Heterogeneous pathway activation and drug response modelled in colorectal-tumor-derived 3D cultures

3D tumor cultures for drug resistance and screening development in clinical applications

Tumor drug resistance presents a growing challenge in medical practice, particularly during anti-cancer therapies, where the emergence of drug-resistant cancer cells significantly complicates clinical treatment. In recent years, three-dimensional (3D) tumor culture technology, which more effectively simulates the in vivo physiological environment, has gained increasing attention in tumor drug resistance research and clinical applications. By mimicking the in vivo cellular microenvironment, 3D tumor culture technology not only recapitulates cell-cell interactions but also more faithfully reproduces the biological effects of therapeutic agents. Consequently, 3D tumor culture technology is emerging as a crucial tool in biomedical and clinical research. We summarize the benefits of 3D culture models and organoid technology, explore their application in the realm of drug resistance, drug screening, and personalized therapy, and discuss their potential application prospects and challenges in clinical transformation, with the aim of providing insights for optimizing cancer treatment strategies and advancing precision therapy.

Harnessing p53 for targeted cancer therapy: new advances and future directions

The transcription factor p53 is the most frequently impaired tumor suppressor in human cancers. In response to various stress stimuli, p53 activates transcription of genes that mediate its tumor-suppressive functions. Distinctive characteristics of p53 outlined here enable a well-defined program of genes involved in cell cycle arrest, apoptosis, senescence, differentiation, metabolism, autophagy, DNA repair, anti-viral response, and anti-metastatic functions, as well as facilitating autoregulation within the p53 network. This versatile, anti-cancer network governed chiefly by a single protein represents an immense opportunity for targeted cancer treatment, since about half of human tumors retain unmutated p53. During the last two decades, numerous compounds have been developed to block the interaction of p53 with the main negative regulator MDM2. However, small molecule inhibitors of MDM2 only induce a therapeutically desirable apoptotic response in a limited number of cancer types. Moreover, clinical trials of the MDM2 inhibitors as monotherapies have not met expectations and have revealed hematological toxicity as a characteristic adverse effect across this drug class. Currently, combination treatments are the leading strategy for enhancing efficacy and reducing adverse effects of MDM2 inhibitors. This review summarizes efforts to identify and test therapeutics that work synergistically with MDM2 inhibitors. Two main types of drugs have emerged among compounds used in the following combination treatments: first, modulators of the p53-regulated transcriptome (including chromatin modifiers), translatome, and proteome, and second, drugs targeting the downstream pathways such as apoptosis, cell cycle arrest, DNA repair, metabolic stress response, immune response, ferroptosis, and growth factor signaling. Here, we review the current literature in this field, while also highlighting overarching principles that could guide target selection in future combination treatments.

Spatial deconvolution from bulk DNA methylation profiles determines intratumoral epigenetic heterogeneity

BACKGROUND

Intratumoral heterogeneity emerges from accumulating genetic and epigenetic changes during tumorigenesis, which may contribute to therapeutic failure and drug resistance. However, the lack of a quick and convenient approach to determine the intratumoral epigenetic heterogeneity (eITH) limit the application of eITH in clinical settings. Here, we aimed to develop a tool that can evaluate the eITH using the DNA methylation profiles from bulk tumors.

METHODS

Genomic DNA of three laser micro-dissected tumor regions, including digestive tract surface, central bulk, and invasive front, was extracted from formalin-fixed paraffin-embedded sections of colorectal cancer patients. The genome-wide methylation profiles were generated with methylation array. The most variable methylated probes were selected to construct a DNA methylation-based heterogeneity (MeHEG) estimation tool that can deconvolve the proportion of each reference tumor region with the support vector machine model-based method. A PCR-based assay for quantitative analysis of DNA methylation (QASM) was developed to specifically determine the methylation status of each CpG in MeHEG assay at single-base resolution to realize fast evaluation of epigenetic heterogeneity.

RESULTS

In the discovery set with 79 patients, the differentially methylated CpGs among the three tumor regions were found. The 7 most representative CpGs were identified and subsequently selected to develop the MeHEG algorithm. We validated its performance of deconvolution of tumor regions in an independent cohort. In addition, we showed the significant association of MeHEG-based epigenetic heterogeneity with the genomic heterogeneity in mutation and copy number variation in our in-house and TCGA cohorts. Besides, we found that the patients with higher MeHEG score had worse disease-free and overall survival outcomes. Finally, we found dynamic change of epigenetic heterogeneity based on MeHEG score in cancer cells under the treatment of therapeutic drugs.

CONCLUSION

By developing a 7-loci panel using a machine learning approach combined with the QASM assay for PCR-based application, we present a valuable method for evaluating intratumoral heterogeneity. The MeHEG algorithm offers novel insights into tumor heterogeneity from an epigenetic perspective, potentially enriching current knowledge of tumor complexity and providing a new tool for clinical and research applications in cancer biology.

High Efficiency Lentiviral Transduction of Colon Organoids Using Reversible 2D/3D Culture Techniques

Organoids are a promising research tool for studying tissue development and disease in vitro. While organoids are frequently considered a replacement or complementary model for in vivo mouse experiments, exploiting their full potential often requires genetically engineered mice as a source of transgenic stem cells, also because genetic manipulation of organoids is rather inefficient and cumbersome. Here, we describe an alternative and optimized murine colon organoid manipulation protocol that reversibly and temporarily interrupts the 3D organoid structure for short-term 2D monolayer culture. This approach allows highly efficient viral transduction and genetic manipulation of stem cells in a 2D setting, followed by 3D stem cell embedding and restoration of the original organoid architecture. This method greatly improves the efficiency of lentiviral-mediated genetic manipulation of organoids and increases their potential applications in CRISPR/Cas9 and compound screens, immune-competent co-cultures, and disease modeling.

Advances in the application of colorectal cancer organoids in precision medicine

Colorectal cancer (CRC) ranks among the most prevalent gastrointestinal tumors globally and poses a significant threat to human health. In recent years, tumor organoids have emerged as ideal models for clinical disease research owing to their ability to closely mimic the original tumor tissue and maintain a stable phenotypic structure. Organoid technology has found widespread application in basic tumor research, precision therapy, and new drug development, establishing itself as a reliable preclinical model in CRC research. This has significantly advanced individualized and precise tumor therapies. Additionally, the integration of single-cell technology has enhanced the precision of organoid studies, offering deeper insights into tumor heterogeneity and treatment response, thereby contributing to the development of personalized treatment approaches. This review outlines the evolution of colorectal cancer organoid technology and highlights its strengths in modeling colorectal malignancies. This review also summarizes the progress made in precision tumor medicine and addresses the challenges in organoid research, particularly when organoid research is combined with single-cell technology. Furthermore, this review explores the future potential of organoid technology in the standardization of culture techniques, high-throughput screening applications, and single-cell multi-omics integration, offering novel directions for future colorectal cancer research.

