Integrated single cell analysis reveals co-evolution of malignant B cells and the tumor microenvironment in transformed follicular lymphoma

Table of Contents

1. Abstract
2. Patient cohort
3. Code structure
4. Publication
5. Acknowledgement

Abstract

• Histological transformation of follicular lymphoma to aggressive form occurs 2-3% per year with poor outcome. Divergent evolution and an altered tumour-microenvironment (TME) have been implicated during transformation. However, phenotypic consequences of this evolution and its implication in TME remain unknown. To address this, we performed single cell whole genome and whole transcriptome sequencing of paired pre/post transformation patient samples. We further performed scWTS of additional samples from patients without transformation. Our analysis revealed evolutionary dynamics of transformation at unprecedented resolution. Integration of scWGS and scWTS identified pathways upregulated during evolution. scWTS analysis revealed a shifting TME landscape, with an exhausted signature emerging during transformation. Using multi-color immunofluorescence we transferred these findings to a TME-based transformation biomarker, subsequently validated in independent pretreatment cohorts. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation, and shifting cross-talk between malignant cells and TME.

Patient cohort

• 11 patients diagnosed with FL but no transformation.
• 11 patients diagnosed with FL and later transformed to DLBCL (two biopsies).
• 2 patients without FL for reactive lymph node biopsy.

Code structure

1. Data preprocessing: 10x BCL files was processed with Cellranger (v3.0.2) and then processed with the Snakefile pipeline to generate a filtered, normalized, batch-corrected SingleCellExperiment object (and monocle3 CellDataSet object) with cell cycle annotations. BCR data was processed with Cellranger vdj to generate clonotype information. DLP data was processed with single cell pipeline to generate phylogenetic trees and clones.
2. Differential expression: DE was also performed with the Snakefile pipeline.
3. Clonealign: For each patient, clonealign was performed using the 10x data (malignant B cells only) and the clone profiles from the DLP data (run parse_cnv pipeline then align_clones pipeline in clonealign folder).
4. IHC: the merge_marker_data.R was used to merge all marker data into one merged dataframe. The distance_analysis_IHC.Rmd file was used to analyze spatial distribution between two phenotypes in the merged dataframe and the DistanceFunctions.r provides utility functions for the Rmd file. (The IHC data for both 11-pair experiment cohort and validation cohort were processed with this pipeline).
5. Survival: analysis was performed using the survival_analysis.R script.

Publication

Integrated single cell analysis reveals co-evolution of malignant B cells and the tumor microenvironment in transformed follicular lymphoma

Acknowledgement

• Roth lab, University of British Columbia.