Cutoff value of IC50 for drug sensitivity in patient-derived tumor organoids in colorectal cancer

Intestinal organoids: The path towards clinical application

Organoids have revolutionized the whole field of biology with their ability to model complex three-dimensional human organs in vitro. Intestinal organoids were especially consequential as the first successful long-term culture of intestinal stem cells, which raised hopes for translational medical applications. Despite significant contributions to basic research, challenges remain to develop intestinal organoids into clinical tools for diagnosis, prognosis, and therapy. In this review, we outline the current state of translational research involving adult stem cell and pluripotent stem cell derived intestinal organoids, highlighting the advances and limitations in disease modeling, drug-screening, personalized medicine, and stem cell therapy. Preclinical studies have demonstrated a remarkable functional recapitulation of infectious and genetic diseases, and there is mounting evidence for the reliability of intestinal organoids as a patient-specific avatar. Breakthroughs now allow the generation of structurally and cellularly complex intestinal models to better capture a wider range of intestinal pathophysiology. As the field develops and evolves, there is a need for standardized frameworks for generation, culture, storage, and analysis of intestinal organoids to ensure reproducibility, comparability, and interpretability of these preclinical and clinical studies to ultimately enable clinical translation.

Patient-Derived Tumor Organoids: A Platform for Precision Therapy of Colorectal Cancer

Colorectal cancer (CRC) represents a significant cause of cancer-related mortality on a global scale. It is a highly heterogeneous cancer, and the response of patients to homogeneous drug therapy varies considerably. Patient-derived tumor organoids (PDTOs) represent an optimal preclinical model for cancer research. A substantial body of evidence from numerous studies has demonstrated that PDTOs can accurately predict a patient's response to different drug treatments. This article outlines the utilization of PDTOs in the management of CRC across a range of therapeutic contexts, including postoperative adjuvant chemotherapy, palliative chemotherapy, neoadjuvant chemoradiotherapy, targeted therapy, third-line and follow-up treatment, and the treatment of elderly patients. This article delineates the manner in which PDTOs can inform therapeutic decisions at all stages of CRC, thereby assisting clinicians in selecting treatment options and reducing the risk of toxicity and resistance associated with clinical drugs. Moreover, it identifies shortcomings of existing PDTOs, including the absence of consistent criteria for assessing drug sensitivity tests, the lack of vascular and tumor microenvironment models, and the high cost of the technology. In conclusion, despite their inherent limitations, PDTOs offer several advantages, including rapid culture, a high success rate, high consistency, and high throughput, which can be employed as a personalized treatment option for CRC. The use of PDTOs in CRC allows for the prediction of responses to different treatment modalities at various stages of disease progression. This has the potential to reduce adverse drug reactions and the emergence of resistance associated with clinical drugs, facilitate evidence-based clinical decision-making, and guide CRC patients in the selection of personalized medications, thereby advancing the individualized treatment of CRC.

Advancements in Research and Treatment Applications of Patient-Derived Tumor Organoids in Colorectal Cancer

Colorectal cancer (CRC) remains a significant health burden globally, being the second leading cause of cancer-related mortality. Despite significant therapeutic advancements, resistance to systemic antineoplastic agents remains an important obstacle, highlighting the need for innovative screening tools to tailor patient-specific treatment. This review explores the application of patient-derived tumor organoids (PDTOs), three-dimensional, self-organizing models derived from patient tumor samples, as screening tools for drug resistance in CRC. PDTOs offer unique advantages over traditional models by recapitulating the tumor architecture, cellular heterogeneity, and genomic landscape and are a valuable ex vivo predictive drug screening tool. This review provides an overview of the current literature surrounding the use of PDTOs as an instrument for predicting therapy responses in CRC. We also explore more complex models, such as co-cultures with important stromal cells, such as cancer-associated fibroblasts, and organ-on-a-chip models. Furthermore, we discuss the use of PDTOs for drug repurposing, offering a new approach to identify the existing drugs effective against drug-resistant CRC. Additionally, we explore how PDTOs serve as models to gain insights into drug resistance mechanisms, using newer techniques, such as single-cell RNA sequencing and CRISPR-Cas9 genome editing. Through this review, we aim to highlight the potential of PDTOs in advancing our understanding of predicting therapy responses, drug resistance, and biomarker identification in CRC management.

