Parin Shah

Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq

Single-cell expression profiles of melanoma Tumors harbor multiple cell types that are thought to play a role in the development of resistance to drug treatments. Tirosh et al. used single-cell sequencing to investigate the distribution of these differing genetic profiles within melanomas. Many cells harbored heterogeneous genetic programs that reflected two different states of genetic expression, one of which was linked to resistance development. Following drug treatment, the resistance-linked expression state was found at a much higher level. Furthermore, the environment of the melanoma cells affected their gene expression programs. Science, this issue p. 189 Melanoma cells show transcriptional heterogeneity. To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.

Adaptive resistance of melanoma cells to RAF inhibition via reversible induction of a slowly dividing de‐differentiated state

Treatment of BRAF‐mutant melanomas with MAP kinase pathway inhibitors is paradigmatic of the promise of precision cancer therapy but also highlights problems with drug resistance that limit patient benefit. We use live‐cell imaging, single‐cell analysis, and molecular profiling to show that exposure of tumor cells to RAF/MEK inhibitors elicits a heterogeneous response in which some cells die, some arrest, and the remainder adapt to drug. Drug‐adapted cells up‐regulate markers of the neural crest (e.g., NGFR), a melanocyte precursor, and grow slowly. This phenotype is transiently stable, reverting to the drug‐naïve state within 9 days of drug withdrawal. Transcriptional profiling of cell lines and human tumors implicates a c‐Jun/ECM/FAK/Src cascade in de‐differentiation in about one‐third of cell lines studied; drug‐induced changes in c‐Jun and NGFR levels are also observed in xenograft and human tumors. Drugs targeting the c‐Jun/ECM/FAK/Src cascade as well as BET bromodomain inhibitors increase the maximum effect (Emax) of RAF/MEK kinase inhibitors by promoting cell killing. Thus, analysis of reversible drug resistance at a single‐cell level identifies signaling pathways and inhibitory drugs missed by assays that focus on cell populations.

Ex Vivo Profiling of PD-1 Blockade Using Organotypic Tumor Spheroids

Ex vivo systems that incorporate features of the tumor microenvironment and model the dynamic response to immune checkpoint blockade (ICB) may facilitate efforts in precision immuno-oncology and the development of effective combination therapies. Here, we demonstrate the ability to interrogate ex vivo response to ICB using murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS). MDOTS/PDOTS isolated from mouse and human tumors retain autologous lymphoid and myeloid cell populations and respond to ICB in short-term three-dimensional microfluidic culture. Response and resistance to ICB was recapitulated using MDOTS derived from established immunocompetent mouse tumor models. MDOTS profiling demonstrated that TBK1/IKKε inhibition enhanced response to PD-1 blockade, which effectively predicted tumor response in vivo Systematic profiling of secreted cytokines in PDOTS captured key features associated with response and resistance to PD-1 blockade. Thus, MDOTS/PDOTS profiling represents a novel platform to evaluate ICB using established murine models as well as clinically relevant patient specimens.Significance: Resistance to PD-1 blockade remains a challenge for many patients, and biomarkers to guide treatment are lacking. Here, we demonstrate feasibility of ex vivo profiling of PD-1 blockade to interrogate the tumor immune microenvironment, develop therapeutic combinations, and facilitate precision immuno-oncology efforts. Cancer Discov; 8(2); 196-215. ©2017 AACR.See related commentary by Balko and Sosman, p. 143See related article by Deng et al., p. 216This article is highlighted in the In This Issue feature, p. 127.

Bidirectional cross talk between patient-derived melanoma and cancer-associated fibroblasts promotes invasion and proliferation.

Tumor–stroma interactions are critical for epithelial‐derived tumors, and among the stromal cell types, cancer‐associated fibroblasts (CAFs) exhibit multiple functions that fuel growth, dissemination, and drug resistance. However, these interactions remain insufficiently characterized in non‐epithelial tumors such as malignant melanoma. We generated monocultures of melanoma cells and matching CAFs from patients’ metastatic lesions, distinguished by oncogenic drivers and immunoblotting of characteristic markers. RNA sequencing of CAFs revealed a homogenous epigenetic program that strongly resembled the signatures from epithelial cancers, including enrichment for an epithelial‐to‐mesenchymal transition (EMT). Melanoma CAFs in monoculture displayed robust invasive behavior while patient‐derived melanoma monocultures showed very little invasiveness. Instead, melanoma cells showed increased invasion when co‐cultured with CAFs. In turn, CAFs showed increased proliferation when exposed to melanoma conditioned media (CM), mediated in part by melanoma‐secreted transforming growth factor‐alpha that acted on CAFs via the epidermal growth factor receptor. This study provides evidence that bidirectional interactions between melanoma and CAFs regulate progression of metastatic melanoma.

