RESUMEN
Hypoxia is a representative tumor characteristic associated with malignant progression in clinical patients. Engineered in vitro models have led to significant advances in cancer research, allowing for the investigation of cells in physiological environments and the study of disease mechanisms and processes with enhanced relevance. In this study, we propose a U-shape pillar strip for a 3D cell-lumped organoid model (3D-COM) to study the effects of hypoxia on lung cancer in a high-throughput manner. We developed a U-pillar strip that facilitates the aggregation of PDCs mixed with an extracellular matrix to make the 3D-COM in 384-plate array form. The response to three hypoxia-activated prodrugs was higher in the 3D-COM than in the 2D culture model. The protein expression of hypoxia-inducible factor 1 alpha (HIF-1α) and HIF-2α, which are markers of hypoxia, was also higher in the 3D-COM than in the 2D culture. The results show that 3D-COM better recapitulated the hypoxic conditions of lung cancer tumors than the 2D culture. Therefore, the U-shape pillar strip for 3D-COM is a good tool to study the effects of hypoxia on lung cancer in a high-throughput manner, which can efficiently develop new drugs targeting hypoxic tumors.
Asunto(s)
Ensayos Analíticos de Alto Rendimiento , Neoplasias Pulmonares , Organoides , Humanos , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/metabolismo , Organoides/metabolismo , Organoides/patología , Subunidad alfa del Factor 1 Inducible por Hipoxia/metabolismo , Hipoxia de la Célula , Técnicas de Cultivo Tridimensional de Células , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/metabolismoRESUMEN
This study proposed an optimized histogel construction method for histological analysis by applying lung cancer patient-derived organoids (PDOs) to the developed histo-pillar strip. Previously, there is the cultured PDOs damage problem during the histogel construction due to forced detachment of the Matrigel spots from the 96-well plate bottom. To address this issue, we cultured PDO on the proposed Histo-pillar strips and then immersed them in 4% paraformaldehyde fixation solution to self-isolate PDO without damage. The 4µl patient-derived cell (PDC)/Matrigel mixtures were dispensed on the surface of a U-shaped histo-pillar strip, and the PDCs were aggregated by gravity and cultured into PDOs. Cultured PDOs were self-detached by simply immersing them in a paraformaldehyde fixing solution without physical processing, showing about two times higher cell recovery rate than conventional method. In addition, we proposed a method for embedding PDOs under conditions where the histogel temperature was maintained such that the histogel did not harden, thereby improving the problem of damaging the histogel block in the conventional sandwich histogel construction method. We performed histological and genotyping analyses using tumor tissues and PDOs from two patients with lung adenocarcinoma. Therefore, the PDO culture and improved histogel block construction method using the histo-pillar strip proposed in this study can be employed as useful tools for the histological analysis of a limited number of PDCs.
Asunto(s)
Neoplasias Pulmonares , Organoides , Humanos , Organoides/metabolismo , Organoides/efectos de los fármacos , Organoides/patología , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/metabolismo , Biomarcadores de Tumor/metabolismo , Laminina/química , Geles/química , Colágeno/química , Colágeno/metabolismo , Combinación de Medicamentos , Proteoglicanos/químicaRESUMEN
Patient-derived organoids (PDOs) are valuable in predicting response to cancer therapy. PDOs are ideal models for precision oncologists. However, their practical application in guiding timely clinical decisions remains challenging. This study focused on patients with advanced EGFR-mutated non-small cell lung cancer and employed a cancer organoid-based diagnosis reactivity prediction (CODRP)-based precision oncology platform to assess the efficacy of EGFR inhibitor treatments. CODRP was employed to evaluate EGFR-tyrosine kinase inhibitors (TKI) drug sensitivity. The results were compared to those obtained using area under the curve index. This study validated this index by testing lung cancer-derived organoids in 14 patients with lung cancer. The CODRP index-based drug sensitivity test reliably classified patient responses to EGFR-TKI treatment within a clinically suitable 10-day timeline, which aligned with clinical drug treatment responses. This approach is promising for predicting and analyzing the efficacy of anticancer, ultimately contributing to the development of a precision medicine platform.