Exploring the potential of human intestinal organoids: Applications, challenges, and future directions

The complex and dynamic environment of the gastrointestinal tract shapes one of the fastest renewing tissues in the human body, the intestinal epithelium. Considering the lack of human preclinical studies, reliable models that mimic the intestinal environment are increasingly explored. Patient-derived intestinal organoids are powerful tools that recapitulate in vitro many pathophysiological features of the human intestine. In this review, the possible applications of human intestinal organoids in different research fields are highlighted. From physiologically relevant to intestinal disease modeling, regenerative medicine, and toxicology studies, the potential of intestinal organoids will be here presented and discussed. Despite the remarkable opportunities offered, limitations related to ethical concerns, tissue collection, reproducibility, and methodologies may hinder the full exploitation of this cell-based model into high throughput studies and clinical practice. Currently, distinct approaches can be used to overcome the numerous challenges found along the way and to allow the full implementation of this ground-breaking technology.

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

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

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.

Revolutionizing digestive system tumor organoids research: Exploring the potential of tumor organoids

Digestive system tumors are the leading cause of cancer-related deaths worldwide. Despite ongoing research, our understanding of their mechanisms and treatment remain inadequate. One promising tool for clinical applications is the use of gastrointestinal tract tumor organoids, which serve as an important in vitro model. Tumor organoids exhibit a genotype similar to the patient's tumor and effectively mimic various biological processes, including tissue renewal, stem cell, and ecological niche functions, and tissue response to drugs, mutations, or injury. As such, they are valuable for drug screening, developing novel drugs, assessing patient outcomes, and supporting immunotherapy. In addition, innovative materials and techniques can be used to optimize tumor organoid culture systems. Several applications of digestive system tumor organoids have been described and have shown promising results in related aspects. In this review, we discuss the current progress, limitations, and prospects of this model for digestive system tumors.

Deciphering the Tumor Microenvironment of Colorectal Cancer and Guiding Clinical Treatment With Patient-Derived Organoid Technology: Progress and Challenges

Colorectal cancer (CRC) is one of the most prevalent malignant tumors of the digestive tract worldwide. Despite notable advancements in CRC treatment, there is an urgent requirement for preclinical model systems capable of accurately predicting drug efficacy in CRC patients, to identify more effective therapeutic options. In recent years, substantial strides have been made in the field of organoid technology, patient-derived organoid models can phenotypically replicate the original intra-tumor and inter-tumor heterogeneity of CRC, reflecting cellular interactions of the tumor microenvironment. Patient-derived organoid models have become an indispensable tool for investigating the pathogenesis of CRC and facilitating translational research. This review focuses on the application of organoid technology in CRC modeling, tumor microenvironment, and guiding clinical treatment, particularly in drug screening and personalized medicine. It also examines the existing challenges encountered in clinical organoid research and provides a prospective outlook on the future development directions of clinical organoid research, encompassing the standardization of organoid culture technology and the application of tissue engineering technology.

Patient-derived tumor models and their distinctive applications in personalized drug therapy

Tumor models in vitro are conventional methods for developing anti-cancer drugs, evaluating drug delivery, or calculating drug efficacy. However, traditional cell line-derived tumor models are unable to capture the tumor heterogeneity in patients or mimic the interaction between tumors and their surroundings. Recently emerging patient-derived preclinical cancer models, including of patient-derived xenograft (PDX) model, circulating tumor cell (CTC)-derived model, and tumor organoids-on-chips, are promising in personalized drug therapy by recapitulating the complexities and personalities of tumors and surroundings. These patient-derived models have demonstrated potential advantages in satisfying the rigorous demands of specificity, accuracy, and efficiency necessary for personalized drug therapy. However, the selection of suitable models is depending on the specific therapeutic requirements dictated by cancer types, progressions, or the assay scale. As an example, PDX models show remarkable advantages to reconstruct solid tumors in vitro to understand drug delivery and metabolism. Similarly, CTC-derived models provide a sensitive platform for drug testing in advanced-stage patients, while also facilitating the development of drugs aimed at suppressing tumor metastasis. Meanwhile, the demand for large-scale testing has promoted the development of tumor organoids-on-chips, which serves as an optimal tool for high-throughput drug screening. This review summarizes the establishment and development of PDX, CTC-derived models, and tumor organoids-on-chips and addresses their distinctive advantages in drug discovery, sensitive testing, and screening, which demonstrate the potential to aid in the selection of suitable models for fundamental cancer research and clinical trials, and further developing the personalized drug therapy.

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.

Patient-Derived Organoids from Locally Advanced Gastric Adenocarcinomas Can Predict Resistance to Neoadjuvant Chemotherapy

BACKGROUND

Patients (pts) with locally advanced gastric adenocarcinoma (LAGA) often receive neoadjuvant chemotherapy. A minority of patients do not respond to chemotherapy and thus may benefit from upfront surgery. Patient-derived organoids (PDOs) are an in vitro model that may mimic the chemotherapy response of the original tumors.

METHODS

PDOs were generated from endoscopic biopsies of LAGAs prior to the initiation of chemotherapy and treated with the two chemotherapy regimens: FLOT and FOLFOX. Cell proliferation was assayed after 3-6 days. Following chemotherapy, pts underwent surgical resection, and percent pathological necrosis was determined.

RESULTS

Successful PDOs were obtained from 13 of 24 (54%) LAGAs. Failure to generate PDOs were due to contamination (n = 3, 13%), early senescence (n = 3, 13%), and late senescence (n = 5, 21%). By H&E staining, there were significant similarities in tumor morphology and high concordance in immunohistochemical expression of 6 markers between tumors and derived PDOs. Four of 13 pts with successful PDOs did not undergo chemotherapy and surgery. For the remaining 9 pts, percent necrosis in resected tumors was ≤ 50% in 2 pts. The corresponding PDOs from these 2 pts were clearly chemoresistant outliers. The Pearson correlation coefficient between chemosensitivity of PDOs to FOLFOX (n = 2) or FLOT (n = 7) and percent tumor necrosis in resected tumors was 0.87 (p = 0.003).

