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Jin Y, Mu W, Shi Y, Qi Q, Wang W, He Y, Sun X, Yang B, Cui P, Li C, Liu F, Liu Y, Wang G, Zhao J, Zhang Y, Zhang S, Cao C, Sun C, Hong N, Cai S, Tian J, Yang F, Chen K. Development and validation of an integrated system for lung cancer screening and post-screening pulmonary nodules management: a proof-of-concept study (ASCEND-LUNG). EClinicalMedicine 2024; 75:102769. [PMID: 39165498 PMCID: PMC11334824 DOI: 10.1016/j.eclinm.2024.102769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 07/14/2024] [Accepted: 07/17/2024] [Indexed: 08/22/2024] Open
Abstract
Background In order to address the low compliance and dissatisfied specificity of low-dose computed tomography (LDCT), efficient and non-invasive approaches are needed to complement its limitations for lung cancer screening and management. The ASCEND-LUNG study is a prospective two-stage case-control study designed to evaluate the performance of a liquid biopsy-based comprehensive lung cancer screening and post-screening pulmonary nodules management system. Methods We aimed to develop a comprehensive lung cancer system called Peking University Lung Cancer Screening and Management System (PKU-LCSMS) which comprises a lung cancer screening model to identify specific populations requiring LDCT and an artificial intelligence-aided (AI-aided) pulmonary nodules diagnostic model to classify pulmonary nodules following LDCT. A dataset of 465 participants (216 cancer, 47 benign, 202 non-cancer control) were used for the two models' development phase. For the lung cancer screening model development, cancer participants were randomly split at a ratio of 1:1 into the train and validation cohorts, and then non-cancer controls were age-matched to the cancer cases in a 1:1 ratio. Similarly, for the AI-aided pulmonary nodules model, cancer and benign participants were also randomly divided at a ratio of 2:1 into the train and validation cohorts. Subsequently, during the model validation phase, sensitivity and specificity were validated using an independent validation cohort consisting of 291 participants (140 cancer, 25 benign, 126 non-cancer control). Prospectively collected blood samples were analyzed for multi-omics including cell-free DNA (cfDNA) methylation, mutation, and serum protein. Computerized tomography (CT) images data was also obtained. Paired tissue samples were additionally analyzed for DNA methylation, DNA mutation, and messenger RNA (mRNA) expression to further explore the potential biological mechanisms. This study is registered with ClinicalTrials.gov, NCT04817046. Findings Baseline blood samples were evaluated for the whole screening and diagnostic process. The cfDNA methylation-based lung cancer screening model exhibited the highest area under the curve (AUC) of 0.910 (95% CI, 0.869-0.950), followed by the protein model (0.891 [95% CI, 0.845-0.938]) and lastly the mutation model (0.577 [95% CI, 0.482-0.672]). Further, the final screening model, which incorporated cfDNA methylation and protein features, achieved an AUC of 0.963 (95% CI, 0.942-0.984). In the independent validation cohort, the multi-omics screening model showed a sensitivity of 99.2% (95% CI, 0.957-1.000) at a specificity of 56.3% (95% CI, 0.472-0.652). For the AI-aided pulmonary nodules diagnostic model, which incorporated cfDNA methylation and CT images features, it yielded a sensitivity of 81.1% (95% CI, 0.732-0.875), a specificity of 76.0% (95% CI, 0.549-0.906) in the independent validation cohort. Furthermore, four differentially methylated regions (DMRs) were shared in the lung cancer screening model and the AI-aided pulmonary nodules diagnostic model. Interpretation We developed and validated a liquid biopsy-based comprehensive lung cancer screening and management system called PKU-LCSMS which combined a blood multi-omics based lung cancer screening model incorporating cfDNA methylation and protein features and an AI-aided pulmonary nodules diagnostic model integrating CT images and cfDNA methylation features in sequence to streamline the entire process of lung cancer screening and post-screening pulmonary nodules management. It might provide a promising applicable solution for lung cancer screening and management. Funding This work was supported by Science, Science, Technology & Innovation Project of Xiongan New Area, Beijing Natural Science Foundation, CAMS Innovation Fund for Medical Sciences (CIFMS), Clinical Medicine Plus X-Young Scholars Project of Peking University, the Fundamental Research Funds for the Central Universities, Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, Peking University People's Hospital Research and Development Funds, National Key Research and Development Program of China, and the fundamental research funds for the central universities.
