Transl Cancer Res. 2026 Apr 30;15(4):314. doi: 10.21037/tcr-2025-aw-2503. Epub 2026 Mar 20.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common lung cancer subtypes worldwide, and its aggressive subtype invasive adenocarcinoma (IAC) has low survival rates. The precise identification of IAC is vital for the clinical diagnosis and treatment. The purpose of this study is to identify novel biomarkers for LUAD using single-cell and bulk RNA sequencing, so as to provide theoretical basis and practical support for the diagnosis, treatment and prognosis evaluation of lung invasive adenocarcinoma.

METHODS: We employed a combination of transcriptomic analysis and single-cell analysis to investigate the molecular characteristics and immune microenvironment of four subtypes of LUAD, including atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and IAC, with the aim of screening for biomarkers to differentiate pre-invasive lesions from invasive lesions.

RESULTS: Transcriptomic and single-cell analyses revealed that IAC subtypes demonstrated the most substantial molecular differences, particularly in immune cell infiltration and immune-related gene expression. Three genes-CD27, TIGIT, and TNFRSF18-that were significantly upregulated in IAC, predominantly expressed in immune cells and closely linked to immune regulatory pathways. We further analyzed T cell subpopulations in the IAC subtype and explored the expression of transcription factors (TFs) corresponding to these three genes, revealing their critical roles in immune cell function. Additionally, communication between T cells and other cells showed significantly enhanced signaling pathways, particularly those related to immune co-stimulatory molecules and inflammation pathways. Immunohistochemical validation of clinical samples showed that these three genes have high diagnostic value in IAC subtypes. These findings establish a crucial biological foundation for diagnosis, classification, and immunotherapy of LUAD, which contributes to the development of individualized treatment strategies.

CONCLUSIONS: This study identifies a three-gene signature (CD27, TIGIT, and TNFRSF18) that not only distinguishes invasive from pre-invasive LUAD with high precision by capturing the immune checkpoint disequilibrium characteristic of IAC, but also provides a clinically actionable biomarker panel for preoperative diagnosis and personalized immunotherapy strategies.

PMID:42180871 | PMC:PMC13190665 | DOI:10.21037/tcr-2025-aw-2503

J Thorac Dis. 2026 Apr 30;18(4):406. doi: 10.21037/jtd-2026-0547. Epub 2026 Apr 27.

ABSTRACT

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, posing a substantial global health burden. Despite advances in early detection, molecular profiling, and targeted therapies, patient outcomes remain unsatisfactory due to tumor heterogeneity, therapeutic resistance, and the lack of reliable preclinical models. In recent years, lung cancer organoids (LCOs), patient-derived three-dimensional (3D) culture systems, have demonstrated the ability to preserve the histological architecture and genomic features of primary tumors more faithfully than conventional models, making them a promising platform for translational research and precision medicine. This study aims to quantitatively evaluate the global research output, identify major contributors and collaboration patterns, and systematically uncover research hotspots and emerging trends in the field of LCOs through bibliometric analysis.

METHODS: A systematic bibliometric analysis was conducted using publications on LCOs retrieved from the Web of Science Core Collection (WoSCC). Articles published between 2015 and 2024 were included. A total of 356 publications were analyzed. Publication outputs, country and institutional contributions, collaboration networks, and keyword co-occurrence were evaluated using Bibliometrix (R package), VOSviewer, and CiteSpace.

RESULTS: The number of publications on LCOs has increased steadily over the past decade, reflecting growing research interest and technological advancement. China and the United States were identified as the leading contributors, accounting for the majority of publications, while Germany, South Korea, and Japan also demonstrated strong research capacity and active collaboration. Keyword and thematic analyses revealed several major research hotspots, including personalized medicine, drug response and resistance mechanisms, tumor microenvironment modeling, and immune-related interactions. Burst keyword analysis further identified emerging trends, such as co-culture systems, immunotherapy evaluation, and the integration of LCOs with high-throughput screening and multi-omics approaches.

CONCLUSIONS: LCOs have evolved into a versatile platform bridging basic research and clinical applications in lung cancer. This study provides a comprehensive overview of the current research landscape and highlights emerging directions in the field. Future research should focus on methodological standardization, optimization of organoid construction and evaluation, integration with multi-omics and immune models, and strengthened international collaboration to facilitate clinical translation and improve patient outcomes.

PMID:42182656 | PMC:PMC13190222 | DOI:10.21037/jtd-2026-0547

J Thorac Dis. 2026 Apr 30;18(4):406. doi: 10.21037/jtd-2026-0547. Epub 2026 Apr 27.

ABSTRACT

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, posing a substantial global health burden. Despite advances in early detection, molecular profiling, and targeted therapies, patient outcomes remain unsatisfactory due to tumor heterogeneity, therapeutic resistance, and the lack of reliable preclinical models. In recent years, lung cancer organoids (LCOs), patient-derived three-dimensional (3D) culture systems, have demonstrated the ability to preserve the histological architecture and genomic features of primary tumors more faithfully than conventional models, making them a promising platform for translational research and precision medicine. This study aims to quantitatively evaluate the global research output, identify major contributors and collaboration patterns, and systematically uncover research hotspots and emerging trends in the field of LCOs through bibliometric analysis.

METHODS: A systematic bibliometric analysis was conducted using publications on LCOs retrieved from the Web of Science Core Collection (WoSCC). Articles published between 2015 and 2024 were included. A total of 356 publications were analyzed. Publication outputs, country and institutional contributions, collaboration networks, and keyword co-occurrence were evaluated using Bibliometrix (R package), VOSviewer, and CiteSpace.

RESULTS: The number of publications on LCOs has increased steadily over the past decade, reflecting growing research interest and technological advancement. China and the United States were identified as the leading contributors, accounting for the majority of publications, while Germany, South Korea, and Japan also demonstrated strong research capacity and active collaboration. Keyword and thematic analyses revealed several major research hotspots, including personalized medicine, drug response and resistance mechanisms, tumor microenvironment modeling, and immune-related interactions. Burst keyword analysis further identified emerging trends, such as co-culture systems, immunotherapy evaluation, and the integration of LCOs with high-throughput screening and multi-omics approaches.

CONCLUSIONS: LCOs have evolved into a versatile platform bridging basic research and clinical applications in lung cancer. This study provides a comprehensive overview of the current research landscape and highlights emerging directions in the field. Future research should focus on methodological standardization, optimization of organoid construction and evaluation, integration with multi-omics and immune models, and strengthened international collaboration to facilitate clinical translation and improve patient outcomes.

PMID:42182656 | PMC:PMC13190222 | DOI:10.21037/jtd-2026-0547