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Yang Q, Huang D, Wu J, Zhong H, Han Y, Jiang H, Chen Y, Chen G, Zhan X, Zhou P. Performance of [ 18F]FDG PET/CT versus FAPI PET/CT for lung cancer assessment: a systematic review and meta-analysis. Eur Radiol 2024; 34:1077-1085. [PMID: 37589901 DOI: 10.1007/s00330-023-10013-7] [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: 01/31/2023] [Revised: 05/08/2023] [Accepted: 06/11/2023] [Indexed: 08/18/2023]
Abstract
PURPOSE This article aims to compare the diagnostic performance of 18-fluorodeoxyglucose ([18F]FDG) PET/CT and fibroblast activating protein inhibitor (FAPI) PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer patients. METHODS A systematic search was conducted on the Cochrane Library, Embase, and PubMed/MEDLINE databases from inception until November 1, 2022. Included studies assessed the use of FAPI PET/CT and [18F]FDG PET/CT in patients with lung cancer. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to evaluate the risk of bias. A random variable model was used to analyze the diagnostic tests of the two imaging modalities. RESULTS The sensitivity of FAPI PET/CT in detecting primary lung cancer lesions was 0.98 (95% CI: 0.88-1.00), while the sensitivity of [18F]FDG PET/CT was 0.99 (95% CI: 0.74-1.00). For the detection of metastatic lesions (lymph node metastases and distant metastases), FAPI PET/CT had a sensitivity of 0.99 (95% CI: 0.90-1.00), while the sensitivity of [18F]FDG PET/CT was 0.77 (95% CI: 0.66-0.85). However, the specificity of the two imaging modalities could not be assessed due to the lack of sufficient information on pertinent true negatives. CONCLUSION In the diagnosis of metastatic lung cancer lesions, FAPI PET/CT demonstrated a higher sensitivity compared to [18F]FDG PET/CT. Therefore, FAPI PET/CT may be considered an alternative imaging modality for the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases. CLINICAL RELEVANCE STATEMENT FAPI may be an alternative to [18F]FDG in the assessment of primary lung cancer tumors, lymph node metastases, and distant metastases, which plays a very important role in treatment. KEY POINTS • This article is to compare the performance of [18F]FDG PET/CT with FAPI PET/CT in the assessment of primary tumors, lymph nodes, and distant metastases in lung cancer. • However, FAPI PET/CT has a higher sensitivity for the diagnostic assessment of metastatic lung cancer lesions.
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Affiliation(s)
- Qiuya Yang
- Southwest Medical University, Luzhou, Sichuan, China
| | - Delong Huang
- Southwest Medical University, Luzhou, Sichuan, China
| | - Junhao Wu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Haoshu Zhong
- Department of Hematology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - YuanHang Han
- Southwest Medical University, Luzhou, Sichuan, China
| | - Haodong Jiang
- Southwest Medical University, Luzhou, Sichuan, China
| | - Yue Chen
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, Sichuan, China
- Institute of Nuclear Medicine, Southwest Medical University, Luzhou, Sichuan, China
| | - Gong Chen
- Chengdu Sport University, Chengdu, Sichuan, China
| | - Xiang Zhan
- Department of Radiology, The Affiliated Hospital of Southwest Medical University, No.25, Taiping St, Luzhou, 646000, Sichuan, China
| | - Ping Zhou
- Department of Radiology, The Affiliated Hospital of Southwest Medical University, No.25, Taiping St, Luzhou, 646000, Sichuan, China.
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Predictive value of intratumor metabolic and heterogeneity parameters on [ 18F]FDG PET/CT for EGFR mutations in patients with lung adenocarcinoma. Jpn J Radiol 2023; 41:209-218. [PMID: 36219311 DOI: 10.1007/s11604-022-01347-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 09/30/2022] [Indexed: 02/03/2023]
Abstract
PURPOSE This study aimed to investigate the value of metabolic and heterogeneity parameters of 2-deoxy-2[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) in predicting epidermal growth factor receptor (EGFR) mutations in patients with lung adenocarcinoma (ADC). MATERIALS AND METHODS A retrospective analysis was performed on 157 patients with lung ADC between September 2015 and June 2021, who had undergone both EGFR mutation testing and [18F]FDG PET/CT examination. Metabolic and heterogeneity parameters were measured and calculated, including maximum diameter (Dmax), maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneity factor (HF). Relationships between PET/CT parameters and EGFR mutation status were evaluated and a multivariate logistic regression analysis was analyzed to establish a combined prediction model. RESULTS 108 (68.8%) patients exhibited EGFR mutations. EGFR mutations were more likely to occur in females (51.9% vs. 48.1%, P = 0.007), non-smokers (83.3% vs. 16.7%, P < 0.001) and right lobes (55.6% vs. 44.4%, P = 0.017). High Dmax, MTV and HF and low SUVmean were significantly correlated with EGFR mutations, and the areas under the ROC curve (AUCs) measuring 0.647, 0.701, 0.757, and 0.661, respectively. Multivariate logistic regression analysis suggested that non-smokers (OR = 0.30, P = 0.034), low SUVmean (≤ 7.75, OR = 0.63, P < 0.001) and high HF (≥ 4.21, OR = 1.80, P = 0.027) were independent predictors of EGFR mutations. The AUC of the combined prediction model measured up to 0.863, significantly higher than that of a single parameter. CONCLUSIONS EGFR mutant in lung ADC patients showed more intratumor heterogeneity (HF) than EGFR wild type, which was combined clinical feature (non-smokers), and metabolic parameter (SUVmean) may be helpful in predicting EGFR mutation status, thus playing a guiding role in EGFR-tyrosine kinase inhibitors (EGFR-TKIs) targeted therapies.
