoid volume. OCT provided a more accurate assessment of organoid volume compared to a volume estimation method based on 2D projections. Single-organoid tracking with OCT also identified heterogeneity in drug response between solid and hollow PCOs. This work demonstrates that OCT and 3D single-organoid tracking are attractive tools to monitor volumetric growth and drug response in PCOs, providing rapid, non-destructive methods to quantify heterogeneity in PCOs.

Intestinal multicellular organoids to study colorectal cancer

Modeling colorectal cancer (CRC) using organoids has burgeoned in the last decade, providing enhanced in vitro models to study the development and possible treatment options for this type of cancer. In this review, we describe both normal and CRC intestinal organoid models and their utility in the cancer research field. Besides highlighting studies that develop epithelial CRC organoid models, i.e. organoids without tumor microenvironment (TME) cellular components, we emphasize on the need for TME in CRC modeling, to help reduce translational disparities in this area. Also, we discuss the utilization of CRC organoids derived from pluripotent stem cells, as well as their potential to be used in cancer research. Finally, limitations and challenges in the current CRC organoids field, are discussed.

Compensatory expression of NRF2-dependent antioxidant genes is required to overcome the lethal effects of Kv11.1 activation in breast cancer cells and PDOs

Potassium channels are important regulators of cellular homeostasis and targeting these proteins pharmacologically is unveiling important mechanisms in cancer cell biology. Here we demonstrate that pharmacological stimulation of the Kv11.1 potassium channel activity results in mitochondrial reactive oxygen species (ROS) production and fragmentation in breast cancer cell lines and patient-derived organoids independent of breast cancer subtype. mRNA expression profiling revealed that Kv11.1 activity significantly altered expression of genes controlling the production of ROS and endoplasmic-reticulum (ER) stress. Characterization of the transcriptional signature of breast cancer cells treated with Kv11.1 potassium channel activators strikingly revealed an adaptive response to the potentially lethal augmentation of ROS by increasing Nrf2-dependent transcription of antioxidant genes. Nrf2 in this context was shown to promote survival in breast cancer, whereas knockdown of Nrf2 lead to Kv11.1-induced cell death. In conclusion, we found that the Kv11.1 channel activity promotes oxidative stress in breast cancer cells and that suppression of the Nrf2-mediated anti-oxidant survival mechanism strongly sensitized breast cancer cells to a lethal effect of pharmacological activation of Kv11.1.

Organoids and Colorectal Cancer

Organoids were first established as a three-dimensional cell culture system from mouse small intestine. Subsequent development has made organoids a key system to study many human physiological and pathological processes that affect a variety of tissues and organs. In particular, organoids are becoming very useful tools to dissect colorectal cancer (CRC) by allowing the circumvention of classical problems and limitations, such as the impossibility of long-term culture of normal intestinal epithelial cells and the lack of good animal models for CRC. In this review, we describe the features and current knowledge of intestinal organoids and how they are largely contributing to our better understanding of intestinal cell biology and CRC genetics. Moreover, recent data show that organoids are appropriate systems for antitumoral drug testing and for the personalized treatment of CRC patients.

Lung cancer organoids analyzed on microwell arrays predict drug responses of patients within a week

While the potential of patient-derived organoids (PDOs) to predict patients’ responses to anti-cancer treatments has been well recognized, the lengthy time and the low efficiency in establishing PDOs hamper the implementation of PDO-based drug sensitivity tests in clinics. We first adapt a mechanical sample processing method to generate lung cancer organoids (LCOs) from surgically resected and biopsy tumor tissues. The LCOs recapitulate the histological and genetic features of the parental tumors and have the potential to expand indefinitely. By employing an integrated superhydrophobic microwell array chip (InSMAR-chip), we demonstrate hundreds of LCOs, a number that can be generated from most of the samples at passage 0, are sufficient to produce clinically meaningful drug responses within a week. The results prove our one-week drug tests are in good agreement with patient-derived xenografts, genetic mutations of tumors, and clinical outcomes. The LCO model coupled with the microwell device provides a technically feasible means for predicting patient-specific drug responses in clinical settings.

The lengthy time in establishing patient-derived organoids(PDOs) hampers the implementation of PDO-based drug sensitivity tests in clinics. Here, the authors show a microwell array-based method to predict patient’s responses to anti-cancer therapies in a week using lung cancer organoids.