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Affiliation(s)
- Yichen Jin
- Department of Thoracic Oncology Institute & Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Peking University People's Hospital, Beijing, 100044, China
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
| | - Wei Mu
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing, 100191, China
| | - Yezhen Shi
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Qingyi Qi
- Department of Radiology, Peking University People's Hospital, Beijing, 100044, China
| | - Wenxiang Wang
- Department of Thoracic Oncology Institute & Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Peking University People's Hospital, Beijing, 100044, China
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
| | - Yue He
- Department of Thoracic Oncology Institute & Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Peking University People's Hospital, Beijing, 100044, China
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
| | - Xiaoran Sun
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Bo Yang
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Peng Cui
- Burning Rock Biotech, Guangzhou, 510300, China
| | | | - Fang Liu
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Yuxia Liu
- Burning Rock Biotech, Guangzhou, 510300, China
| | | | - Jing Zhao
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Yuzi Zhang
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Shuaitong Zhang
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Caifang Cao
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing, 100191, China
| | - Chao Sun
- Department of Radiology, Peking University People's Hospital, Beijing, 100044, China
| | - Nan Hong
- Department of Radiology, Peking University People's Hospital, Beijing, 100044, China
| | - Shangli Cai
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Jie Tian
- School of Engineering Medicine, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing, 100191, China
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100191, China
| | - Fan Yang
- Department of Thoracic Oncology Institute & Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Peking University People's Hospital, Beijing, 100044, China
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
| | - Kezhong Chen
- Department of Thoracic Oncology Institute & Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Peking University People's Hospital, Beijing, 100044, China
- Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
- Institute of Advanced Clinical Medicine, Peking University, Beijing, 100191, China
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Groth SS. Commentary: It's all in the (cell-free) DNA: Risk stratification of high-risk pulmonary nodules. J Thorac Cardiovasc Surg 2024:S0022-5223(24)00628-7. [PMID: 39053625 DOI: 10.1016/j.jtcvs.2024.07.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2024] [Accepted: 07/18/2024] [Indexed: 07/27/2024]
Affiliation(s)
- Shawn S Groth
- Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Tex.
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Sun Z, Sun J, Hu H, Han S, Ma P, Zuo B, Wang Z, Liu Z. A novel microRNA miR-4433a-3p as a potential diagnostic biomarker for lung adenocarcinoma. Heliyon 2024; 10:e30646. [PMID: 38765119 PMCID: PMC11101798 DOI: 10.1016/j.heliyon.2024.e30646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 05/01/2024] [Accepted: 05/01/2024] [Indexed: 05/21/2024] Open
Abstract
Background Lung adenocarcinoma is one of the leading causes of cancer-related deaths because of the lack of early specific clinical indicators. MicroRNAs (miRNAs) have become the focus in lung cancer diagnosis. Further studies are required to explore miRNA expression in the serum of lung adenocarcinoma patients and their correlation with therapy and analyse specific messenger RNA targets to improve the specificity and sensitivity of early diagnosis. Methods The Toray 3D-Gene miRNA array was used to compare the expression levels of various miRNAs in the sera of patients with lung adenocarcinoma and healthy volunteers. Highly expressed miRNAs were selected for further analysis. To verify the screening results, serum and pleural fluid samples were analysed using qRT-PCR. Serum levels of the miRNAs and their correlation with the clinical information of patients with lung adenocarcinoma were analysed. The functions of miRNAs were further analysed using the Kyoto Encyclopedia of Gene and Genomes and Gene Ontology databases. Results Microarray analysis identified 60 and 50 miRNAs with upregulated and downregulated expressions, respectively, in the serum of patients with lung adenocarcinoma compared to those in healthy individuals. Using qRT-qPCR to detection of miRNAs expression in the serum or pleural effusion of patients with early and advanced lung adenocarcinoma, we found that miR-4433a-3p could be used as a diagnostic marker and therapeutic evaluation indicator for lung adenocarcinoma. Serum of miR-4433a-3p levels significantly correlated with the clinical stage. miR-4433a-3p may be more suitable than other tumour markers for the early diagnosis and evaluation of therapeutic effects in lung adenocarcinoma. miR-4433a-3p may affect tumour growth and metastasis by acting on target genes (PIK3CD, UBE2J2, ICMT, PRDM16 and others) and regulating tumour-related signalling pathways (MAPK signal pathway, Ras signalling pathway and others). Conclusion miR-4433a-3p may serve as a biomarker for the early diagnosis of lung adenocarcinoma and monitoring of therapeutic effects.
