Tumour infiltrating B cells discriminate checkpoint blockade-induced responses.

BACKGROUND: Immune cell-driven anti-cancer activity is paramount for effective responses to checkpoint inhibitors (ICB). However, the contribution of the different immune cell subsets in the circulation and within the tumour is poorly understood. MATERIALS AND METHODS: To elucidate the role of the different cell subsets in anti-tumour responses elicited by ICB, we performed single-cell analysis of the transcriptome and surface proteome of paired pre- and early on-treatment metastatic melanoma tumour biopsies and matched peripheral blood mononuclear cell samples. We next compared the survival of metastatic melanoma patients treated with ICB according to the abundance of pre-treatment tumour-infiltrating B cell clonotypes. RESULTS: We identified cell clusters associated with disease control or progression, defined differential expression of biological pathways likely involved in the immune awakening against the tumour and examined how cell-cell communication patterns between the tumour cell subsets change during treatment. Furthermore, we discovered that B cells (immunoglobulin expression and abundance of B cell clonotypes) discriminate the clinical response after ICB and propose that B cells likely contribute to anti-tumour immunity by antigen presentation through major histocompatibility complex molecules. Finally, we demonstrated that the abundance of tumour-infiltrating B cell clonotypes at baseline identifies two distinct risk groups, a finding that we confirmed in an independent cohort. CONCLUSIONS: Our exploratory translational study provides new insights on the mechanistic role of B cells in anti-melanoma immunity during treatment with ICB. Additionally, we support pre-treatment B cell tumour infiltration as a promising prognostic biomarker to be further validated as a tool for clinical risk stratification.

Publisher Correction: Pulmonary venous circulating tumor cell dissemination before tumor resection and disease relapse.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A biobank of small cell lung cancer CDX models elucidates inter- and intratumoral phenotypic heterogeneity.

Although small cell lung cancer (SCLC) is treated as a homogeneous disease, biopsies and preclinical models reveal heterogeneity in transcriptomes and morphology. SCLC subtypes were recently defined by neuroendocrine transcription factor (NETF) expression. Circulating-tumor-cell-derived explant models (CDX) recapitulate donor patients' tumor morphology, diagnostic NE marker expression and chemotherapy responses. We describe a biobank of 38 CDX models, including six CDX pairs generated pretreatment and at disease progression revealing complex intra- and intertumoral heterogeneity. Transcriptomic analysis confirmed three of four previously described subtypes based on ASCL1, NEUROD1 and POU2F3 expression and identified a previously unreported subtype based on another NETF, ATOH1. We document evolution during disease progression exemplified by altered MYC and NOTCH gene expression, increased 'variant' cell morphology, and metastasis without strong evidence of epithelial to mesenchymal transition. This CDX biobank provides a research resource to facilitate SCLC personalized medicine.

Pulmonary venous circulating tumor cell dissemination before tumor resection and disease relapse.

Approximately 50% of patients with early-stage non-small-cell lung cancer (NSCLC) who undergo surgery with curative intent will relapse within 5 years1,2. Detection of circulating tumor cells (CTCs) at the time of surgery may represent a tool to identify patients at higher risk of recurrence for whom more frequent monitoring is advised. Here we asked whether CellSearch-detected pulmonary venous CTCs (PV-CTCs) at surgical resection of early-stage NSCLC represent subclones responsible for subsequent disease relapse. PV-CTCs were detected in 48% of 100 patients enrolled into the TRACERx study3, were associated with lung-cancer-specific relapse and remained an independent predictor of relapse in multivariate analysis adjusted for tumor stage. In a case study, genomic profiling of single PV-CTCs collected at surgery revealed higher mutation overlap with metastasis detected 10 months later (91%) than with the primary tumor (79%), suggesting that early-disseminating PV-CTCs were responsible for disease relapse. Together, PV-CTC enumeration and genomic profiling highlight the potential of PV-CTCs as early predictors of NSCLC recurrence after surgery. However, the limited sensitivity of PV-CTCs in predicting relapse suggests that further studies using a larger, independent cohort are warranted to confirm and better define the potential clinical utility of PV-CTCs in early-stage NSCLC.

