Lung Cancer Organoids: The Rough Path to Personalized Medicine

Applied models and molecular characteristics of small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive type of cancer frequently diagnosed with metastatic spread, rendering it surgically unresectable for the majority of patients. Although initial responses to platinum-based therapies are often observed, SCLC invariably relapses within months, frequently developing drug-resistance ultimately contributing to short overall survival rates. Recently, SCLC research aimed to elucidate the dynamic changes in the genetic and epigenetic landscape. These have revealed distinct subtypes of SCLC, each characterized by unique molecular signatures. The recent understanding of the molecular heterogeneity of SCLC has opened up potential avenues for precision medicine, enabling the development of targeted therapeutic strategies. In this review, we delve into the applied models and computational approaches that have been instrumental in the identification of promising drug candidates. We also explore the emerging molecular diagnostic tools that hold the potential to transform clinical practice and patient care.

Small cells - big issues: biological implications and preclinical advancements in small cell lung cancer

Current treatment guidelines refer to small cell lung cancer (SCLC), one of the deadliest human malignancies, as a homogeneous disease. Accordingly, SCLC therapy comprises chemoradiation with or without immunotherapy. Meanwhile, recent studies have made significant advances in subclassifying SCLC based on the elevated expression of the transcription factors ASCL1, NEUROD1, and POU2F3, as well as on certain inflammatory characteristics. The role of the transcription regulator YAP1 in defining a unique SCLC subset remains to be established. Although preclinical analyses have described numerous subtype-specific characteristics and vulnerabilities, the so far non-existing clinical subtype distinction may be a contributor to negative clinical trial outcomes. This comprehensive review aims to provide a framework for the development of novel personalized therapeutic approaches by compiling the most recent discoveries achieved by preclinical SCLC research. We highlight the challenges faced due to limited access to patient material as well as the advances accomplished by implementing state-of-the-art models and methodologies.

Mathematical Modeling of Non-Small-Cell Lung Cancer Biology through the Experimental Data on Cell Composition and Growth of Patient-Derived Organoids

Mathematical models of non-small-cell lung cancer are powerful tools that use clinical and experimental data to describe various aspects of tumorigenesis. The developed algorithms capture phenotypic changes in the tumor and predict changes in tumor behavior, drug resistance, and clinical outcomes of anti-cancer therapy. The aim of this study was to propose a mathematical model that predicts the changes in the cellular composition of patient-derived tumor organoids over time with a perspective of translation of these results to the parental tumor, and therefore to possible clinical course and outcomes for the patient. Using the data on specific biomarkers of cancer cells (PD-L1), tumor-associated macrophages (CD206), natural killer cells (CD8), and fibroblasts (αSMA) as input, we proposed a model that accurately predicts the cellular composition of patient-derived tumor organoids at a desired time point. Combining the obtained results with "omics" approaches will improve our understanding of the nature of non-small-cell lung cancer. Moreover, their implementation into clinical practice will facilitate a decision-making process on treatment strategy and develop a new personalized approach in anti-cancer therapy.

Clinical insights into small cell lung cancer: Tumor heterogeneity, diagnosis, therapy, and future directions

Small cell lung cancer (SCLC) is characterized by rapid growth and high metastatic capacity. It has strong epidemiologic and biologic links to tobacco carcinogens. Although the majority of SCLCs exhibit neuroendocrine features, an important subset of tumors lacks these properties. Genomic profiling of SCLC reveals genetic instability, almost universal inactivation of the tumor suppressor genes TP53 and RB1, and a high mutation burden. Because of early metastasis, only a small fraction of patients are amenable to curative-intent lung resection, and these individuals require adjuvant platinum-etoposide chemotherapy. Therefore, the vast majority of patients are currently being treated with chemoradiation with or without immunotherapy. In patients with disease confined to the chest, standard therapy includes thoracic radiotherapy and concurrent platinum-etoposide chemotherapy. Patients with metastatic (extensive-stage) disease are treated with a combination of platinum-etoposide chemotherapy plus immunotherapy with an anti-programmed death-ligand 1 monoclonal antibody. Although SCLC is initially very responsive to platinum-based chemotherapy, these responses are transient because of the development of drug resistance. In recent years, the authors have witnessed an accelerating pace of biologic insights into the disease, leading to the redefinition of the SCLC classification scheme. This emerging knowledge of SCLC molecular subtypes has the potential to define unique therapeutic vulnerabilities. Synthesizing these new discoveries with the current knowledge of SCLC biology and clinical management may lead to unprecedented advances in SCLC patient care. Here, the authors present an overview of multimodal clinical approaches in SCLC, with a special focus on illuminating how recent advancements in SCLC research could accelerate clinical development.