A simple open-source method for highly multiplexed imaging of single cells in tissues and tumours

Intratumoural heterogeneity strongly influences the development and progression of cancer as well as responsiveness and resistance to therapy. To improve our ability to measure and analyze such heterogeneity we have developed an open source method for fluorescence imaging of up to 60 protein antigens at subcellular resolution using formalin-fixed, paraffin-embedded (FFPE) tissue samples mounted on glass slides, the most widely used specimens for the diagnosis of cancer and other diseases. As described here, tissue-based cyclic immunofluorescence (t-CyCIF) creates high-dimensional imaging data through successive acquisition of four-color images and requires no specialized instruments or reagents. We apply t-CyCIF to 14 cancer and healthy tissue types and quantify the extent of cell to cell variability in signal transduction cascades, tumor antigens and stromal markers. By imaging immune cell lineage markers we enumerate classes of tumour-infiltrating lymphocytes (TILs) and their spatial relationships to the tumor microenvironment (TME). The simplicity and adaptability of t-CyCIF makes it a powerful method for pre-clinical and clinical research and a natural complement to single-cell genomics.The architecture of normal and diseased tissues strongly influences the development and progression of disease as well as responsiveness and resistance to therapy. We describe a tissue-based cyclic immunofluorescence (t-CyCIF) method for highly multiplexed immuno-fluorescence imaging of formalin-fixed, paraffin-embedded (FFPE) specimens mounted on glass slides, the most widely used specimens for histopathological diagnosis of cancer and other diseases. t-CyCIF generates up to 60-plex images using an iterative process (a cycle) in which conventional low-plex fluorescence images are repeatedly collected from the same sample and then assembled into a high dimensional representation. t-CyCIF requires no specialized instruments or reagents and is compatible with super-resolution imaging; we demonstrate its application to quantifying signal transduction cascades, tumor antigens and immune markers in diverse tissues and tumors. The simplicity and adaptability of t-CyCIF makes it an effective method for pre-clinical and clinical research and a natural complement to single-cell genomics.

Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes

The architecture of normal and diseased tissues strongly influences the development and progression of disease as well as responsiveness and resistance to therapy. We describe a tissue-based cyclic immunofluorescence (t-CyCIF) method for highly multiplexed immuno-fluorescence imaging of formalin-fixed, paraffin-embedded (FFPE) specimens mounted on glass slides, the most widely used specimens for histopathological diagnosis of cancer and other diseases. t-CyCIF generates up to 60-plex images using an iterative process (a cycle) in which conventional low-plex fluorescence images are repeatedly collected from the same sample and then assembled into a high-dimensional representation. t-CyCIF requires no specialized instruments or reagents and is compatible with super-resolution imaging; we demonstrate its application to quantifying signal transduction cascades, tumor antigens and immune markers in diverse tissues and tumors. The simplicity and adaptability of t-CyCIF makes it an effective method for pre-clinical and clinical research and a natural complement to single-cell genomics.

Abstract 3037: Dissecting treatment resistance in patients with ovarian cancer and PDX-models using single-cell RNA-sequencing

Background: Ovarian cancer (OvCa) is frequently associated with malignant effusions, which are complex ecosystems with heterogeneous populations of malignant cells and non-malignant cells. Bulk RNA-seq or whole-exome sequencing (WES) only reflect average cellular behavior and thereby mask intrinsic cell diversity with potential relevance for treatment resistance. Approach: To overcome some of these barriers, we applied single-cell RNA-sequencing (scRNA-seq) to malignant and non-malignant cells isolated from patients with platinum treatment resistant disease. Furthermore, we used patient-derived xenograft (PDX) cohorts, in which we isolated cells for scRNA-seq from vehicle tumors (VEH), treated the other models with carboplatin, and harvested cells at the time of minimal residual disease (MRD) or disease progression (PROG). Results: To date, we have profiled ~12000 single cells from 12 patients with treatment naive (n=3) or platinum-resistant disease (n=9), including sequential sampling in 3 patients with resistant disease. We observed significant inter- and intra-individual transcriptional heterogeneity in malignant cells. A recurrent pattern across resistant patients was the differential expression of inflammatory pathways in a subset of cells. In a patient with three consecutive specimens, we observed increasing accumulation of cells expressing a cell state characterized by tumor necrosis factor alpha (TNF-a) signaling, Importantly, these cells were genetically identical to the entire population, supporting the hypothesis that non-encoded mechanisms conferred treatment resistance. In a BRCA-mutant patient, unbiased analysis identified a stemness program in a subpopulation of cells, which was genetically identical to other cells, indicating phenotypic conversion. To systemically interrogate mechanisms of resistance to platinum therapy, sequenced single cells isolated from PDX models at three time points (VEH, MRD and PROG). In a BRCA-WT PDX model, resistant cells isolated at MRD and PROG shared a transcriptional program that was dominated by expression of a STAT3 program. Ex vivo cultures from platinum-resistant patients were exquisitely sensitivity to JAK/STAT3-inhibitor. Live cell imaging revealed that STAT3-inhibition prevented spheroid formation, attachment and clearance through a mesothelial monolayer in vitro. Conclusion: Our results indicate that non-encoded mechanisms play an important role in the development of treatment resistance in ovarian cancer. Our initial studies indicate an important role of inflammatory pathways in treatment resistance, in particular STAT3 signaling, which can be overcome with specific inhibitors at nanomolar concentrations. These data suggests that single-cell profiling can be performed on clinical ovarian cancer specimens and may yield novel therapeutic avenues for patients with treatment-resistant ovarian cancer. Citation Format: Benjamin Izar, Itay Tirosh, Elizabeth Stover, Asaf Rotem, Parin Shah, Mike Cuoco, Chris Rodman, Joyce Liu, Ursula Matulonis, Orit Rozenblatt-Rosen, Levi Garraway, Aviv Regev. Dissecting treatment resistance in patients with ovarian cancer and PDX-models using single-cell RNA-sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3037. doi:10.1158/1538-7445.AM2017-3037