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Aide N, Weyts K, Lasnon C. Prediction of the Presence of Targetable Molecular Alteration(s) with Clinico-Metabolic 18 F-FDG PET Radiomics in Non-Asian Lung Adenocarcinoma Patients. Diagnostics (Basel) 2022; 12:diagnostics12102448. [PMID: 36292136 PMCID: PMC9601118 DOI: 10.3390/diagnostics12102448] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 09/30/2022] [Accepted: 10/07/2022] [Indexed: 11/16/2022] Open
Abstract
This study aimed to investigate if combining clinical characteristics with pre-therapeutic 18 F-fluorodeoxyglucose (18 F-FDG) positron emission tomography (PET) radiomics could predict the presence of molecular alteration(s) in key molecular targets in lung adenocarcinoma. This non-interventional monocentric study included patients with newly diagnosed lung adenocarcinoma referred for baseline PET who had tumour molecular analyses. The data were randomly split into training and test datasets. LASSO regression with 100-fold cross-validation was performed, including sex, age, smoking history, AJCC cancer stage and 31 PET variables. In total, 109 patients were analysed, and it was found that 63 (57.8%) patients had at least one molecular alteration. Using the training dataset (n = 87), the model included 10 variables, namely age, sex, smoking history, AJCC stage, excessKustosis_HISTO, sphericity_SHAPE, variance_GLCM, correlation_GLCM, LZE_GLZLM, and GLNU_GLZLM. The ROC analysis for molecular alteration prediction using this model found an AUC equal to 0.866 (p < 0.0001). A cut-off value set to 0.48 led to a sensitivity of 90.6% and a positive likelihood ratio (LR+) value equal to 2.4. After application of this cut-off value in the unseen test dataset of patients (n = 22), the test presented a sensitivity equal to 90.0% and an LR+ value of 1.35. A clinico-metabolic 18 F-FDG PET phenotype allows the detection of key molecular target alterations with high sensitivity and negative predictive value. Hence, it opens the way to the selection of patients for molecular analysis.
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Affiliation(s)
- Nicolas Aide
- UNICAEN, INSERM 1086 ANTICIPE, Normandy University, 14000 Caen, France
| | - Kathleen Weyts
- Nuclear Medicine Department, Comprehensive Cancer Centre F. Baclesse, UNICANCER, 14000 Caen, France
| | - Charline Lasnon
- UNICAEN, INSERM 1086 ANTICIPE, Normandy University, 14000 Caen, France
- Nuclear Medicine Department, Comprehensive Cancer Centre F. Baclesse, UNICANCER, 14000 Caen, France
- Correspondence: ; Tel.: +33-261-455-268; Fax: +33-231-455-101
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Hu N, Yan G, Wu Y, Wang L, Wang Y, Xiang Y, Lei P, Luo P. Recent and current advances in PET/CT imaging in the field of predicting epidermal growth factor receptor mutations in non-small cell lung cancer. Front Oncol 2022; 12:879341. [PMID: 36276079 PMCID: PMC9582655 DOI: 10.3389/fonc.2022.879341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 09/20/2022] [Indexed: 11/05/2022] Open
Abstract
Tyrosine kinase inhibitors (TKIs) are a significant treatment strategy for the management of non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutation status. Currently, EGFR mutation status is established based on tumor tissue acquired by biopsy or resection, so there is a compelling need to develop non-invasive, rapid, and accurate gene mutation detection methods. Non-invasive molecular imaging, such as positron emission tomography/computed tomography (PET/CT), has been widely applied to obtain the tumor molecular and genomic features for NSCLC treatment. Recent studies have shown that PET/CT can precisely quantify EGFR mutation status in NSCLC patients for precision therapy. This review article discusses PET/CT advances in predicting EGFR mutation status in NSCLC and their clinical usefulness.
