The biological and functional heterogeneity between tumors-both across and within cancer types-poses a challenge for immunotherapy. To understand the factors underlying tumor immune heterogeneity and immunotherapy sensitivity, we established a library of congenic tumor cell clones from an autochthonous mouse model of pancreatic adenocarcinoma. These clones generated tumors that recapitulated T cell-inflamed and non-T-cell-inflamed tumor microenvironments upon implantation in immunocompetent mice, with distinct patterns of infiltration by immune cell subsets. Co-injecting tumor cell clones revealed the non-T-cell-inflamed phenotype is dominant and that both quantitative and qualitative features of intratumoral CD8 T cells determine response to therapy. Transcriptomic and epigenetic analyses revealed tumor-cell-intrinsic production of the chemokine CXCL1 as a determinant of the non-T-cell-inflamed microenvironment, and ablation of CXCL1 promoted T cell infiltration and sensitivity to a combination immunotherapy regimen. Thus, tumor cell-intrinsic factors shape the tumor immune microenvironment and influence the outcome of immunotherapy.

Summary Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells, where information regarding genetic heterogeneity is lost. Here, we present a protocol that allows for the genome wide copy number analysis of single nuclei isolated from mixed populations of cells. Single nucleus sequencing (SNS), combines flow sorting of single nuclei based on DNA content, whole genome amplification (WGA), followed by next generation sequencing to quantize genomic intervals in a genome wide manner. Multiplexing of single cells is discussed. Additionally, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ~3 days from flow cytometry to sequence-ready DNA libraries.

We present an open-source web platform, Ginkgo (http://qb.cshl.edu/ginkgo), for the analysis and assessment of single-cell copy-number variations (CNVs). Ginkgo automatically constructs copy-number profiles of cells from mapped reads and constructs phylogenetic trees of related cells. We validate Ginkgo by reproducing the results of five major studies and examine the characteristics of three commonly used single-cell amplification techniques to conclude degenerate oligonucleotide-primed PCR to be the most consistent for CNV analysis.