Lung cancer organoid-based drug evaluation models and new drug development application trends

Introduction

Lung cancer is the most commonly diagnosed cancer globally. Lung cancer is a leading cause of death worldwide (1). Lung cancer is histologically classified as small cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC). SCLC accounts for 15–20% of all lung cancers and NSCLC accounts for 80–85% of all lung cancers (2,3). Patients with SCLC had a higher smoking rate than those with NSCLC. In addition, SCLC worsens rapidly (4). Adenocarcinoma and squamous cell carcinoma comprise the major proportion of NSCLC (5). Adenocarcinoma, which usually develops in the peripheral region of the lungs, is the most common type of lung cancer (6). Squamous cell carcinoma is more associated with smoking compared to other NSCLC subtypes and tends to occur in the central part of the lung. Lung cancer is treated by various treatment modalities such as surgery, radiation, and different anti-cancer regimens. Treatment is performed depending on the stage of cancer, histological characteristics, and the patient’s condition (7). For patients diagnosed at an early stage (stages I or II), curative treatment such as surgery or stereotactic radiotherapy for medically inoperable patients, is considered. However, surgery is not possible for advanced or metastatic lung cancers. Palliative chemotherapy and/or radiation therapy is the primary treatment approach in these cases (7).

Certain genetic alterations such as common epidermal growth factor receptor (EGFR) mutation or anaplastic lymphoma kinase (ALK) translocations enable the use of targeted therapy in patients with targetable mutations. In patients with common EGFR mutations such as exon 19 deletion or L858R point mutation of exon 21, EGFR tyrosine kinase inhibitors (TKIs) can be used, with relatively more favorable outcomes when compared to advanced NSCLC patients without targetable mutations (8-10). For patients with ALK rearrangement, which results from the inversion of ALK with echinoderm microtubule-associated protein-like 4 (EML4), ALK TKIs can be used (11-13). Molecular factors are also important in lung cancer immunotherapy, with targets such as programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1), used to predict responses to immunotherapy drugs (14,15) like nivolumab and pembrolizumab. Disease burden is also important, and tumour, node and metastasis (TNM) classification which comprises primary tumor size, concurrent mediastinal lymph node metastases, and metastasis burden predicts the prognosis of lung cancer patients. Treatment plans vary depending on the stage (16).

Existing biomarkers and prognostic factors typically focus on general characteristics associated with lung cancer (17). However, even if the cancer type is identical, the phenotypic and molecular characteristics of lung cancer can vary significantly between individuals and even among cancer cells within the same patient (18). Additionally, treatment modalities have become increasingly diverse, encompassing traditional chemotherapy, targeted therapy, immunotherapy, and antibody-drug conjugates (ADCs). Furthermore, novel treatment strategies based on the combination of different treatment modalities are being studied as well (19,20), highlighting the increasing demand for a personalized approach. In this context, predicting drug efficacy using lung cancer patient-derived organoids (PDOs) can provide a precision medicine platform and be applied to clinical patient treatment (21). Therefore, research and development (R&D) is actively being conducted on lung cancer PDO platforms for commercialization (22,23). Lung cancer PDOs are three-dimensional (3D) in vitro models cultured with patient-derived cells (PDCs). Cells from tissue or pleural fluid are extracted and cultured from lung cancer patients (24,25). These lung cancer PDOs more accurately represent the characteristics of primary cancer tissue compared to two-dimensional (2D) cultured cells. Additionally, lung cancer PDOs have lower ethical and economic burdens than patient-derived tumor xenograft (PDTX) animal models (26). In order to use PDOs as a personalized chemotherapy screen platform, it is essential to reproduce each patient’s genetic alteration as exactly as possible, because anti-cancer regimens, especially targeted therapies are meant to target specific mutations of cancer cells. One study was performed to cross-validate the genetic alterations in lung cancer tissues and lung cancer PDOs. When sequencing analysis was performed on 164 cancer-related genes, most somatic mutations present in lung cancer tissue were identified in lung cancer PDOs, with mutation concordance ranging from 73% to 100% across 11 samples, while single nucleotide polymorphism (SNP) genotypes showed full concordance at 100%. The variant allele fraction (VAF) of somatic mutations in lung cancer PDOs was linearly correlated with the lung cancer tissues, though higher VAF values were observed in lung cancer PDOs. Whole exome sequencing (WES) analysis showed that the VAF distribution in lung cancer PDOs reflected that of the tissue, though a higher number of mutations were occasionally detected in lung cancer PDOs. Lung cancer PDOs are cultured from isolated epithelial cells without stromal support or immune cells, whereas lung cancer tissues coexist with non-neoplastic stroma and immune cells. Therefore, although in lung cancer PDOs contain all mutations in lung cancer tissues, there is a limitation that somatic mutation concordance and VAF differences appear between lung cancer tissues (27).

In other words, lung cancer organoids (LCOs) exhibit the characteristics of lung cancer tissues under in vitro conditions. Therefore, the efficacy of anticancer drugs for each patient can be predicted based on the lung cancer PDOs. Owing to their characteristics and advantages, lung cancer PDOs are valuable for precision medicine research and new anticancer drug development. Clinical studies on drug responsiveness prediction using PDOs have recently been reported (28-30).

With technological advancements, various targeted therapy and immunotherapy are being developed and used to treat lung cancer patients. The combination of immunotherapy with chemotherapy is expected to increase the demand for personalized drug treatments (31). Consequently, the need for drug efficacy prediction analysis is anticipated to grow. LCO models can predict the efficacy of various anticancer drugs, including immunotherapy, and can evaluate combinations of multiple drugs. These models can also serve as efficacy prediction tools for next-generation anticancer drugs under development.

In this paper, we summarize LCO culture models and discuss the evaluation of various anticancer drugs’ efficacy, as well as research and R&D trends in new drugs targeting lung cancer utilizing these models.