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Affiliation(s)
- Zhixiao Sun
- Department of Pulmonary and Critical Care Medicine, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
- Department of Central Laboratory, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
| | - Jian Sun
- Department of Cardiothoracic Surgery, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
| | - Hang Hu
- Department of Pulmonary and Critical Care Medicine, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
| | - Shuhua Han
- Department of Pulmonary and Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, China
| | - Panpan Ma
- Department of Clinical Laboratory, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
| | - Bingqing Zuo
- Department of Pulmonary and Critical Care Medicine, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
| | - Zheng Wang
- Department of Chronic Disease Medical Center, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
| | - Zhongxiang Liu
- Department of Pulmonary and Critical Care Medicine, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
- Department of Central Laboratory, The Yancheng Clinical College of Xuzhou Medical University, The First People's Hospital of Yancheng, China
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Hu K, Gao L, Zhang R, Lu M, Zhou D, Xie S, Fan X, Zhu M. Clinical application of serum seven tumour-associated autoantibodies in patients with pulmonary nodules. Heliyon 2024; 10:e30576. [PMID: 38765082 PMCID: PMC11098830 DOI: 10.1016/j.heliyon.2024.e30576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 05/21/2024] Open
Abstract
Background The incidence of pulmonary nodules is increasing because of the promotion and popularisation of low-dose computed tomography (LDCT) screening for populations with suspected lung cancer. However, a high rate of false positives and concerns regarding the radiation-related cancer risk of repeated CT scanning remain major obstacles to its wide application. This study aimed to investigate the clinical value of seven tumour-associated autoantibodies (7-TAAbs) in the differentiation of malignant pulmonary tumours from benign ones and the early detection of lung cancer in routine clinical practice. Methods We included 377 patients who underwent both the 7-TAAbs panel test and LDCT screening, and were diagnosed with pulmonary nodules using LDCT. An enzyme-linked immunosorbent assay (ELISA) was used to measure the serum levels antibodies for P53, PGP9.5, SOX2, GAGE7, GBU4-5, CAGE, and MAGE-A1. The relationships between the positive rates of the 7-TAAbs and the patient sex, and age, and the number, size, and composition of pulmonary nodules were analysed. We then statistically evaluated the clinical application value. Results The positive rates of the 7-TAAbs did not correlate with sex, age, number, size, or composition of pulmonary nodules. The serum antibody level of GBU4-5 in patients with pulmonary nodules tended to increase with age; the serum antibody level of SOX2 tended to increase with nodule size and was the highest among patients with mixed ground-glass opacity (mGGO) nodules. The antibody positive rate for CAGE in female patients with pulmonary nodules was significantly higher than that in male patients (P < 0.05). The positive rate of GBU4-5 antibody in patients aged 60 years and above was higher than that in younger patients (P < 0.05). The positive rate of GAGE7 antibody in patients with pulmonary nodules sized 8-20 mm was also significantly higher than that in patients with pulmonary nodules sized less than 8 mm (P < 0.01). Significant differences were observed in the GAGE7 antibody levels of patients with pulmonary nodules of different compositions (P < 0.01). The positive rate of the 7-TAAbs panel test in patients with lung cancer was significantly higher than in patients with pulmonary nodules (P < 0.01). Serum levels of P53, SOX2, GBU4-5, and MAGE-A1 antibodies were significantly higher in patients with lung cancer than in those with pulmonary nodules (P < 0.05). Conclusion The low positive rates of serum 7-TAAbs in patients with lung cancer and pulmonary nodules may be related to different case selection, population differences, geographical differences, different degrees of progression, and detection methods. The combined detection of 7-TAAbs has some clinical value for screening and early detection of lung cancer.
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Affiliation(s)
- Kaiming Hu
- Department of Clinical Laboratory, the Affiliated Chaohu Hospital of Anhui Medical University, Hefei, China
| | - Lili Gao
- Department of Clinical Laboratory, the Affiliated Chaohu Hospital of Anhui Medical University, Hefei, China
| | - Ruyi Zhang
- Department of Clinical Laboratory, the Affiliated Chaohu Hospital of Anhui Medical University, Hefei, China
| | - Meiyi Lu
- Department of Clinical Laboratory, the Affiliated Chaohu Hospital of Anhui Medical University, Hefei, China
| | - Dangui Zhou
- Department of Clinical Laboratory, the Affiliated Chaohu Hospital of Anhui Medical University, Hefei, China
| | - Siqi Xie
- Department of Clinical Laboratory, the Affiliated Chaohu Hospital of Anhui Medical University, Hefei, China
| | - Xinyue Fan
- Department of Clinical Laboratory, the Affiliated Chaohu Hospital of Anhui Medical University, Hefei, China
| | - Mei Zhu
- Department of Clinical Laboratory, the Affiliated Chaohu Hospital of Anhui Medical University, Hefei, China
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Kim RY. Radiomics and artificial intelligence for risk stratification of pulmonary nodules: Ready for primetime? Cancer Biomark 2024:CBM230360. [PMID: 38427470 PMCID: PMC11300708 DOI: 10.3233/cbm-230360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
Abstract
Pulmonary nodules are ubiquitously found on computed tomography (CT) imaging either incidentally or via lung cancer screening and require careful diagnostic evaluation and management to both diagnose malignancy when present and avoid unnecessary biopsy of benign lesions. To engage in this complex decision-making, clinicians must first risk stratify pulmonary nodules to determine what the best course of action should be. Recent developments in imaging technology, computer processing power, and artificial intelligence algorithms have yielded radiomics-based computer-aided diagnosis tools that use CT imaging data including features invisible to the naked human eye to predict pulmonary nodule malignancy risk and are designed to be used as a supplement to routine clinical risk assessment. These tools vary widely in their algorithm construction, internal and external validation populations, intended-use populations, and commercial availability. While several clinical validation studies have been published, robust clinical utility and clinical effectiveness data are not yet currently available. However, there is reason for optimism as ongoing and future studies aim to target this knowledge gap, in the hopes of improving the diagnostic process for patients with pulmonary nodules.
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van den Broek D, Groen HJM. Screening approaches for lung cancer by blood-based biomarkers: Challenges and opportunities. Tumour Biol 2024; 46:S65-S80. [PMID: 37393461 DOI: 10.3233/tub-230004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/03/2023] Open
Abstract
Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.
