sciCSR infers B cell state transition and predicts class-switch recombination dynamics using single-cell transcriptomic data.

Class-switch recombination (CSR) is an integral part of B cell maturation. Here we present sciCSR (pronounced 'scissor', single-cell inference of class-switch recombination), a computational pipeline that analyzes CSR events and dynamics of B cells from single-cell RNA sequencing (scRNA-seq) experiments. Validated on both simulated and real data, sciCSR re-analyzes scRNA-seq alignments to differentiate productive heavy-chain immunoglobulin transcripts from germline 'sterile' transcripts. From a snapshot of B cell scRNA-seq data, a Markov state model is built to infer the dynamics and direction of CSR. Applying sciCSR on severe acute respiratory syndrome coronavirus 2 vaccination time-course scRNA-seq data, we observe that sciCSR predicts, using data from an earlier time point in the collected time-course, the isotype distribution of B cell receptor repertoires of subsequent time points with high accuracy (cosine similarity ~0.9). Using processes specific to B cells, sciCSR identifies transitions that are often missed by conventional RNA velocity analyses and can reveal insights into the dynamics of B cell CSR during immune response.

Pan-cancer transcriptomic analysis dissects immune and proliferative functions of APOBEC3 cytidine deaminases.

APOBEC3 cytidine deaminases are largely known for their innate immune protection from viral infections. Recently, members of the family have been associated with a distinct mutational activity in some cancer types. We report a pan-tissue, pan-cancer analysis of RNA-seq data specific to the APOBEC3 genes in 8,951 tumours, 786 cancer cell lines and 6,119 normal tissues. By deconvolution of levels of different cell types in tumour admixtures, we demonstrate that APOBEC3B (A3B), the primary candidate as a cancer mutagen, shows little association with immune cell types compared to its paralogues. We present a pipeline called RESPECTEx (REconstituting SPecific Cell-Type Expression) and use it to deconvolute cell-type specific expression levels in a given cohort of tumour samples. We functionally annotate APOBEC3 co-expressing genes, and create an interactive visualization tool which 'barcodes' the functional enrichment (http://fraternalilab.kcl.ac.uk/apobec-barcodes/). These analyses reveal that A3B expression correlates with cell cycle and DNA repair genes, whereas the other APOBEC3 members display specificity for immune processes and immune cell populations. We offer molecular insights into the functions of individual APOBEC3 proteins in antiviral and proliferative contexts, and demonstrate the diversification this family of enzymes displays at the transcriptomic level, despite their high similarity in protein sequences and structures.

Short loop functional commonality identified in leukaemia proteome highlights crucial protein sub-networks.

Direct drug targeting of mutated proteins in cancer is not always possible and efficacy can be nullified by compensating protein-protein interactions (PPIs). Here, we establish an in silico pipeline to identify specific PPI sub-networks containing mutated proteins as potential targets, which we apply to mutation data of four different leukaemias. Our method is based on extracting cyclic interactions of a small number of proteins topologically and functionally linked in the Protein-Protein Interaction Network (PPIN), which we call short loop network motifs (SLM). We uncover a new property of PPINs named 'short loop commonality' to measure indirect PPIs occurring via common SLM interactions. This detects 'modules' of PPI networks enriched with annotated biological functions of proteins containing mutation hotspots, exemplified by FLT3 and other receptor tyrosine kinase proteins. We further identify functional dependency or mutual exclusivity of short loop commonality pairs in large-scale cellular CRISPR-Cas9 knockout screening data. Our pipeline provides a new strategy for identifying new therapeutic targets for drug discovery.

Tumor-Infiltrating B Lymphocyte Profiling Identifies IgG-Biased, Clonally Expanded Prognostic Phenotypes in Triple-Negative Breast Cancer.

In breast cancer, humoral immune responses may contribute to clinical outcomes, especially in more immunogenic subtypes. Here, we investigated B lymphocyte subsets, immunoglobulin expression, and clonal features in breast tumors, focusing on aggressive triple-negative breast cancers (TNBC). In samples from patients with TNBC and healthy volunteers, circulating and tumor-infiltrating B lymphocytes (TIL-B) were evaluated. CD20+CD27+IgD- isotype-switched B lymphocytes were increased in tumors, compared with matched blood. TIL-B frequently formed stromal clusters with T lymphocytes and engaged in bidirectional functional cross-talk, consistent with gene signatures associated with lymphoid assembly, costimulation, cytokine-cytokine receptor interactions, cytotoxic T-cell activation, and T-cell-dependent B-cell activation. TIL-B-upregulated B-cell receptor (BCR) pathway molecules FOS and JUN, germinal center chemokine regulator RGS1, activation marker CD69, and TNFα signal transduction via NFκB, suggesting BCR-immune complex formation. Expression of genes associated with B lymphocyte recruitment and lymphoid assembly, including CXCL13, CXCR4, and DC-LAMP, was elevated in TNBC compared with other subtypes and normal breast. TIL-B-rich tumors showed expansion of IgG but not IgA isotypes, and IgG isotype switching positively associated with survival outcomes in TNBC. Clonal expansion was biased toward IgG, showing expansive clonal families with specific variable region gene combinations and narrow repertoires. Stronger positive selection pressure was present in the complementarity determining regions of IgG compared with their clonally related IgA in tumor samples. Overall, class-switched B lymphocyte lineage traits were conspicuous in TNBC, associated with improved clinical outcomes, and conferred IgG-biased, clonally expanded, and likely antigen-driven humoral responses. SIGNIFICANCE: Tumor-infiltrating B lymphocytes assemble in clusters, undergoing B-cell receptor-driven activation, proliferation, and isotype switching. Clonally expanded, IgG isotype-biased humoral immunity associates with favorable prognosis primarily in triple-negative breast cancers.