Dataset Information

Transcriptional profiling of tumor associated macrophages in human renal cell carcinoma reveals significant heterogeneity and opportunity for immunomodulation.

ABSTRACT: Among the more notable immunotherapies are checkpoint inhibitors, which prevent suppressive signaling on T cells, thereby (re)activating them to kill tumor cells. Despite remarkable treatment responses to immune checkpoint blockade, with a subset of patients achieving complete responses, a large population have little-to-no response, dictating the necessity of further research in this field. Myeloid derived cells heavily infiltrate the tumor microenvironment (TME) of many cancers and are believed to have a number of potent anti-inflammatory effects. Here we use primary non-metastatic renal cell carcinoma to interrogate the gene expression profiles of M2-tumor associated macrophages (M2-TAMs). We performed Fluorescent Activated Cell (FACS) sorting on monocytes from the peripheral blood and tumors of fresh clear cell renal cell carcinoma (ccRCC) samples obtained after patients underwent a partial (7 patients-87.5%) or radical (1 patient-12.5%) nephrectomy. We then utilized NanoString gene expression profiling to show that TAMs express a heterogeneous transcriptional profile that does not cleanly fit into the traditional M1-M2 TAM paradigm. We identified expression of M1 associated costimulatory molecules, a multitude of diverse chemokines, canonical M2 associated molecules, as well as factors involved in the Complement system and checkpoint receptors. Our data are in agreement with other published literature investigating TAMs in various non-ccRCC TMEs, and support the growing literature concerning expression of Complement factors and checkpoint receptors on TAMs.

SUBMITTER: Nirschl TR

PROVIDER: S-EPMC7076295 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Transcriptional profiling of tumor associated macrophages in human renal cell carcinoma reveals significant heterogeneity and opportunity for immunomodulation.

Nirschl Thomas R TR El Asmar Margueritta M Ludwig Wesley W WW Ganguly Sudipto S Gorin Michael A MA Johnson Michael H MH Pierorazio Phillip M PM Drake Charles G CG Allaf Mohamad E ME Zarif Jelani C JC

American journal of clinical and experimental urology 20200225 1

Among the more notable immunotherapies are checkpoint inhibitors, which prevent suppressive signaling on T cells, thereby (re)activating them to kill tumor cells. Despite remarkable treatment responses to immune checkpoint blockade, with a subset of patients achieving complete responses, a large population have little-to-no response, dictating the necessity of further research in this field. Myeloid derived cells heavily infiltrate the tumor microenvironment (TME) of many cancers and are believe ...[more]

PMID: 32211454

Similar Datasets

Project description:BackgroundThe combination of immune checkpoint blockade (ICB) with standard therapies is becoming a common approach for overcoming resistance to cancer immunotherapy in most human malignancies including metastatic renal cell carcinoma (mRCC). In this regard, insights into the immunomodulatory properties of antiangiogenic agents may help designing multidrug schedules based on specific immune synergisms.MethodsWe used orthogonal transcriptomic and phenotyping platforms combined with functional analytic pipelines to elucidate the immunomodulatory effect of the antiangiogenic agent pazopanib in mRCC patients. Nine patients were studied longitudinally over a period of 6 months. We also analyzed transcriptional data from The Cancer Genome Atlas (TCGA) RCC cohort (N = 571) to assess the prognostic implications of our findings. The effect of pazopanib was assessed in vitro on NK cells and T cells. Additionally, myeloid-derived suppressor (MDSC)-like cells were generated from CD14+ monocytes transfected with mimics of miRNAs associated with MDSC function in the presence or absence of pazopanib.ResultsPazopanib administration caused a rapid and dramatic reshaping in terms of frequency and transcriptional activity of multiple blood immune cell subsets, with a downsizing of MDSC and regulatory T cells in favor of a strong enhancement in PD-1 expressing cytotoxic T and Natural Killer effectors. These changes were paired with an increase of the expression of transcripts reflecting activation of immune-effector functions. This immunomodulation was marked but transient, peaking at the third month of treatment. Moreover, the intratumoral expression level of a MDSC signature (MDSC INT) was strongly associated with poor prognosis in RCC patients. In vitro experiments indicate that the observed immunomodulation might be due to an inhibitory effect on MDSC-mediated suppression, rather than a direct effect on NK and T cells.ConclusionsThe marked but transient nature of this immunomodulation, peaking at the third month of treatment, provides the rationale for the use of antiangiogenics as a preconditioning strategy to improve the efficacy of ICB.

Project description:BACKGROUND:The two Caenorhabditis elegans somatic gonadal precursors (SGPs) are multipotent progenitors that generate all somatic tissues of the adult reproductive system. The sister cells of the SGPs are two head mesodermal cells (hmcs); one hmc dies by programmed cell death and the other terminally differentiates. Thus, a single cell division gives rise to one multipotent progenitor and one differentiated cell with identical lineage histories. We compared the transcriptomes of SGPs and hmcs in order to learn the determinants of multipotency and differentiation in this lineage. RESULTS:We generated a strain that expressed fluorescent markers specifically in SGPs (ehn-3A::tdTomato) and hmcs (bgal-1::GFP). We dissociated cells from animals after the SGP/hmc cell division, but before the SGPs had further divided, and subjected the dissociated cells to fluorescence-activated cell sorting to collect isolated SGPs and hmcs. We analyzed the transcriptomes of these cells and found that 5912 transcripts were significantly differentially expressed, with at least two-fold change in expression, between the two cell types. The hmc-biased genes were enriched with those that are characteristic of neurons. The SGP-biased genes were enriched with those indicative of cell proliferation and development. We assessed the validity of our differentially expressed genes by examining existing reporters for five of the 10 genes with the most significantly biased expression in SGPs and found that two showed expression in SGPs. For one reporter that did not show expression in SGPs, we generated a GFP knock-in using CRISPR/Cas9. This reporter, in the native genomic context, was expressed in SGPs. CONCLUSIONS:We found that the transcriptional profiles of SGPs and hmcs are strikingly different. The hmc-biased genes are enriched with those that encode synaptic transmission machinery, which strongly suggests that it has neuron-like signaling properties. In contrast, the SGP-biased genes are enriched with genes that encode factors involved in transcription and translation, as would be expected from a cell preparing to undergo proliferative divisions. Mediators of multipotency are likely to be among the genes differentially expressed in SGPs.