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Affiliation(s)
- Daniel van den Broek
- Department of laboratory Medicine, The Netherlands Cancer Institute, Amsterdam, The Netherlands
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Heidarian S, Takbiri Osgoei L, Zare Karizi S, Amani J, Arbabian S. Signal-On Fluorescence Biosensor for Detection of miRNA-21 Based on ROX labeled Specific Stem-Loop Probe. IRANIAN JOURNAL OF PHARMACEUTICAL RESEARCH : IJPR 2024; 23:e144368. [PMID: 39005737 PMCID: PMC11246647 DOI: 10.5812/ijpr-144368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 02/21/2024] [Accepted: 02/26/2024] [Indexed: 07/16/2024]
Abstract
Background The abnormal expression of microRNA (miRNA) influences RNA transcription and protein translation, leading to tumor progression and metastasis. Today, reliably identifying aberrant miRNA expression remains challenging, especially when employing quick, simple, and portable detection methods. Objectives This study aimed to diagnose and detect the miR-21 biomarker with high sensitivity and specificity. Methods Our detection approach involves immobilizing ROX dye-labeled single-stranded DNA probes (ROX-labeled ssDNA) onto MWCNTs to detect target miRNA-21. Initially, adsorbing ROX-labeled ssDNA onto MWCNTs causes fluorescence quenching of ROX. Subsequently, introducing its complementary DNA (cDNA) forms double-stranded DNA (dsDNA), which results in the desorption and release from MWCNTs, thus restoring ROX fluorescence. Results The study examined changes in fluorescence intensities before and after hybridization with miRNA-21. The fluorescence emission intensities responded linearly to increases in miR-21 concentration from 10-9 to 3.2 × 10-6 M. The developed fluorescence sensor exhibited a detection limit of 1.12 × 10-9 M. Conclusions This work demonstrates that using a nano-biosensor based on carbon nanotubes offers a highly sensitive method for the early detection of colorectal cancer (CRC), supplementing existing techniques.
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Affiliation(s)
- Somayeh Heidarian
- Department of Biology, Faculty of Biological Science, North Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Laya Takbiri Osgoei
- Department of Microbiology, Faculty of Biological Science, North Tehran Branch. Islamic Azad University, Tehran, Iran
| | - Shohreh Zare Karizi
- Department of Biology, Varamin Pishva, Branch, Islamic Azad University Pishva, Varamin, Iran
| | - Jafar Amani
- Microbiology Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Sedigheh Arbabian
- Department of Biology, Faculty of Biological Science, North Tehran Branch, Islamic Azad University, Tehran, Iran
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Wang Q, Song X, Zhao F, Chen Q, Xia W, Dong G, Xu L, Mao Q, Jiang F. Noninvasive diagnosis of pulmonary nodules using a circulating tsRNA-based nomogram. Cancer Sci 2023; 114:4607-4621. [PMID: 37770420 PMCID: PMC10728016 DOI: 10.1111/cas.15971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 07/20/2023] [Accepted: 08/31/2023] [Indexed: 09/30/2023] Open
Abstract
Evaluating the accuracy of pulmonary nodule diagnosis avoids repeated low-dose computed tomography (LDCT)/CT scans or invasive examination, yet remains a main clinical challenge. Screening for new diagnostic tools is urgent. Herein, we established a nomogram based on the diagnostic signature of five circulating tsRNAs and CT information to predict malignant pulmonary nodules. In total, 249 blood samples of patients with pulmonary nodules were selected from three different lung cancer centers. Five tsRNAs were identified in the discovery and training cohorts and the diagnostic signature was established by the randomForest algorithm (tRF-Ser-TGA-003, tRF-Val-CAC-005, tRF-Ala-AGC-060, tRF-Val-CAC-024, and tiRNA-Gln-TTG-001). A nomogram was developed by combining tsRNA signature and CT information. The high level of accuracy was identified in an internal validation cohort (n = 83, area under the receiver operating characteristic curve [AUC] = 0.930, sensitivity 100.0%, specificity 73.8%) and external validation cohort (n = 66, AUC = 0.943, sensitivity 100.0%, specificity 86.8%). Furthermore, the diagnostic ability of our model discriminating invasive malignant ones from noninvasive lesions was assessed. A robust performance was achieved in the diagnosis of invasive malignant lesions in both training and validation cohorts (discovery cohort: AUC = 0.850, sensitivity 86.0%, specificity 81.4%; internal validation cohort: AUC = 0.784, sensitivity 78.8%, specificity 78.1%; and external validation cohort: AUC = 0.837, sensitivity 85.7%, specificity 84.0%). This novel circulating tsRNA-based diagnostic model has potential significance in predicting malignant pulmonary nodules. Application of the model could improve the accuracy of pulmonary nodule diagnosis and optimize surgical plans.