CONCLUSIONS

PDOs from pts with LAGAs in many respects mimic the original tumors from which they are derived and may be used to predict resistance to neoadjuvant chemotherapy.

SYNOPSIS

Patient-derived organoids (PDOs) can serve as personalized in vitro models of patient tumors. In this study, PDOs from locally advanced gastric cancers were able to reliably predict resistance to neoadjuvant chemotherapy.

Functional precision oncology using patient-derived assays: bridging genotype and phenotype

Genomics-based precision medicine has revolutionized oncology but also has inherent limitations. Functional precision oncology is emerging as a complementary approach that aims to bridge the gap between genotype and phenotype by modelling individual tumours in vitro. These patient-derived ex vivo models largely preserve several tumour characteristics that are not captured by genomics approaches and enable the functional dissection of tumour vulnerabilities in a personalized manner. In this Review, we discuss several examples of personalized functional assays involving tumour organoids, spheroids and explants and their potential to predict treatment responses and drug-induced toxicities in individual patients. These developments have opened exciting new avenues for precision oncology, with the potential for successful clinical applications in contexts in which genomic data alone are not informative. To implement these assays into clinical practice, we outline four key barriers that need to be overcome: assay success rates, turnaround times, the need for standardized conditions and the definition of in vitro responders. Furthermore, we discuss novel technological advances such as microfluidics that might reduce sample requirements, assay times and labour intensity and thereby enable functional precision oncology to be implemented in routine clinical practice.

Sunitinib efficacy with minimal toxicity in patient-derived retinoblastoma organoids

BACKGROUND

Recurrence of retinoblastoma (RB) following chemoreduction is common and is often managed with local (intra-arterial/intravitreal) chemotherapy. However, some tumors are resistant to even local administration of maximum feasible drug dosages, or effective tumor control and globe preservation may be achieved at the cost of vision loss due to drug-induced retinal toxicity. The aim of this study was to identify drugs with improved antitumor activity and more favorable retinal toxicity profiles via screening of potentially repurposable FDA-approved drugs in patient-derived tumor organoids.

METHODS

Genomic profiling of five RB organoids and the corresponding parental tissues was performed. RB organoids were screened with 133 FDA-approved drugs, and candidate drugs were selected based on cytotoxicity and potency. RNA sequencing was conducted to generate a drug signature from RB organoids, and the effects of drugs on cell cycle progression and proliferative tumor cone restriction were examined. Drug toxicity was assessed with human embryonic stem cell-derived normal retinal organoids. The efficacy/toxicity profiles of candidate drugs were compared with those of drugs in clinical use.

RESULTS

RB organoids maintained the genomic features of the parental tumors. Sunitinib was identified as highly cytotoxic against both classical RB1-deficient and novel MYCN-amplified RB organoids and inhibited proliferation while inducing differentiation in RB. Sunitinib was a more effective suppressor of proliferative tumor cones in RB organoids and had lower toxicity in normal retinal organoids than either melphalan or topotecan.

CONCLUSION

The efficacy and retinal toxicity profiles of sunitinib suggest that it could potentially be repurposed for local chemotherapy of RB.

Development of bioinformatics and multi-omics analyses in organoids

Pre-clinical models are critical in gaining mechanistic and biological insights into disease progression. Recently, patient-derived organoid models have been developed to facilitate our understanding of disease development and to improve the discovery of therapeutic options by faithfully recapitulating in vivo tissues or organs. As technological developments of organoid models are rapidly growing, computational methods are gaining attention in organoid researchers to improve the ability to systematically analyze experimental results. In this review, we summarize the recent advances in organoid models to recapitulate human diseases and computational advancements to analyze experimental results from organoids. [BMB Reports 2023; 56(1): 43-48].

Organoids for Modeling (Colorectal) Cancer in a Dish

Simple Summary

Despite remarkable progress in the treatment of cancer patients, the medical need for drugs with better efficacy is still unmet and high. In addition to accurate prediction of drug efficacy for individual patients, pathophysiologically relevant preclinical model systems with increased predictive power are urgently needed to reduce the high rate of clinical trial failure in oncology. Organoids grown from patient material represent exceptionally valuable model systems to mimic and study human diseased tissues such as tumors. Here, we elaborate an overview of innovative and advanced organoid model systems and highlight the exciting opportunities of organoids for personalized precision medicine and the field of immuno-oncology drug development.

Abstract

Functional studies of primary cancer have been limited to animal models for a long time making it difficult to study aspects specific to human cancer biology. The development of organoid technology enabled us to culture human healthy and tumor cells as three-dimensional self-organizing structures in vitro for a prolonged time. Organoid cultures conserve the heterogeneity of the originating epithelium regarding cell types and tumor clonality. Therefore, organoids are considered an invaluable tool to study and genetically dissect various aspects of human cancer biology. In this review, we describe the applications, advantages, and limitations of organoids as human cancer models with the main emphasis on colorectal cancer.

The pivotal application of patient-derived organoid biobanks for personalized treatment of gastrointestinal cancers

Gastrointestinal cancers (GICs) occupy more than 30% of the cancer-related incidence and mortality around the world. Despite advances in the treatment strategies, the long-term overall survival has not been improved for patients with GICs. Recently, the novel patient-derived organoid (PDO) culture technology has become a powerful tool for GICs in a manner that recapitulates the morphology, pathology, genetic, phenotypic, and behavior traits of the original tumors. Excitingly, a number of evidences suggest that the versatile technology has great potential for personalized treatment, suppling the clinical application of molecularly guided personalized treatment. In the paper, we summarize the literature on the topics of establishing organoid biobanks of PDOs, and their application in the personalized treatment allowing for radiotherapy, chemotherapy, targeted therapy, and immunotherapy selection for GICs. Despite the limitations of current organoid models, high-throughput drug screening of GIC PDO combined with next-generation sequencing technology represents a novel and pivotal preclinical model for precision medicine of tumors and has a great value in promoting the transformation from basic cancer research to clinical application.

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.

Patient-derived rectal cancer organoids—applications in basic and translational cancer research

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and among the leading causes of death in both men and women. Rectal cancer (RC) is particularly challenging compared with colon cancer as the treatment after diagnosis of RC is more complex on account of its narrow anatomical location in the pelvis adjacent to the urogenital organs. More and more existing studies have begun to refine the research on RC and colon cancer separately. Early diagnosis and multiple treatment strategies optimize outcomes for individual patients. However, the need for more accurate and precise models to facilitate RC research is underscored due to the heterogeneity of clinical response and morbidity interrelated with radical surgery. Organoids generated from biopsies of patients have developed as powerful models to recapitulate many aspects of their primary tissue, consisting of 3-D self-organizing structures, which shed great light on the applications in both biomedical and clinical research. As the preclinical research models for RC are usually confused with colon cancer, research on patient-derived RC organoid models enable personalized analysis of cancer pathobiology, organizational function, and tumor initiation and progression. In this review, we discuss the various applications of patient-derived RC organoids over the past two years in basic cancer biology and clinical translation, including sequencing analysis, drug screening, precision therapy practice, tumor microenvironment studies, and genetic engineering opportunities.