Project description:BackgroundTranscriptional dysregulation drives cancer formation but the underlying mechanisms are still poorly understood. Renal cell carcinoma (RCC) is the most common malignant kidney tumor which canonically activates the hypoxia-inducible transcription factor (HIF) pathway. Despite intensive study, novel therapeutic strategies to target RCC have been difficult to develop. Since the RCC epigenome is relatively understudied, we sought to elucidate key mechanisms underpinning the tumor phenotype and its clinical behavior.MethodsWe performed genome-wide chromatin accessibility (DNase-seq) and transcriptome profiling (RNA-seq) on paired tumor/normal samples from 3 patients undergoing nephrectomy for removal of RCC. We incorporated publicly available data on HIF binding (ChIP-seq) in a RCC cell line. We performed integrated analyses of these high-resolution, genome-scale datasets together with larger transcriptomic data available through The Cancer Genome Atlas (TCGA).FindingsThough HIF transcription factors play a cardinal role in RCC oncogenesis, we found that numerous transcription factors with a RCC-selective expression pattern also demonstrated evidence of HIF binding near their gene body. Examination of chromatin accessibility profiles revealed that some of these transcription factors influenced the tumor's regulatory landscape, notably the stem cell transcription factor POU5F1 (OCT4). Elevated POU5F1 transcript levels were correlated with advanced tumor stage and poorer overall survival in RCC patients. Unexpectedly, we discovered a HIF-pathway-responsive promoter embedded within a endogenous retroviral long terminal repeat (LTR) element at the transcriptional start site of the PSOR1C3 long non-coding RNA gene upstream of POU5F1. RNA transcripts are induced from this promoter and read through PSOR1C3 into POU5F1 producing a novel POU5F1 transcript isoform. Rather than being unique to the POU5F1 locus, we found that HIF binds to several other transcriptionally active LTR elements genome-wide correlating with broad gene expression changes in RCC.InterpretationIntegrated transcriptomic and epigenomic analysis of matched tumor and normal tissues from even a small number of primary patient samples revealed remarkably convergent shared regulatory landscapes. Several transcription factors appear to act downstream of HIF including the potent stem cell transcription factor POU5F1. Dysregulated expression of POU5F1 is part of a larger pattern of gene expression changes in RCC that may be induced by HIF-dependent reactivation of dormant promoters embedded within endogenous retroviral LTRs.

Project description:Renal cell carcinoma (RCC) is one of the leading causes of cancer-related death worldwide. Tumour metastasis and heterogeneity lead to poor survival outcomes and drug resistance in patients with metastatic RCC (mRCC). In this study, we aimed to assess intratumoural heterogeneity (ITH) in mRCC cells by performing a combined analysis of bulk data and single-cell RNA-sequencing data, and develop novel biomarkers for prognosis prediction on the basis of the potential molecular mechanisms underlying tumorigenesis. Eligible single-cell cohorts related to mRCC were acquired using the Gene Expression Omnibus (GEO) dataset to identify potential mRCC subpopulations. We then performed gene set variation analysis to understand the differential function in primary RCC and mRCC samples. Subsequently, we applied weighted correlation network analysis to identify coexpressing gene modules that were related to the external trait of metastasis. Protein-protein interactions were used to screen hub subpopulation-difference (sub-dif) markers (ACTG1, IL6, CASP3, ACTB and RAP1B) that might be involved in the regulation of RCC metastasis and progression. Cox regression analysis revealed that ACTG1 was a protective factor (HR < 1), whereas the other four genes (IL6, CASP3, ACTB and RAP1B) were risk factors (HR > 1). Kaplan-Meier survival analysis suggested the potential prognostic value of these sub-dif markers. The expression of sub-dif markers in mRCC was further evaluated in clinical samples by immunohistochemistry (IHC). Additionally, the genetic features of sub-dif marker expression patterns, such as genetic variation profiles, correlations with tumour-infiltrating lymphocytes (TILs), and targeted signalling pathway activities, were assessed in bulk RNA-seq datasets. In conclusion, we established novel subpopulation markers as key prognostic factors affecting EMT-related signalling pathway activation in mRCC, which could facilitate the implementation of a treatment for mRCC patients.

Dataset Information

Transcriptional profiling of tumor associated macrophages in human renal cell carcinoma reveals significant heterogeneity and opportunity for immunomodulation.

Publications

Transcriptional profiling of tumor associated macrophages in human renal cell carcinoma reveals significant heterogeneity and opportunity for immunomodulation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets