The power and the promise of organoid models for cancer precision medicine with next-generation functional diagnostics and pharmaceutical exploitation

Next-Generation Modeling of Cancer Using Organoids

In the last decade, organoid technology has become a cornerstone in cancer research. Organoids are long-term primary cell cultures, usually of epithelial origin, grown in a three-dimensional (3D) protein matrix and a fully defined medium. Organoids can be derived from many organs and cancer types and sites, encompassing both murine and human tissues. Importantly, they can be established from various stages during tumor evolution and recapitulate with high accuracy patient genomics and phenotypes in vitro, offering a platform for personalized medicine. Additionally, organoids are remarkably amendable for experimental manipulation. Taken together, these features make organoids a powerful tool with applications in basic cancer research and personalized medicine. Here, we will discuss the origins of organoid culture, applications in cancer research, and how cancer organoids can synergize with other models of cancer to drive basic discoveries as well as to translate these toward clinical solutions.

Building consensus on the application of organoid-based drug sensitivity testing in cancer precision medicine and drug development

Patient-derived organoids (PDOs) have emerged as a promising platform for clinical and translational studies. A strong correlation exists between clinical outcomes and the use of PDOs to predict the efficacy of chemotherapy and/or radiotherapy. To standardize interpretation and enhance scientific communication in the field of cancer precision medicine, we revisit the concept of PDO-based drug sensitivity testing (DST). We present an expert consensus-driven approach for medication selection aimed at predicting patient responses. To further standardize PDO-based DST, we propose guidelines for clarification and characterization. Additionally, we identify several major challenges in clinical prediction when utilizing PDOs.

Liver organoids and their application in liver cancer research

Liver cancer, a common and intractable liver-related disease, is a malignant tumor with a high morbidity, which needs a high treatment cost but still lacks perfect clinical treatment methods. Looking for an effective platform for liver cancer study and drug screening is urgent and important. Traditional analytical methods for liver disease studies mainly rely on the 2D cell culture and animal experiments, which both cannot fully recapitulate physiological and pathological processes of human liver. For example, cell culture can only show basic functions of cells in vitro, while animal models always hold the problem of species divergence. The organoids, a 3D invitro culture system emerged in recent years, is a cell-bound body with different cell types and has partial tissue functions. The organoid technology can reveal the growth state, structure, function and characteristics of the tissue or organ, and plays an important role in reconstructing invitro experimental models that can truly simulate the human liver. In this paper, we will give a brief introduction of liver organoids and review their applications in liver cancer research, especially in liver cancer pathogenesis, drug screening, precision medicine, regenerative medicine, and other fields. We have also discussed advantages and disadvantages of organoids, as well as future directions and perspectives towards liver organoids.

Breast cancer brain metastasis: from etiology to state-of-the-art modeling

Currently, breast carcinoma is the most common form of malignancy and the main cause of cancer mortality in women worldwide. The metastasis of cancer cells from the primary tumor site to other organs in the body, notably the lungs, bones, brain, and liver, is what causes breast cancer to ultimately be fatal. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Many researchers have focused on brain metastasis, but due to its complexities, many aspects of this process are still relatively unclear. To develop and test novel therapies for this fatal condition, pre-clinical models are required that can mimic the biological processes involved in breast cancer brain metastasis (BCBM). The application of many breakthroughs in the area of tissue engineering has resulted in the development of scaffold or matrix-based culture methods that more accurately imitate the original extracellular matrix (ECM) of metastatic tumors. Furthermore, specific cell lines are now being used to create three-dimensional (3D) cultures that can be used to model metastasis. These 3D cultures satisfy the requirement for in vitro methodologies that allow for a more accurate investigation of the molecular pathways as well as a more in-depth examination of the effects of the medication being tested. In this review, we talk about the latest advances in modeling BCBM using cell lines, animals, and tissue engineering methods.

Drug screening at single-organoid resolution via bioprinting and interferometry

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection.

Precision medicine applied to metastatic colorectal cancer using tumor-derived organoids and in-vitro sensitivity testing: a phase 2, single-center, open-label, and non-comparative study

BACKGROUND

Patients with colorectal metastatic disease have a poor prognosis, limited therapeutic options, and frequent development of resistance. Strategies based on tumor-derived organoids are a powerful tool to assess drug sensitivity at an individual level and to suggest new treatment options or re-challenge. Here, we evaluated the method's feasibility and clinical outcome as applied to patients with no satisfactory treatment options.

METHODS

In this phase 2, single-center, open-label, non-comparative study (ClinicalTrials.gov, register NCT03251612), we enrolled 90 patients with metastatic colorectal cancer following progression on or after standard therapy. Participants were 18 years or older with an Eastern Cooperative Oncology Group performance status of 0-2, adequate organ function, and metastasis available for biopsy. Biopsies from the metastatic site were cultured using organoids model. Sensitivity testing was performed with a panel of drugs with proven activity in phase II or III trials. At the discretion of the investigator considering toxicity, the drug with the highest relative activity was offered. The primary endpoint was the proportion of patients alive without disease progression at two months per local assessment.

RESULTS

Biopsies available from 82 to 90 patients were processed for cell culture, of which 44 successfully generated organoids with at least one treatment suggested. The precision cohort of 34 patients started treatment and the primary endpoint, progression-free survival (PFS) at two months was met in 17 patients (50%, 95% CI 32-68), exceeding the pre-defined level (14 of 45; 31%). The median PFS was 67 days (95% CI 51-108), and the median overall survival was 189 days (95% CI 103-277).

CONCLUSIONS

Patient-derived organoids and in-vitro sensitivity testing were feasible in a cohort of metastatic colorectal cancer. The primary endpoint was met, as half of the patients were without progression at two months. Cancer patients may benefit from functional testing using tumor-derived organoids.

TRIAL REGISTRATION

ClinicalTrials.gov, register NCT03251612.

Engineering high throughput screening platforms of cervical cancer

Cervical cancer is the second leading cause of cancer-related death in women under 40 and is one of the few cancers to have an increased incidence rate and decreased survival rate over the last 10 years. One in five patients will have recurrent and/or distant metastatic disease and these patients face a 5-year survival rate of less than 17%. Thus, there is a pressing need to develop new anticancer therapeutics for this underserved patient population. However, the development of new anticancer drugs remains a challenge, as only 7% of novel anticancer drugs are approved for clinical use. To facilitate identification of novel and effective anticancer drugs for cervical cancer, we developed a multilayer multicellular platform of human cervical cancer cell lines and primary human microvascular endothelial cells that interfaces with high throughput drug screening methods to evaluate the anti-metastatic and anti-angiogenic drug efficacy simultaneously. Through the use of design of experiments statistical optimization, we identified the specific concentrations of collagen I, fibrinogen, fibronectin, GelMA, and PEGDA in each hydrogel layer that maximized both cervical cancer invasion and endothelial microvessel length. We then validated the optimized platform and assessed its viscoelastic properties. Finally, using this optimized platform, we conducted a targeted drug screen of four clinically relevant drugs on two cervical cancer cell lines. Overall, this work provides a valuable platform that can be used to screen large compound libraries for mechanistic studies, drug discovery, and precision oncology for cervical cancer patients.