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Affiliation(s)
- Na Hu
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Gang Yan
- Department of Nuclear Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Yuhui Wu
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Li Wang
- School of Nursing, Guizhou Medical University, Guiyang, China
| | - Yang Wang
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Yining Xiang
- Department of Pathology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Pinggui Lei
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China,School of Public Health, Guizhou Medical University, Guiyang, China,*Correspondence: Pinggui Lei, ; Peng Luo,
| | - Peng Luo
- School of Public Health, Guizhou Medical University, Guiyang, China,*Correspondence: Pinggui Lei, ; Peng Luo,
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Agüloğlu N, Aksu A, Akyol M, Katgı N, Doksöz TÇ. IMPORTANCE of PRETREATMENT 18F-FDG PET/CT TEXTURE ANALYSIS in PREDICTING EGFR and ALK MUTATION in PATIENTS with NON-SMALL CELL LUNG CANCER. Nuklearmedizin 2022; 61:433-439. [PMID: 35977671 DOI: 10.1055/a-1868-4918] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Abstract
OBJECTIVE Identification of anaplastic lymphoma kinase (ALK) and epidermal growth factor receptor (EGFR) mutation types is of great importance before treatment with tyrosine kinase inhibitors (TKIs). Radiomics is a new strategy for noninvasively predicting the genetic status of cancer. We aimed to evaluate the predictive power of 18F-FDG PET/CT-based radiomic features for mutational status before treatment in non-small cell lung cancer (NSCLC) and to develop a predictive model based on radiomic features. METHODS Images of patients who underwent 18F-FDG PET/CT for initial staging with the diagnosis of NSCLC between January 2015 and July 2020 were evaluated using LIFEx software. The region of interest (ROI) of the primary tumor was established and volumetric and textural features were obtained. Clinical data and radiomic data were evaluated with machine learning (ML) algorithms to create a model. RESULTS For EGFR mutation prediction, the most successful machine learning algorithm obtained with GLZLM_GLNU and clinical data was Naive Bayes (AUC: 0.751, MCC: 0.347, acc: 71.4%). For ALK rearrangement prediction, the most successful machine learning algorithm obtained with GLCM_correlation, GLZLM_LZHGE and clinical data was evaluated as Naive Bayes (AUC: 0.682, MCC: 0.221, acc: 77.4%). CONCLUSIONS In our study, we created prediction models based on radiomic analysis of 18F-FDG PET/CT images. Tissue analysis with ML algorithms are non-invasive methods for predicting ALK rearrangement and EGFR mutation status in NSCLC, which may be useful for targeted therapy selection in a clinical setting.
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Affiliation(s)
| | - Ayşegül Aksu
- Bahçeşehir Çam ve Sakura Hastanesi, İstanbul, Turkey
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Wu J, Deng H, Zhong H, Wang T, Rao Z, Wang Y, Chen Y, Zhang C. Comparison of 68Ga-FAPI and 18F-FDG PET/CT in the Evaluation of Patients With Newly Diagnosed Non-Small Cell Lung Cancer. Front Oncol 2022; 12:924223. [PMID: 35860594 PMCID: PMC9289292 DOI: 10.3389/fonc.2022.924223] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/03/2022] [Indexed: 12/11/2022] Open
Abstract
Purpose Several studies have demonstrated that 68Ga-FAPI PET/CT shows high intratumoral tracer uptake and low normal tissue uptake, allowing for excellent visualization of cancer. The purpose of this study was to compare the ability of 68Ga-FAPI and 18F-FDG PET/CT for the evaluation of newly diagnosed NSCLC. Materials and Methods A prospective analysis of 28 individuals with histopathologically newly confirmed NSCLC that underwent 68Ga-FAPI and 18F-FDG PET/CT was conducted. The performance of two imaging modalities was compared based upon visual assessment, rates of cancer detection, and semi-quantitative parameters (target-to-background ratio [TBR], maximum standard uptake value [SUVmax]) for both primary tumors and metastases. Results In total, this study enrolled 28 participants (13 male, 15 female; median age: 60.5 years, range: 34 – 78 years. <u>For primary tumors, 68Ga-FAPI and 18F-FDG PET/CT have similar detection performance (28 vs. 27). However, 68Ga-FAPI PET/CT was found to more effectively evaluate most metastases as compared to 18F-FDG PET/CT. 68Ga-FAPI PET/CT detecting more metastases present within the lymph nodes (53 vs. 49), pleura (8 vs. 7), liver (4 vs. 1), and bone (41 vs. 35).</u> The SUVmax and TBR values for 68Ga-FAPI were substantially superior to those for 18F-FDG in lymph node, pleural, and bone metastases. While the SUVmax for these two imaging approaches was comparable for hepatic metastases, 68Ga-FAPI exhibited a significantly higher TBR in relation to that of 18F-FDG. In addition, 68Ga-FAPI PET/CT demonstrates excellent N (80% [8/10]) and M (92.9% [26/28]) staging accuracy in NSCLC patients. Conclusions 68Ga-FAPI PET/CT as an examination modality is excellent for evaluation of newly diagnosed NSCLC. 68Ga-FAPI PET/CT improves the detection rates of most metastases and facilitating the superior staging of patients with newly diagnosed NSCLC, relative to that achieved by 18F-FDG PET/CT.
