Single-cell RNA-seq meta-analysis in Richter's transformation

Richter’s transformation (RT), characterised by progression from chronic lymphocytic leukaemia (CLL) to an aggressive lymphoma phenotype, remains associated with poor clinical outcomes. This progression is strongly influenced by the tumour microenvironment (TME), which promotes tumour survival and facilitates immune evasion. Herein, we performed an integrative single-cell data analysis with batch correction across seven human RT studies identified through PubMed, Scopus, and Web of Science. The integrated dataset, comprising 593,424 cells, enabled the construction of a simulated biological system of RT progression and facilitated the investigation of tumour-microenvironment interplay through gene expression profiling, cell–cell communication, and trajectory analyses. Consistent with findings from previous individual tumour studies, tumour heterogeneity remained evident following batch correction. This repository contains processed count matrices for both bulk and single-cell RNA-seq data, together with associated metadata and R objects used in our analyses.