LCO source

Obtaining samples from clinical lung cancer patients

The cells used in organoid culture are obtained from lung cancer tissue biopsies or pleural fluids. Lung cancer PDOs are organ analogs cultured in vitro by isolating single cells from tissues or malignant pleural effusions of patients. These cancer PDO models can maintain the heterogeneity of the primary tumor and implement a tumor microenvironment (TME) such as hypoxic conditions (32,33). Therefore, it has the advantage of efficiently recapitulating the tumor tissue and TME of lung cancer patients. However, there are several limitations in generating organoids using patient-derived samples. When obtaining organoids from tumor tissues, the normal cells surrounding the tumor may proliferate faster than the cancer cells, contaminating LCOs and restricting their development and application. A study examining the purity of lung adenocarcinoma organoids reported contamination by healthy airway cells in 58% of cases (34).

Tumor tissue dissociation methods

The dissociation of tumor tissue to extract PDCs typically involves a combination of mechanical and chemical dissociation methods. Mechanical dissociation is performed by finely mincing the tissue sample with a scalpel in a sterile glass petri dish. Chemical dissociation utilizes enzymatic solutions, such as collagenase, dispase, trypsin, and elastase, to break down the tissue (35). Tissue obtained from a patient who has given consent is minced using a scalpel in a sterilized glass petri dish. And then, minced tissue is placed in an enzymatic solution and separated into single cells. After chemical dissociation using the enzymatic solution, Dulbecco’s modified eagle medium/nutrient mixture F-12 (DMEM/F12) with 10% fetal bovine serum (FBS) is added to stop enzyme response. To remove impurities, the solution containing dissociated cells is filtered using a cell strainer (36,37).

PDC isolation method

The cells and dissociation solution are separated using a centrifuge to obtain the extracted PDCs in a single-cell state. Tumor tissue contains blood, which can cause contamination problems and adversely affect organoid culture. Therefore, to remove the cells from the blood and prevent the risk of contamination, the sample is treated with red blood cell (RBC) lysis buffer. Extracted PDCs are mixed with extracellular matrix (ECM) biomaterials and cultured as organoids (Figure 1). PDCs extracted from patient tissues typically contain a combination of cancer and normal cells. During LCO culture, the excessive growth of healthy epithelial cells can be problematic (38). To solve this problem, efforts are being made to selectively culture cancer organoids using selective media specialized for LCO culture. Typically, the mouse double minute 2 (MDM2) inhibitor Nutlin-3α is added to the LCO medium. Nutlin-3α induces the death of tumor protein P53 (TP53) wild-type normal cells, allowing for the selective culture of NSCLC cancer organoids with p53 mutations (39).

Figure 1 Cell source processing schematic for producing lung cancer PDO model. Lung cancer organoids are formed by isolating single cells through the patient’s tumor or malignant pleural effusions and mixing them with ECM. Organoids are cultured using a medium containing EGF, FGF7, Noggin, etc. Lung cancer organoid models can be formed using methods such as 3D-embedded culture, hanging drop culture, ALI culture, 3D bioreactor, and lung-on-a-chip. This figure is created via BioRender with credit. ECM, extracellular matrix; EGF, epidermal growth factor; FGF7, fibroblast growth factor 7; FGF10, fibroblast growth factor 10; ALI, air-liquid interface; EGFR, epidermal growth factor receptor; TKI, tyrosine kinase inhibitor; PD-1, programmed cell death protein 1; PD-L1, programmed cell death-ligand protein 1; PDO, patient-derived organoid.

ECM and organoid media for PDC culture

Cancer PDO models can maintain the heterogeneity of the primary tumor and implement a TME such as hypoxic conditions. Therefore, it has the advantage of efficiently recapitulating the tumor tissue and TME in clinical cancer patients. Several in vitro methods are available for culturing cancer PDOs. Culture methods that can be utilized include 3D dome-embedded organoid culture (40), hanging drop culture (41,42), bioreactor-based culture (43), and organoid-on-chip culture (44,45). To culture cancer PDOs under in vitro conditions, it’s necessary to have biological materials like ECM. Additionally, the cancer organoid culture medium must contain growth factors that promote cancer cell growth.

PDO cultures require ECM. The ECM is composed of various proteins and polysaccharides. In addition, the ECM forms a 3D structure and organized network. Matrigel or basement membrane extract (BME) is used as the biomaterial. These biomaterials are similar to ECM components in the body. Therefore, the ECM provides a cellular environment in tissues and creates a 3D culture environment. Matrigel, collagen, alginate, and hydrogels are representative biomaterials that constitute ECM. Matrigel, a natural ECM extracted from the basement membrane of mouse sarcoma cells, is composed of laminin, collagen IV, heparin sulfate, fibroblast growth factor (FGF), and insulin-like growth factor (IGF) (46). 3D cancer cell culture using Matrigel structures has been shown to promote tumor growth. Cancer organoids based on Matrigel efficiently implement the heterogeneity of patient tumor tissues (29,47). Hydrogels are polymeric materials characterized by a hydrophilic structure that allows them to retain large amounts of water within their highly cross-linked 3D networks. This unique structure imparts hydrogels with high elasticity and enables them to mimic the ECM (48). To increase experimental reproducibility and minimize the complexity of organoid studies, single-component hydrogels such as collagen I, gelatin and polyethylene glycol (PEG) have been used to culture various organoids (49). Furthermore, hydrogels, with their modifiable physical, chemical, and mechanical properties, serve as a versatile tool for the development of organoid models (50). Cancer organoids composed of malignant tumor cells in vitro mimic the characteristics of malignant tumors, such as proliferation and invasive behavior (34,51).

