1
|
Han Y, Dong Z, Xing Y, Zhan Y, Zou J, Wang X. Establishment of a prognosis prediction model for lung squamous cell carcinoma related to PET/CT: basing on immunogenic cell death-related lncRNA. BMC Pulm Med 2023; 23:511. [PMID: 38102594 PMCID: PMC10724919 DOI: 10.1186/s12890-023-02792-y] [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] [Received: 04/27/2023] [Accepted: 11/28/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Immunogenic cell death (ICD) stimulates adaptive immunity and holds significant promise in cancer therapy. Nevertheless, the influence of ICD-associated long non-coding RNAs (lncRNAs) on the prognosis of patients with lung squamous cell carcinoma (LUSC) remains unexplored. METHODS We employed data from the The Cancer Genome Atlas (TCGA)database to identify ICD-related lncRNAs associated with the prognosis of LUSC using univariate Cox regression analysis. Subsequently, we utilized the LOSS regression model to construct a predictive risk model for assessing the prognosis of LUSC patients based on ICD-related lncRNAs. Our study randomly allocated187 TCGA patients into a training group and 184 patients for testing the predictive model. Furthermore, we conducted quantitative polymerase chain reaction (qPCR) analysis on 43 tumor tissues from LUSC patients to evaluate lncRNA expression levelsPearson correlation analysis was utilized to analyze the correlation of risk scores with positron emission tomography/computed tomography (PET/CT) parameters among LUSC patients. RESULTS The findings from the univariate Cox regression revealed 16 ICD-associated lncRNAs linked to LUSC prognosis, with 12 of these lncRNAs integrated into our risk model utilizing the LOSS regression. Survival analysis indicated a markedly higher overall survival time among patients in the low-risk group compared to those in the high-risk group. The area under the Receiver operating characteristic (ROC) curve to differentiate high-risk and low-risk patients was 0.688. Additionally, the overall survival rate was superior in the low-risk group compared to the high-risk group. Correlation analysis demonstrated a positive association between the risk score calculated based on the ICD-lncRNA risk model and the maximum standard uptake value (SUVmax) (r = 0.427, P = 0.0043) as well as metabolic volume (MTV)of PET-CT (r = 0.360, P = 0.0177) in 43 LUSC patients. CONCLUSION We have successfully developed a risk model founded on ICD-related lncRNAs that proves effective in predicting the overall survival of LUSC patients.
Collapse
Affiliation(s)
- Yu Han
- Nuclear medicine, Cangzhou Central Hospital, Cangzhou, China
| | - Zhiqiang Dong
- 2nd Department of Hepatobiliary and Pancreatic Surgery, Cangzhou People's Hospital, Cangzhou, China
| | - Yu Xing
- Nuclear medicine, Cangzhou Central Hospital, Cangzhou, China
| | - Yingying Zhan
- Nuclear medicine, Cangzhou Central Hospital, Cangzhou, China
| | - Jinhai Zou
- Nuclear medicine, Cangzhou Central Hospital, Cangzhou, China.
