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Lu X, Wang S, Hua X, Chen X, Zhan M, Hu Q, Cao L, Wu Z, Zhang W, Zuo X, Gui R, Fan L, Li J, Shi W, Jin H. Targeting the cGAS-STING Pathway Inhibits Peripheral T-cell Lymphoma Progression and Enhances the Chemotherapeutic Efficacy. Adv Sci (Weinh) 2024; 11:e2306092. [PMID: 38145335 PMCID: PMC10933671 DOI: 10.1002/advs.202306092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 12/01/2023] [Indexed: 12/26/2023]
Abstract
Peripheral T-cell lymphoma (PTCL) is a highly heterogeneous group of mature T-cell malignancies. The efficacy of current first-line treatment is dismal, and novel agents are urgently needed to improve patient outcomes. A close association between the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway and tumor promotion exists, revealing prospective therapeutic targets. This study, investigates the role of the cGAS-STING pathway and its underlying mechanisms in PTCL progression. Single-cell RNA sequencing showes that the cGAS-STING pathway is highly expressed and closely associated with PTCL proliferation. cGAS inhibition suppresses tumor growth and impaires DNA damage repair. Moreover, Cdc2-like kinase 1 (CLK1) is critical for residual tumor cell survival after treatment with cGAS inhibitors, and CLK1 suppression enhances sensitivity to cGAS inhibitors. Single-cell dynamic transcriptomic analysis indicates reduced proliferation-associated nascent RNAs as the underlying mechanism. In first-line therapy, chemotherapy-triggered DNA damage activates the cGAS-STING pathway, and cGAS inhibitors can synergize with chemotherapeutic agents to kill tumors. The cGAS-STING pathway is oncogenic in PTCL, whereas targeting cGAS suppresses tumor growth, and CLK1 may be a sensitivity indicator for cGAS inhibitors. These findings provide a theoretical foundation for optimizing therapeutic strategies for PTCL, especially in patients with relapsed/refractory disease.
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Affiliation(s)
- Xueying Lu
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
| | - Shunan Wang
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
| | - Xin Hua
- Department of OncologyAffiliated Hospital of Nantong UniversityNantong226001China
| | - Xiao Chen
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
| | - Mengtao Zhan
- Nanjing Aoyin Biotechnology Company LimitedNanjing210043China
| | - Qiaoyun Hu
- Singleron BiotechnologiesNanjing211899China
| | - Lei Cao
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
- Nanjing Pukou Central HospitalPuKou Branch Hospital of Jiangsu Province HospitalNanjing211800China
| | - Zijuan Wu
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
| | - Wei Zhang
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
| | - Xiaoling Zuo
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
| | - Renfu Gui
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
| | - Lei Fan
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
| | - Jianyong Li
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
- National Clinical Research Center for Hematologic DiseasesThe First Affiliated Hospital of Soochow UniversitySuzhou215006China
| | - Wenyu Shi
- Department of OncologyAffiliated Hospital of Nantong UniversityNantong226001China
| | - Hui Jin
- Lymphoma Center, Department of HematologyJiangsu Province HospitalThe First Affiliated Hospital of Nanjing Medical UniversityNanjing210029China
- Key Laboratory of Hematology of Nanjing Medical UniversityNanjing210029China
- Jiangsu Key Lab of Cancer BiomarkersPrevention, and TreatmentCollaborative Innovation Center for Personalized Cancer MedicineNanjing Medical UniversityNanjing210029China
- National Clinical Research Center for Hematologic DiseasesThe First Affiliated Hospital of Soochow UniversitySuzhou215006China
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Wu W, Zhao L, Wang Y, Chen P, Yuan X, Miao L, Zhu Y, Mao J, Cai Z, Ji Y, Wang L, Jia T. Prognostic value of the peripheral blood lymphocyte/monocyte ratio combined with 18F-FDG PET/CT in patients with diffuse large B-cell lymphoma. Curr Probl Cancer 2024; 48:101066. [PMID: 38364336 DOI: 10.1016/j.currproblcancer.2024.101066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 12/18/2023] [Accepted: 01/30/2024] [Indexed: 02/18/2024]