The biomaterial was then mixed with lung cancer cells to form a dome. After hardening the formed dome, medium was added to culture the organoids. The medium must be supplemented with growth factors, Rho-associated protein kinase (ROCK) inhibitors, and other components. The medium was used differently depending on the type of cancer organoid used. In previous studies, the culture of LCOs utilized common media, such as DMEM/F12, hydroxyethyl piperazine ethane sulfonic acid (HEPES), penicillin-streptomycin (PS), and glutamax. The medium contained N-acetyl-L-cysteine, B-27 supplement, A83-01, Noggin, Y-27632, nicotinamide, SB202190, epidermal growth factor (EGF), FGF7, and FGF10 (52-54) (Table 1). Recent studies have focused on culturing 3D organoid models by mixing the ECM with cells. While 3D organoid models, particularly those based on cancer cells, have been successfully developed and are relatively easy to culture (29,51), the 3D culture of immune cells presents distinct challenges. Immune cells, which contribute to the TME, have growth characteristics that differ significantly from those of cancer cells, often resulting in limitations when co-cultured in 3D systems (55,56). In vitro culture of immune cells requires an immune cell-specific culture medium that is different from that for cancer organoid culture, consisting of Roswell Park Memorial Institute 1640 (RPMI 1640) medium supplemented with cytokines such as interleukin 2 (IL-2) and IL-15 (56,57).

The use of different conditioned media across studies on LCO cultures may influence the standardization of lung cancer PDO modeling (23). Achieving standardization in lung cancer PDOs is a key challenge to enhance the recapitulation and the feasibility of clinical applications. Hence, there is a need to develop culture media that not only increase the success rate of organoid formation but also better mimic tumor characteristics and predict anticancer drug responses effectively.

LCO models

Conventional 3D dome-embedded organoid culture method

3D dome-embedded organoid culture requires cells to be resuspended in biomaterials such as Matrigel. Afterward, they are dispensed into well plates and cultured. Speed and temperature are the important variables in this process. It is necessary to prevent the Matrigel from sticking to the pipette tip. Before mixing with Matrigel, the cells are pre-wetted with phosphate-buffered saline (PBS) supplemented with 0.1% bovine serum albumin (BSA). The PDCs suspension is added to a microtube at a 1:4 ratio with Matrigel and gently mixed on ice. During this process, care is taken to avoid bubble formation in the mixture. Matrigel-cell mixture is dispensed onto the plate. Dispensed Matrigel-cell mixture is incubated to allow for solidification. The incubator conditions are set to 37 ℃ and 5% CO₂. Through this process, a dome is formed. Once the dome is formed, the organoid medium is carefully added to the well plate. Additionally, the medium was changed every 3 days (58).

Recently, researchers have attempted to develop a co-culture model with immune cells using 3D PDOs. An in vitro immune cell co-culture model for studying the interaction between T cells and tumor cells has been reported. In the present study, lung cancer PDOs and peripheral blood mononuclear cells (PBMC) were cultured. The geltrex basement membrane was used as the ECM. PBMC and dissociated single-cells were seeded at an effector-to-target ratio of 20:1. PBMC and tumor organoids were cultured in 96 well plates coated with an anti-cluster of differentiation 28 (CD28). In addition, co-culture was performed under conditions of 150 U/mL IL-2 and 20 µg/mL anti-PD-1-blocking antibody in a 96-well plate. This immune cell co-culture model can quantitatively analyze the tumor-killing efficacy of T cells (39). However, this platform has difficulty in reproducing the complexity of existing organs, such as vascularization. Various 3D lung cancer PDO culture methods have been developed (59).

Hanging drop method for lung cancer PDO culture

The hanging drop method is a 3D organoid culture method. In this method, 20–40 µL of cell suspension is dispensed onto the bottom of the plate and then inverted. The cell suspension was dispensed onto a hanging drop culture plate and organoids were cultured. Due to the combined effects of surface tension and gravity, dispensed cells are aggregated and cultured as organoids (60,61). The surface tension maintains the liquid droplets suspended, while gravity pulls the cells down to the bottom of the drop. The hanging drop culture method can form organoids such as embryoid bodies, normal microtissues, and tumors (62,63). LCOs are cultured using the hanging drop culture method (64). The hanging drop method is improved to facilitate organoid formation. The hanging-drop method is a simple procedure. In addition, it has high efficiency and throughput by forming many uniform organoids (65). However, the hanging drop method has the disadvantage of difficulty in replacing the culture medium. To overcome this, special types of hanging-drop culture plates (e.g., 3D Biomatrix or InSphero) have recently been developed. The conventional hanging drop method involves culturing cells using only hanging drop plates. In contrast, the newly developed platform uses a combination of hanging drops and cell-culture plates. Organoids were cultured on hanging-drop plates. Afterward, the organoids are transferred onto a cell culture plate. This culture platform solves the problem of medium exchange (66,67).

Air-liquid interface (ALI) culture method for lung cancer PDO culture

ALI culture is an ALI culture model that uses a Transwell insert. The TME represents a complex network surrounding tumors, requiring research on the influence of its individual components to overcome treatment resistance. Studies using ALI culture have been conducted to form a 3D tumor model that mimics the TME such as oxygen concentration gradient, immune cells, fibroblast cells (68-72). For ALI culture, the interior of the Transwell insert must be pre-coated with Matrigel or collagen. After coating, lung cancer cells are mixed with Matrigel or collagen. The cell-ECM mixture is dispensed inside the Transwell insert and hardened in a 37 ℃ incubator (69). The Transwell insert containing lung cancer cells is placed into a plate containing the organoid culture medium. This structure exposes the matrix’s upper surface to air, facilitating oxygen diffusion and recapitulating the oxygen concentration gradient.

Furthermore, the ALI culture method was improved by co-culturing cancer cells, stromal cells, and immune cells. Cultured LCOs mimic the tumor immune microenvironment (TIME), thereby maintaining complex cellular components. Moreover, the pathological and genetic characteristics of the tumors are preserved. It has been reported that LCOs using the ALI culture method maintain a microenvironment of tumor immune cells, fibroblasts, tumor epithelial cells, and tumor stromal cells for 30 days (70). Additionally, reports have shown that T cell receptor (TCR) heterogeneity is maintained within early-stage tumors. LCOs based on ALI culture preserve tumor structure and stroma, as cross-validated by the expression of smooth muscle actin (SMA) and vimentin. According to fluorescence activated cell sorting (FACS) analysis of lung cancer PDOs based on ALI culture, the presence of CD8⁺ T, CD4⁺ T, B, natural killer (NK), and natural killer T (NKT) cells was confirmed. Additionally, FACS analysis confirmed the infiltration of CD3⁺ T cells expressing immune checkpoints (IC) (71).