In vitro vascularized immunocompetent patient-derived model to test cancer therapies

This work describes a patient-derived tumoroid model (PDTs) to support precision medicine in lung oncology. The use of human adipose tissue-derived microvasculature and patient-derived peripheral blood mononuclear cells (PBMCs) permits to achieve a physiologically relevant tumor microenvironment. This study involved ten patients at various stages of tumor progression. The vascularized, immune-infiltrated PDT model could be obtained within two weeks, matching the requirements of the therapeutic decision. Histological and transcriptomic analyses confirmed that the main features from the original tumor were reproduced. The 3D tumor model could be used to determine the dynamics of response to antiangiogenic therapy and platinum-based chemotherapy. Antiangiogenic therapy showed a significant decrease in vascular endothelial growth factor (VEGF)-A expression, reflecting its therapeutic effect in the model. In an immune-infiltrated PDT model, chemotherapy showed the ability to decrease the levels of lymphocyte activation gene-3 protein (LAG-3), B and T lymphocyte attenuator (BTLA), and inhibitory receptors of T cells functions.

Cell Culture Model Evolution and Its Impact on Improving Therapy Efficiency in Lung Cancer

Optimizing cell culture conditions is essential to ensure experimental reproducibility. To improve the accuracy of preclinical predictions about the response of tumor cells to different classes of drugs, researchers have used 2D or 3D cell cultures in vitro to mimic the cellular processes occurring in vivo. While 2D cell culture provides valuable information on how therapeutic agents act on tumor cells, it cannot quantify how the tumor microenvironment influences the response to therapy. This review presents the necessary strategies for transitioning from 2D to 3D cell cultures, which have facilitated the rapid evolution of bioengineering techniques, leading to the development of microfluidic technology, including organ-on-chip and tumor-on-chip devices. Additionally, the study aims to highlight the impact of the advent of 3D bioprinting and microfluidic technology and their implications for improving cancer treatment and approaching personalized therapy, especially for lung cancer. Furthermore, implementing microfluidic technology in cancer studies can generate a series of challenges and future perspectives that lead to the discovery of new predictive markers or targets for antitumor treatment.

Zebrafish in Lung Cancer Research

Zebrafish is increasingly used as a model organism for cancer research because of its genetic and physiological similarities to humans. Modeling lung cancer (LC) in zebrafish has received significant attention. This review focuses on the insights gained from using zebrafish in LC research. These insights range from investigating the genetic and molecular mechanisms that contribute to the development and progression of LC to identifying potential drug targets, testing the efficacy and toxicity of new therapies, and applying zebrafish for personalized medicine studies. This review provides a comprehensive overview of the current state of LC research performed using zebrafish, highlights the advantages and limitations of this model organism, and discusses future directions in the field.