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Affiliation(s)
- Junhao Wu
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Hao Deng
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Haoshu Zhong
- Department of Hematology, Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
- Stem Cell Laboratory, The Clinical Research Institute, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Tao Wang
- Department of the General Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Zijuan Rao
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Yingwei Wang
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Yue Chen
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Chunyin Zhang
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
- *Correspondence: Chunyin Zhang,
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Predictive value of multiple metabolic and heterogeneity parameters of 18F-FDG PET/CT for EGFR mutations in non-small cell lung cancer. Ann Nucl Med 2022; 36:393-400. [PMID: 35084711 DOI: 10.1007/s12149-022-01718-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 01/10/2022] [Indexed: 11/01/2022]
Abstract
OBJECTIVES To explore the value of multiple metabolic and heterogeneity parameters of 2-deoxy-2-[fluorine-18] fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting epidermal growth factor receptor gene (EGFR) mutations in non-small cell lung cancer (NSCLC). MATERIALS AND METHODS A retrospective analysis was performed by reviewing 98 patients with NSCLC who underwent EGFR mutation testing and 18F-FDG PET/CT examination in our hospital between March 2016 and March 2021. Patients were divided into an EGFR-mutant group and a wild-type group. A multivariate logistic regression analysis was performed to screen and construct a prediction model. The diagnostic performance of the model was evaluated using a receiver-operating characteristic (ROC) curve. RESULTS The study found that EGFR mutations were more likely to occur in women, non-smokers, and patients with peripheral lesions, shorter maximum tumor diameter, adenocarcinoma, and T1 stage cancer. Low maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, total lesion glycolysis, and high coefficient of variation (COV) were significantly correlated with EGFR mutations, and the area under the ROC curve (AUC) was 0.622, 0.638, 0.679, 0.687, and 0.672, respectively. Multivariate logistic regression analysis indicated that non-smokers (odds ratio (OR) = 0.109, P = 0.014), peripheral lesions (OR = 6.917, P = 0.022), low SUVmax (≤ 7.85, OR = 5.471, P = 0.001), SUVmean (≤ 5.34, OR = 0.044, P = 0.000), and high COV (≥ 106.08, OR = 0.996, P = 0.045) were independent predictors of EGFR mutations. The AUC of the prediction model established by combining the above factors was 0.926; the diagnostic efficiency was significantly higher than that of a single parameter. CONCLUSION Among the metabolic and heterogeneity parameters of 18F-FDG PET/CT, low SUVmax, SUVmean, and high COV were significantly associated with EGFR mutations, and the predictive value of EGFR mutations could be enhanced when combined with clinicopathological features.
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Bu L, Tu N, Wang K, Zhou Y, Xie X, Han X, Lin H, Feng H. Relationship between 18F-FDG PET/CT Semi-Quantitative Parameters and International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society Classification in Lung Adenocarcinomas. Korean J Radiol 2022; 23:112-123. [PMID: 34983098 PMCID: PMC8743143 DOI: 10.3348/kjr.2021.0455] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 08/30/2021] [Accepted: 09/26/2021] [Indexed: 12/24/2022] Open
Abstract
Objective To investigate the relationship between 18F-FDG PET/CT semi-quantitative parameters and the International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) histopathologic classification, including histological subtypes, proliferation activity, and somatic mutations. Materials and Methods This retrospective study included 419 patients (150 males, 269 females; median age, 59.0 years; age range, 23.0–84.0 years) who had undergone surgical removal of stage IA–IIIA lung adenocarcinoma and had preoperative PET/CT data of lung tumors. The maximum standardized uptake values (SUVmax), background-subtracted volume (BSV), and background-subtracted lesion activity (BSL) derived from PET/CT were measured. The IASLC/ATS/ERS subtypes, Ki67 score, and epidermal growth factor/anaplastic lymphoma kinase (EGFR/ALK) mutation status were evaluated. The PET/CT semi-quantitative parameters were compared between the tumor subtypes using the Mann–Whitney U test or the Kruskal–Wallis test. The optimum cutoff values of the PET/CT semi-quantitative parameters for distinguishing the IASLC/ATS/ERS subtypes were calculated using receiver operating characteristic curve analysis. The correlation between the PET/CT semi-quantitative parameters and pathological parameters was analyzed using Spearman’s correlation. Statistical significance was set at p < 0.05. Results SUVmax, BSV, and BSL values were significantly higher in invasive adenocarcinoma (IA) than in minimally IA (MIA), and the values were higher in MIA than in adenocarcinoma in situ (AIS) (all p < 0.05). Remarkably, an SUVmax of 0.90 and a BSL of 3.62 were shown to be the optimal cutoff values for differentiating MIA from AIS, manifesting as pure ground-glass nodules with 100% sensitivity and specificity. Metabolic-volumetric parameters (BSV and BSL) were better potential independent factors than metabolic parameters (SUVmax) in differentiating growth patterns. SUVmax and BSL, rather than BSV, were strongly or moderately correlated with Ki67 in most subtypes, except for the micropapillary and solid predominant groups. PET/CT parameters were not correlated with EGFR/ALK mutation status. Conclusion As noninvasive surrogates, preoperative PET/CT semi-quantitative parameters could imply IASLC/ATS/ERS subtypes and Ki67 index and thus may contribute to improved management of precise surgery and postoperative adjuvant therapy.
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Affiliation(s)
- Lihong Bu
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ning Tu
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ke Wang
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ying Zhou
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xinli Xie
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xingmin Han
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huiqin Lin
- Department of Thoracic Surgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Hongyan Feng
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China.