3D bioreactor method for lung cancer PDO culture

The 3D bioreactor is a cylindrical rotating biological incubator. The cylindrical structure is constantly stirred. Constant agitation is necessary to prevent cell sedimentation. It is essential to maintain a continuous agitation speed in an organoid culture in a bioreactor. High agitation speeds may damage organoids, while slow agitation rates can cause the organoids to settle. PDO culture based on a bioreactor uses ECM-coated microcarrier beads or scaffolding. PDOs cultured in bioreactors can mimic the 3D structure of tissues and cell functions (73,74). However, cells cultured in bioreactors have the limitation of taking a long time to grow.

Organoid-on-a-chip for lung cancer PDO culture

Organoid-on-a-chip systems involve cell culture using chips that mimic real organs. In 2010, the lung-on-a-chip system was developed at the Wyss Institute of Harvard University in the United States (75). Since then, various chips have been developed to mimic the characteristics of organs (76). Organoids must implement and recapitulate a patient’s organ microenvironment. This was achieved by incorporating microfluidic technology into 3D cell culture technology. This technology is called an “organoid-on-a-chip”.

The application of cancer organoids to a microfluidic chip allows interaction with the TME. Cancer organoids based on microfluidic chips reproduce an environment similar to that of cancer tissue in a patient’s body. The proposed 3D vascularized lung cancer-on-a-chip (VLCC) model implements a lung microenvironment. In this study, cancer spheroids were formed using lung decellularized ECM (LdECM), A549 lung cancer cells, human umbilical vein endothelial cells (HUVECs), and human lung fibroblasts (HLFs). Cancer spheroids were applied to the developed 3D VLCC. The 3D VLCC model has a vascular structure that mimics arteries, veins, and capillaries. It is also suitable for doxorubicin drug screening (77). A recent study has reported on an “organoid-on-a-chip” model that implements the brain metastasis environment using a microfluidic device. A brain metastasis-simulating microfluidic device was designed to culture the three cell types. Metastatic brain NSCLC (BM-NSCLC) cells, astrocytes, and cerebrovascular endothelial cells were cultured. Astrocytes and cerebrovascular endothelial cells are important components of the TME in brain cancer. The brain metastasis-simulating microfluidic device consisted of four units. Each unit had three hydrogel channels (channels #2 and #4) and four intermediate channels (channels #1 and #3). BM-NSCLC cells were suspended in type 1 collagen hydrogel (COL1) solution. Afterward, the suspended solution was dispensed into channel 4 and gelled. The neurobasal medium to help form the brain TME (bTME) was supplemented in channel #3. The astrocytes and COL1 were mixed and dispensed into channel #2. Cerebrovascular endothelial cells were seeded in channel 1. The stemness of BM-NSCLC cells depends on the establishment of bTME. Stemness was confirmed by measuring CD44 and CD133 expression (78).

In addition, the microfluidic chip can implement the TME through co-culture of the patient’s immune cells and cancer cells. These coculture microfluidic chip platforms can establish treatment strategies for precision medicine. Tumors contain structurally and functionally abnormal vascular structures. Abnormal blood vessels in these tumors cause hypoxia and high interstitial pressure and act as a physical barrier to T-cell infiltration. Consequently, blood vessels are formed in both primary and immunosuppressive environments. Microfluidic technology has advanced, enabling the implementation of 3D tumor microvascular models based on chips. In addition, it presents a tumor-on-a-chip platform that implements the TME through the co-culture of immune and cancer cells. In tumor-on-a-chip platform studies, monocytes migrate from the intravascular compartment to the extravascular microenvironment. This induces monocyte differentiation into macrophages. These results imply that the tumor-on-a-chip mimics physiological differences in monocyte subsets and the complexity of the TIME (79).

Drug screening using LCO

Chemotherapy

Chemotherapy has been developed to suppress the division of abnormally proliferating cancer cells, thereby preventing their growth and causing their destruction. However, cell division is a primary characteristic that occurs not only in cancer cells but also in normal cells. Therefore, chemotherapy has the side effect of causing fatal damage to tissues, such as nails and hair, which causes many divisions (80).

Clinical response to chemotherapy varies among patients. Therefore, accurate in vitro drug screening is crucial for personalized medicine. Chemotherapy drug screening for PDOs in lung cancer can be used to analyze sensitivity to anticancer drugs. In one study involving chemotherapy drug screening, lung cancer PDCs were mixed with Matrigel at a 1:1 ratio and cultured in a 384-well plate to establish a lung cancer PDO model. Drug response analysis was performed using a cultured lung cancer PDO model. In this study, the sensitivity of LCOs to chemotherapeutic drugs was 83.3% (10/12). Etoposide + cisplatin (EP) drug screening was performed on lung cancer PDOs from a group of patients treated with the EP regimen. Analysis of EP drug screening of four types of lung cancer PDOs predicted that two patients would exhibit partial response (PR), whereas the remaining two would show progressive disease (PD). Clinically consistent with lung cancer PDO drug screening, two patients demonstrated PR and two patients had PD (81).

Another study tested the sensitivity of lung cancer PDOs to chemotherapy. In this study, chemotherapy drug sensitivity tests were performed using lung cancer PDOs cultured on an integrated superhydrophobic microwell array chip (InSMAR chip). Chemotherapy drug screening was performed for one week and compared with genetic tumor mutations and clinical outcomes. A sensitive response to gemcitabine + cisplatin (GC) has been observed in PDOs from patients with small-cell lung cancer. Clinical treatment of this patient showed that both the primary tumor and metastatic lymph nodes decreased following GC treatment. However, PDOs from other patients with SCLC showed resistance to GC drug screening. In this patient, new metastases were discovered two weeks after GC treatment (82).

