A Single-cell Transcriptome Study in Patients With Non-Hodgkin's Lymphoma

In recent decades, the incidence of lymphoma has been increasing year by year in the world. Non-Hodgkin lymphoma accounts for about 90% of lymphoma, of which the classification is complex and the efficacy is poor compared to Hodgkin's lymphoma. Non-Hodgkin's lymphoma is often associated with the extra nodal involvement, and according to literature, extra nodal lymphoma accounts for 1/3 to 1/2 of all non-Hodgkin lymphomas. Compared with non-Hodgkin's lymphoma without extra nodal involvement, the prognosis of lymphoma with extra nodal involvement was relatively poor. The recurrence rate was higher, and its incidence, histology type, clinical staging and so on all had their own characteristics. Tumor cells depend to some extent on the interaction with non-tumor cells and matrix components of the tumor microenvironment to maintain survival and proliferation. In addition, the non tumor cells and matrix components can mediate immunosuppressive action to promote tumor escape from immunosurveillance, resulting in disease progression. At the same time, more and more data show that the tumor microenvironment plays a key role in the development of tumor resistance. The cellular composition and spatial properties of the tumor microenvironment show significant heterogeneity, depending on a number of factors, including subtypes of lymphomas and extra nodal sites of lymphomas. Studying the tumor microenvironment will provide rationale for more precise target therapy. Through single-cell RNA sequencing, this study hopes to identify the heterogeneity of nodal and extra nodal lymphoma cells, to understand the differences in tumor microenvironment, and to provide a basis for diagnosis and precision treatment. There are new target drugs for different antigen targets. But patients may not be sensitive to a certain drug, and the drug is often expensive, resulting in increased financial burden on patients without efficacy. Therefore, the research for biomarkers to predict patient efficacy and prognosis is particularly important. The treatment efficacy of patients with relapsed lymphoma is often not good, so the prediction and treatment of patients with high-risk of relapsing is a clinical significant problem. On the basis of single-cell transcriptomics, this study hopes to find biomarkers for predicting the relapse of lymphoma and provide new ideas for clinical diagnosis and treatment.