Clearance of senescent macrophages ameliorates tumorigenesis in KRAS-driven lung cancer.

The accumulation of senescent cells in the tumor microenvironment can drive tumorigenesis in a paracrine manner through the senescence-associated secretory phenotype (SASP). Using a new p16-FDR mouse line, we show that macrophages and endothelial cells are the predominant senescent cell types in murine KRAS-driven lung tumors. Through single cell transcriptomics, we identify a population of tumor-associated macrophages that express a unique array of pro-tumorigenic SASP factors and surface proteins and are also present in normal aged lungs. Genetic or senolytic ablation of senescent cells, or macrophage depletion, result in a significant decrease in tumor burden and increased survival in KRAS-driven lung cancer models. Moreover, we reveal the presence of macrophages with senescent features in human lung pre-malignant lesions, but not in adenocarcinomas. Taken together, our results have uncovered the important role of senescent macrophages in the initiation and progression of lung cancer, highlighting potential therapeutic avenues and cancer preventative strategies.

Patterns of Oncogene Coexpression at Single-Cell Resolution Influence Survival in Lymphoma.

Cancers often overexpress multiple clinically relevant oncogenes, but it is not known if combinations of oncogenes in cellular subpopulations within a cancer influence clinical outcomes. Using quantitative multispectral imaging of the prognostically relevant oncogenes MYC, BCL2, and BCL6 in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination MYC+BCL2+BCL6- (M+2+6-) consistently predicts survival across four independent cohorts (n = 449), an effect not observed with other combinations including M+2+6+. We show that the M+2+6- percentage can be mathematically derived from quantitative measurements of the individual oncogenes and correlates with survival in IHC (n = 316) and gene expression (n = 2,521) datasets. Comparative bulk/single-cell transcriptomic analyses of DLBCL samples and MYC/BCL2/BCL6-transformed primary B cells identify molecular features, including cyclin D2 and PI3K/AKT as candidate regulators of M+2+6- unfavorable biology. Similar analyses evaluating oncogenic combinations at single-cell resolution in other cancers may facilitate an understanding of cancer evolution and therapy resistance. SIGNIFICANCE: Using single-cell-resolved multiplexed imaging, we show that selected subpopulations of cells expressing specific combinations of oncogenes influence clinical outcomes in lymphoma. We describe a probabilistic metric for the estimation of cellular oncogenic coexpression from IHC or bulk transcriptomes, with possible implications for prognostication and therapeutic target discovery in cancer. This article is highlighted in the In This Issue feature, p. 1027.

bulkAnalyseR: an accessible, interactive pipeline for analysing and sharing bulk multi-modal sequencing data.

Bulk sequencing experiments (single- and multi-omics) are essential for exploring wide-ranging biological questions. To facilitate interactive, exploratory tasks, coupled with the sharing of easily accessible information, we present bulkAnalyseR, a package integrating state-of-the-art approaches using an expression matrix as the starting point (pre-processing functions are available as part of the package). Static summary images are replaced with interactive panels illustrating quality-checking, differential expression analysis (with noise detection) and biological interpretation (enrichment analyses, identification of expression patterns, followed by inference and comparison of regulatory interactions). bulkAnalyseR can handle different modalities, facilitating robust integration and comparison of cis-, trans- and customised regulatory networks.

Viral transduction of primary human lymphoma B cells reveals mechanisms of NOTCH-mediated immune escape.

Hotspot mutations in the PEST-domain of NOTCH1 and NOTCH2 are recurrently identified in B cell malignancies. To address how NOTCH-mutations contribute to a dismal prognosis, we have generated isogenic primary human tumor cells from patients with Chronic Lymphocytic Leukemia (CLL) and Mantle Cell Lymphoma (MCL), differing only in their expression of the intracellular domain (ICD) of NOTCH1 or NOTCH2. Our data demonstrate that both NOTCH-paralogs facilitate immune-escape of malignant B cells by up-regulating PD-L1, partly dependent on autocrine interferon-γ signaling. In addition, NOTCH-activation causes silencing of the entire HLA-class II locus via epigenetic regulation of the transcriptional co-activator CIITA. Notably, while NOTCH1 and NOTCH2 govern similar transcriptional programs, disease-specific differences in their expression levels can favor paralog-specific selection. Importantly, NOTCH-ICD also strongly down-regulates the expression of CD19, possibly limiting the effectiveness of immune-therapies. These NOTCH-mediated immune escape mechanisms are associated with the expansion of exhausted CD8+ T cells in vivo.

Myeloid cell interferon secretion restricts Zika flavivirus infection of developing and malignant human neural progenitor cells.

Zika virus (ZIKV) can infect human developing brain (HDB) progenitors resulting in epidemic microcephaly, whereas analogous cellular tropism offers treatment potential for the adult brain cancer, glioblastoma (GBM). We compared productive ZIKV infection in HDB and GBM primary tissue explants that both contain SOX2+ neural progenitors. Strikingly, although the HDB proved uniformly vulnerable to ZIKV infection, GBM was more refractory, and this correlated with an innate immune expression signature. Indeed, GBM-derived CD11b+ microglia/macrophages were necessary and sufficient to protect progenitors against ZIKV infection in a non-cell autonomous manner. Using SOX2+ GBM cell lines, we found that CD11b+-conditioned medium containing type 1 interferon beta (IFNß) promoted progenitor resistance to ZIKV, whereas inhibition of JAK1/2 signaling restored productive infection. Additionally, CD11b+ conditioned medium, and IFNß treatment rendered HDB progenitor lines and explants refractory to ZIKV. These findings provide insight into neuroprotection for HDB progenitors as well as enhanced GBM oncolytic therapies.

noisyR: enhancing biological signal in sequencing datasets by characterizing random technical noise.

High-throughput sequencing enables an unprecedented resolution in transcript quantification, at the cost of magnifying the impact of technical noise. The consistent reduction of random background noise to capture functionally meaningful biological signals is still challenging. Intrinsic sequencing variability introducing low-level expression variations can obscure patterns in downstream analyses. We introduce noisyR, a comprehensive noise filter to assess the variation in signal distribution and achieve an optimal information-consistency across replicates and samples; this selection also facilitates meaningful pattern recognition outside the background-noise range. noisyR is applicable to count matrices and sequencing data; it outputs sample-specific signal/noise thresholds and filtered expression matrices. We exemplify the effects of minimizing technical noise on several datasets, across various sequencing assays: coding, non-coding RNAs and interactions, at bulk and single-cell level. An immediate consequence of filtering out noise is the convergence of predictions (differential-expression calls, enrichment analyses and inference of gene regulatory networks) across different approaches.