Multifocal organoids reveal clonal associations between synchronous intestinal tumors with pervasive heterogeneous drug responses

Multifocal colorectal cancer (CRC) comprises both clonally independent primary tumors caused by inherited predisposition and clonally related tumors mainly due to intraluminal spreading along an intact basement membrane. The distinction between these multifocal CRCs is essential because therapeutic strategies vary according to the clonal association of multiple tumor masses. Here, we report one unique case of synchronous intestinal cancer (SIC) with tumors occurring along the entire bowel tract, including the small intestine. We established six patient-derived organoids (PDOs), and patient-derived cell lines (PDCs) from each site of the SIC, which were subjected to extensive genomic, transcriptomic, and epigenomic sequencing. We also estimated the drug responses of each multifocal SIC to 25 clinically relevant therapeutic compounds to validate how the clinically actionable alternations between SICs were associated with drug sensitivity. Our data demonstrated distinct clonal associations across different organs, which were consistently supported by multi-omics analysis, as well as the accordant responses to various therapeutic compounds. Our results indicated the imminent drawback of a single tumor-based diagnosis of multifocal CRC and suggested the necessity of an in-depth molecular analysis of all tumor regions to avoid unexpected resistance to the currently available targeted therapies.

Functional Drug Screening in the Era of Precision Medicine

The focus of precision medicine is providing the right treatment to each unique patient. This scientific movement has incited monumental advances in oncology including the approval of effective, targeted agnostic therapies. Yet, precision oncology has focused largely on genomics in the treatment decision making process, and several recent clinical trials demonstrate that genomics is not the only variable to be considered. Drug screening in three dimensional (3D) models, including patient derived organoids, organs on a chip, xenografts, and 3D-bioprinted models provide a functional medicine perspective and necessary complement to genomic testing. In this review, we discuss the practicality of various 3D drug screening models and each model's ability to capture the patient's tumor microenvironment. We highlight the potential for enhancing precision medicine that personalized functional drug testing holds in combination with genomic testing and emerging mathematical models.

A RAS-Independent Biomarker Panel to Reliably Predict Response to MEK Inhibition in Colorectal Cancer

Simple Summary

Today, clinical management for the majority of cancer patients is still based on a “one-size-fits-all” approach. To improve the outcomes in the era of personalized medicine, it is essential to stratify patients based on established and novel biomarkers. In the present study, we investigated a SMAD4 loss-of-function mutation, which is associated with chemoresistance and decreased overall survival in colorectal cancer (CRC). To investigate the molecular mechanism behind the impact on drug response, we used CRISPR technology on patient-derived organoid models (PDOs) of CRC. We showed that PDOs with loss-of-function SMAD4 mutations are sensitive to MEK-inhibitors. Using a novel four-gene signature reliably predicts sensitivity towards MEK-inhibitors, regardless of the RAS and BRAF status. The present study is a significant step towards personalized cancer therapy by identifying a new biomarker.

Abstract

Background: In colorectal cancer (CRC), mutations of genes associated with the TGF-β/BMP signaling pathway, particularly affecting SMAD4, are known to correlate with decreased overall survival and it is assumed that this signaling axis plays a key role in chemoresistance. Methods: Using CRISPR technology on syngeneic patient-derived organoids (PDOs), we investigated the role of a loss-of-function of SMAD4 in sensitivity to MEK-inhibitors. CRISPR-engineered SMAD4^R361H PDOs were subjected to drug screening, RNA-Sequencing, and multiplex protein profiling (DigiWest^®). Initial observations were validated on an additional set of 62 PDOs with known mutational status. Results: We show that loss-of-function of SMAD4 renders PDOs sensitive to MEK-inhibitors. Multiomics analyses indicate that disruption of the BMP branch within the TGF-β/BMP pathway is the pivotal mechanism of increased drug sensitivity. Further investigation led to the identification of the SFAB-signature (SMAD4, FBXW7, ARID1A, or BMPR2), coherently predicting sensitivity towards MEK-inhibitors, independent of both RAS and BRAF status. Conclusion: We identified a novel mutational signature that reliably predicts sensitivity towards MEK-inhibitors, regardless of the RAS and BRAF status. This finding poses a significant step towards better-tailored cancer therapies guided by the use of molecular biomarkers.

Patient-derived Tumour Organoids: A Bridge between Cancer Biology and Personalised Therapy

Patient-derived tumour organoids (PDOs) have revolutionised our understanding of cancer biology and the applications of personalised therapies. These advancements are principally ascribed to the ability of PDOs to consistently recapitulate and maintain the genomic, proteomic and morphological characteristics of parental tumours. Given these characteristics, PDOs (and their extended biobanks) are a representative preclinical model eminently suited to translate relevant scientific findings into personalized therapies rapidly. Here, we summarise recent advancements in PDOs from the perspective of cancer biology and clinical applications, focusing on the current challenges and opportunities of reconstructing and standardising more sophisticated PDO models. STATEMENT OF SIGNIFICANCE: Patient-derived tumour organoids (PDOs), three-dimensional (3D) self-assembled organotypic structures, have revolutionised our understanding of cancer biology and the applications of personalised therapies. These advancements are principally ascribed to the ability of PDOs to consistently recapitulate and maintain the genomic, proteomic and morphological characteristics of parental tumours. Given these characteristics, PDOs (and their extended biobanks) are a representative preclinical model eminently suited to translate relevant scientific findings into personalized therapies rapidly.

Patient-Derived Organoids of Colorectal Cancer: A Useful Tool for Personalized Medicine

Colorectal cancer is one of the most important malignancies worldwide, with high incidence and mortality rates. Several studies have been conducted using two-dimensional cultured cell lines; however, these cells do not represent a study model of patient tumors very well. In recent years, advancements in three-dimensional culture methods have facilitated the establishment of patient-derived organoids, which have become indispensable for molecular biology-related studies of colorectal cancer. Patient-derived organoids are useful in both basic science and clinical practice; they can help predict the sensitivity of patients with cancer to chemotherapy and radiotherapy and provide the right treatment to the right patient. Regarding precision medicine, combining gene panel testing and organoid-based screening can increase the effectiveness of medical care. In this study, we review the development of three-dimensional culture methods and present the most recent information on the clinical application of patient-derived organoids. Moreover, we discuss the problems and future prospects of organoid-based personalized medicine.

