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Zhang J, Jiang YM, Xu AD, Lin S, Fang N, Wang YL. Characteristics of fibrotic-foci-like lung adenocarcinoma on 18 F-FDG PET/computed tomography and HRCT. Nucl Med Commun 2023; 44:502-508. [PMID: 37036299 DOI: 10.1097/mnm.0000000000001690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2023]
Abstract
PURPOSE To assess the characteristics of fibrotic-foci-like lung adenocarcinoma on 18 F-fluorodeoxyglucose PET/computed tomography ( 18 F-FDG PET/CT) and high-resolution computed tomography (HRCT). MATERIAL AND METHODS This was a retrospective study with 20 cases in the fibrotic-foci-like lung adenocarcinoma group; the control group was old fibrotic-foci of the lung with 20 cases. The following 18 F-FDG PET/CT and HRCT features were evaluated: the maximum standardized uptake value (SUVmax); the tumor-to-background ratios of SUVmax (TBRmax); the long-to-short diameter ratio (L/S); anatomic location; location type; internal characteristics; marginal characteristics and surrounding structures. In the fibrotic-foci-like lung adenocarcinoma group, a comparison of 18 F-FDG uptake between the metastatic group ( n = 10) and the non-metastatic group ( n = 10) was performed. Finally, the comparison of diagnostic accuracy for fibrotic-foci-like lung adenocarcinoma between 18 F-FDG PET/CT and HRCT was performed. RESULTS The SUVmax [2.6 (1.7-7.9) vs. 1.0 (0.7-1.4)], TBRmax [2.9 (2.1-9.9) vs. 1.3 (1.2- 1.7)], L/S [2.4 (1.7-3.8) vs. 4.0 (3.2-6.3)], ground-glass opacity (GGO) [13/20 (65.0%) vs. 4/20 (20.0%)], and vessel convergence [7/20 (35.0%) vs. 1/20 (5.0%)] were found to be statistically significant differences between the fibrotic-foci-like lung adenocarcinoma group and the old fibrotic-foci group ( P < 0.05). SUVmax [7.9 (4.7-8.8) vs. 1.7 (1.2-2.2)] and TBRmax [9.9 (6.5-11.0) vs. 2.1 (1.6-2.9)] were found to be statistically significant differences between the metastatic group and the non-metastatic group ( P < 0.05). 18 F-FDG PET/CT showed the higher diagnostic accuracy for fibrotic-foci-like lung adenocarcinoma than HRCT [95.0% (19/20) vs. 65.0% (13/20), P < 0.05]. CONCLUSION The specific characteristics of fibrotic-foci-like lung adenocarcinoma on 18 F-FDG PET/CT and HRCT were high 18 F-FDG uptake, GGO, and vessel convergence, which could be distinguished from old fibrotic-foci of the lung.
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Affiliation(s)
- Jing Zhang
- Department of PET/CT, The Affiliated Qingdao Central Hospital of Qingdao University, The Second Affiliated Hospital of Medical College of Qingdao University, Shandong Province, China
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Duan M, Song H, Wang C, Zheng J, Xie H, He Y, Huang L, Zhou F. Detection and Independent Validation of Model-Based Quantitative Transcriptional Regulation Relationships Altered in Lung Cancers. Front Bioeng Biotechnol 2020; 8:582. [PMID: 32656193 PMCID: PMC7325891 DOI: 10.3389/fbioe.2020.00582] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 05/13/2020] [Indexed: 12/27/2022] Open
Abstract
Differential expressions of genes are widely evaluated for the diagnosis and prognosis correlations with diseases. But limited studies investigate how transcriptional regulations are quantitatively altered in diseases. This study proposes a novel model-based quantitative measurement of transcriptional regulatory relationships between mRNA genes and Transcription Factor (TF) genes (mqTrans features). This study didn't consider the regulatory relationships between TF genes, so the mRNA genes were the protein-coding genes excluding the TF genes. The models are trained in the control samples in a lung cancer dataset and evaluated in two independent datasets and the hold-out testing samples from the third dataset. Twenty-nine mRNA genes are detected with transcriptional regulations quantitatively altered in lung cancers. The transcriptional modification technologies like RNA interference (RNAi) may be utilized to restore the altered transcriptional regulations in lung cancers.