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Du B, Wang S, Cui Y, Liu G, Li X, Li Y. Can 18F-FDG PET/CT predict EGFR status in patients with non-small cell lung cancer? A systematic review and meta-analysis. BMJ Open 2021; 11:e044313. [PMID: 34103313 PMCID: PMC8190055 DOI: 10.1136/bmjopen-2020-044313] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
OBJECTIVES This study aimed to explore the diagnostic significance of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/CT for predicting the presence of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC). DESIGN A systematic review and meta-analysis. DATA SOURCES The PubMed, EMBASE and Cochrane library databases were searched from the earliest available date to December 2020. ELIGIBILITY CRITERIA FOR SELECTING STUDIES The review included primary studies that compared the mean maximum of standard uptake value (SUVmax) between wild-type and mutant EGFR, and evaluated the diagnostic value of 18F-FDG PET/CT using SUVmax for prediction of EGFR status in patients with NSCLC. DATA EXTRACTION AND SYNTHESIS The main analysis was to assess the sensitivity and specificity, the positive diagnostic likelihood ratio (DLR+) and DLR-, as well as the diagnostic OR (DOR) of SUVmax in prediction of EGFR mutations. Each data point of the summary receiver operator characteristic (SROC) graph was derived from a separate study. A random effects model was used for statistical analysis of the data, and then diagnostic performance for prediction was further assessed. RESULTS Across 15 studies (3574 patients), the pooled sensitivity for 18F-FDG PET/CT was 0.70 (95% CI 0.60 to 0.79) with a pooled specificity of 0.59 (95% CI 0.52 to 0.66). The overall DLR+ was 1.74 (95% CI 1.49 to 2.03) and DLR- was 0.50 (95% CI 0.38 to 0.65). The pooled DOR was 3.50 (95% CI 2.37 to 5.17). The area under the SROC curve was 0.68 (95% CI 0.64 to 0.72). The likelihood ratio scatter plot based on average sensitivity and specificity was in the lower right quadrant. CONCLUSION Meta-analysis results showed 18F-FDG PET/CT had low pooled sensitivity and specificity. The low DOR and the likelihood ratio scatter plot indicated that 18F-FDG PET/CT should be used with caution when predicting EGFR mutations in patients with NSCLC.
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Affiliation(s)
- Bulin Du
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Shu Wang
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Yan Cui
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Guanghui Liu
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Xuena Li
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
| | - Yaming Li
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, China
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Guo Y, Zhu H, Yao Z, Liu F, Yang D. The diagnostic and predictive efficacy of 18F-FDG PET/CT metabolic parameters for EGFR mutation status in non-small-cell lung cancer: A meta-analysis. Eur J Radiol 2021; 141:109792. [PMID: 34062472 DOI: 10.1016/j.ejrad.2021.109792] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 05/19/2021] [Accepted: 05/21/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE To investigate the predictive performance of the maximum standardized uptake value (SUVmax) and mean standardized uptake value (SUVmean) of primary lesions based on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for EGFR mutation status in patients with non-small cell lung cancer (NSCLC). METHODS The PubMed/Medline, Embase, Cochrane Library and Web of Science databases were searched as of January 1, 2021. Studies whose reported data could be used to construct contingency tables were included. Study characteristics were extracted, and methodological quality assessment was conducted by two separate reviewers using the Quality Assessment of Diagnostic Accuracy Studies. The pooled sensitivity, specificity and area under the summary receiver operating characteristic curve (AUROC) were calculated. The possible causes of heterogeneity were analysed by meta-regression. RESULTS The 18 included studies had a total of 4024 patients. The majority of the studies showed a low to unclear risk of bias and concerns of applicability. For differentiating EGFR-mutant NSCLC from wild-type NSCLC, the pooled sensitivity and specificity were 71 % and 60 % for SUVmax and 64 % and 63 % for SUVmean, respectively. The summary AUROCs of SUVmax and SUVmean were 0.69 (95 % CI, 0.65-0.73) and 0.68 (95 % CI, 0.64-0.72), respectively. The meta-regression analysis indicated that blindness to EGFR mutation test results, the number of readers and the number of PET/CT scanners were possible causes of heterogeneity. CONCLUSIONS Our meta-analysis implied that SUVmax and SUVmean of primary lesions from 18F-FDG PET/CT harboured moderate predictive efficacy for the EGFR mutation status of NSCLC.
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Affiliation(s)
- Yue Guo
- Department of Nuclear Medicine, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
| | - Hui Zhu
- Department of Nuclear Medicine, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
| | - Zhiming Yao
- Department of Nuclear Medicine, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
| | - Fugeng Liu
- Department of Nuclear Medicine, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730, PR China.
| | - Dawei Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No.95 Yongan Road, West District, Beijing 100050, PR China.