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.

Predicting Mutational Status of Driver and Suppressor Genes Directly from Histopathology With Deep Learning: A Systematic Study Across 23 Solid Tumor Types

In the last four years, advances in Deep Learning technology have enabled the inference of selected mutational alterations directly from routine histopathology slides. In particular, recent studies have shown that genetic changes in clinically relevant driver genes are reflected in the histological phenotype of solid tumors and can be inferred by analysing routine Haematoxylin and Eosin (H&E) stained tissue sections with Deep Learning. However, these studies mostly focused on selected individual genes in selected tumor types. In addition, genetic changes in solid tumors primarily act by changing signaling pathways that regulate cell behaviour. In this study, we hypothesized that Deep Learning networks can be trained to directly predict alterations of genes and pathways across a spectrum of solid tumors. We manually outlined tumor tissue in H&E-stained tissue sections from 7,829 patients with 23 different tumor types from The Cancer Genome Atlas. We then trained convolutional neural networks in an end-to-end way to detect alterations in the most clinically relevant pathways or genes, directly from histology images. Using this automatic approach, we found that alterations in 12 out of 14 clinically relevant pathways and numerous single gene alterations appear to be detectable in tissue sections, many of which have not been reported before. Interestingly, we show that the prediction performance for single gene alterations is better than that for pathway alterations. Collectively, these data demonstrate the predictability of genetic alterations directly from routine cancer histology images and show that individual genes leave a stronger morphological signature than genetic pathways.

Multifocal Organoid Capturing of Colon Cancer Reveals Pervasive Intratumoral Heterogenous Drug Responses

Intratumor heterogeneity (ITH) stands as one of the main difficulties in the treatment of colorectal cancer (CRC) as it causes the development of resistant clones and leads to heterogeneous drug responses. Here, 12 sets of patient-derived organoids (PDOs) and cell lines (PDCs) isolated from multiple regions of single tumors from 12 patients, capturing ITH by multiregion sampling of individual tumors, are presented. Whole-exome sequencing and RNA sequencing of the 12 sets are performed. The PDOs and PDCs of the 12 sets are also analyzed with a clinically relevant 24-compound library to assess their drug responses. The results reveal unexpectedly widespread subregional heterogeneity among PDOs and PDCs isolated from a single tumor, which is manifested by genetic and transcriptional heterogeneity and strong variance in drug responses, while each PDO still recapitulates the major histologic, genomic, and transcriptomic characteristics of the primary tumor. The data suggest an imminent drawback of single biopsy-originated PDO-based clinical diagnosis in evaluating CRC patient responses. Instead, the results indicate the importance of targeting common somatic driver mutations positioned in the trunk of all tumor subregional clones in parallel with a comprehensive understanding of the molecular ITH of each tumor.

Development and Application of Patient-Derived Cancer Organoidsin Clinical Management of Gastrointestinal Cancer: A State-of-the-Art Review

Human gastrointestinal cancer (e.g., gastric cancer and colorectal cancer) has been a leading cause of cancer-related deaths worldwide and has imposed a great threat to the public health. Although early-stage gastrointestinal cancer can be effectively treated by surgery, followed by postoperative chemotherapy, patients with advanced gastrointestinal cancer often exhibit poor prognosis and cancer relapse due to the absence of effective personalized treatment strategies. Patient-derived cancer organoid technology has been rapidly developed in recent years, and its emergence has opened up an unprecedented approach to model human cancers in vitro. Patient-derived cancer organoids involve the ex vivo culture of fragments of freshly resected human tumors that retain the histological features of original tumors. This review thoroughly discussed the evolutionary process of human gastrointestinal organoids cultured since 2009, and highlighted the potentials of patient-derived cancer organoids in clinical management of gastrointestinal cancer in terms of advances achieved in cancer modelling compared with conventional modelling methods, high-throughput drug screening, and development of personalized treatment selection. Additionally, the current limitations of patient-derived cancer organoids and the potential solutions to overcome these problems were summarized.

Regulation of signal transduction pathways in colorectal cancer: implications for therapeutic resistance

Resistance to anti-cancer treatments is a critical and widespread health issue that has brought serious impacts on lives, the economy and public policies. Mounting research has suggested that a selected spectrum of patients with advanced colorectal cancer (CRC) tend to respond poorly to both chemotherapeutic and targeted therapeutic regimens. Drug resistance in tumours can occur in an intrinsic or acquired manner, rendering cancer cells insensitive to the treatment of anti-cancer therapies. Multiple factors have been associated with drug resistance. The most well-established factors are the emergence of cancer stem cell-like properties and overexpression of ABC transporters that mediate drug efflux. Besides, there is emerging evidence that signalling pathways that modulate cell survival and drug metabolism play major roles in the maintenance of multidrug resistance in CRC. This article reviews drug resistance in CRC as a result of alterations in the MAPK, PI3K/PKB, Wnt/β-catenin and Notch pathways.

Context Matters-Why We Need to Change From a One Size Fits all Approach to Made-to-Measure Therapies for Individual Patients With Pancreatic Cancer

Pancreatic cancer is one of the deadliest cancers and remains a major unsolved health problem. While pancreatic ductal adenocarcinoma (PDAC) is associated with driver mutations in only four major genes (KRAS, TP53, SMAD4, and CDKN2A), every tumor differs in its molecular landscape, histology, and prognosis. It is crucial to understand and consider these differences to be able to tailor treatment regimens specific to the vulnerabilities of the individual tumor to enhance patient outcome. This review focuses on the heterogeneity of pancreatic tumor cells and how in addition to genetic alterations, the subsequent dysregulation of multiple signaling cascades at various levels, epigenetic and metabolic factors contribute to the oncogenesis of PDAC and compensate for each other in driving cancer progression if one is tackled by a therapeutic approach. This implicates that besides the need for new combinatorial therapies for PDAC, a personalized approach for treating this highly complex cancer is required. A strategy that combines both a target-based and phenotypic approach to identify an effective treatment, like Reverse Clinical Engineering® using patient-derived organoids, is discussed as a promising way forward in the field of personalized medicine to tackle this deadly disease.