The LCO drug sensitivity test using chemotherapy achieved a high prediction accuracy of 83.3%, and the InSMAR chip, designed to test drug sensitivity within a week is ideal for clinical application. Consequently, chemotherapy drug screening based on lung cancer PDOs could effectively reflect a patient's clinical response to chemotherapy drugs.

Targeted therapy

Targeted therapeutic drugs, developed to treat advanced lung cancers by focusing on specific genetic mutations such as EGFR, ALK, and Kirsten rat sarcoma virus (KRAS), enable personalized treatment. However, these drugs are costly and may lead to resistance over long-term use (83). Therefore, there is an urgent need to overcome the problem of resistance between cancer-specific genetic mutations and targeted anticancer drugs (84). To overcome this resistance problem, various targeted anticancer drugs are being developed. The clinical response to various targeted anticancer drugs varies from person to person (85). Accordingly, a drug screening platform based on lung cancer PDOs is being developed to predict patient responsiveness to targeted anticancer drugs (86).

EGFR mutations are found in around 40–59% of NSCLC cases among Asian patients and in 5–19.4% of NSCLC cases among Caucasian patients (87). EGFR is a receptor that activates various mechanisms such as rat sarcoma/mitogen-activated protein kinase (RAS-MAPK), and phosphoinositide 3-kinases AKT (PI3K-AKT). EGFR is crucial for cellular processes such as proliferation, survival, and migration (88,89). Owing to EGFR overexpression, lung cancer with EGFR mutations has impaired signaling pathway regulatory mechanisms (90). EGFR-TKIs are targeted anticancer drugs that specifically inhibit the mutated EGFR. In the treatment of EGFR-positive lung cancer patients, EGFR-TKIs offer enhanced efficacy compared to chemotherapy anticancer drugs, while minimizing side effects (91). Drug screening for EGFR-TKIs was performed using lung cancer PDOs with EGFR mutations, cultured using the InSMAR chip. This study confirmed that the EGFR-TKI drug screening results from two types of EGFR mutation-positive lung cancer PDOs were consistent with the clinical response. Patients with EGFR L848R mutation were sensitive to gefitinib but resistant to afatinib in lung cancer PDO-based EGFR-TKI drug screening. In the clinic, the patient exhibited TKI tolerance and lymph node metastasis after afatinib treatment. Another patient with an EGFR 19 deletion mutation was sensitive to gefitinib during lung cancer PDO-based EGFR-TKI drug screening. The patient was prescribed icotinib (an analog of gefitinib), which resulted in reduced lymph node metastases and a PR for 4 months (82).

In this study, lung cancer cells derived from 15 patients were mixed with Matrigel at a 1:1 ratio. The lung cancer cells and the Matrigel mixture were dispensed into a 384-well plate and cultured to form lung cancer PDOs. Using lung cancer PDOs, we conducted drug screening to predict clinical response to osimertinib a third-generation EGFR-TKI. The clinical response of the patient to osimertinib was predicted using drug screening based on the lung cancer PDOs. Drug screening based on lung cancer PDOs showed a sensitivity of 86.7% (13/15) in predicting lung cancer patients’ responses, particularly to osimertinib (81).

This study evaluated the responsiveness of organoids derived from patients with different types of lung cancer to the EGFR inhibitor erlotinib. Erlotinib drug response was targeted to three EGFR wild-type organoids and one EGFR 19 deletion mutant organoid. Differences in the drug response of each organoid were analyzed. To generate lung cancer PDOs, lung cancer PDCs were seeded at 3,000 cells per well in a Matrigel-coated 384-well plate. Afterward, the 384-well plate in which the cells were seeded was cultured for 24 h. Cultured organoids were treated with various concentrations of erlotinib (0.01–10 µmol/L) for 96 hours. To confirm erlotinib responsiveness, cell viability was measured using a CellTiter-Glo 3D viability assay. Drug responsiveness analysis showed that EGFR 19 deletion mutant organoids were more sensitive to erlotinib than EGFR wild-type organoids (92).

EGFR-TKI therapy is the standard treatment for patients with advanced EGFR-mutated NSCLC. Patients with NSCLC initially responded effectively to EGFR-TKI therapy. However, there is a problem of resistance developing over time (93). After EGFR-TKI treatment, the primary resistance mechanism is the T790M mutation and the secondary resistance mechanism is the C797S mutation (94). EGFR T790M mutations occur mainly after treatment with second-generation EGFR-TKIs. A therapeutic model using third-generation EGFR-TKIs was developed to suppress the resistance caused by EGFR T790M (95). The EGFR C797S mutation is a resistance mechanism to third-generation EGFR-TKI therapy, such as osimertinib. In patients treated with second-line therapy using osimertinib, the EGFR C797S mutation occurs in approximately 10–26% of cases (96). The EGFR C797 mutation is a site for covalent binding of an irreversible EGFR inhibitor. Therefore, the EGFR C797 mutation reduces the inhibitory effect on EGFR phosphorylation by 100–1,000-fold (97,98). Currently, no new targeted therapies are available since the development of third-generation EGFR-TKI models. Therefore, new fourth-generation EGFR-TKI models are required to overcome third-generation EGFR-TKI resistance caused by the EGFR C797S mutation (99,100). The high-throughput screening (HTS) was performed to predict the effectiveness of the fourth-generation EGFR-TKI compounds. The efficacy of BI-4732, a fourth-generation EGFR-TKI, was evaluated by lung cancer PDO-based drug screening. Lung cancer PDOs were formed from lung cancer PDCs and were classified by epithelial cell adhesion molecule (EpCAM) staining using FACS analysis. These lung cancer PDCs were seeded at a density of 2×10³ cells/well in 96-well ultra-low attachment plates containing 5% Matrigel and cultured for 1 day. Subsequently, the resulting PDOs were treated with various concentrations of BI-4732 and osimertinib. After drug treatment, the lung cancer PDOs were cultured for 72 h, and drug efficacy was compared and analyzed. The lung cancer PDOs used were of one type and had the E19del/T790M/C797S genotype. A comparison of the efficacies of BI-4732 and osimertinib in lung cancer PDOs showed that BI-4732 was more sensitive than osimertinib (101). Additionally, various targeted anticancer drugs are being developed and tested in clinical trials for lung cancer (Table 2).