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11
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Wang Y, Han R, Wang Q, Zheng J, Lin C, Lu C, Li L, Chen H, Jin R, He Y. Biological Significance of 18F-FDG PET/CT Maximum Standard Uptake Value for Predicting EGFR Mutation Status in Non-Small Cell Lung Cancer Patients. Int J Gen Med 2021; 14:347-356. [PMID: 33568935 PMCID: PMC7868188 DOI: 10.2147/ijgm.s287506] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 12/31/2020] [Indexed: 12/27/2022] Open
Abstract
Purpose To investigate the potential of maximum standardized uptake value (SUVmax) in predicting epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients. Methods Clinical data of 311 NSCLC patients who had undergone both EGFR mutation test and 18F-FDG PET/CT scans between January 2013 and December 2017 at our hospital were retrospectively analyzed. Patients were sub-grouped by their origin of SUVmax. Univariate and multivariate analyses were performed to investigate the association between clinical factors and EGFR mutations. Receiver operating characteristic curve (ROC) analysis was performed to confirm the predictive value of clinical factors. In vitro experiments were performed to confirm the correlation between EGFR mutations and glycolysis. Results EGFR-mutant patients had higher SUVmax than the wild-type patients in both primary tumors and metastases. In the multivariate analysis, SUVmax, gender and histopathologic type were determined as independent predictors of EGFR mutation status for patients whose SUVmax were obtained from the primary tumors; while for patients whose SUVmax were obtained from the metastases, SUVmax, smoking status and histopathologic type were regarded as independent predictors. ROC analysis showed that SUVmax of the primary tumors (cut off >10.92), not of the metastases, has better predictive value than other clinical factors in predicting EGFR mutation status. The predict performance was improved after combined SUVmax with other independent predictors. In addition, our in vitro experiments demonstrated that lung cancer cells with EGFR mutations have higher aerobic glycolysis level than wild-type cells. Conclusion SUVmax of the primary tumors has the potential to serve as a biomarker to predict EGFR mutation status in NSCLC patients.
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Affiliation(s)
- Yubo Wang
- Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Rui Han
- Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Qiushi Wang
- Department of Pathology, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Jie Zheng
- Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Caiyu Lin
- Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Conghua Lu
- Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Li Li
- Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Hengyi Chen
- Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Rongbing Jin
- Department of Nuclear Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Yong He
- Department of Respiratory Medicine, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
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12
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Hong IK, Lee JM, Hwang IK, Paik SS, Kim C, Lee SH. Diagnostic and Predictive Values of 18F-FDG PET/CT Metabolic Parameters in EGFR-Mutated Advanced Lung Adenocarcinoma. Cancer Manag Res 2020; 12:6453-6465. [PMID: 32801885 PMCID: PMC7396957 DOI: 10.2147/cmar.s259055] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 07/16/2020] [Indexed: 12/23/2022] Open
Abstract
Purpose The clinical implications of the metabolic parameters of 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) in epidermal growth factor receptor (EGFR)-mutated lung cancer are not fully understood. The aim of this study was to evaluate the diagnostic and prognostic utility of the parameters in EGFR-mutated lung cancer patients. Patients and Methods We retrospectively enrolled 134 patients with advanced lung adenocarcinoma (72 EGFR-negative and 62 EGFR-positive). We evaluated the correlation between EGFR mutational status and the maximum standardized uptake value (SUVmax), as well as the associations between treatment outcomes in EGFR-mutated patients and various metabolic parameters of primary tumors. For the best predictive parameters, we calculated the metabolic tumor volume (MTV) and total lesion glycolysis (TLG) using two SUV cutoffs: 1.5 (MTV1.5, TLG1.5) and 2.5 (MTV2.5, TLG2.5). Results Mean SUVmax was lower for EGFR-mutated tumors compared with EGFR wild-type (6.11 vs 10.41, p < 0.001) tumors. Low SUVmax was significantly associated with positive EGFR mutation (odds ratio = 1.74). Multivariate analysis for survival demonstrated that high MTV1.5, TLG1.5, MTV2.5, and TLG2.5 were independently associated with shorter progression-free survival (PFS) and overall survival (OS), and the highest hazard ratios were found in TLG1.5 (3.26 for PFS and 4.62 for OS). Conclusion SUVmax may be predictive for EGFR mutational status, and MTV and TLG of primary tumors may be promising prognostic parameters; 18F-FDG PET/CT has potential utility for the risk stratification of EGFR-mutated patients treated with targeted therapy.
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Affiliation(s)
- Il Ki Hong
- Department of Nuclear Medicine, Kyung Hee University Medical Center, Kyung Hee University School of Medicine, Seoul, South Korea
| | - Jeong Mi Lee
- Department of Internal Medicine, Graduate School, Kyung Hee University, Seoul, South Korea
| | - In Kyoung Hwang
- Department of Internal Medicine, Graduate School, Kyung Hee University, Seoul, South Korea
| | - Seung Sook Paik
- Department of Internal Medicine, Graduate School, Kyung Hee University, Seoul, South Korea
| | - Chanwoo Kim
- Department of Nuclear Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, Seoul, South Korea
| | - Seung Hyeun Lee
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Kyung Hee University Medical Center, Kyung Hee University School of Medicine, Seoul, South Korea
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13
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Yao G, Zhou Y, Gu Y, Wang Z, Yang M, Sun J, Luo Q, Zhao H. Value of combining PET/CT and clinicopathological features in predicting EGFR mutation in Lung Adenocarcinoma with Bone Metastasis. J Cancer 2020; 11:5511-5517. [PMID: 32742498 PMCID: PMC7391209 DOI: 10.7150/jca.46414] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 06/29/2020] [Indexed: 12/22/2022] Open
Abstract
Purpose: Epidermal growth factor receptor (EGFR) mutation is the most common target for precision treatment in metastatic lung adenocarcinoma. We investigated the predictive role of 18F-FDG PET/CT and clinicopathological features for EGFR mutations in lung adenocarcinoma with bone metastasis. Methods: Seventy-five lung adenocarcinoma patients with histologically confirmed bone metastasis were included. They all received EGFR status test and PET/CT before systemic treatment. The differences of maximum standardized uptake value (SUVmax) in primary tumor (pSUVmax), regional lymph node (nSUVmax) and bone metastasis (bmSUVmax) between different EGFR status groups were compared, alongside with common clinicopathological features. Multivariate logistic regression analysis was performed to evaluate predictors of EGFR mutations. Results: EGFR mutations were found in 37 patients (49.3%). EGFR mutations were more common in females, non-smokers, expression of Thyroid Transcription Factor-1 (TTF-1) and NaspinA. Low bmSUVmax was significantly associated with EGFR mutations, while no significant difference was observed in pSUVmax and nSUVmax. Multivariate analysis showed that bmSUVmax ≤7, non-smoking, expression of TTF-1 were predictors of EGFR mutations. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was 0.84 for the combination of the three factors. Conclusion: Low bmSUVmax is more frequently in EGFR mutations, and bmSUVmax is an independent predictor of EGFR mutations. Combining bmSUVmax with other clinicopathological features could forecast the EGFR status in lung adenocarcinoma with unavailable EGFR gene testing.
