Dissecting intratumor heterogeneity of nodal B cell lymphomas on the transcriptional, genetic, and drug response level

Abstract

Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer drugs, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

Dissecting intratumour heterogeneity of nodal B-cell lymphomas at the transcriptional, genetic and drug-response levels

“…Alignment of sequencing read pairs and variant calling were performed as recently described [66]. Briefly, reads were mapped to human reference genome (hg19) with bwa-mem (version 0.7.8, minimum base quality threshold set to zero [-T 0], remaining settings left to default) [67].…”

“…SNV and indels in matched tumor normal pairs were identified using the internal DKFZ variant calling workflows based on samtools/bcftools 0.1.19 with additional custom filters (optimized for somatic variant calling by deactivating the pval-threshold in bcftools) and Platypus 0.8.1, respectively, as described previously [66]. Gene annotation of variants was done with Annovar [68].…”

“…While bulk genomic tissue profiling has only a limited ability to reconstruct the complex cellular composition of tumors, single cell DNA-sequencing [6,7] and RNA-sequencing (scRNA-seq) methods [8][9][10][11] have emerged as powerful tools to study intratumor heterogeneity and reconstruct the full picture of malignant and non-malignant cells. These technologies further enable researchers to identify rare cell types such as cancer stem cells [12] and circulating tumor cells [13,14], or to follow clonal dynamics during cancer treatment [15].…”

EOMES is essential for antitumor activity of CD8+ T cells in chronic lymphocytic leukemia

“…For flow cytometry staining, samples were thawed and let rest for 3 h before further processing. LN samples were processed as previously described [44].…”

The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma

“…Recently, the advent of single-cell RNA sequencing (scRNAseq) has enabled detailed surveys of cell subsets in diverse tumor types (Suva `and Tirosh, 2019). For example, scRNA-seq studies identified checkpoint molecule expression on lymphoma-associated T cell subsets (Andor et al, 2019;Aoki et al, 2020) and have uncovered the impact of tumor subclonal heterogeneity on drug response (Roider et al, 2020). While such studies can provide critical insights into clinically relevant cellular diversity, scRNA-seq studies of lymphomas have thus far been of moderate size and are potentially prone to dissociation distortions and patient-specific heterogeneity (Segerstolpe et al, 2016;van den Brink et al, 2017).…”