NSCLC patients with ALK rearrangement-positive account for 2–5% of all NSCLC patients (102). A previous study analyzed ALK-TKI drug responsiveness in ALK-mutant and wild-type lung cancer PDOs. ALK-TKI drug response in lung cancer PDOs was compared with the clinical ALK-TKI drug response in patients with lung cancer to predict the drug sensitivity of lung cancer PDOs. This study confirmed that the lung cancer PDO model is useful in predicting a patient’s ALK-TKI drug response. A 384-pillar/well plate was used to form the lung cancer PDOs. Lung cancer cells derived from patients were seeded at 5,000 cells per 1.5 µL of 80% matrigel (80 v/v) in each pillar spot and cultured. The ALK-TKI drugs used in the drug screening were crizotinib, alectinib, and brigatinib. The drug sensitivities of lung cancer PDOs to the drugs crizotinib, alectinib, and brigatinib were reported to be 100% (5/5), 100% (3/3), and 100% (5/5). Additionally, the drug specificity of lung cancer PDOs for these drugs was confirmed to be 66.6% (8/12), 83.3% (10/12), and 83.3% (10/12) (103). Another study compared the drug response to alectinib in ALK mutation-positive lung cancer PDOs with the clinical response. The patient group comprised individuals diagnosed with ALK mutation-positive lung cancer who were treated with alectinib. The drug sensitivity of lung cancer PDOs was 100% (5/5). Although the sample size was small, it shows the potential for personalized medicine utilizing tumor organoids (81). The other study conducted an observational study to assess the correlation between PDO drug sensitivity and clinical outcomes. In this study, PDOs with ALK rearrangements were successfully established in 7 out of 9 cases (77%). And drug sensitivity testing was performed on PDOs from a male patient with ALK C1556Y and I1171T mutations, revealing no response to lorlatinib but a positive response to crizotinib in vitro. This patient was subsequently treated with crizotinib, and a PR was observed after 6 months (104).

KRAS mutations account for approximately 12% of lung adenocarcinomas and are primarily induced by smoking (105). Currently, among KRAS mutations, only NSCLC patients with the KRASG12C mutation can be treated with sotorasib or adagrasib (106,107). In a previous study, KRAS mutant cell lines showed higher MEK inhibitor responsiveness than wild-type KRAS cell lines. To confirm the sensitivity of lung cancer cells to MEK inhibitors, trametinib drug screening was performed using LCOs with different mutant patterns. The response of one KRAS-mutant LCO to trametinib was compared with that of three KRAS wild-type LCOs without the KRAS mutant. KRAS mutant LCOs had half-maximal inhibitory concentration (IC₅₀) <0.05 µmol/L, while KRAS wild-type LCOs had IC₅₀ >0.5 µmol/L. These results showed that KRAS-mutant LCOs were more sensitive to trametinib than KRAS wild-type LCOs. In addition, patient-derived xenograft (PDX) models using KRAS mutation organoids were sensitive to trametinib, whereas those using KRAS wild-type organoids were resistant to trametinib (92).

The aforementioned studies showed a significant correlation between clinical data and the sensitivity of lung cancer PDOs to targeted therapies, suggesting the potential for personalized medicine through the use of organoids in drug efficacy testing. The application of lung cancer PDOs in clinical trials for fourth-generation EGFR-targeted therapies is a noteworthy achievement. However, further studies are needed on the recapitulation of lung cancer PDOs in modeling the TME, which is known to be linked to anti-cancer drug resistance in lung cancer, to enhance targeted therapy sensitivity platforms.

Immunotherapy

Immunotherapy activates the patient’s immune system, enabling immune cells to attack the cancer cells. Traditional chemotherapy directly targets and destroys the cancer cells. Immunotherapy improves the immune function of cancer patients by helping immune cells around the tumor recognize and attack the cancer cells. Cancer cells possess mechanisms to evade recognition by immune cells. Immunotherapeutic drugs block the binding of PD-L1 on cancer cells to PD-1 on immune cells, thereby inhibiting these evasion mechanisms. Consequently, immune cells recognize and destroy the cancer cells (108).

Immune checkpoint inhibitors (ICIs) are used in the treatment of various cancer types. They primarily target the most commonly recognized ICs, including cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), PD-1, and PD-L1. The main advantage of immunotherapy is the low possibility of recurrence during long-term follow-up. Immunotherapy for lung cancer has advanced since the discovery of ICs and ICIs. For patients with NSCLC, immunotherapy involves ICIs, including PD-1 inhibitors (nivolumab and pembrolizumab), PD-L1 inhibitors (durvalumab and atezolizumab), and CTLA-4 inhibitors (ipilimumab) (109-113). As first-line treatment for SCLC, PD-L1 inhibitors (atezolizumab or durvalumab) are used in combination with platinum-based chemotherapy. However, the use of ICIs for the treatment of SCLC is limited. Furthermore, the patient population likely to respond effectively to ICIs is limited. Therefore, research is being conducted to categorize treatment responses to ICIs based on the characteristics and mutations of the cancer. Recently, there has been research into strategies aimed at augmenting the efficacy of ICIs through their combination with chemotherapy or targeted therapy agents (114-116).

To measure the tumor responsiveness of CD8⁺ T cells, NSCLC and colorectal cancer (CRC) organoids were initially stimulated with PBMCs at a 20:1 ratio (effector: target). Subsequently, the cancer organoids were seeded on anti-CD28 coated plates with 20 µg/mL anti-PD-1. CD8⁺ cells and cancer organoids were co-cultured through this process. After 2 weeks of co-culture, CD8⁺ T cells exhibited increased expression of interferon-gamma (IFNγ) and CD107a. In addition, a major histocompatibility complex (MHC)-dependent cytotoxic T cell-mediated killing effect was observed. Furthermore, the response of CD8⁺ T cells to tumor cells did not affect normal lung organoids, indicating the specificity of the CD8⁺ T cell response. This study presents a method to enhance the effectiveness of T cell-based immunotherapy using cancer organoids. Additionally, it provides an in vitro model for studying the interactions between T cells and tumor cells (117).

