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Xu H, Yan R, Ye C, Li J, Ji G. Specific mortality in patients with diffuse large B-cell lymphoma: a retrospective analysis based on the surveillance, epidemiology, and end results database. Eur J Med Res 2024; 29:241. [PMID: 38643217 PMCID: PMC11031870 DOI: 10.1186/s40001-024-01833-4] [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: 01/17/2024] [Accepted: 04/06/2024] [Indexed: 04/22/2024] Open
Abstract
BACKGROUND The full potential of competing risk modeling approaches in the context of diffuse large B-cell lymphoma (DLBCL) patients has yet to be fully harnessed. This study aims to address this gap by developing a sophisticated competing risk model specifically designed to predict specific mortality in DLBCL patients. METHODS We extracted DLBCL patients' data from the SEER (Surveillance, Epidemiology, and End Results) database. To identify relevant variables, we conducted a two-step screening process using univariate and multivariate Fine and Gray regression analyses. Subsequently, a nomogram was constructed based on the results. The model's consistency index (C-index) was calculated to assess its performance. Additionally, calibration curves and receiver operator characteristic (ROC) curves were generated to validate the model's effectiveness. RESULTS This study enrolled a total of 24,402 patients. The feature selection analysis identified 13 variables that were statistically significant and therefore included in the model. The model validation results demonstrated that the area under the receiver operating characteristic (ROC) curve (AUC) for predicting 6-month, 1-year, and 3-year DLBCL-specific mortality was 0.748, 0.718, and 0.698, respectively, in the training cohort. In the validation cohort, the AUC values were 0.747, 0.721, and 0.697. The calibration curves indicated good consistency between the training and validation cohorts. CONCLUSION The most significant predictor of DLBCL-specific mortality is the age of the patient, followed by the Ann Arbor stage and the administration of chemotherapy. This predictive model has the potential to facilitate the identification of high-risk DLBCL patients by clinicians, ultimately leading to improved prognosis.
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Affiliation(s)
- Hui Xu
- Department of Hematology, Taixing People's Hospital, No. 98, Runtai South Road, Taixing, 225400, Jiangsu, China
| | - Rong Yan
- Taixing People's Hospital, Taixing, Jiangsu, China
| | - Chunmei Ye
- Department of Hematology, Taixing People's Hospital, No. 98, Runtai South Road, Taixing, 225400, Jiangsu, China
| | - Jun Li
- Department of Hematology, Taixing People's Hospital, No. 98, Runtai South Road, Taixing, 225400, Jiangsu, China
| | - Guo Ji
- Department of Hematology, Taixing People's Hospital, No. 98, Runtai South Road, Taixing, 225400, Jiangsu, China.
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Wang Y, Shi Q, Shi ZY, Tian S, Zhang MC, Shen R, Fu D, Dong L, Yi HM, Ouyang BS, Mu RJ, Cheng S, Wang L, Xu PP, Zhao WL. Biological signatures of the International Prognostic Index in diffuse large B-cell lymphoma. Blood Adv 2024; 8:1587-1599. [PMID: 38170757 PMCID: PMC10987882 DOI: 10.1182/bloodadvances.2023011425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/14/2023] [Accepted: 12/03/2023] [Indexed: 01/05/2024] Open
Abstract
ABSTRACT Diffuse large B-cell lymphoma (DLBCL) is a highly aggressive subtype of lymphoma with clinical and biological heterogeneity. The International Prognostic Index (IPI) shows great prognostic capability in the era of rituximab, but the biological signatures of IPI remain to be discovered. In this study, we analyzed the clinical data in a large cohort of 2592 patients with newly diagnosed DLBCL. Among them, 1233 underwent DNA sequencing for oncogenic mutations, and 487 patients underwent RNA sequencing for lymphoma microenvironment (LME) alterations. Based on IPI scores, patients were categorized into 4 distinct groups, with 5-year overall survival of 41.6%, 55.3%, 71.7%, and 89.7%, respectively. MCD-like subtype was associated with age of >60 years, multiple extranodal involvement, elevated serum lactate dehydrogenase (LDH), and IPI scores ranging from 2 to 5, whereas ST2-like subtype showed an opposite trend. Patients with EZB-like MYC+ and TP53Mut subtypes exhibited poor clinical outcome independent of the IPI; integrating TP53Mut into IPI could better distinguish patients with dismal survival. The EZB-like MYC-, BN2-like, N1-like, and MCD-like subtypes had inferior prognosis in patients with IPI scores of ≥2, indicating necessity for enhanced treatment. Regarding LME categories, the germinal center-like LME was more prevalent in patients with normal LDH and IPI scores of 0 to 1. The mesenchymal LME served as an independent protective factor, whereas the germinal center-like, inflammatory, and depleted LME categories correlated with inferior prognosis for IPI scores of 2 to 5. In summary, our work explored the biological signatures of IPI, thus providing useful rationale for future optimization of the IPI-based treatment strategies with multi-omics information in DLBCL.