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Affiliation(s)
- Guangyu Yao
- Department of Internal Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200030, China
| | - Yiyi Zhou
- Department of Internal Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200030, China
| | - Yifeng Gu
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200030, China
| | - Zhiyu Wang
- Department of Internal Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200030, China
| | - Mengdi Yang
- Department of Internal Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200030, China
| | - Jing Sun
- Department of Internal Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200030, China
| | - Quanyong Luo
- Department of Nuclear Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200030, China
| | - Hui Zhao
- Department of Internal Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200030, China
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14
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Liu Q, Sun D, Li N, Kim J, Feng D, Huang G, Wang L, Song S. Predicting EGFR mutation subtypes in lung adenocarcinoma using 18F-FDG PET/CT radiomic features. Transl Lung Cancer Res 2020; 9:549-562. [PMID: 32676319 PMCID: PMC7354146 DOI: 10.21037/tlcr.2020.04.17] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Background Identification of epidermal growth factor receptor (EGFR) mutation types is crucial before tyrosine kinase inhibitors (TKIs) treatment. Radiomics is a new strategy to noninvasively predict the genetic status of cancer. In this study, we aimed to develop a predictive model based on 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) radiomic features to identify the specific EGFR mutation subtypes. Methods We retrospectively studied 18F-FDG PET/CT images of 148 patients with isolated lung lesions, which were scanned in two hospitals with different CT scan setting (slice thickness: 3 and 5 mm, respectively). The tumor regions were manually segmented on PET/CT images, and 1,570 radiomic features (1,470 from CT and 100 from PET) were extracted from the tumor regions. Seven hundred and ninety-four radiomic features insensitive to different CT settings were first selected using the Mann white U test, and collinear features were further removed from them by recursively calculating the variation inflation factor. Then, multiple supervised machine learning models were applied to identify prognostic radiomic features through: (I) a multi-variate random forest to select features of high importance in discriminating different EGFR mutation status; (II) a logistic regression model to select features of the highest predictive value of the EGFR subtypes. The EGFR mutation predicting model was constructed from prognostic radiomic features using the popular Xgboost machine-learning algorithm and validated using 3-fold cross-validation. The performance of predicting model was analyzed using the receiver operating characteristic curve (ROC) and measured with the area under the curve (AUC). Results Two sets of prognostic radiomic features were found for specific EGFR mutation subtypes: 5 radiomic features for EGFR exon 19 deletions, and 5 radiomic features for EGFR exon 21 L858R missense. The corresponding radiomic predictors achieved the prediction accuracies of 0.77 and 0.92 in terms of AUC, respectively. Combing these two predictors, the overall model for predicting EGFR mutation positivity was also constructed, and the AUC was 0.87. Conclusions In our study, we established predictive models based on radiomic analysis of 18F-FDG PET/CT images. And it achieved a satisfying prediction power in the identification of EGFR mutation status as well as the certain EGFR mutation subtypes in lung cancer.