Non-coding RNA-directed therapeutics in lung cancer: Delivery technologies and clinical applications

Lung cancer is one of the most aggressive and deadliest health threats. There has been an increasing interest in non-coding RNA (ncRNA) recently, especially in the areas of carcinogenesis and tumour progression. However, ncRNA-directed therapies are still encountering obstacles on their way to the clinic. In the present article, we provide an overview on the potential of targeting ncRNA in the treatment of lung cancer. Then, we discuss the delivery challenges and recent approaches enabling the delivery of ncRNA-directed therapies to the lung cancer cells, where we illuminate some advanced technologies including chemically-modified oligonucleotides, nuclear targeting, and three-dimensional in vitro models. Furthermore, advanced non-viral delivery systems recruiting nanoparticles, biomimetic delivery systems, and extracellular vesicles are also highlighted. Lastly, the challenges limiting the clinical trials on the therapeutic targeting of ncRNAs in lung cancer and future directions to tackle them are explored.

Cryobiopsy: A Breakthrough Strategy for Clinical Utilization of Lung Cancer Organoids

One major challenge associated with lung cancer organoids (LCOs) is their predominant derivation from surgical specimens of patients with early-stage lung cancer. However, patients with advanced lung cancer, who are in need of chemotherapy, often cannot undergo surgery. Therefore, there is an urgent need to successfully generate LCOs from biopsy specimens. Conventional lung biopsy techniques, such as transthoracic needle biopsy and forceps biopsy, only yield small amounts of lung tissue, resulting in a low success rate for culturing LCOs from biopsy samples. Furthermore, potential complications, like bleeding and pneumothorax, make it difficult to obtain sufficient tissue. Another critical issue is the overgrowth of normal lung cells in later passages of LCO culture, and the optimal culture conditions for LCOs are yet to be determined. To address these limitations, we attempted to create LCOs from cryobiopsy specimens obtained from patients with lung cancer (n = 113). Overall, the initial success rate of establishing LCOs from cryobiopsy samples was 40.7% (n = 46). Transbronchial cryobiopsy enables the retrieval of significantly larger amounts of lung tissue than bronchoscopic forceps biopsy. Additionally, cryobiopsy can be employed for peripheral lesions, and it is aided via radial endobronchial ultrasonography. This study significantly improved the success rate of LCO culture and demonstrated that the LCOs retained characteristics that resembled the primary tumors. Single-cell RNA sequencing confirmed high cancer cell purity in early passages of LCOs derived from patients with advanced lung cancer. Furthermore, the three-dimensional structure and intracellular components of LCOs were characterized using three-dimensional holotomography. Finally, drug screening was performed using a specialized micropillar culture system with cryobiopsy-derived LCOs. LCOs derived from cryobiopsy specimens offer a promising solution to the critical limitations of conventional LCOs. Cryobiopsy can be applied to patients with lung cancer at all stages, including those with peripheral lesions, and can provide sufficient cells for LCO generation. Therefore, we anticipate that cryobiopsy will serve as a breakthrough strategy for the clinical application of LCOs in all stages of lung cancer.

The Role of Patient-Derived Organoids in Triple-Negative Breast Cancer Drug Screening

Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes, with a grave prognosis and few effective treatment options. Organoids represent revolutionary three-dimensional cell culture models, derived from stem or differentiated cells and preserving the capacity to differentiate into the cell types of their tissue of origin. The current review aims at studying the potential of patient-derived TNBC organoids for drug sensitivity testing as well as highlighting the advantages of the organoid technology in terms of drug screening. In order to identify relevant studies, a literature review was conducted using the MEDLINE and LIVIVO databases. The search terms “organoid” and “triple-negative breast cancer” were employed, and we were able to identify 25 studies published between 2018 and 2022. The current manuscript represents the first comprehensive review of the literature focusing on the use of patient-derived organoids for drug sensitivity testing in TNBC. Patient-derived organoids are excellent in vitro study models capable of promoting personalized TNBC therapy by reflecting the treatment responses of the corresponding patients and exhibiting high predictive value in the context of patient survival evaluation.

Moving toward precision medicine with lung cancer organoids

In this issue of Cell Reports Medicine, Wang et al.1 generated 160 human lung cancer organoids, primarily from malignant effusions, and tested their responses to clinically used drugs to determine whether the ex vivo organoid responses predicted patient responses.