Current methods in translational cancer research

Recent developments in pre-clinical screening tools, that more reliably predict the clinical effects and adverse events of candidate therapeutic agents, has ushered in a new era of drug development and screening. However, given the rapid pace with which these models have emerged, the individual merits of these translational research tools warrant careful evaluation in order to furnish clinical researchers with appropriate information to conduct pre-clinical screening in an accelerated and rational manner. This review assesses the predictive utility of both well-established and emerging pre-clinical methods in terms of their suitability as a screening platform for treatment response, ability to represent pharmacodynamic and pharmacokinetic drug properties, and lastly debates the translational limitations and benefits of these models. To this end, we will describe the current literature on cell culture, organoids, in vivo mouse models, and in silico computational approaches. Particular focus will be devoted to discussing gaps and unmet needs in the literature as well as current advancements and innovations achieved in the field, such as co-clinical trials and future avenues for refinement.

Patient-derived xenografts and organoids model therapy response in prostate cancer

Therapy resistance and metastatic processes in prostate cancer (PCa) remain undefined, due to lack of experimental models that mimic different disease stages. We describe an androgen-dependent PCa patient-derived xenograft (PDX) model from treatment-naïve, soft tissue metastasis (PNPCa). RNA and whole-exome sequencing of the PDX tissue and organoids confirmed transcriptomic and genomic similarity to primary tumor. PNPCa harbors BRCA2 and CHD1 somatic mutations, shows an SPOP/FOXA1-like transcriptomic signature and microsatellite instability, which occurs in 3% of advanced PCa and has never been modeled in vivo. Comparison of the treatment-naïve PNPCa with additional metastatic PDXs (BM18, LAPC9), in a medium-throughput organoid screen of FDA-approved compounds, revealed differential drug sensitivities. Multikinase inhibitors (ponatinib, sunitinib, sorafenib) were broadly effective on all PDX- and patient-derived organoids from advanced cases with acquired resistance to standard-of-care compounds. This proof-of-principle study may provide a preclinical tool to screen drug responses to standard-of-care and newly identified, repurposed compounds.

Challenges and solutions for fabrication of three-dimensional cocultures of neural cell-loaded biomimetic constructs

Fabrication of three-dimensional (3D) constructs to model body tissues and organs can contribute to research into tissue development and models for studying disease, as well as supporting preclinical drug screening in vitro. Furthermore, 3D constructs can also be used for diagnosis and therapy of disease conditions via lab on a chip and microarrays for diagnosis and engineered products for tissue repair, replacement, and regeneration. While cell culture approaches for studying tissue development and disease in two dimensions are long-established, the translation of this knowledge into 3D environments remains a fertile field of research. In this Tutorial, we specifically focus on the application of biosynthetic hydrogels for neural cell encapsulation. The Tutorial briefly covers background on using biosynthetic hydrogels for cell encapsulation, as well as common fabrication techniques. The Methods section focuses on the hydrogel design and characterization, highlighting key elements and tips for more effective approaches. Coencapsulation of different cell types, and the challenges associated with different growth and maintenance requirements, is the main focus of this Tutorial. Much care is needed to blend different cell types, and this Tutorial provides tips and insights that have proven successful for 3D coculture in biosynthetic hydrogels.

Patient-Derived Tumor Organoids for Drug Repositioning in Cancer Care: A Promising Approach in the Era of Tailored Treatment

Simple Summary

Currently, organoid research is having a growing impact in oncology. Tumor organoids, directly derived from patients’ specimens, can easily be expanded and cryopreserved. For that reason, they are becoming an indispensable ally in clinics for quicker diagnosis and prognosis of malignancies. Patient-derived cancer organoids are used as a platform to predict the efficacy of standard-of-care, as well as novel drugs. Therefore, this approach might be further utilized for validating off-label molecules, in order to widen the cancer care offer.

Abstract

Malignancies heterogeneity represents a critical issue in cancer care, as it often causes therapy resistance and tumor relapse. Organoids are three-dimensional (3D) miniaturized representations of selected tissues within a dish. Lately, organoid technology has been applied to oncology with growing success and Patients Derived Tumor Organoids (PDTOs) constitute a novel available tool which fastens cancer research. PDTOs are in vitro models of cancer, and importantly, they can be used as a platform to validate the efficacy of anti-cancer drugs. For that reason, they are currently utilized in clinics as emerging in vitro screening technology to tailor the therapy around the patient, with the final goal of beating cancer resistance and recurrence. In this sense, PDTOs biobanking is widely used and PDTO-libraries are helping the discovery of novel anticancer molecules. Moreover, they represent a good model to screen and validate compounds employed for other pathologies as off-label drugs potentially repurposed for the treatment of tumors. This will open up novel avenues of care thus ameliorating the life expectancy of cancer patients. This review discusses the present advancements in organoids research applied to oncology, with special attention to PDTOs and their translational potential, especially for anti-cancer drug testing, including off-label molecules.