| | - Xiaodong Wang
- Department of Pathology, Zhangjiakou Integrated Traditional Chinese and Western Medicine Hospital, Zhangjiakou, China
| |
Collapse
|
2
|
Grambozov B, Kalantari F, Beheshti M, Stana M, Karner J, Ruznic E, Zellinger B, Sedlmayer F, Rinnerthaler G, Zehentmayr F. Pretreatment 18-FDG-PET/CT parameters can serve as prognostic imaging biomarkers in recurrent NSCLC patients treated with reirradiation-chemoimmunotherapy. Radiother Oncol 2023; 185:109728. [PMID: 37301259 DOI: 10.1016/j.radonc.2023.109728] [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] [Received: 02/20/2023] [Revised: 05/02/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND AND PURPOSE Our study aimed to assess whether quantitative pretreatment 18F-FDG-PET/CT parameters could predict prognostic clinical outcome of recurrent NSCLC patients who may benefit from ablative reirradiation. MATERIALS AND METHODS Forty-eight patients with recurrent NSCLC of all UICC stages who underwent ablative thoracic reirradiation were analyzed. Twenty-nine (60%) patients received immunotherapy with or without chemotherapy in addition to reirradiation. Twelve patients (25%) received reirradiation only and seven (15%) received chemotherapy and reirradiation. Pretreatment 18-FDG-PET/CT was mandatory in initial diagnosis and recurrence, based on which volumetric and intensity quantitative parameters were measured before reirradiation and their impact on overall survival, progression-free survival, and locoregional control was assessed. RESULTS With a median follow-up time of 16.7 months, the median OS was 21.8 months (95%-CI: 16.2-27.3). On multivariate analysis, OS and PFS were significantly influenced by MTV (p < 0.001 for OS; p = 0.006 for PFS), TLG (p < 0.001 for OS; p = 0.001 for PFS) and SUL peak (p = 0.0024 for OS; p = 0.02 for PFS) of the tumor and MTV (p = 0.004 for OS; p < 0.001 for PFS) as well as TLG (p = 0.007 for OS; p = 0.015 for PFS) of the metastatic lymph nodes. SUL peak of the tumor (p = 0.05) and the MTV of the lymph nodes (p = 0.003) were only PET quantitative parameters that significantly impacted LRC. CONCLUSION Pretreatment tumor and metastastic lymph node MTV, TLG and tumor SUL peak significantly correlated with clinical outcome in recurrent NSCLC patients treated with reirradiation-chemoimmunotherapy.
Collapse
Affiliation(s)
- Brane Grambozov
- Department of Radiation Oncology, Paracelsus Medical University, SALK, Salzburg, Austria.
| | - Forough Kalantari
- Department of Nuclear Medicine, Rasoul Akram Hospital, Iran University of Medical Sciences, Tehran, Iran; Division of Molecular Imaging and Theranostics, Department of Nuclear Medicine, University Hospital Salzburg, Paracelsus Medical University, Salzburg, Austria
| | - Mohsen Beheshti
- Division of Molecular Imaging and Theranostics, Department of Nuclear Medicine, University Hospital Salzburg, Paracelsus Medical University, Salzburg, Austria
| | - Markus Stana
- Department of Radiation Oncology, Paracelsus Medical University, SALK, Salzburg, Austria
| | - Josef Karner
- Department of Radiation Oncology, Paracelsus Medical University, SALK, Salzburg, Austria
| | - Elvis Ruznic
- Department of Radiation Oncology, Paracelsus Medical University, SALK, Salzburg, Austria
| | - Barbara Zellinger
- Institute of Pathology, Paracelsus Medical University, SALK, Salzburg, Austria
| | - Felix Sedlmayer
- Department of Radiation Oncology, Paracelsus Medical University, SALK, Salzburg, Austria; radART - Institute for Research and Development on Advanced Radiation Technologies, Paracelsus Medical University, Salzburg, Austria
| | - Gabriel Rinnerthaler
- Department of Internal Medicine III with Haematology, Medical Oncology, Haemostaseology, Infectiology and Rheumatology, Oncologic Center, Salzburg Cancer Research Institute-Laboratory for Immunological and Molecular Cancer Research (SCRI-LIMCR), Paracelsus Medical University Salzburg, 5020 Salzburg, Austria; Cancer Cluster Salzburg, 5020 Salzburg, Austria
| | - Franz Zehentmayr
- Department of Radiation Oncology, Paracelsus Medical University, SALK, Salzburg, Austria; radART - Institute for Research and Development on Advanced Radiation Technologies, Paracelsus Medical University, Salzburg, Austria
| |
Collapse
|
3
|