Abstract
OBJECTIVE To explore the prognostic value of the peripheral blood lymphocyte/monocyte ratio (LMR) combined with 18F-FDG PET/CT for diffuse large B-cell lymphoma (DLBCL). METHODS The clinical data of 203 patients with primary DLBCL who were hospitalized to the First People's Hospital of Lianyungang between January 2017 and December 2022 were retrospectively analyzed. Before and after three courses of treatment, PET/CT was performed on forty DLBCL patients. The subject operating characteristic (ROC) curve has been employed to determine the most effective LMR cutoff points. According to the criteria for assessing the efficacy of Lugano lymphoma, the PET/CT findings after 3 courses of treatment were specified as complete remission (CR), partial remission (PR), stable disease (SD) and disease progression (PD). The CR group, PR+SD group, and PD group were the three groups created from the four outcomes. Results were analyzed using the Cox proportional risk model, the Kaplan-Meier method (K-M), and the log-rank test. RESULTS An optimal cutoff point of 3.00 for the LMR in 203 patients was determined by the SPSS 26 software ROC curve. When LMR≥3.00, the 1-year, 3-year, and 5-year OS (Overall Survival) rates are 98%, 88%, and 64% respectively, and the PFS (Progression-free Survival) rates are 90%, 75%, and 56% respectively. When LMR <3.00, the 1-year, 3-year, and 5-year OS rates are 96%, 72%, and 28% respectively, and the PFS rates are 83%, 60%, and 28% respectively. A lower LMR was substantially related with shorter OS, and PFS, according to a K-M survival analysis (P<0.005). LMR<3.00 was an independent predictor of OS, based on a multifactorial Cox analysis (P=0.037). K-M survival analysis of the 18F-FDG PET/CT results of 40 patients revealed that both OS and PFS were statistically significant (P<0.001). Patients were separated into 3 groups combining LMR and 18F-FDG PET/CT: PET/CT CR patients with LMR≥3.00, PET/CT PD patients with LMR<3.00, and others. The Kaplan-Meier analysis revealed that there were significant differences in OS and PFS for each of the three groups (P<0.001). ROC curves showed that the area under the curve (AUC) of the combined testing of the two was 0.735, and the combined testing of the two was better compared to testing alone (PET/CT AUC=0.535, LMR AUC=0.567). This indicates that combining both PET/CT and LMR is a favorable prediction for DLBCL. CONCLUSION A decreased LMR at initial diagnosis suggests an unfavorable prognosis for DLBCL patients; For patients with DLBCL, combining 18F-FDG PET/CT and the LMR has a better predictive value.
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Affiliation(s)
- Wenke Wu
- Jinzhou Medical University, Jinzhou, Liaoning 121001, China; Department of Hematology, Postgraduate Training Base of the Lian Yungang First People's Hospital of Jinzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Lidong Zhao
- Department of Hematology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Ying Wang
- Department of Hematology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Peng Chen
- Department of Nuclear Medicine, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Xiaoshuai Yuan
- Department of Nuclear Medicine, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Lei Miao
- Department of Hematology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Yuanxin Zhu
- Department of Hematology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Jianping Mao
- Department of Hematology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Zhimei Cai
- Department of Hematology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Yajun Ji
- Department of Oncology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Lei Wang
- Department of Oncology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China
| | - Tao Jia
- Department of Hematology, The First People's Hospital of Lianyungang, The First Affiliated Hospital of Kangda College of Nanjing Medical University, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu 222000, China.