Patient-derived organoids as individual patient models for chemoradiation response prediction in gastrointestinal malignancies

Chemoradiotherapy (CRT) is an important treatment modality for specific gastrointestinal (GI) cancers, as it has been shown to improve clinical outcomes. Recent developments in the neoadjuvant setting such as wait-and-see strategies for rectal as well as for esophageal cancers have even proven that CRT might be an effective organ-sparing treatment. However, due to molecular heterogeneity, only a subset of patients will show a complete response to CRT, which addresses the need for an individualized treatment approach. In recent years, the demand for more physiologically relevant predictive in vitro models has fostered the development of patient-derived tumor organoids. In this review, we describe the current treatment options for patients with GI cancers who are treated with (neo)adjuvant CRT. Furthermore, we provide an in-depth discussion of the organoid technology in the context of predicting CRT response for GI cancers as well as possible challenges for clinical implementation.

Genome-Wide Sex and Gender Differences in Cancer

Despite their known importance in clinical medicine, differences based on sex and gender are among the least studied factors affecting cancer susceptibility, progression, survival, and therapeutic response. In particular, the molecular mechanisms driving sex differences are poorly understood and so most approaches to precision medicine use mutational or other genomic data to assign therapy without considering how the sex of the individual might influence therapeutic efficacy. The mandate by the National Institutes of Health that research studies include sex as a biological variable has begun to expand our understanding on its importance. Sex differences in cancer may arise due to a combination of environmental, genetic, and epigenetic factors, as well as differences in gene regulation, and expression. Extensive sex differences occur genome-wide, and ultimately influence cancer biology and outcomes. In this review, we summarize the current state of knowledge about sex-specific genetic and genome-wide influences in cancer, describe how differences in response to environmental exposures and genetic and epigenetic alterations alter the trajectory of the disease, and provide insights into the importance of integrative analyses in understanding the interplay of sex and genomics in cancer. In particular, we will explore some of the emerging analytical approaches, such as the use of network methods, that are providing a deeper understanding of the drivers of differences based on sex and gender. Better understanding these complex factors and their interactions will improve cancer prevention, treatment, and outcomes for all individuals.

Patient-Derived Xenograft vs. Organoids: A Preliminary Analysis of Cancer Research Output, Funding and Human Health Impact in 2014-2019

Cancer remains a major threat to mortality and morbidity globally, despite intense research and generous funding. Patient-derived xenograft (PDX) models-where tumor biopsies are injected into an animal-were developed to improve the predictive capacity of preclinical animal models. However, recent observations have called into question the clinical relevance, and therefore the translational accuracy, of these. Patient-derived organoids (PDO) use patient tumor samples to create in vitro models that maintain aspects of tumor structure and heterogeneity. We undertook a preliminary analysis of the number of breast, colorectal, and lung cancer research studies using PDX or PDO published worldwide between 2014-2019. We looked for evidence of impacts of this research on human health. The number of publications that focused on PDO is gradually increasing over time, but is still very low compared to publications using PDX models. Support for new research projects using PDO is gradually increasing, a promising indicator of a shift towards more human-relevant approaches to understanding human disease. Overall, increases in total funding for these three major cancer types does not appear to be translating to any consequential increase in outputs, defined for this purpose as publications associated with clinical trials. With increasing public discomfort in research using animals and demands for 'alternative' methods, it is timely to consider how to implement non-animal methods more effectively.

Tumor in 3D: In Vitro Complex Cellular Models to Improve Nanodrugs Cancer Therapy

Nanodrugs represent novel solutions to reshuffle repurposed drugs for cancer therapy. They might offer different therapeutic options by combining targeted drug delivery and imaging in unique platforms. Such nanomaterials are deemed to overcome the limitations of currently available treatments, ultimately improving patients' life quality. However, despite these promises being made for over three decades, the poor clinical translation of nanoparticle- based therapies calls for deeper in vit.. and in vivo investigations. Translational issues arise very early during the development of nanodrugs, where complex and more reliable cell models are often replaced by easily accessible and convenient 2D monocultures. This is particularly true in the field of cancer therapy. In fact, 2D monocultures provide poor information about the real impact of the nanodrugs in a complex living organism, especially given the poor mimicry of the solid Tumors Microenvironment (TME). The dense and complex extracellular matrix (ECM) of solid tumors dramatically restricts nanoparticles efficacy, impairing the successful implementation of nanodrugs in medical applications. Herein, we propose a comprehensive guideline of the 3D cell culture models currently available, including their potential and limitations for the evaluation of nanodrugs activity. Advanced culture techniques, more closely resembling the physiological conditions of the TME, might give a better prediction of the reciprocal interactions between cells and nanoparticles and eventually help reconsider the use of old drugs for new applications.