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Affiliation(s)
- Qinglin Wang
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Xuming Song
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Feng Zhao
- Department of Thoracic SurgeryTaixing People's HospitalTaizhouChina
| | - Qiang Chen
- Department of Thoracic SurgeryXuzhou Central HospitalXuzhouChina
| | - Wenjie Xia
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Gaochao Dong
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Lin Xu
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Qixing Mao
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Feng Jiang
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
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Archer JM, Mendoza DP, Hung YP, Lanuti M, Digumarthy SR. Surgical Resection of Benign Nodules in Lung Cancer Screening: Incidence and Features. JTO Clin Res Rep 2023; 4:100605. [PMID: 38124789 PMCID: PMC10730375 DOI: 10.1016/j.jtocrr.2023.100605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 10/25/2023] [Accepted: 11/11/2023] [Indexed: 12/23/2023] Open
Abstract
Introduction Interventions and surgical procedures are common for nonmalignant lung lesions detected on lung cancer screening (LCS). Inadvertent surgical resection of benign nodules with a clinical suspicion of lung cancer can occur, can be associated with complications, and adds to the cost of screening. The objective of this study is to assess the characteristics of surgically resected benign nodules detected on LCS computed tomography which were presumed to be lung cancers. Methods This retrospective study included 4798 patients who underwent LCS between June 2014 and January 2021. The benign lung nodules, surgically resected with a presumed cancer diagnosis, were identified from the LCS registry. Patient demographics, imaging characteristics, and pathologic diagnoses of benign nodules were analyzed. Results Of the 4798 patients who underwent LCS, 148 (3.1%) underwent surgical resection of a lung nodule, and of those who had a resection, 19 of 148 (12.8%) had a benign diagnosis (median age = 64 y, range: 56-77 y; F = 12 of 19, 63.2%; M = seven of 19, 36.8%). The median nodule size was 10 mm (range: 6-31 mm). Most nodules were solid (15 of 19, 78.9%), located in the upper lobes (11 of 19; 57.9%), and were peripheral (17 of 19, 89.5%). Most nodules (13 of 17; 76.5%) had interval growth, and four of 17 (23.5%) had increased fluorodeoxyglucose uptake. Of the 19 patients, 17 (89.5%) underwent sublobar resection (16 wedge resection and one segmentectomy), whereas two central nodules (10.5%) had lobectomies. Pathologies identified included focal areas of fibrosis or scarring (n = 8), necrotizing granulomatous inflammation (n = 3), other nonspecific inflammatory focus (n = 3), benign tumors (n = 3), reactive lymphoid hyperplasia (n = 1), and organizing pneumonia (n = 1). Conclusions Surgical resections of benign nodules that were presumed malignant are infrequent and may be unavoidable given overlapping imaging features of benign and malignant nodules. Knowledge of benign pathologies that can mimic malignancy may help reduce the incidence of unnecessary surgeries.
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Affiliation(s)
- John M. Archer
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Dexter P. Mendoza
- Department of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Yin P. Hung
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | - Michael Lanuti
- Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts
| | - Subba R. Digumarthy
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
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Xie C, Huang Q, Liu Y. Utility of peripheral blood macrophage factor Apo10 and TKTL1 as markers in distinguishing malignant from benign lung nodules: a protocol for a prospective cohort study in Southern China. BMJ Open 2023; 13:e076573. [PMID: 37914307 PMCID: PMC10626805 DOI: 10.1136/bmjopen-2023-076573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 09/13/2023] [Indexed: 11/03/2023] Open
Abstract
INTRODUCTION Lung nodules are one of the most prevalent diseases. Medical imaging methods have a high false positive rate for distinguishing malignant nodules from benign nodules. Therefore, developing new technologies with high accuracy for screening malignant nodules is of great importance for lung nodule surveillance. Use of flow cytometry to detect biomarkers in blood macrophages (epitop detect in macrophages/macrophages) has opened a new era for early and noninvasive diagnosis of cancer. This planned study aims to examine whether the peripheral blood macrophage factors Apo10 and TKTL1 accurately distinguish malignant nodules from benign nodules. METHODS AND ANALYSES We plan to enrol in this study 3825 participants with lung nodules who will attend their annual physical examination at Sun Yat-sen University Cancer Center. Apo10 and TKTL1 levels in all patients will be tested at 60 min after their last meal every 6 months during their 3-year follow-up. Biopsy or surgical pathology results will be collected as the gold standard to assess the accuracy of Apo10 and TKTL1 in distinguishing malignant nodules from benign nodules. The sensitivity, specificity, positive predictive value, negative predictive value and area under the receiving operating characteristic curve will also be evaluated. ETHICS AND DISSEMINATION The study is approved by the medical ethics committee of Sun Yat-sen University (SL-G2022-005-02). The results of this study will be disseminated in peer-reviewed publications and presentations at international scientific meetings and will also be disseminated to the participants. TRIAL REGISTRATION NUMBER ChiCTR2300073823; Pre-results.