In one study, lung cancer PDOs generated using the ALI-culture method were used to evaluate the potential tumor control of combination therapy with methyltransferase enhancer of zeste homolog 2 (EZH2) inhibitors and anti-PD-1 to enhance the response rate of first-line immunotherapy targeting PD-1/PD-L1 in patients with lung squamous cell carcinoma (LSCC). The 3D organoid culture of tumor cells was conducted by seeding murine and patient-derived cancer cells into Matrigel and incubating them in Transwell to form organoids. The EZH2 inhibition and IFNγ treatment increased MHC I and MHC II expression in lung cancer PDOs and combining EZH2 inhibition with IFNγ preserved the upregulation of pro-T cell cytokines CXCL9/10/11. While EZH2 inhibition combined with anti-PD-1 therapy showed potential for tumor control in LSCC models, this was validated through in vivo experiments using mice, rather than with organoid-based methods (118).

Murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS) of 40–100 µm were cultured in microfluidic systems to mimic the TME and assess the molecular responses to ICIs, including pembrolizumab, ipilimumab, and their combination. The results showed a strong correlation between in vivo mouse experiments of anti-PD-1 therapy and ex vivo MDOTS studies, demonstrating that MDOTS in 3D microfluidic culture can effectively recapitulate both sensitivity and resistance to PD-1 blockade. In addition, immune phenotypes across NSCLC, SCLC, and other cancer types correlated with T-cell profiles in PDOTS. Cytokine release on day 3 of PD-1 blockade further demonstrated the immunotherapy response, with CCL19 and CXCL13 upregulated in both PDOTS and patient tissues. These data provide crucial evidence supporting the use of MDOTS and PDOTS for ex vivo immune profiling of Immune Checkpoint Blockade (ICB) responses (72).

After the development of ICIs targeting CTLA-4, PD-1, and PD-L1, newly discovered ICs involved in tumor immunity, such as T-cell immunoreceptors with immunoglobulin and ITIM domains (TIGIT), lymphocyte-activation gene 3 (LAG3), T-cell immunoglobulin and mucin domain-3 (TIM3), and V-domain immunoglobulin suppressor of T cell activation (VISTA) (119). Inhibitors targeting newly discovered ICs have been developed in recent years and are currently undergoing clinical trials (Table 3). TIGIT has emerged as new IC molecules that negatively regulate cytotoxic T lymphocyte (CTL) function in the TME. TIGIT is expressed on activated T, regulatory T cells (Tregs), and NK cells. TIGIT plays an immunosuppressive role by binding to its ligands CD155 and CD112, which are expressed on the surface of tumor cells and antigen-presenting cells (APCs), thereby suppressing T cell activation. The PD-1/TIGIT blockade was found to increase the number of CD8⁺ T cells, whereas the overexpression of TIGIT⁺ CD8⁺ T cells was associated with impaired CD8⁺ T cell function. CD8⁺ T cells isolated from the tumor tissues of patients with NSCLC were cultured with PDOs and then treated with IL-15, anti-TIGIT alone, or anti-TIGIT plus IL-15. The combination of anti-TIGIT and IL-15 significantly increased the LCO death rate compared to TIGIT inhibition or IL-15 treatment alone (120).

PD-L1 expression in lung cancer tissue is associated with the efficacy of lung cancer immunotherapy, but low levels of PD-L1 expression (1–49%) require the selection of monotherapy and combination therapy for immunotherapy in NSCLC patients without targetable mutations. An ICI drug evaluation platform using lung cancer PDO is needed to predict responsiveness in these patients (121,122). Lung cancer PDO-based prediction of immunotherapy response requires co-culturing with immune cells, but immune cell viability decreases over time, posing a limitation for long-term co-culture (123). To overcome the limitation of long-term co-culture, studies are being conducted using various cytokine combinations, such as IL-2 and IL-15, to enhance immune cell proliferation and efficacy (124-126). Additionally, vascular formation in the co-culture of organoids and immune cells remains a significant challenge, and research is being conducted to establish vascularized organoids using microfluidic platforms (127). The co-culture of LCOs with immune cells is still in its infancy, so there are limited studies on whether drug sensitivity and specificity in this model match patient responses. Despite the need for more studies to standardize anticancer drug screening, this co-culture system holds significant potential for mimicking the TME and discovering new ICIS.

ADCs

Various anticancer drugs related to targeted therapy and immunotherapy have been developed to treat patients with lung cancer. However, owing to the limitations of existing anticancer drugs, such as low drug efficacy and side effects, ADCs are emerging as treatment alternatives for patients with lung cancer. Currently, ADCs are being actively studied and developed as next-generation anticancer drugs. Additionally, it has great potential for use in drug therapy in clinical settings. ADC combines with a target antigen specifically expressed by cancer cells to selectively target cancer cells. ADC, combined with the target antigen, is internalized by cancer cells and fused with lysosomes. Subsequently, ADC is degraded, and the payload drug is released, targeting the DNA or microtubules of cancer cells. This induces apoptosis directly or through the release of cytotoxic substances that subsequently lead to apoptosis. Some payloads may be released through the cell membrane from target cancer cells after internalization and degradation of ADC. In these cases, it induces a bystander effect that leads to the apoptosis of adjacent cancer cells.