RESUMEN
Background and Objective: Immune checkpoint inhibitors (ICI) were a major clinical advancement that provided an opportunity to improve the prognosis of patients with non-small cell lung cancer (NSCLC). However, programmed death-ligand-1 (PD-L1) expression does not sufficiently predict ICI efficacy in NSCLC patients. In recent studies, the tumor immune microenvironment (TIME) was shown to have a central role in lung cancer progression and to affect clinical outcome of patients diagnosed with lung cancer. As development of new therapeutic targets to overcome ICI resistance is a priority, understanding the TIME is important. Recently, a series of studies was conducted to target each component of TIME to improve efficacy of cancer treatment. In this review, important features related to TIME, its heterogeneity and current trends in treatment targeting the component of TIME are discussed. Methods: PubMed and PMC were searched from January 1st, 2012 to August 16th, 2022 using the following key words: "NSCLC", "Tumor microenvironment", "Immune", "Metastasis" and "Heterogeneity". Key Content and Findings: Heterogeneity in the TIME can be either spatial or temporal. Subsequent to heterogeneous changes in the TIME, treatment of lung cancer can be more challenging because drug resistance is more likely to occur. In terms of the TIME, the main concept for increasing the chance of successful NSCLC treatment is to activate immune responses against tumor cells and inhibit immunosuppressive activities. In addition, relevant research is focused on normalizing an otherwise aberrant TIME in NSCLC patients. Potential therapeutic targets include immune cells, cytokine interactions, and non-immune cells such as fibroblasts or vessels. Conclusions: In management of lung cancer, understanding TIME and its heterogeneity is significant to treatment outcomes. Ongoing trials including various treatment modalities such as radiotherapy, cytotoxic chemotherapy, and anti-angiogenic treatment and regimens inhibiting other immunoinhibitory molecules are promising.
RESUMEN
BACKGROUND: Recently, cancer organoid-based drug sensitivity tests have been studied to predict patient responses to anticancer drugs. The area under curve (AUC) or IC50 value of the dose-response curve (DRC) is used to differentiate between sensitive and resistant patient's groups. This study proposes a multi-parameter analysis method (cancer organoid-based diagnosis reactivity prediction, CODRP) that considers the cancer stage and cancer cell growth rate, which represent the severity of cancer patients, in the sensitivity test. METHODS: On the CODRP platform, patient-derived organoids (PDOs) that recapitulate patients with lung cancer were implemented by applying a mechanical dissociation method capable of high yields and proliferation rates. A disposable nozzle-type cell spotter with efficient high-throughput screening (HTS) has also been developed to dispense a very small number of cells due to limited patient cells. A drug sensitivity test was performed using PDO from the patient tissue and the primary cancer characteristics of PDOs were confirmed by pathological comparision with tissue slides. RESULTS: The conventional index of drug sensitivity is the AUC of the DRC. In this study, the CODRP index for drug sensitivity test was proposed through multi-parameter analyses considering cancer cell proliferation rate, the cancer diagnosis stage, and AUC values. We tested PDOs from eight patients with lung cancer to verify the CODRP index. According to the anaplastic lymphoma kinase (ALK) rearrangement status, the conventional AUC index for the three ALK-targeted drugs (crizotinib, alectinib, and brigatinib) did not classify into sensitive and resistant groups. The proposed CODRP index-based drug sensitivity test classified ALK-targeted drug responses according to ALK rearrangement status and was verified to be consistent with the clinical drug treatment response. CONCLUSIONS: Therefore, the PDO-based HTS and CODRP index drug sensitivity tests described in this paper may be useful for predicting and analyzing promising anticancer drug efficacy for patients with lung cancer and can be applied to a precision medicine platform.