Gastrointestinal cancer organoids-applications in basic and translational cancer research

Cancer is a major health problem and a leading cause of death worldwide. Early cancer detection and continuous changes in treatment strategies have improved overall patient survival. The recent development of targeted drugs offers new opportunities for personalized cancer treatment. Nevertheless, individualized treatment is accompanied by the need for biomarkers predicting the response of a patient to a certain drug. One of the most promising breakthroughs in recent years that might help to overcome this problem is the organoid technology. Organoid cultures exhibit self-renewal capacity, self-organization, and long-term proliferation, while recapitulating many aspects of their primary tissue. Generated patient-derived organoid (PDO) libraries constitute "living" biobanks, allowing the in-depth analysis of tissue function, development, tumor initiation, and cancer pathobiology. Organoids can be derived from all gastrointestinal tissues, including esophageal, gastric, liver, pancreatic, small intestinal and colorectal tissues, and cancers of these tissues. PDOs are amenable to various techniques, including sequencing analyses, drug screening, targeted therapy testing, tumor microenvironment studies, and genetic engineering capabilities. In this review, we discuss the different applications of gastrointestinal organoids in basic cancer biology and clinical translation.

Low-viscosity matrix suspension culture enables scalable analysis of patient-derived organoids and tumoroids from the large intestine

Cell embedment into a solid support matrix is considered essential for the culture of intestinal epithelial organoids and tumoroids, but this technique presents challenges that impede scalable culture expansion, experimental manipulation, high-throughput screening and diagnostic applications. We have developed a low-viscosity matrix (LVM) suspension culture method that enables efficient establishment and propagation of organoids and tumoroids from the human large intestine. Organoids and tumoroids cultured in LVM suspension recapitulate the morphological development observed in solid matrices, with tumoroids reflecting the histological features and genetic heterogeneity of primary colorectal cancers. We demonstrate the utility of LVM suspension culture for organoid and tumoroid bioreactor applications and biobanking, as well as tumoroid high-throughput drug sensitivity testing. These methods provide opportunities for the study and use of patient-derived organoids and tumoroids from the large intestine.

Given the practical limitations of solid matrix-based protocols in organoid culture, Yumiko Hirokawa et al. assess the ability of low-concentration Matrigel conditions to promote intestinal organoid growth. Their results suggest that a low-viscosity culture system can improve live cell yield compared to the existing dome method, while maintaining similar morphology, and represents a useful approach for high-throughput applications of organoids.

Increased sensitivity to SMAC mimetic LCL161 identified by longitudinal ex vivo pharmacogenomics of recurrent, KRAS mutated rectal cancer liver metastases

Tumor heterogeneity is a primary cause of treatment failure. However, changes in drug sensitivity over time are not well mapped in cancer. Patient-derived organoids (PDOs) may predict clinical drug responses ex vivo and offer an opportunity to evaluate novel treatment strategies in a personalized fashion. Here we have evaluated spatio-temporal functional and molecular dynamics of five PDO models established after hepatic re-resections and neoadjuvant combination chemotherapies in a patient with microsatellite stable and KRAS mutated metastatic rectal cancer. Histopathological differentiation phenotypes of the PDOs corresponded with the liver metastases, and ex vivo drug sensitivities generally reflected clinical responses and selection pressure, assessed in comparison to a reference data set of PDOs from metastatic colorectal cancers. PDOs from the initial versus the two recurrent metastatic settings showed heterogeneous cell morphologies, protein marker expression, and drug sensitivities. Exploratory analyses of a drug screen library of 33 investigational anticancer agents showed the strongest ex vivo sensitivity to the SMAC mimetic LCL161 in PDOs of recurrent disease compared to those of the initial metastasis. Functional analyses confirmed target inhibition and apoptosis induction in the LCL161 sensitive PDOs from the recurrent metastases. Gene expression analyses indicated an association between LCL161 sensitivity and tumor necrosis factor alpha signaling and RIPK1 gene expression. In conclusion, LCL161 was identified as a possible experimental therapy of a metastatic rectal cancer that relapsed after hepatic resection and standard systemic treatment.

Delineating the longitudinal tumor evolution using organoid models

Cancer is an evolutionary process fueled by genetic or epigenetic alterations in the genome. Understanding the evolutionary dynamics that are operative at different stages of tumor progression might inform effective strategies in early detection, diagnosis, and treatment of cancer. However, our understanding on the dynamics of tumor evolution through time is very limited since it is usually impossible to sample patient tumors repeatedly. The recent advances in in vitro 3D organoid culture technologies have opened new avenues for the development of more realistic human cancer models that mimic many in vivo biological characteristics in human tumors. Here, we review recent progresses and challenges in cancer genomic evolution studies and advantages of using tumor organoids to study cancer evolution. We propose to establish an experimental evolution model based on continuous passages of patient-derived organoids and longitudinal sampling to study clonal dynamics and evolutionary patterns over time. Development and integration of population genetic theories and computational models into time-course genomic data in tumor organoids will help to pinpoint the key cellular mechanisms underlying cancer evolutionary dynamics, thus providing novel insights on therapeutic strategies for highly dynamic and heterogeneous tumors.

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.

Preclinical models as patients' avatars for precision medicine in colorectal cancer: past and future challenges

Colorectal cancer (CRC) is a complex and heterogeneous disease, characterized by dismal prognosis and low survival rate in the advanced (metastatic) stage. During the last decade, the establishment of novel preclinical models, leading to the generation of translational discovery and validation platforms, has opened up a new scenario for the clinical practice of CRC patients. To bridge the results developed at the bench with the medical decision process, the ideal model should be easily scalable, reliable to predict treatment responses, and flexibly adapted for various applications in the research. As such, the improved benefit of novel therapies being tested initially on valuable and reproducible preclinical models would lie in personalized treatment recommendations based on the biology and genomics of the patient's tumor with the overall aim to avoid overtreatment and unnecessary toxicity. In this review, we summarize different in vitro and in vivo models, which proved efficacy in detection of novel CRC culprits and shed light into the biology and therapy of this complex disease. Even though cell lines and patient-derived xenografts remain the mainstay of colorectal cancer research, the field has been confidently shifting to the use of organoids as the most relevant preclinical model. Prioritization of organoids is supported by increasing body of evidence that these represent excellent tools worth further therapeutic explorations. In addition, novel preclinical models such as zebrafish avatars are emerging as useful tools for pharmacological interrogation. Finally, all available models represent complementary tools that can be utilized for precision medicine applications.