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Affiliation(s)
- Yue Wang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qing Shi
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zi-Yang Shi
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuang Tian
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mu-Chen Zhang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rong Shen
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Di Fu
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lei Dong
- Department of Pathology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong-Mei Yi
- Department of Pathology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bin-Shen Ouyang
- Department of Pathology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rong-Ji Mu
- Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shu Cheng
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Li Wang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Pôle de Recherches Sino-Français en Science du Vivant et Génomique, Laboratory of Molecular Pathology, Shanghai, China
| | - Peng-Peng Xu
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei-Li Zhao
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Pôle de Recherches Sino-Français en Science du Vivant et Génomique, Laboratory of Molecular Pathology, Shanghai, China
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Wang WT, Xing TY, Du KX, Hua W, Guo JR, Duan ZW, Wu YF, Wu JZ, Li Y, Yin H, Shen HR, Wang L, Li JY, Liang JH, Xu W. CD30 protects EBV-positive diffuse large B-cell lymphoma cells against mitochondrial dysfunction through BNIP3-mediated mitophagy. Cancer Lett 2024; 583:216616. [PMID: 38211650 DOI: 10.1016/j.canlet.2024.216616] [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: 09/08/2023] [Revised: 12/13/2023] [Accepted: 12/19/2023] [Indexed: 01/13/2024]
Abstract
Epstein-Barr virus (EBV) positive diffuse large B-cell lymphoma (EBV+ DLBCL) predicts poor prognosis and CD30 expression aggravates the worse consequences. Here, we reported that CD30 positivity was an independent prognostic indicator in EBV+ DLBCL patients in a retrospective cohort study. We harnessed CRISPR/Cas9 editing to engineer the first loss-of-function models of CD30 deficiency to identify that CD30 was critical for EBV+ DLBCL growth and survival. We established a pathway that EBV infection mediated CD30 expression through EBV-encoded latent membrane protein 1 (LMP1), which involved NF-κB signaling. CRISPR CD30 knockout significantly repressed BCL2 interacting protein 3 (BNIP3) expression and co-IP assay indicated a binding between CD30 and BNIP3. Moreover, silencing of CD30 induced mitochondrial dysfunction and suppressed mitophagy, resulting in the accumulation of damaged mitochondria by depressing BNIP3 expression. Additionally, CRISPR BNIP3 knockout caused proliferation defects and increased sensitivity to apoptosis. All the findings reveal a strong relationship between mitophagy and adverse prognosis of EBV+ DLBCL and discover a new regulatory mechanism of BNIP3-mediated mitophagy, which may help develop effective treatment regimens with anti-CD30 antibody brentuximab vedotin to improve the prognosis of CD30+ EBV+ DLBCL patients.
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Affiliation(s)
- Wei-Ting Wang
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Tong-Yao Xing
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Kai-Xin Du
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Wei Hua
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Jing-Ran Guo
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Zi-Wen Duan
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Yi-Fan Wu
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Jia-Zhu Wu
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Yue Li
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Hua Yin
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Hao-Rui Shen
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Li Wang
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Jian-Yong Li
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China
| | - Jin-Hua Liang
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China.
| | - Wei Xu
- Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, China; Key Laboratory of Hematology of Nanjing Medical University, Nanjing 210029, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, China.
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Li Z, Guo W, Bai O. Mechanism of action and therapeutic targeting of CD30 molecule in lymphomas. Front Oncol 2023; 13:1301437. [PMID: 38188299 PMCID: PMC10767573 DOI: 10.3389/fonc.2023.1301437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 12/06/2023] [Indexed: 01/09/2024] Open
Abstract
At present, the treatment of lymphoma has entered the era of precision medicine, and CD30, as a transmembrane protein, has become an important marker to help the diagnosis and formulation of treatment plans for lymphomas. This protein is widely expressed in various types of lymphomas and can play a role through nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), and other pathways, and ultimately lead to the up-regulation of CD30 expression to give tumor cells a survival advantage. Brentuximab vedotin (BV), as an antibody-drug conjugate (ADC) targeting CD30, is one of the first new drugs to significantly improve survival in patients with CD30+lymphomas. However, the biological function of CD30 has not been fully elucidated. Therefore, this review highlights the CD30-mediated tumor-promoting mechanisms and the molecular factors that regulate CD30 expression. We hope that a better understanding of CD30 biology will provide new insights into clinical treatment and improve the survival and quality of life of lymphoma patients.
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Affiliation(s)
| | | | - Ou Bai
- Department of Hematology, The First Hospital of Jilin University, Changchun, Jilin, China
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