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Affiliation(s)
- Chuanbo Xie
- Cancer Prevention Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Qiyu Huang
- School of Public Health, Guangxi Medical University, Nanning, China
| | - Yuying Liu
- Cancer Prevention Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
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11
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Chen Y, Zhang S, Lu J, Li D, Wu H, Zhang L, Li X, Gao X, Xu Y, Zeng Z, Zeng L, Ding X, Li X, Ding S. DNA-Guided Extracellular-Vesicle Metallization with High Catalytic Activity for Accurate Diagnosis of Pulmonary Nodules. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2208142. [PMID: 37066711 DOI: 10.1002/smll.202208142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Revised: 03/19/2023] [Indexed: 06/19/2023]
Abstract
Sensitive and specific analysis of extracellular vesicles (EVs) offers a promising minimally invasive way to identify malignant pulmonary nodules from benign lesions. However, accurate analysis of EVs is subject to free target proteins in blood samples, which compromises the clinical diagnosis value of EVs. Here a DNA-guided extracellular-vesicle metallization (DEVM) strategy is described for ultrasensitive and specific analysis of EV protein biomarkers and classification of pulmonary nodules. The facile DEVM process mainly includes the incorporation of DNA labeled with cholesterol and thiol groups into EV membranes and subsequent deposition of Au3+ and Pt4+ to allow the DNA-functionalized EVs to be encapsulated with AuPt nanoshells. It is found that the synthesized AuPt-metallized EVs possess extrinsic peroxidase-like activity. Utilizing the feature of the catalytic metal nanoshells just growth on the EV membranes, the DEVM method enables multiparametric recognition of target proteins and EV membranes and can produce an amplified colorimetric signal, avoiding the interference of free proteins. By profiling four surface proteins of EVs from 48 patients with pulmonary nodules, the highest area under the receiver operating characteristic curve (0.9983) is obtained. Therefore, this work provides a feasible EVs analysis tool for accurate pulmonary nodules management.
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Affiliation(s)
- Yirong Chen
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Songzhi Zhang
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Jun Lu
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Dandan Li
- Department of Laboratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Haiping Wu
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Lu Zhang
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Xinyu Li
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Xin Gao
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Yuan Xu
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Zijie Zeng
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Li Zeng
- Department of Laboratory Medicine, Chongqing Traditional Chinese Medicine Hospital, Chongqing, Chongqing, 400016, China
| | - Xiaojuan Ding
- Department of Laboratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xinmin Li
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
| | - Shijia Ding
- Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016, China
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Zhou J, Hu B, Feng W, Zhang Z, Fu X, Shao H, Wang H, Jin L, Ai S, Ji Y. An ensemble deep learning model for risk stratification of invasive lung adenocarcinoma using thin-slice CT. NPJ Digit Med 2023; 6:119. [PMID: 37407729 DOI: 10.1038/s41746-023-00866-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 06/26/2023] [Indexed: 07/07/2023] Open
Abstract
Lung cancer screening using computed tomography (CT) has increased the detection rate of small pulmonary nodules and early-stage lung adenocarcinoma. It would be clinically meaningful to accurate assessment of the nodule histology by CT scans with advanced deep learning algorithms. However, recent studies mainly focus on predicting benign and malignant nodules, lacking of model for the risk stratification of invasive adenocarcinoma. We propose an ensemble multi-view 3D convolutional neural network (EMV-3D-CNN) model to study the risk stratification of lung adenocarcinoma. We include 1075 lung nodules (≤30 mm and ≥4 mm) with preoperative thin-section CT scans and definite pathology confirmed by surgery. Our model achieves a state-of-art performance of 91.3% and 92.9% AUC for diagnosis of benign/malignant and pre-invasive/invasive nodules, respectively. Importantly, our model outperforms senior doctors in risk stratification of invasive adenocarcinoma with 77.6% accuracy [i.e., Grades 1, 2, 3]). It provides detailed predictive histological information for the surgical management of pulmonary nodules. Finally, for user-friendly access, the proposed model is implemented as a web-based system ( https://seeyourlung.com.cn ).
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Affiliation(s)
- Jing Zhou
- Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China
| | - Bin Hu
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Wei Feng
- Department of Cardiothoracic Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Zhang Zhang
- Department of Thoracic Surgery, Changsha Central Hospital, Changsha, China
| | - Xiaotong Fu
- Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China
| | - Handie Shao
- Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China
| | - Hansheng Wang
- Guanghua School of Management, Peking University, Beijing, China
| | - Longyu Jin
- Department of Cardiothoracic Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Siyuan Ai
- Department of Thoracic Surgery, Beijing LIANGXIANG Hospital, Beijing, China
| | - Ying Ji
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
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Clinical value of CT-guided biopsy of small (≤1.5 cm) suspicious lung nodules: Diagnostic accuracy, molecular characterization and long-term clinical outcomes. Cancer Treat Res Commun 2022; 33:100626. [PMID: 36041372 DOI: 10.1016/j.ctarc.2022.100626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/10/2022] [Accepted: 08/20/2022] [Indexed: 12/14/2022]
Abstract
Small pulmonary nodules (≤1.5 cm) are frequently detected on routine chest imaging and lung cancer screening studies. Our goal was to determine the clinical value of CT-guided core needle biopsy (CNB) in the evaluation of such nodules. In this single-center study, we retrospectively analyzed patient data (n = 44) for CNBs on lung nodules (≤1.5 cm) performed at our biopsy center between May 2017 and March 2020. We analyzed for the rate of pathology diagnosis, molecular/biomarker analysis, complications, and change in clinical management and outcome over a period ranging up to 60 months after biopsy. A pathology diagnosis of malignancy or benign lesion was obtained in 97.9% of biopsies in this cohort. The rate of complications was low with only 6.8% of patients requiring the insertion of a temporary small profile interventional radiology (IR) pigtail chest tube for pneumothorax. Out of the subset of biopsy specimens that were sent for tissue molecular analysis, 90% had enough tissue preserved after initial pathological analysis to obtain at least one molecular marker. Our data show that CT-guided CNB is safe and reliable, and should be considered for the evaluation of small, suspicious lung nodules found on routine screenings for the early detection and evaluation of malignant lesions.