Next-Generation Sequencing Analysis and Algorithms for PDX and CDX Models.

Patient-derived xenograft (PDX) and circulating tumor cell-derived explant (CDX) models are powerful methods for the study of human disease. In cancer research, these methods have been applied to multiple questions, including the study of metastatic progression, genetic evolution, and therapeutic drug responses. As PDX and CDX models can recapitulate the highly heterogeneous characteristics of a patient tumor, as well as their response to chemotherapy, there is considerable interest in combining them with next-generation sequencing to monitor the genomic, transcriptional, and epigenetic changes that accompany oncogenesis. When used for this purpose, their reliability is highly dependent on being able to accurately distinguish between sequencing reads that originate from the host, and those that arise from the xenograft itself. Here, we demonstrate that failure to correctly identify contaminating host reads when analyzing DNA- and RNA-sequencing (DNA-Seq and RNA-Seq) data from PDX and CDX models is a major confounding factor that can lead to incorrect mutation calls and a failure to identify canonical mutation signatures associated with tumorigenicity. In addition, a highly sensitive algorithm and open source software tool for identifying and removing contaminating host sequences is described. Importantly, when applied to PDX and CDX models of melanoma, these data demonstrate its utility as a sensitive and selective tool for the correction of PDX- and CDX-derived whole-exome and RNA-Seq data.Implications: This study describes a sensitive method to identify contaminating host reads in xenograft and explant DNA- and RNA-Seq data and is applicable to other forms of deep sequencing. Mol Cancer Res; 15(8); 1012-6. ©2017 AACR.

VIH2 Regulates the Synthesis of Inositol Pyrophosphate InsP8 and Jasmonate-Dependent Defenses in Arabidopsis.

Diphosphorylated inositol polyphosphates, also referred to as inositol pyrophosphates, are important signaling molecules that regulate critical cellular activities in many eukaryotic organisms, such as membrane trafficking, telomere maintenance, ribosome biogenesis, and apoptosis. In mammals and fungi, two distinct classes of inositol phosphate kinases mediate biosynthesis of inositol pyrophosphates: Kcs1/IP6K- and Vip1/PPIP5K-like proteins. Here, we report that PPIP5K homologs are widely distributed in plants and that Arabidopsis thaliana VIH1 and VIH2 are functional PPIP5K enzymes. We show a specific induction of inositol pyrophosphate InsP8 by jasmonate and demonstrate that steady state and jasmonate-induced pools of InsP8 in Arabidopsis seedlings depend on VIH2. We identify a role of VIH2 in regulating jasmonate perception and plant defenses against herbivorous insects and necrotrophic fungi. In silico docking experiments and radioligand binding-based reconstitution assays show high-affinity binding of inositol pyrophosphates to the F-box protein COI1-JAZ jasmonate coreceptor complex and suggest that coincidence detection of jasmonate and InsP8 by COI1-JAZ is a critical component in jasmonate-regulated defenses.

Crystal structure and functional mechanism of a human antimicrobial membrane channel.

Multicellular organisms fight bacterial and fungal infections by producing peptide-derived broad-spectrum antibiotics. These host-defense peptides compromise the integrity of microbial cell membranes and thus evade pathways by which bacteria develop rapid antibiotic resistance. Although more than 1,700 host-defense peptides have been identified, the structural and mechanistic basis of their action remains speculative. This impedes the desired rational development of these agents into next-generation antibiotics. We present the X-ray crystal structure as well as solid-state NMR spectroscopy, electrophysiology, and MD simulations of human dermcidin in membranes that reveal the antibiotic mechanism of this major human antimicrobial, found to suppress Staphylococcus aureus growth on the epidermal surface. Dermcidin forms an architecture of high-conductance transmembrane channels, composed of zinc-connected trimers of antiparallel helix pairs. Molecular dynamics simulations elucidate the unusual membrane permeation pathway for ions and show adjustment of the pore to various membranes. Our study unravels the comprehensive mechanism for the membrane-disruptive action of this mammalian host-defense peptide at atomistic level. The results may form a foundation for the structure-based design of peptide antibiotics.