Park SY, Cho DG, Shim BY, Cho U. Relationship between Systemic Inflammatory Markers, GLUT1 Expression, and Maximum 18F-Fluorodeoxyglucose Uptake in Non-Small Cell Lung Carcinoma and Their Prognostic Significance. Diagnostics (Basel) 2023; 13:diagnostics13061013. [PMID: 36980320 PMCID: PMC10047418 DOI: 10.3390/diagnostics13061013] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/03/2023] [Accepted: 02/05/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND Factors involved in inflammation and cancer interact in various ways with each other, and biomarkers of systemic inflammation may have a prognostic value in cancer. Glucose transporter 1 (GLUT1) plays a pivotal role in glucose transport and metabolism and it is aberrantly expressed in various cancer types. We evaluated the differential expression of GLUT1, along with 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) in non-small-cell lung cancer (NSCLC), and then analyzed their prognostic significance. METHODS A total of 163 patients with resectable NSCLC were included in this study. Tumor sections were immunohistochemically stained for GLUT1 and GLUT3. Maximum standardized uptake value (SUVmax) was measured by preoperative FDG-PET, and neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and lymphocyte-monocyte ratio (LMR) were derived from pretreatment blood count. RESULTS GLUT1 and GLUT3 was positively expressed in 74.8% and 6.1% of the NSCLC tissues, respectively. GLUT1 expression was significantly correlated with squamous cell carcinoma histology, poor differentiation, high pathologic stage, old age, male, smoking, and high SUVmax (>7) (all p < 0.05). The squamous cell carcinoma and smoker group also showed significantly higher SUVmax (both p < 0.001). Systemic inflammation markers, including NLR, PLR, and LMR, were positively correlated with high SUVmax (all p < 0.05). High GLUT1 expression, high SUVmax, high NLR, and low LMR, were significantly associated with poor overall survival in patients with NSCLC. However, in the multivariate survival analysis, LMR was an independent prognostic factor overall (HR 1.86, 95% CI 1.05-3.3) and for the stage I/II cohort (HR 2.3, 95% CI 1.24-4.3) (all p < 0.05). CONCLUSIONS Systemic inflammatory markers-NLR, PLR, and LMR are strongly correlated with the SUVmax and are indicators of aggressive tumor behavior. Specifically, LMR is a promising prognostic biomarker in NSCLC patients.
Collapse
Affiliation(s)
- Sonya Youngju Park
- Department of Nuclear Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Deog-Gon Cho
- Department of Thoracic Surgery, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Byoung-Yong Shim
- Division of Medical Oncology, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Uiju Cho
- Department of Pathology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| |
Collapse
|
4
|
Zhang L, Xu C, Zhang X, Wang J, Jiang H, Chen J, Zhang H. A novel analytical approach for outcome prediction in newly diagnosed NSCLC based on [ 18F]FDG PET/CT metabolic parameters, inflammatory markers, and clinical variables. Eur Radiol 2023; 33:1757-1768. [PMID: 36222865 DOI: 10.1007/s00330-022-09150-2] [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: 05/07/2022] [Revised: 08/24/2022] [Accepted: 09/06/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To develop a novel analytical approach based on 18F-fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) metabolic parameters, serum inflammatory markers, and clinical variables to improve the outcome prediction in NSCLC. METHODS A total of 190 newly diagnosed NSCLC patients who underwent pretreatment [18F]FDG PET/CT were retrospectively enrolled and divided into a training cohort (n = 127) and a test cohort (n = 63). Cox regression analysis was used to investigate the predictive values of PET metabolic parameters, inflammation markers, and clinical variables for progression-free survival (PFS) and overall survival (OS). Based on the results of multivariate analysis, PET-based, clinical, and combined models were constructed. The predictive performance of different models was evaluated using time-dependent ROC curve analysis, Harrell concordance index (C-index), calibration curve, and decision curve analysis. RESULTS The combined models incorporating SULmax, MTV, NLR, and ECOG PS demonstrated significant prognostic superiority over PET-based models, clinical models, and TNM stage in terms of both PFS (C-index: 0.813 vs. 0.786 vs. 0.776 vs. 0.678, respectively) and OS (C-index: 0.856 vs. 0.792 vs. 0.781 vs. 0.674, respectively) in the training cohort. Similar results were observed in the test cohort for PFS (C-index: 0.808 vs. 0.764 vs. 0.748 vs. 0.679, respectively) and OS (C-index: 0.836 vs. 0.785 vs. 0.726 vs. 0.660, respectively) prediction. The combined model calibrated well in two cohorts. Decision curve analysis supported the clinical utility of the combined model. CONCLUSIONS We reported a novel analytical approach combining PET metabolic information with inflammatory biomarker and clinical characteristics, which could significantly improve outcome prediction in newly diagnosed NSCLC. KEY POINTS • The nomogram incorporating SULmax, MTV, NLR, and ECOG PS outperformed the TNM stage for outcome prediction in patients with newly diagnosed NSCLC. • The established nomogram could provide refined prognostic stratification.
