SCITO-seq: single-cell combinatorial indexed cytometry sequencing.

The development of DNA-barcoded antibodies to tag cell surface molecules has enabled the use of droplet-based single-cell sequencing (dsc-seq) to profile protein abundances from thousands of cells simultaneously. As compared to flow and mass cytometry, the high per cell cost of current dsc-seq-based workflows precludes their use in clinical applications and large-scale pooled screens. Here, we introduce SCITO-seq, a workflow that uses splint oligonucleotides (oligos) to enable combinatorially indexed dsc-seq of DNA-barcoded antibodies from over 105 cells per reaction using commercial microfluidics. By encoding sample barcodes into splint oligos, we demonstrate that multiplexed SCITO-seq produces reproducible estimates of cellular composition and surface protein expression comparable to those from mass cytometry. We further demonstrate two modified splint oligo designs that extend SCITO-seq to achieve compatibility with commercial DNA-barcoded antibodies and simultaneous expression profiling of the transcriptome and surface proteins from the same cell. These results demonstrate SCITO-seq as a flexible and ultra-high-throughput platform for sequencing-based single-cell protein and multimodal profiling.

Nivolumab and ipilimumab are associated with distinct immune landscape changes and response-associated immunophenotypes.

BACKGROUNDThe reshaping of the immune landscape by nivolumab (NIVO) and ipilimumab (IPI) and its relation to patient outcomes is not well described.METHODSWe used high-parameter flow cytometry and a computational platform, CytoBrute, to define immunophenotypes of up to 15 markers to assess peripheral blood samples from metastatic melanoma patients receiving sequential NIVO > IPI or IPI > NIVO (Checkmate-064).RESULTSThe 2 treatments were associated with distinct immunophenotypic changes and had differing profiles associated with response. Only 2 immunophenotypes were shared but had opposing relationships to response/survival. To understand the impact of sequential treatment on response/survival, phenotypes that changed after the initial treatment and differentiated response in the other cohort were identified. Immunophenotypic changes occurring after NIVO were predominately associated with response to IPI > NIVO, but changes occurring after IPI were predominately associated with progression after NIVO > IPI. Among these changes, CD4+CD38+CD39+CD127-GARP- T cell subsets were increased after IPI treatment and were negatively associated with response/survival for the NIVO > IPI cohort.CONCLUSIONCollectively, these data suggest that the impact of IPI and NIVO on the immunophenotypic landscape of patients is distinct and that the impact of IPI may be associated with resistance to subsequent NIVO therapy, consistent with poor outcomes in the IPI > NIVO cohort of Checkmate-064.

High-Parameter Single-Cell Analysis.

Thousands of transcripts and proteins confer function and discriminate cell types in the body. Using high-parameter technologies, we can now measure many of these markers at once, and multiple platforms are now capable of analysis on a cell-by-cell basis. Three high-parameter single-cell technologies have particular potential for discovering new biomarkers, revealing disease mechanisms, and increasing our fundamental understanding of cell biology. We review these three platforms (high-parameter flow cytometry, mass cytometry, and a new class of technologies called integrated molecular cytometry platforms) in this article. We describe the underlying hardware and instrumentation, the reagents involved, and the limitations and advantages of each platform. We also highlight the emerging field of high-parameter single-cell data analysis, providing an accessible overview of the data analysis process and choice of tools.

Molecular definition of a metastatic lung cancer state reveals a targetable CD109-Janus kinase-Stat axis.

Lung cancer is the leading cause of cancer deaths worldwide, with the majority of mortality resulting from metastatic spread. However, the molecular mechanism by which cancer cells acquire the ability to disseminate from primary tumors, seed distant organs, and grow into tissue-destructive metastases remains incompletely understood. We combined tumor barcoding in a mouse model of human lung adenocarcinoma with unbiased genomic approaches to identify a transcriptional program that confers metastatic ability and predicts patient survival. Small-scale in vivo screening identified several genes, including Cd109, that encode novel pro-metastatic factors. We uncovered signaling mediated by Janus kinases (Jaks) and the transcription factor Stat3 as a critical, pharmacologically targetable effector of CD109-driven lung cancer metastasis. In summary, by coupling the systematic genomic analysis of purified cancer cells in distinct malignant states from mouse models with extensive human validation, we uncovered several key regulators of metastatic ability, including an actionable pro-metastatic CD109-Jak-Stat3 axis.