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Ding Y, He C, Zhao X, Xue S, Tang J. Adding predictive and diagnostic values of pulmonary ground-glass nodules on lung cancer via novel non-invasive tests. Front Med (Lausanne) 2022; 9:936595. [PMID: 36059824 PMCID: PMC9433577 DOI: 10.3389/fmed.2022.936595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 07/29/2022] [Indexed: 11/13/2022] Open
Abstract
Pulmonary ground-glass nodules (GGNs) are highly associated with lung cancer. Extensive studies using thin-section high-resolution CT images have been conducted to analyze characteristics of different types of GGNs in order to evaluate and determine the predictive and diagnostic values of GGNs on lung cancer. Accurate prediction of their malignancy and invasiveness is critical for developing individualized therapies and follow-up strategies for a better clinical outcome. Through reviewing the recent 5-year research on the association between pulmonary GGNs and lung cancer, we focused on the radiologic and pathological characteristics of different types of GGNs, pointed out the risk factors associated with malignancy, discussed recent genetic analysis and biomarker studies (including autoantibodies, cell-free miRNAs, cell-free DNA, and DNA methylation) for developing novel diagnostic tools. Based on current progress in this research area, we summarized a process from screening, diagnosis to follow-up of GGNs.
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Affiliation(s)
- Yizong Ding
- Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunming He
- Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaojing Zhao
- Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Song Xue
- Department of Cardiovascular Surgery, Reiji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jian Tang
- Department of Thoracic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Jian Tang,
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He X, Lu M, Hu X, Li L, Zou C, Luo Y, Zhou Y, Min L, Tu C. Osteosarcoma immune prognostic index can indicate the nature of indeterminate pulmonary nodules and predict the metachronous metastasis in osteosarcoma patients. Front Oncol 2022; 12:952228. [PMID: 35936683 PMCID: PMC9354693 DOI: 10.3389/fonc.2022.952228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 06/27/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose The relationship between indeterminate pulmonary nodules (IPNs) and metastasis is difficult to determine. We expect to explore a predictive model that can assist in indicating the nature of IPNs, as well as predicting the probability of metachronous metastasis in osteosarcoma patients. Patients and methods We conducted a retrospective study including 184 osteosarcoma patients at West China Hospital from January 2016 to January 2021. Hematological markers and clinical features of osteosarcoma patients were collected and analyzed. Results In this study, we constructed an osteosarcoma immune prognostic index (OIPI) based on the lung immune prognostic index (LIPI). Compared to other hematological markers and clinical features, OIPI had a better ability to predict metastasis. OIPI divided 184 patients into four groups, with the no-OIPI group (34 patients), the light-OIPI group (35 patients), the moderate-OIPI group (75 patients), and the severe-OIPI group (40 patients) (P < 0.0001). Subgroup analysis showed that the OIPI could have a stable predictive effect in both the no-nodule group and the IPN group. Spearman’s rank correlation test and Kruskal–Wallis test demonstrated that the OIPI was related to metastatic site and metastatic time, respectively. In addition, patients with IPNs in high-OIPI (moderate and severe) groups were more likely to develop metastasis than those in low-OIPI (none and light) groups. Furthermore, the combination of OIPI with IPNs can more accurately identify patients with metastasis, in which the high-OIPI group had a higher metastasis rate, and the severe-OIPI group tended to develop metastasis earlier than the no-OIPI group. Finally, we constructed an OIPI-based nomogram to predict 3- and 5-year metastasis rates. This nomogram could bring net benefits for more patients according to the decision curve analysis and clinical impact curve. Conclusion This study is the first to assist chest CT in diagnosing the nature of IPNs in osteosarcoma based on hematological markers. Our findings suggested that the OIPI was superior to other hematological markers and that OIPI can act as an auxiliary tool to determine the malignant transformation tendency of IPNs. The combination of OIPI with IPNs can further improve the metastatic predictive ability in osteosarcoma patients.