Patient-Derived Ovarian Cancer Organoids Mimic Clinical Response and Exhibit Heterogeneous Inter- and Intrapatient Drug Responses

There remains an unmet need for preclinical models to enable personalized therapy for ovarian cancer (OC) patients. Here we evaluate the capacity of patient-derived organoids (PDOs) to predict clinical drug response and functional consequences of tumor heterogeneity. We included 36 whole-genome-characterized PDOs from 23 OC patients with known clinical histories. OC PDOs maintain the genomic features of the original tumor lesion and recapitulate patient response to neoadjuvant carboplatin/paclitaxel combination treatment. PDOs display inter- and intrapatient drug response heterogeneity to chemotherapy and targeted drugs, which can be partially explained by genetic aberrations. PDO drug screening identifies high responsiveness to at least one drug for 88% of patients. PDOs are valuable preclinical models that can provide insights into drug response for individual patients with OC, complementary to genetic testing. Generating PDOs of multiple tumor locations can improve clinical decision making and increase our knowledge of genetic and drug response heterogeneity.

High Yap and Mll1 promote a persistent regenerative cell state induced by Notch signaling and loss of p53

Specified intestinal epithelial cells reprogram and contribute to the regeneration and renewal of the epithelium upon injury. Mutations that deregulate such renewal processes may contribute to tumorigenesis. Using intestinal organoids, we show that concomitant activation of Notch signaling and ablation of p53 induce a highly proliferative and regenerative cell state, which is associated with increased levels of Yap and the histone methyltransferase Mll1. The induced signaling system orchestrates high proliferation, self-renewal, and niche-factor-independent growth, and elevates the trimethylation of histone 3 at lysine 4 (H3K4me3). We demonstrate that Yap and Mll1 are also elevated in patient-derived colorectal cancer (CRC) organoids and control growth and viability. Our data suggest that Notch activation and p53 ablation induce a signaling circuitry involving Yap and the epigenetic regulator Mll1, which locks cells in a proliferative and regenerative state that renders them susceptible for tumorigenesis.

Precision Oncology Beyond Genomics: The Future Is Here-It Is Just Not Evenly Distributed

Cancer is a multifactorial disease with increasing incidence. There are more than 100 different cancer types, defined by location, cell of origin, and genomic alterations that influence oncogenesis and therapeutic response. This heterogeneity between tumors of different patients and also the heterogeneity within the same patient's tumor pose an enormous challenge to cancer treatment. In this review, we explore tumor heterogeneity on the longitudinal and the latitudinal axis, reviewing current and future approaches to study this heterogeneity and their potential to support oncologists in tailoring a patient's treatment regimen. We highlight how the ideal of precision oncology is reaching far beyond the knowledge of genetic variants to inform clinical practice and discuss the technologies and strategies already available to improve our understanding and management of heterogeneity in cancer treatment. We will focus on integrating multi-omics technologies with suitable in vitro models and their proficiency in mimicking endogenous tumor heterogeneity.

A molecular subtype of colorectal cancers initiates independently of epidermal growth factor receptor and has an accelerated growth rate mediated by IL10-dependent anergy

Although epidermal growth factor receptor (EGFR)-targeted therapies are approved for colorectal cancer (CRC) treatment, only 15% of CRC patients respond to EGFR inhibition. Here, we show that colorectal cancers (CRC) can initiate and grow faster through an EGFR-independent mechanism, irrespective of the presence of EGFR, in two different mouse models using tissue-specific ablation of Egfr. The growth benefit in the absence of EGFR is also independent of Kras status. An EGFR-independent gene expression signature, also observed in human CRCs, revealed that anergy-inducing genes are overexpressed in EGFR-independent polyps, suggesting increased infiltration of anergic lymphocytes promotes an accelerated growth rate that is partially caused by escape from cell-mediated immune responses. Many genes in the EGFR-independent gene expression signature are downstream targets of interleukin 10 receptor alpha (IL10RA). We further show that IL10 is detectable in serum from mice with EGFR-independent colon polyps. Using organoids in vitro and Src ablation in vivo, we show that IL10 contributes to growth of EGFR-independent CRCs, potentially mediated by the well-documented role of SRC in IL10 signaling. Based on these data, we show that the combination of an EGFR inhibitor with an anti-IL10 neutralizing antibody results in decreased cell proliferation in organoids and in decreased polyp size in pre-clinical models harboring EGFR-independent CRCs, providing a new therapeutic intervention for CRCs resistant to EGFR inhibitor therapies.

Patient-Derived Cancer Organoids as Predictors of Treatment Response

Patient-derived cancer organoids have taken a prominent role in pre-clinical and translational research and have been generated for most common solid tumors. Cancer organoids have been shown to retain key genetic and phenotypic characteristics of their tissue of origin, tumor subtype and maintain intratumoral heterogeneity and therefore have the potential to be used as predictors for individualized treatment response. In this review, we highlight studies that have used cancer organoids to compare the efficacy of standard-of-care and targeted combination treatments with clinical patient response. Furthermore, we review studies using cancer organoids to identify new anti-cancer treatments using drug screening. Finally, we discuss the current limitations and improvements needed to understand the full potential of cancer organoids as avatars for clinical management of cancer therapy.

Academic collaborative models fostering the translation of physiological in vitro systems from basic research into drug discovery

The success of preclinical drug discovery strongly relies on the ability of experimental models to resemble human pathophysiology. The number of compounds receiving approval for clinical use is limited, and this has led to the development of more physiologically relevant cellular models aimed at making preclinical results more prone to be successfully translated into clinical use. In this review, we summarize the technologies available in the field of high-throughput screening (HTS) using complex cellular models, and describe collaborative initiatives, such as EU-OPENSCREEN, which can efficiently support researchers to easily access state-of-the-art chemical biology platforms for improving the drug discovery process.

Patient-derived cancer organoid tracking with wide-field one-photon redox imaging to assess treatment response

SIGNIFICANCE

Accessible tools are needed for rapid, non-destructive imaging of patient-derived cancer organoid (PCO) treatment response to accelerate drug discovery and streamline treatment planning for individual patients.

AIM

To segment and track individual PCOs with wide-field one-photon redox imaging to extract morphological and metabolic variables of treatment response.

APPROACH

Redox imaging of the endogenous fluorophores, nicotinamide dinucleotide (NADH), nicotinamide dinucleotide phosphate (NADPH), and flavin adenine dinucleotide (FAD), was used to monitor the metabolic state and morphology of PCOs. Redox imaging was performed on a wide-field one-photon epifluorescence microscope to evaluate drug response in two colorectal PCO lines. An automated image analysis framework was developed to track PCOs across multiple time points over 48 h. Variables quantified for each PCO captured metabolic and morphological response to drug treatment, including the optical redox ratio (ORR) and organoid area.