Organoid forming potential as complementary parameter for accurate evaluation of breast cancer neoadjuvant therapeutic efficacy

BACKGROUND

13-15% of breast cancer/BC patients diagnosed as pathological complete response/pCR after neoadjuvant systemic therapy/NST suffer from recurrence. This study aims to estimate the rationality of organoid forming potential/OFP for more accurate evaluation of NST efficacy.

METHODS

OFPs of post-NST residual disease/RD were checked and compared with clinical approaches to estimate the recurrence risk. The phenotypes of organoids were classified via HE staining and ER, PR, HER2, Ki67 and CD133 immuno-labeling. The active growing organoids were subjected to drug sensitivity tests.

RESULTS

Of 62 post-NST BC specimens, 24 were classified as OFP-I with long-term active organoid growth, 19 as OFP-II with stable organoid growth within 3 weeks, and 19 as OFP-III without organoid formation. Residual tumors were overall correlated with OFP grades (P < 0.001), while 3 of the 18 patients (16.67%) pathologically diagnosed as tumor-free (ypT0N0M0) showed tumor derived-organoid formation. The disease-free survival/DFS of OFP-I cases was worse than other two groups (Log-rank P < 0.05). Organoids of OFP-I/-II groups well maintained the biological features of their parental tumors and were resistant to the drugs used in NST.

CONCLUSIONS

The OFP would be a complementary parameter to improve the evaluation accuracy of NST efficacy of breast cancers.

Organoids as a biomarker for personalized treatment in metastatic colorectal cancer: drug screen optimization and correlation with patient response

BACKGROUND

The inability to predict treatment response of colorectal cancer patients results in unnecessary toxicity, decreased efficacy and survival. Response testing on patient-derived organoids (PDOs) is a promising biomarker for treatment efficacy. The aim of this study is to optimize PDO drug screening methods for correlation with patient response and explore the potential to predict responses to standard chemotherapies.

METHODS

We optimized drug screen methods on 5-11 PDOs per condition of the complete set of 23 PDOs from patients treated for metastatic colorectal cancer (mCRC). PDOs were exposed to 5-fluorouracil (5-FU), irinotecan- and oxaliplatin-based chemotherapy. We compared medium with and without N-acetylcysteine (NAC), different readouts and different combination treatment set-ups to capture the strongest association with patient response. We expanded the screens using the optimized methods for all PDOs. Organoid sensitivity was correlated to the patient's response, determined by % change in the size of target lesions. We assessed organoid sensitivity in relation to prior exposure to chemotherapy, mutational status and sidedness.

RESULTS

Drug screen optimization involved excluding N-acetylcysteine from the medium and biphasic curve fitting for 5-FU & oxaliplatin combination screens. CellTiter-Glo measurements were comparable with CyQUANT and did not affect the correlation with patient response. Furthermore, the correlation improved with application of growth rate metrics, when 5-FU & oxaliplatin was screened in a ratio, and 5-FU & SN-38 using a fixed dose of SN-38. Area under the curve was the most robust drug response curve metric. After optimization, organoid and patient response showed a correlation coefficient of 0.58 for 5-FU (n = 6, 95% CI -0.44,0.95), 0.61 for irinotecan- (n = 10, 95% CI -0.03,0.90) and 0.60 for oxaliplatin-based chemotherapy (n = 11, 95% CI -0.01,0.88). Median progression-free survival of patients with resistant PDOs to oxaliplatin-based chemotherapy was significantly shorter than sensitive PDOs (3.3 vs 10.9 months, p = 0.007). Increased resistance to 5-FU in patients with prior exposure to 5-FU/capecitabine was adequately reflected in PDOs (p = 0.003).

CONCLUSIONS

Our study emphasizes the critical impact of the screening methods for determining correlation between PDO drug screens and mCRC patient outcomes. Our 5-step optimization strategy provides a basis for future research on the clinical utility of PDO screens.

Systematic review: predictive value of organoids in colorectal cancer

While chemotherapy alone or in combination with radiotherapy and surgery are important modalities in the treatment of colorectal cancer, their widespread use is not paired with an abundance of diagnostic tools to match individual patients with the most effective standard-of-care chemo- or radiotherapy regimens. Patient-derived organoids are tumour-derived structures that have been shown to retain certain aspects of the tissue of origin. We present here a systematic review of studies that have tested the performance of patient derived organoids to predict the effect of anti-cancer therapies in colorectal cancer, for chemotherapies, targeted drugs, and radiation therapy, and we found overall a positive predictive value of 68% and a negative predictive value of 78% for organoid informed treatment, which outperforms response rates observed with empirically guided treatment selection.