Single-cell transcriptomics is a powerful tool for analyzing the tissues of living organisms. One of its applications is the analysis of the population of T-lymphocytes of people suffering from various diseases, in particular cancer. Based on the analysis of single-cell transcriptomes of T-cells infiltrating tumors, it is possible to make assumptions about progress of the disease and the appropriate therapy for the patient, as well as to study the dynamics of the development of the disease in the course of fundamental research. From this point of view, it is especially important to know which groups of lymphocytes are cycling. However, the signal of cycling stage markers in such cells is stronger than the signal of cell type markers. When defining clusters, сycling cells usually form a separate cluster, which makes it impossible to tell which cell type the cycling cell belongs to.
The main goal of this work is to develop a method for determining the types of cycling cells and its application for the analysis of T cells from the tumor microenvironment.
We have prepared 3 classification pipelines and to validate their performance we used data from single-cell sequencing of T cell receptors (TCR).
At a certain stage of maturation of a T-lymphocyte, its T cell receptors mature; during this maturation, the receptor gene sequence undergoes recombination and mutational changes, due to which it becomes unique in the hypervariable CDR3 locus . Subsequently, all descendants of a particular lymphocyte can be determined from this unique sequence. The descendants of a single lymphocyte are called a clonotype. It was noted that most of the cells of the same clonotype belong to the same cell type, but some of them may belong to the group of dividing cells. Determining clonotypes in a group of dividing cells and finding representatives of the same clonotypes in clusters of certain cell types, we can reliably tell which cell type the dividing cells belong to. We used these properties to validate the pipelines we developed.