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A 6-tsRNA signature for early detection, treatment response monitoring, and prognosis prediction in diffuse large B cell lymphoma

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机构： [1]Medical Center of Hematology, Xinqiao Hospital, Army Medical University, Chongqing, China. [2]State Key Laboratory of Trauma and Chemical Poisoning, Chongqing Key Laboratory of Hematology and Microenvironment, Chongqing, China. [3]National Clinical Research Center for Hematologic Diseases, The First Affiliated Hospital of Soochow University, Soochow, China. [4]Department of Hematology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China. [5]Department of Hematology, General Hospital of Chengdu Military Region, Chengdu, Chongqing, China. [6]Department of Hematology, North Sichuan Medical College, Nanchong, China. [7]Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, CA, USA. [8]CHOC Children’s Research Institute, Children’s Hospital of Orange County (CHOC®), part of Rady Children’s Heath, Orange, CA, USA. [9]Department of Neurology, University of California-Irvine School of Medicine, Orange, CA, USA. [10]Jinfeng Laboratory, Chongqing, China.

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Diffuse large B-cell lymphoma (DLBCL) presents considerable clinical challenges due to its aggressive nature and diverse clinical progression. New molecular biomarkers are urgently needed for outcome prediction. We analyzed blood samples from DLBCL patients and healthy individuals using short, non-coding RNA sequencing. A classifier based on six tsRNAs was developed through random forest and primary component analysis. This classifier, established using Cox proportional hazards modeling with repeated 10-fold cross-validation on an internal cohort of 100 samples analyzed using RT-qPCR, effectively identified high-risk patients with significantly lower overall survival compared to low-risk patients (Hazard ratio: 6.657, 95%CI 2.827-15.68, P = 0.0006). Validation in an external cohort of 160 samples using RT-qPCR confirmed the classifier's robust performance. High-risk status was strongly associated with disease histological subtype, stage, and International Prognostic Index scores. Integration of the classifier into the IPI model enhanced the precision and consistency of prognostic predictions. A dynamic study revealed that patients experiencing a 1.06-fold decrease after one therapy cycle (early molecular response) exhibited better treatment outcomes and prognosis. Furthermore, the 6-tsRNA signature accurately differentiated healthy individuals from DLBCL (AUC 0.882, 95%CI 0.826-0.939). These findings underscore the potential of the identified 6-tsRNA profile as a biomarker for monitoring treatment effectiveness and predicting DLBCL outcomes.© 2025. The Author(s).

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出版当年[2025]版：

大类 | 1 区

医学

小类 | 1 区血液学 1 区肿瘤学

最新[2025]版：

大类 | 1 区

医学

小类 | 1 区血液学 1 区肿瘤学

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出版当年[2024]版：

Q1 HEMATOLOGY Q1 ONCOLOGY

最新[2024]版：

Q1 HEMATOLOGY Q1 ONCOLOGY

影响因子： 11.6 最新[2024版] 12.1 最新五年平均 11.6 出版当年[2024版] 0 出版当年五年平均 11.6 出版前一年[2024版]

第一作者：

第一作者机构： [1]Medical Center of Hematology, Xinqiao Hospital, Army Medical University, Chongqing, China. [2]State Key Laboratory of Trauma and Chemical Poisoning, Chongqing Key Laboratory of Hematology and Microenvironment, Chongqing, China. [3]National Clinical Research Center for Hematologic Diseases, The First Affiliated Hospital of Soochow University, Soochow, China.

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通讯作者：

通讯机构： [1]Medical Center of Hematology, Xinqiao Hospital, Army Medical University, Chongqing, China. [2]State Key Laboratory of Trauma and Chemical Poisoning, Chongqing Key Laboratory of Hematology and Microenvironment, Chongqing, China. [3]National Clinical Research Center for Hematologic Diseases, The First Affiliated Hospital of Soochow University, Soochow, China. [8]CHOC Children’s Research Institute, Children’s Hospital of Orange County (CHOC®), part of Rady Children’s Heath, Orange, CA, USA. [9]Department of Neurology, University of California-Irvine School of Medicine, Orange, CA, USA. [10]Jinfeng Laboratory, Chongqing, China.

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