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Affiliation(s)
- Meiyu Duan
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, China
| | - Haoqiu Song
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, China.,College of Computer Science, Hubei University of Technology, Wuhan, China
| | - Chaoyu Wang
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Software, Jilin University, Changchun, China
| | - Jiaxin Zheng
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Software, Jilin University, Changchun, China
| | - Hui Xie
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, China
| | - Yupeng He
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Software, Jilin University, Changchun, China
| | - Lan Huang
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, China
| | - Fengfeng Zhou
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, China
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Liu SH, Shen PC, Chen CY, Hsu AN, Cho YC, Lai YL, Chen FH, Li CY, Wang SC, Chen M, Chung IF, Cheng WC. DriverDBv3: a multi-omics database for cancer driver gene research. Nucleic Acids Res 2020; 48:D863-D870. [PMID: 31701128 PMCID: PMC7145679 DOI: 10.1093/nar/gkz964] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Revised: 10/09/2019] [Accepted: 11/06/2019] [Indexed: 12/13/2022] Open
Abstract
An integrative multi-omics database is needed urgently, because focusing only on analysis of one-dimensional data falls far short of providing an understanding of cancer. Previously, we presented DriverDB, a cancer driver gene database that applies published bioinformatics algorithms to identify driver genes/mutations. The updated DriverDBv3 database (http://ngs.ym.edu.tw/driverdb) is designed to interpret cancer omics’ sophisticated information with concise data visualization. To offer diverse insights into molecular dysregulation/dysfunction events, we incorporated computational tools to define CNV and methylation drivers. Further, four new features, CNV, Methylation, Survival, and miRNA, allow users to explore the relations from two perspectives in the ‘Cancer’ and ‘Gene’ sections. The ‘Survival’ panel offers not only significant survival genes, but gene pairs synergistic effects determine. A fresh function, ‘Survival Analysis’ in ‘Customized-analysis,’ allows users to investigate the co-occurring events in user-defined gene(s) by mutation status or by expression in a specific patient group. Moreover, we redesigned the web interface and provided interactive figures to interpret cancer omics’ sophisticated information, and also constructed a Summary panel in the ‘Cancer’ and ‘Gene’ sections to visualize the features on multi-omics levels concisely. DriverDBv3 seeks to improve the study of integrative cancer omics data by identifying driver genes and contributes to cancer biology.
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Affiliation(s)
- Shu-Hsuan Liu
- Graduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan
| | - Pei-Chun Shen
- Graduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan
| | - Chen-Yang Chen
- Cytoaurora Biotechnologies, Inc. Hsinchu Science Park, Hsinchu 30261, Taiwan
| | - An-Ni Hsu
- Graduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan
| | - Yi-Chun Cho
- Graduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan
| | - Yo-Liang Lai
- Graduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan.,Department of Radiation Oncology, China Medical University Hospital, Taichung 40403, Taiwan
| | - Fang-Hsin Chen
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan.,Department of Radiation Oncology, Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan.,Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan 33302, Taiwan
| | - Chia-Yang Li
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Shu-Chi Wang
- Department of Medical Laboratory Science and Biotechnology, College of Health Sciences, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Ming Chen
- Center for Medical Genetics, Changhua Christian Hospital, Changhua 50006, Taiwan
| | - I-Fang Chung
- Institute of BioMedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan
| | - Wei-Chung Cheng
- Graduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan.,Research Center for Tumor Medical Science, China Medical University, Taichung 40403, Taiwan
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Xu J, Zhang S, Zhang W, Xie E, Gu M, Wang Y, Yang L, Zhang B, Zhang J, Gu C, Xu T, Li D, Wang F, Huang P, Pan S. SP70-Targeted Imaging for the Early Detection of Lung Adenocarcinoma. Sci Rep 2020; 10:2509. [PMID: 32054922 PMCID: PMC7018733 DOI: 10.1038/s41598-020-59439-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 01/27/2020] [Indexed: 12/12/2022] Open
Abstract
NJ001 is a monoclonal antibody that can specifically recognize the SP70 antigen on lung adenocarcinoma cells. The goal of this study was to explore its utility in targeted imaging. Subcutaneous xenograft and orthotopic lung tumor implantation BALB/c mouse models were established. Near-infrared fluorescent CF750-labeled NJ001 was injected into two tumor mouse models. Mice that received orthotopic lung tumor implantation were also injected with NJ001-conjugated nanomagnetic beads intravenously, and then underwent micro-CT scanning. Meanwhile, mice with lung tumor were intravenously injected with normal saline and bare nanomagnetic beads as a control. Fluorescence could be monitored in the mice detected by anti-SP70 fluorescence imaging, which was consistent with tumor burden. Signal intensities detected with SP70-targeted micro-CT scans were greater than those in control mice. More importantly, orthotopic tumor lesions could be found on the fourth week with SP70-targeted imaging, which was 2 weeks earlier than detection in the control. Our results suggest that SP70 is a promising target for molecular imaging, and molecularly targeted imaging with an NJ001-labeled probe could be applied for the early detection of lung adenocarcinoma.
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Affiliation(s)
- Jian Xu
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Shichang Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Wei Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Erfu Xie
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Min Gu
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Yue Wang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Lu Yang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Bingfeng Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Jiexin Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Chunrong Gu
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Ting Xu
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Daqian Li
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Fang Wang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Peijun Huang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China
| | - Shiyang Pan
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), Nanjing, China.