RESULTS

The ORR (NAD(P)H/(FAD + NAD(P)H)) was independent of PCO morphology pretreatment. Drugs that induced cell death decreased the ORR and growth rate compared to control. Multivariate analysis of redox and morphology variables identified distinct PCO subpopulations. Single-organoid tracking improved sensitivity to drug treatment compared to pooled organoid analysis.

CONCLUSIONS

Wide-field one-photon redox imaging can monitor metabolic and morphological changes on a single organoid-level, providing an accessible, non-destructive tool to screen drugs in patient-matched samples.

Organoid research in digestive system tumors

Digestive system tumors are the most common cause of cancer-associated mortality worldwide, although their underlying biological behavior still requires further investigation. Most of the in vitro studies that have been published have been based on the two-dimensional (2D) culture system. However, digestive system tumors exhibit considerable histological and functional heterogeneity, and clonal diversity and heterogeneity cannot be entirely reflected in the 2D culture system. Recently, the development of organoids appears to have shed some light on this area of cancer research. The present review discusses the recent advancements that have been made in the development of several specific organoids in digestive system solid tumors.

Identification of LncRNAs Associated With FOLFOX Chemoresistance in mCRC and Construction of a Predictive Model

Oxaliplatin, fluorouracil plus leucovorin (FOLFOX) regimen is the first-line chemotherapy of patients with metastatic colorectal cancer (mCRC). However, studies are limited regarding long non-coding RNAs (lncRNAs) associated with FOLFOX chemotherapy response and prognosis. This study aimed to identify lncRNAs associated with FOLFOX chemotherapy response and prognosis in mCRC patients and to construct a predictive model. We analyzed lncRNA expression in 11 mCRC patients treated with FOLFOX chemotherapy before surgery (four sensitive, seven resistant) by Gene Array Chip. The top eight lncRNAs (AC007193.8, CTD-2008N3.1, FLJ36777, RP11-509J21.4, RP3-508I15.20, LOC100130950, RP5-1042K10.13, and LINC00476) for chemotherapy response were identified according to weighted correlation network analysis (WGCNA). A competitive endogenous RNA (ceRNA) network was then constructed. The crucial functions of the eight lncRNAs enriched in chemotherapy resistance were mitogen-activated protein kinase (MAPK) and proteoglycans signaling pathway. Receiver operating characteristic (ROC) analysis demonstrated that the eight lncRNAs were potent predictors for chemotherapy resistance of mCRC patients. To further identify a signature model lncRNA chemotherapy response and prognosis, the validation set consisted of 196 CRC patients from our center was used to validate lncRNAs expression and prognosis by quantitative PCR (qPCR). The expression of the eight lncRNAs expression between CRC cancerous and adjacent non-cancerous tissues was also verified in the validation data set to determine the prognostic value. A generalized linear model was established to predict the probability of chemotherapy resistance and survival. Our findings showed that the eight-lncRNA signature may be a novel biomarker for the prediction of FOLFOX chemotherapy response and prognosis of mCRC patients.

Generation of Patient-Derived Colorectal Cancer Organoids for RAS Studies

Human cell line models have been widely used for testing of novel anticancer compounds and for predicting clinical response to monotherapies and combinatorial therapies. For many years, standard monolayer culture conditions were used as gold standard, only surpassed by in vivo testing of mouse models. Recently, the incorporation of three-dimensional culture has been shown to further improve predictive compound testing. In view of the renewed interest in anti-RAS cancer therapy, we provide a protocol for establishing colorectal cancer organoids which are characterized by a high prevalence of KRAS mutations.

Mutation-specific effects of NRAS oncogenes in colorectal cancer cells

In colorectal cancer (CRC), the prevalence of NRAS mutations (5-9%) is inferior to that of KRAS mutations (40-50%). NRAS mutations feature lately during tumour progression and drive resistance to anti-EGFR therapy in KRAS wild-type tumours. To elucidate specific functions of NRAS mutations in CRC, we expressed doxycycline-inducible G12D and Q61K mutations in the CRC cell line Caco-2. A focused phospho-proteome analysis based on the Bio-Plex platform, which interrogated the activity of MAPK, PI3K, mTOR, STAT, p38, JNK and ATF2, did not reveal significant differences between Caco-2 cells expressing NRAS^G12D, NRAS^Q61K and KRAS^G12V. However, phenotypic read-outs were different. The NRAS Q61K mutation promoted anchorage-independent proliferation and tumorigenicity, similar to features driven by canonical KRAS mutations. In contrast, expression of NRAS^G12D resulted in reduced proliferation and apoptosis. At the transcriptome level, we saw upregulation of cytokines and chemokines. IL1A, IL11, CXCL8 (IL-8) and CCL20 exhibited enhanced secretion into the culture medium. In addition, RNA sequencing results indicated activation of the IL1-, JAK/STAT-, NFκB- and TNFα signalling pathways. These results form the basis for an NRAS^G12D-driven inflammatory phenotype in CRC.

Applications of Organoids for Cancer Biology and Precision Medicine

Organoid technologies enable the creation of in vitro physiologic systems that model tissues of origin more accurately than classical culture approaches. Seminal characteristics, including three-dimensional structure and recapitulation of self-renewal, differentiation, and disease pathology, render organoids eminently suited as hybrids that combine the experimental tractability of traditional 2D cell lines with cellular attributes of in vivo model systems. Here, we describe recent advances in this rapidly evolving field and their applications in cancer biology, clinical translation and precision medicine.

Drug resistance in cancer: mechanisms and tackling strategies

Drug resistance developed towards conventional therapy is one of the important reasons for chemotherapy failure in cancer. The various underlying mechanism for drug resistance development in tumor includes tumor heterogeneity, some cellular levels changes, genetic factors, and others novel mechanisms which have been highlighted in the past few years. In the present scenario, researchers have to focus on these novel mechanisms and their tackling strategies. The small molecules, peptides, and nanotherapeutics have emerged to overcome the drug resistance in cancer. The drug delivery systems with targeting moiety enhance the site-specificity, receptor-mediated endocytosis, and increase the drug concentration inside the cells, thus minimizing drug resistance and improve their therapeutic efficacy. These therapeutic approaches work by modulating the different pathways responsible for drug resistance. This review focuses on the different mechanisms of drug resistance and the recent advancements in therapeutic approaches to improve the sensitivity and effectiveness of chemotherapeutics.