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Shaker N, Phelps R, Cabala CT, Niedt G, Sangueza OP, Pradhan D. Cutaneous Involvement by Diffuse Large B-Cell Lymphoma With Dual B-Cell and T-Cell Clonality and Heavy Admixed T-Cell Infiltrate: Answer. Am J Dermatopathol 2023; 45:859-860. [PMID: 37982471 DOI: 10.1097/dad.0000000000002576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Affiliation(s)
- Nada Shaker
- Department of Pathology, The Ohio State University, Wexner Medical Center, Columbus, OH
| | - Robert Phelps
- Department of Dermatology, Mount Sinai Medical Center, New York, NY
- Department of Dermatopathology, Mount Sinai Medical Center, New York, NY
| | - Carlos Torres Cabala
- Department of Dermatopathology and Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - George Niedt
- Department of Dermatology, Mount Sinai Medical Center, New York, NY
- Department of Dermatopathology, Mount Sinai Medical Center, New York, NY
| | - Omar P Sangueza
- Department of Dermatology, Wake Forest University, School of Medicine, Medical Center BoulevardWinston-Salem, NC
- Department of Dermatopathology, Wake Forest University, School of Medicine, Medical Center BoulevardWinston-Salem, NC; and
| | - Dinesh Pradhan
- Department of Pathology & Microbiology, University of Nebraska Medical Center, Nebraska Medical Center, Omaha, NE
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Jiang C, Qian C, Jiang Z, Teng Y, Lai R, Sun Y, Ni X, Ding C, Xu Y, Tian R. Robust deep learning-based PET prognostic imaging biomarker for DLBCL patients: a multicenter study. Eur J Nucl Med Mol Imaging 2023; 50:3949-3960. [PMID: 37606859 DOI: 10.1007/s00259-023-06405-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 08/16/2023] [Indexed: 08/23/2023]
Abstract
OBJECTIVE To develop and independently externally validate robust prognostic imaging biomarkers distilled from PET images using deep learning techniques for precise survival prediction in patients with diffuse large B cell lymphoma (DLBCL). METHODS A total of 684 DLBCL patients from three independent medical centers were included in this retrospective study. Deep learning scores (DLS) were generated from PET images using deep convolutional neural network architecture known as VGG19 and DenseNet121. These DLSs were utilized to predict progression-free survival (PFS) and overall survival (OS). Furthermore, multiparametric models were designed based on results from the Cox proportional hazards model and assessed through calibration curves, concordance index (C-index), and decision curve analysis (DCA) in the training and validation cohorts. RESULTS The DLSPFS and DLSOS exhibited significant associations with PFS and OS, respectively (P<0.05) in the training and validation cohorts. The multiparametric models that incorporated DLSs demonstrated superior efficacy in predicting PFS (C-index: 0.866) and OS (C-index: 0.835) compared to competing models in training cohorts. In external validation cohorts, the C-indices for PFS and OS were 0.760 and. 0.770 and 0.748 and 0.766, respectively, indicating the reliable validity of the multiparametric models. The calibration curves displayed good consistency, and the decision curve analysis (DCA) confirmed that the multiparametric models offered more net clinical benefits. CONCLUSIONS The DLSs were identified as robust prognostic imaging biomarkers for survival in DLBCL patients. Moreover, the multiparametric models developed in this study exhibited promising potential in accurately stratifying patients based on their survival risk.
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Affiliation(s)
- Chong Jiang
- Department of Nuclear Medicine, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Chunjun Qian
- School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou, 213032, Jiangsu, China
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Center of Medical Physics, Nanjing Medical University, Changzhou, 213003, China
| | - Zekun Jiang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Yue Teng
- Department of Nuclear Medicine, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Ruihe Lai
- Department of Nuclear Medicine, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Yiwen Sun
- Department of Nuclear Medicine, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Xinye Ni
- The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China
- Center of Medical Physics, Nanjing Medical University, Changzhou, 213003, China
| | - Chongyang Ding
- Department of Nuclear Medicine, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Jiangsu Province, No. 321, Zhongshan Road, Nanjing, 210008, China.
| | - Yuchao Xu
- School of Nuclear Science and Technology, University of South China, Hengyang City, China
| | - Rong Tian
- Department of Nuclear Medicine, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China.
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