To develop ADC anticancer drugs, it is essential to consider target cell selection, antigen characteristics, antibody structure and stability, linker chemistry, and cytotoxic payload when designing ADC molecules. Human epidermal growth factor receptor 2 (HER2), human epidermal growth factor receptor 3 (HER3), and tumor-associated calcium signal transducer 2 (Trop2) are currently being studied and developed as targets for the representative ADCs related to lung cancer (Table 4). Trastuzumab deruxtecan (T-DXd) was the first ADC approved for NSCLC. It has received the Food and Drug Administration (FDA) approval for patients with HER2-mutant NSCLC in 2022. Various ADCs are in clinical trials as mono-and combination therapies for advanced lung cancer (128). A list of lung cancer-targeting ADC drugs currently used in clinical trials is summarized in Table 4.

HER3 is a member of the EGFR tyrosine kinase family, mainly expressed in lung, breast, and colon cancers, and is associated with resistance to anticancer treatments (129). Patritumab deruxtecan was the first HER3-targeting ADC with proven clinical therapeutic efficacy in NSCLC. Currently, development is being conducted for AMT-562, which is considered to potentially show higher anti-tumor efficacy than the conventional patritumab deruxtecan. This ADC is in the preclinical research stage and was developed by combining Ab562, a HER3 targeting antibody, with exatecan. Currently, preclinical studies are being conducted to analyze the anti-tumor efficacy of PDX and cancer organoid models in lung, colon, and CRCs. In a TKI-resistant EGFR ex19del/MET-amplified NSCLC PDX model, both AMT-562 and patritumab deruxtecan showed anti-tumor efficacy in the early stages of drug administration. However, after 3 weeks of drug administration, the tumors in the patritumab deruxtecan group grew and the disease progressed. In other words, the higher anti-tumor efficacy of the developed ADC, AMT-562, was confirmed compared to the conventional patritumab deruxtecan (128). The anti-tumor efficacy of the ADC was analyzed using cancer organoids. First, the cancer organoids were dispensed and cultured in a 96-well plate using the 3D sandwich cell culture method. To culture cancer organoids using the 3D sandwich cell culture method, 50% Matrigel (1:1 mixture of Matrigel and PBS) was dispensed at the bottom of a 96-well plate. Subsequently, 10 µL of 10% Matrigel (a 1:9 mixture of Matrigel and PBS) containing approximately 50 cancer cells per well was added. Afterward, 200 µL of organoid culture medium was added to each well and cultured for stabilization for 1 d. Drug efficacy was quantitatively analyzed through a live/dead assay using Calcein AM and propidium iodide (PI) after treating cancer organoids with the two types of ADC for 6 days. The drug efficacy analysis results using cancer organoids also confirmed higher anti-tumor efficacy in AMT-562 cells compared to the existing patritumab deruxtecan, consistent with the drug efficacy analysis results using PDX (130).

MET amplification is one of the mechanisms that causes resistance to EGFR-TKIs in NSCLC containing EGFR mutations. In this regard, preclinical studies are being conducted on REGN5093-M114, an ADC that targets MET. The anti-tumor efficacy of REGN5093-M114 was tested using PDOs from patients with NSCLC with EGFR mutations. Lung cancer PDOs were treated with dispase for 30 min and collected as a pellet by centrifugation. The PDOs with a diameter of approximately 20 to 70 µm were mixed with a 5% concentration of Matrigel and dispensed into a 96-Ultra low-attached well plate. After dispensing the PDOs into a well plate, a drug efficacy analysis was performed by treating the cells with various concentrations of the drugs for 120 h. The cell viability of PDOs was quantitatively analyzed using 3D-CellTiter Glo. IC₅₀ values ranging from 0.03 to 0.06 µg/mL were quantitatively analyzed in five lung cancer PDOs with acquired EGFR TKI resistance and amplified MET expression. In other words, the high efficacy of REGN5093-M114 was verified in lung cancer PDOs with amplified MET expression. Particularly, the efficacy of REGN5093-M114 increased as the copy number of MET increased (131).

The application of LCO models for drug screening provides an innovative platform to assess the efficacy and safety of ADCs in a more physiologically relevant context. The application of ADCs in the LCO drug screening platform represents a significant case in clinical research. However, limitation of using organoid models is their inability to fully recapitulate the complexity of the TME, which may affect the predictive validity of the drug responses observed. This combination of ADC technology and organoid-based drug screening holds great potential to advance personalized medicine in lung cancer treatment.

Conclusions

LCOs recapitulate the characteristics and heterogeneity of primary cancer tissues and are important tools in precision medicine and new drug development. Lung cancer is a malignant tumor with a high incidence and mortality rate and is difficult to treat because it shows various drug responses in each patient. To overcome this limitation, a lung cancer PDO-based anticancer drug efficacy prediction model is being developed, which will contribute to the establishment of personalized therapy strategies. Responses to various drugs, such as EGFR-TKIs, ALK-TKIs, and immunotherapy, can be predicted using LCO models. Additionally, the LCO-based anticancer drug susceptibility test results were in line with clinical patient responses. This is thought to increase the efficiency of lung cancer treatments. Despite its potential, the LCO model remains underdeveloped in terms of reflecting the TME, indicating that further research is necessary to support its advancement. However, the clinical application of lung cancer PDO-based drug screening platforms to targeted therapies such as EGFR-TKIs and ALK inhibitors, IC inhibitors, and ADCs, which are currently under development, demonstrates the clinical potential of LCOs. In summary, LCO-based anticancer drug response analyses and new drug development models are important tools for precision medicine and personalized treatment. Therefore, it is expected to play an important role in the development of lung cancer treatment strategies and accelerate new drug development.

Acknowledgments

Funding: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-00212410); the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023- 00280374); the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) (No. RS-2023-00222910); the Korea Medical Device Development Fund grant funded by the Korea government (the Ministry of Science and ICT; the Ministry of Trade, Industry and Energy; the Ministry of Health & Welfare; and the Ministry of Food and Drug Safety) (project No. RS_2023-00255627); Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. RS-2024-00453887); and Ministry of Food and Drug Safety (No. RS-2024-00332142).

Footnote

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-603/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-603/coif). S.Y.L. and B.K. are affiliated with Medical & Bio Decision (MBD) Co., Ltd. The company had no influence on the design, data collection, analysis, interpretation of results, nor the decision to publish this manuscript. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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