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Affiliation(s)
- Qiufang Liu
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.,SJTU-USYD Joint Research Alliance for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Dazhen Sun
- SJTU-USYD Joint Research Alliance for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.,Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Nan Li
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Jinman Kim
- SJTU-USYD Joint Research Alliance for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.,Biomedical and Multimedia Information Technology Research Group, School of Computer Science, University of Sydney, Sydney, Australia.,Shanghai Key Laboratory for Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
| | - Dagan Feng
- SJTU-USYD Joint Research Alliance for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.,Biomedical and Multimedia Information Technology Research Group, School of Computer Science, University of Sydney, Sydney, Australia.,Shanghai Key Laboratory for Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
| | - Gang Huang
- SJTU-USYD Joint Research Alliance for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.,Shanghai Key Laboratory for Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China.,Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Lisheng Wang
- SJTU-USYD Joint Research Alliance for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.,Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China.,Shanghai Key Laboratory for Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
| | - Shaoli Song
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.,SJTU-USYD Joint Research Alliance for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.,Shanghai Key Laboratory for Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
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15
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Zhang Y, Liu J, Sun Y, Yu X, Wang J, Dai D, Zhu Y, Song X, Zhu L, Li X, Xu W. Enhanced glucose metabolism mediated by CD147 is associated with 18 F-FDG PET/CT imaging in lung adenocarcinoma. Thorac Cancer 2020; 11:1245-1257. [PMID: 32162491 PMCID: PMC7180588 DOI: 10.1111/1759-7714.13383] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 02/18/2020] [Accepted: 02/19/2020] [Indexed: 12/12/2022] Open
Abstract
Background Lung adenocarcinoma (LUAD) is one of the most deadly thoracic tumors. Reprogrammed glycolytic metabolism is a hallmark of cancer cells and significantly affects several cellular functions. In the current study, we aimed to investigate cluster of differentiation 147 (CD147)‐mediated glucose metabolic regulation in LUAD and its association with 18F‐FDG PET/CT imaging. Methods The expression profile and prognostic potential of CD147 in LUAD were analyzed using UALCAN and a Kaplan‐Meier plotter. Tissue immunohistochemical analyses and PET metabolic parameters were used to identify the relationship between CD147 expression and reprogrammed glycolysis. The role of CD147 in glucose metabolic reprogramming was assessed by radioactive uptake of 18F‐FDG through γ‐radioimmunoassays in vitro and micro‐PET/CT imaging in vivo. Western blotting assays were used to determine the expression level of monocarboxylate transporter 1 (MCT1) and MCT4 in established human LUAD cell lines (ie, HCC827 and H1975) with different CD147 expression levels via lentiviral transduction. Results CD147 was highly expressed in LUAD. A significant positive correlation existed between CD147 expression and PET metabolic parameters(SUVmax,SUVmean, SUVpeak). CD147 could promote radioactive uptake of 18F‐FDG in vitro and in vivo, suggesting the ability of CD147 to enhance glycolytic metabolism. Furthermore, as an obligate chaperone for MCT1 and MCT4, CD147 positively correlated with MCT1 and MCT4 expression in LUAD tissues and established cell lines with different CD147 expression. Conclusions Our study revealed that CD147 is a promising novel target for LUAD treatment and CD147‐mediated glucose metabolism demonstrated its contribution to the predictive role of 18F‐FDG PET/CT imaging for targeted therapeutic efficacy.
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Affiliation(s)
- Yufan Zhang
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Jianjing Liu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Yunchuan Sun
- Department of Nuclear Medicine, Hebei Province Cangzhou Hospital of Integrated Traditional and Western Medicine, Cangzhou, China
| | - Xiaozhou Yu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Jian Wang
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Dong Dai
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Yanjia Zhu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Xiuyu Song
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Lei Zhu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Xiaofeng Li
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Wengui Xu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
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16
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Goodman A, Mahmud W, Buckingham L. Gene variant profiles and tumor metabolic activity as measured by FOXM1 expression and glucose uptake in lung adenocarcinoma. J Pathol Transl Med 2020; 54:237-245. [PMID: 32126739 PMCID: PMC7253958 DOI: 10.4132/jptm.2020.02.08] [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: 10/09/2019] [Accepted: 02/08/2020] [Indexed: 11/17/2022] Open
Abstract
Background Cancer cells displaying aberrant metabolism switch energy production from oxidative phosphorylation to glycolysis. Measure of glucose standardized uptake value (SUV) by positron emission tomography (PET), used for staging of adenocarcinoma in high-risk patients, can reflect cellular use of the glycolysis pathway. The transcription factor, FOXM1 plays a role in regulation of glycolytic genes. Cancer cell transformation is driven by mutations in tumor suppressor genes such as TP53 and STK11 and oncogenes such as KRAS and EGFR. In this study, SUV and FOXM1 gene expression were compared in the background of selected cancer gene mutations. Methods Archival tumor tissue from cases of lung adenocarcinoma were analyzed. SUV was collected from patient records. FOXM1 gene expression was assessed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). Gene mutations were detected by allele-specific PCR and gene sequencing. Results SUV and FOXM1 gene expression patterns differed in the presence of single and coexisting gene mutations. Gene mutations affected SUV and FOXM1 differently. EGFR mutations were found in tumors with lower FOXM1 expression but did not affect SUV. Tumors with TP53 mutations had increased SUV (p = .029). FOXM1 expression was significantly higher in tumors with STK11 mutations alone (p < .001) and in combination with KRAS or TP53 mutations (p < .001 and p = .002, respectively). Conclusions Cancer gene mutations may affect tumor metabolic activity. These observations support consideration of tumor cell metabolic state in the presence of gene mutations for optimal prognosis and treatment strategy.
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Affiliation(s)
- Ashley Goodman
- Rush University College of Health Sciences, Chicago, IL, USA
| | - Waqas Mahmud
- Department of Pathology, Rush University Medical Center, Chicago, IL, USA
| | - Lela Buckingham
- Rush University College of Health Sciences, Chicago, IL, USA.,Department of Pathology, Rush University Medical Center, Chicago, IL, USA
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