Collapse
Affiliation(s)
- Lixia Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Caiyun Xu
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Xiaohui Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
| | - Jing Wang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
| | - Han Jiang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China.,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China
| | - Jinyan Chen
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, 310006, Zhejiang, China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009, Zhejiang, China. .,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, Zhejiang, China.
| |
Collapse
|
5
|
Dong H, Liang X, Gao Y, Cai Y, Li X, Miao J, Wang W, Hu B, Li H. Postoperative venous thromboembolism after surgery for stage IA non-small-cell lung cancer: A single-center, prospective cohort study. Thorac Cancer 2022; 13:1258-1266. [PMID: 35315227 PMCID: PMC9058304 DOI: 10.1111/1759-7714.14373] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 02/16/2022] [Accepted: 02/20/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Venous thromboembolism (VTE) is a common postoperative complication of lung cancer, but the incidence and risk stratification of postoperative VTE in stage IA non-small-cell lung cancer (NSCLC) patients remains unclear, therefore we conducted a single-center prospective study. METHODS A total of 314 consecutive patients hospitalized for lung cancer surgery and diagnosed with stage IA NSCLC from January 2017 to July 2021 were included. The patients were divided into the VTE group and the non-VTE group according to whether VTE occurred after the operation. The patient's age, operation time, D-dimer (D-D) value, tumor pathology, and Caprini score were recorded. The different items were compared and included in logistic regression analysis to obtain independent risk factors, and the area under the receiver operating characteristics curve (AUC) was calculated. RESULTS The incidence of VTE was 7.3%. Significant differences in age, operation time, preoperative and postoperative day 1 D-D value, neuron-specific enolase value, forced expiratory volume in 1 second, maximum ventilation, carbon monoxide diffusion capacity, and pathological diameter were noted between the two groups. Age (95% confidence interval [CI] 1.056-1.216) and postoperative day 1 D-D value (95% CI 1.125-1.767) were independent risk factors. The incidence of VTE in the low-, medium-, and high-risk groups with Caprini scores was 0%, 7.3%, and 11.5%, respectively. The AUC of the Caprini score was 0.704 (p < 0.05). CONCLUSIONS The incidence of postoperative VTE in patients with stage IA NSCLC was 7.3%. Age and postoperative day 1 D-D value were independent risk factors for VTE. The Caprini score has a certain value in the diagnosis of postoperative VTE of stage IA NSCLC.
Collapse
Affiliation(s)
- Honghong Dong
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Xiaoning Liang
- Department of Ultrasound, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Yingdi Gao
- Department of Cardiac Surgery, Heart Center and Beijing Key Laboratory of Hypertension, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Yongsheng Cai
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Xinyang Li
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Jinbai Miao
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Wenjiao Wang
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Bin Hu
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Hui Li
- Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| |
Collapse
|