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Amjadi M, Mohammadi Khoshraj J, Majidi MR, Baradaran B, de la Guardia M. Evaluation of Flavonoid Derivative and Doxorubicin Effects in Lung Cancer Cells (A549) Using Differential Pulse Voltammetry Method. Adv Pharm Bull 2018; 8:637-642. [PMID: 30607336 PMCID: PMC6311643 DOI: 10.15171/apb.2018.072] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 07/21/2018] [Accepted: 08/15/2018] [Indexed: 12/14/2022] Open
Abstract
Purpose: Electrochemical measurements have prompted the progress as a consequence of their affectability, cost-affectivity and comparatively short examination time. The aim of this study was the fast evaluation of the effect of chemotherapy compounds on the viability of lung cancer cells (A549) via electrochemical methods. Methods: Cyclic voltammetry (CV) was used as a primary method to distinguish between electrochemical behavior of normal and lung cancer cells. Differential pulse voltammetry (DPV) was employed as a complementary analyses method for the impact of doxorubicin (DOX) and Flavonoid modified drug (FMD) (US patent Application number: 62548886) on Lung cancer cells. Results: Only one oxidative peak, at approximately -0.15 V was detected through DPV method in cancer cell line. While a significant distinguish was not seen in CV. The current intensity (I) was decreased in cancer cells with increasing the DOX and FMD levels (t=99.027, α=0.05, P=0.0000), (t=135.513, α=0.05, P=0.0000), respectively. Conclusion: The movement of cancerous cells towards death through chemotherapy drugs such as DOX and FMD can make distinct and significant changes in the electrochemical behaviors of those cells.
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Affiliation(s)
- Mohammad Amjadi
- Department of Analytical Chemistry, Chemistry Faculty, Tabriz University, Tabriz, Iran
| | | | - Mir Reza Majidi
- Department of Analytical Chemistry, Chemistry Faculty, Tabriz University, Tabriz, Iran
| | - Behzad Baradaran
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
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A novel stereotactic frame for real PET-guided biopsies: A preclinical proof-of-concept. Phys Med 2017; 41:124-128. [DOI: 10.1016/j.ejmp.2017.05.047] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 05/03/2017] [Accepted: 05/04/2017] [Indexed: 12/25/2022] Open
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7
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Jiao Y, Ren Y, Zheng X. [Quantitative Imaging Assessment of Tumor Response to Chemoradiation
in Lung Cancer]. ZHONGGUO FEI AI ZA ZHI = CHINESE JOURNAL OF LUNG CANCER 2017. [PMID: 28641699 PMCID: PMC5973359 DOI: 10.3779/j.issn.1009-3419.2017.06.07] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
精准医疗的实施要求及时准确地对治疗疗效进行评估,以便于治疗方案的调整和优化,从而进一步提高疗效,改善预后。以定量评估为基础的影像组学以其无创、直观和可重复的特点在临床疗效评估方面具有不可替代的作用。本文将综述定量影像学在肺癌放化疗疗效评估中的应用现状及其相关进展。
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Affiliation(s)
- Yuxin Jiao
- Department of Radiology Oncology;Department of Radiology, Fudan University Huadong Hospital, Shanghai 200040, China
| | - Yanping Ren
- Department of Radiology Oncology, Fudan University Huadong Hospital, Shanghai 200040, China
| | - Xiangpeng Zheng
- Department of Radiology Oncology;Zhang Guozhen Diagnosis and Treatment Center of Micronodular Lung Cancer (DTC-MLC), Fudan University Huadong Hospital, Shanghai 200040, China
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8
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Zhong H, Xuan L, Wang D, Zhou J, Li Y, Jiang Q. Generation of a co-culture cell micropattern model to simulate lung cancer bone metastasis for anti-cancer drug evaluation. RSC Adv 2017. [DOI: 10.1039/c7ra01868a] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
A549/OB co-culture micropattern was fabricated through μ-eraser strategy to mimic lung cancer bone metastasis for DOX efficacy evaluation.
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Affiliation(s)
- Huixiang Zhong
- Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument
- Department of Biomedical Engineering
- School of Engineering
- Sun Yat-sen University
- Guangzhou
| | - Liuyang Xuan
- Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument
- Department of Biomedical Engineering
- School of Engineering
- Sun Yat-sen University
- Guangzhou
| | - Dandan Wang
- Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument
- Department of Biomedical Engineering
- School of Engineering
- Sun Yat-sen University
- Guangzhou
| | - Jianhua Zhou
- Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument
- Department of Biomedical Engineering
- School of Engineering
- Sun Yat-sen University
- Guangzhou
| | - Yan Li
- Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument
- Department of Biomedical Engineering
- School of Engineering
- Sun Yat-sen University
- Guangzhou
| | - Qing Jiang
- Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument
- Department of Biomedical Engineering
- School of Engineering
- Sun Yat-sen University
- Guangzhou
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