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A novel angiogenesis-related scoring model predicts prognosis risk and treatment responsiveness in diffuse large B-cell lymphoma

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Abstract

Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous disease with varying therapeutic responses and prognoses. Angiogenesis is a crucial factor in lymphoma growth and progression, but no scoring model based on angiogenesis-related genes (ARGs) has been developed for prognostic evaluation of DLBCL patients. In this study, we used univariate Cox regression to identify prognostic ARGs and found two distinct clusters of DLBCL patients in the GSE10846 dataset based on the expression of these prognostic ARGs. These two clusters had different prognoses and immune cell infiltration. Using LASSO regression analysis, we constructed a novel seven-ARG-based scoring model in GSE10846 dataset, and it was further validated in the GSE87371 dataset. The DLBCL patients were divided into high- and low-score groups based on the median risk score as a cut-off. The high-score group had a worse prognosis and showed higher expression of immune checkpoints, M2 macrophages, myeloid-derived suppressor cells, and regulatory T cells, indicating a stronger immunosuppressive environment. DLBCL patients in high-score group were resistant to doxorubicin and cisplatin, which are components of frequently used chemotherapy regimens, but more sensitive to gemcitabine and temozolomide. Using RT-qPCR, we found that two candidate risk genes, RAPGEF2 and PTGER2, were over-expressed in DLBCL tissues compared with control tissues. Taken together, the ARG-based scoring model provides a promising direction for the prognosis and immune status of DLBCL patients, and benefits the development of personalized treatment for DLBCL patients.

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Data availability

The datasets generated and/or analyzed during the current study are available in the GEO dataset (https://www.ncbi.nlm.nih.gov/geo/).

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Funding

The study was supported by National Natural Science Foundation of China (81800203), Doctoral Startup Scientific Research Foundation of Liaoning Province (20180540088) and 1 + X program for clinical competency enhancement–improvement of MDT project, the Second Affiliated Hospital of Dalian Medical University (2022MDTZY02).

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  1. Yu Liu and Jinhua Wang have contributed equally.

Authors and Affiliations

  1. Department of Infectious Disease, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People’s Republic of China

    Yu Liu

  2. Department of Hematology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, Liaoning, People’s Republic of China

    Jinhua Wang, Li Li, Xiaobo Wang & Bo Tang

  3. Department of Pathology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People’s Republic of China

    Xiaochen Shen

  4. Department of Thyroid Surgery, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, People’s Republic of China

    Ning Zhang

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  1. Yu Liu
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  4. Li Li
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Contributions

YL and LL performed the data analysis and interpreted the data. NZ collected samples. JW and XS contributed to the experiments of this study. JW prepared the draft. YL and BT performed the visualization and revised the draft. BT, YL and XW designed the research and supervised all the work. All authors contributed to the article and approved the submitted version.

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Correspondence to Xiaobo Wang or Bo Tang.

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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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The study was approved by the Ethics Committee of the Second Affiliated Hospital of Dalian Medical University (No.2023–138).

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Liu, Y., Wang, J., Shen, X. et al. A novel angiogenesis-related scoring model predicts prognosis risk and treatment responsiveness in diffuse large B-cell lymphoma. Clin Exp Med 23, 3781–3797 (2023). https://doi.org/10.1007/s10238-023-01127-9

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