Development of a novel prognostic model for mantle cell lymphoma based on quantitative detection of CD3 by Quantitative Dot Blot

Ning Zhu^1,2Yunjun Wang²Jiajia Hu³Xiaoyan Lin⁴Cuijuan Zhang⁵Fangrong Tang⁶Guohua Yu^1,2*

• ¹Department of Pathology, Binzhou Medical University, Binzhou, China
• ²Department of Pathology, Yantai Yuhuangding Hospital, Yantai, Shandong Province, China
• ³Department of Pathology, College of Basic Medical Sciences, Southwest Medical University, Luzhou, China
• ⁴Department of Pathology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
• ⁵Department of Pathology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
• ⁶Yantai Quanticision Diagnostics, Inc., a Division of Quanticision Diagnostics, Inc., of USA, Yantai, China

Background The Mantle Cell Lymphoma International Prognostic Index (MIPI) is the standard risk stratification model, but it primarily relies on clinical parameters and does not incorporate molecular markers. Studies suggest that CD3+ T cells, as a key component of the tumor microenvironment (TME), play a crucial role in mantle cell lymphoma (MCL) progression and prognosis. However, conventional immunohistochemistry (IHC) has limitations in quantifying CD3 expression due to its subjectivity and variability. Quantitative Dot Blot (QDB) is an emerging high-throughput protein quantification technique that allows for precise measurement of CD3+ T cells. This study aimed to evaluate the prognostic significance of CD3+ T cells quantified using QDB and IHC in MCL patients and to introduce the MIPI/CD3 model to enhance risk stratification and improve prognostic accuracy. Methods A retrospective analysis of 120 newly diagnosed MCL patients from four hospitals between 2008 2 / 11 and 2020. The CD3 expression was assessed using both IHC and QDB. Patients were classified into CD3low and CD3high groups based on an optimal cutoff value. MIPI and MIPI-c scores were calculated, and a novel MIPI/CD3 model was developed by integrating QDB-based CD3 quantification. Kaplan-Meier survival curves were used to evaluate overall survival (OS), and differences between groups were compared using the log-rank test. A p-value < 0.05 was considered statistically significant. Results CD3 quantification by IHC was correlated with OS (p=0.47), whereas QDB-based CD3 quantification showed a significant association with OS (p=0.0051), with the CD3high group exhibiting better prognosis compared to the CD3low group. The MIPI/CD3 model outperformed both the MIPI and MIPI-c models in prognostic prediction (p=0.0075) and demonstrated greater accuracy in distinguishing between low-risk and high-risk patients. Conclusion CD3+ T cells are an important prognostic biomarker in MCL, with high expression indicating a better prognosis. Integrating CD3 into the MIPI model enhances risk stratification accuracy. Compared to traditional IHC, QDB provides a more precise and reliable method for measuring CD3+ T cells. However, further validation in larger MCL cohorts is necessary to confirm its clinical utility. Future research should integrate immune and molecular biomarkers to further refine MCL risk models and advance personalized treatment.