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Affiliation(s)
| | | | | | | | | | | | | | - Li Min
- *Correspondence: Li Min, ; Chongqi Tu,
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16
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Zheng D, Zhu Y, Zhang J, Zhang W, Wang H, Chen H, Wu C, Ni J, Xu X, Nian B, Chen S, Wang B, Li X, Zhang Y, Zhang J, Zhong W, Xiong L, Li F, Zhang D, Xu J, Jiang G. Identification and evaluation of circulating small extracellular vesicle microRNAs as diagnostic biomarkers for patients with indeterminate pulmonary nodules. J Nanobiotechnology 2022; 20:172. [PMID: 35366907 PMCID: PMC8976298 DOI: 10.1186/s12951-022-01366-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 03/10/2022] [Indexed: 12/13/2022] Open
Abstract
Background The identification of indeterminate pulmonary nodules (IPNs) following a low-dose computed tomography (LDCT) is a major challenge for early diagnosis of lung cancer. The inadequate assessment of IPNs’ malignancy risk results in a large number of unnecessary surgeries or an increased risk of cancer metastases. However, limited studies on non-invasive diagnosis of IPNs have been reported. Methods In this study, we identified and evaluated the diagnostic value of circulating small extracellular vesicle (sEV) microRNAs (miRNAs) in patients with IPNs that had been newly detected using LDCT scanning and were scheduled for surgery. Out of 459 recruited patients, 109 eligible patients with IPNs were enrolled in the training cohort (n = 47) and the test cohort (n = 62). An external cohort (n = 99) was used for validation. MiRNAs were extracted from plasma sEVs, and assessed using Small RNA sequencing. 490 lung adenocarcinoma samples and follow-up data were used to investigate the role of miRNAs in overall survival. Results A circulating sEV miRNA (CirsEV-miR) model was constructed from five differentially expressed miRNAs (DEMs), showing 0.920 AUC in the training cohort (n = 47), and further identified in the test cohort (n = 62) and in an external validation cohort (n = 99). Among five DEMs of the CirsEV-miR model, miR-101-3p and miR-150-5p were significantly associated with better overall survival (p = 0.0001 and p = 0.0069). The CirsEV-miR scores were calculated, which significantly correlated with IPNs diameters (p < 0.05), and were able to discriminate between benign and malignant PNs (diameter ≤ 1 cm). The expression patterns of sEV miRNAs in the benign, adenocarcinoma in situ/minimally invasive adenocarcinoma, and invasive adenocarcinoma subgroups were found to gradually change with the increase in aggressiveness for the first time. Among all DEMs of the three subgroups, five miRNAs (miR-30c-5p, miR-30e-5p, miR-500a-3p, miR-125a-5p, and miR-99a-5p) were also significantly associated with overall survival of lung adenocarcinoma patients. Conclusions Our results indicate that the CirsEV-miR model could help distinguish between benign and malignant PNs, providing insights into the feasibility of circulating sEV miRNAs in diagnostic biomarker development. Trial registration: Chinese Clinical Trials: ChiCTR1800019877. Registered 05 December 2018, https://www.chictr.org.cn/showproj.aspx?proj=31346. Graphical Abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s12951-022-01366-0.
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Tao R, Cao W, Zhu F, Nie J, Wang H, Wang L, Liu P, Chen H, Hong B, Zhao D. Liquid biopsies to distinguish malignant from benign pulmonary nodules. Thorac Cancer 2021; 12:1647-1655. [PMID: 33960710 PMCID: PMC8169297 DOI: 10.1111/1759-7714.13982] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 04/12/2021] [Accepted: 04/13/2021] [Indexed: 12/24/2022] Open
Abstract
Over the past decades, low-dose computed tomography (LD-CT) screening has been widely used for the early detection of lung cancer. Increasing numbers of indeterminate pulmonary nodules are now being discovered. However, it remains challenging to distinguish malignant from benign pulmonary nodules, especially those considered to be small or ground-glass (GGN) nodules. Liquid biopsies have been successfully applied in the diagnosis of advanced lung cancer, and the potential value for early detection of lung cancer has made great progress. Recent studies have demonstrated the value of various blood-based tumor biomarkers in determining the nature of pulmonary nodules, including cell-free DNA (cfDNA), microRNAs (miRNAs), circulating tumor cells (CTCs) and tumor-associated autoantibodies (AAbs). In this review, we summarize the latest progress of liquid biopsies, and their potential applications and challenges in the diagnosis of malignant pulmonary nodules.
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Affiliation(s)
- Rui Tao
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Wei Cao
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Feng Zhu
- Department of Thoracic Surgery, Anhui Chest Hospital, Thoracic Clinical College of Anhui Medical University, Hefei, China
| | - Jinfu Nie
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Heath & Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Hefei Cancer Hospital, Chinese Academy of Science, Hefei, China
| | - Hongzhi Wang
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Heath & Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Hefei Cancer Hospital, Chinese Academy of Science, Hefei, China
| | - Lixiang Wang
- Department of Cardiothoracic Surgery, the Second Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Pengcheng Liu
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Hailong Chen
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital, Anhui Medical University, Hefei, China
| | - Bo Hong
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Heath & Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Hefei Cancer Hospital, Chinese Academy of Science, Hefei, China
| | - Dahai Zhao
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital, Anhui Medical University, Hefei, China
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