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  • 1
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 6, No. 1 ( 2016-07-20)
    Abstract: Current therapies for metastatic clear cell renal cell carcinoma (ccRCC) show limited efficacy. Drug efficacy, typically investigated in preclinical cell line models during drug development, is influenced by pharmacogenes involved in targeting and disposition of drugs. Here we show through genome-wide DNA methylation profiling, that methylation patterns are concordant between primary ccRCC and macro-metastases irrespective of metastatic sites (r s  ≥ 0.92). However, 195,038 (41%) of all investigated CpG sites, including sites within pharmacogenes, were differentially methylated (adjusted P  〈  0.05) in five established RCC cell lines compared to primary tumors, resulting in altered transcriptional expression. Exemplarily, gene-specific analyses of DNA methylation, mRNA and protein expression demonstrate lack of expression of the clinically important drug transporter OCT2 (encoded by SLC22A2 ) in cell lines due to hypermethylation compared to tumors or metastases. Our findings provide evidence that RCC cell lines are of limited benefit for prediction of drug effects due to epigenetic alterations. Similar epigenetic landscape of ccRCC-metastases and tumors opens new avenue for future therapeutic strategies.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
    detail.hit.zdb_id: 2615211-3
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 2529-2529
    Abstract: Renal cell carcinoma (RCC) accounts for 5% in men and 3% in women of all oncological diagnoses worldwide (Capitanio et al., Eur Urol 2018). In 0.7-4.7% of patients both kidneys are affected by cancer. Although hereditary forms of RCC do exist (VHL disease, hereditary papillary RCC), the majority of bilateral RCC are sporadic. RCC comprises histologically distinct subtypes, and clear cell renal cell carcinoma (ccRCC) constitutes 65-70% of all RCC. Here, we present genomic analyses of three cases with bilateral ccRCC. In particular, we are interested in understanding the origin and evolution of these bilateral tumors. Our study includes bilateral tumors from three patients (P1 - P3). Tumors from patients P1 and P2 are metachronous. Patient P3 showed synchronous bilateral ccRCC, with two distinct tumors in one kidney. Two samples were retrieved per tumor to take account of intratumor heterogeneity. In addition one non-tumor sample was obtained per patient. Paired-end whole exome sequencing (WES) was performed using DNA isolated from all tissue samples. Single nucleotide and short indel variants were called using the Mutect2 software. Additionally, DNA samples were sequenced at ultra-deep coverage (median 1000) using a custom NGS panel comprising 33 genes frequently mutated in RCC to confirm results obtained from WES. The deepSNV method (Gerstung et al., Nat Commun 2012) was used to call somatic mutations from targeted sequencing data. Further, WES data as well as SNP data deriving from microarray analysis (Infinium Global Screening Array-24 v2.0) will be used to reconstruct somatic copy number aberrations for each tumor. We have analyzed relationships between the bilateral tumors by means of somatic mutations from WES data that were shared within and between tumors of a patient. In patient P1 Venn diagram analysis revealed that 1.9% (n=4) of 213 mutations detected in at least in two samples were shared between samples from different tumors. 32% (n=35) of 108 non-unique mutations were shared between tumors from patient P2; 16 mutations were even present in all four samples of P2. 3% (n=9) of 301 non-unique mutations occurred in samples from different tumors in patient P3. None of these mutations was present in all three tumors. Pairwise comparison between tumors of P3 revealed 1.6%, 0.6%, and 2.2% of non-unique mutations overlapping between tumor pairs, respectively. These first observations suggest a common origin of tumors from patient P2, whereas bilateral tumors from patients P1 and P3 seem to be independent events. Data from deep sequencing support these findings in all three cases, e.g. they confirm one of the ubiquitous mutations in P2 that is located in the von Hippel-Lindau gene. In summary, we present a comprehensive genomic analysis of a small case series of bilateral RCC indicating that even a metachronous bilateral RCC can share the common origin. The work was supported by the Robert Bosch Stiftung, Stuttgart, Germany. Citation Format: Florian Büttner, Carolin Meyerhoff, Siarhei Kandabarau, Stefan Winter, Steffen Rausch, Arnulf Stenzl, Falko Fend, Christopher Schroeder, Peter Bauer, Per Hoffmann, Markus M. Nöthen, Jens Bedke, Matthias Schwab, Elke Schaeffeler. Comprehensive genomic analyses of a case series of bilateral renal cell carcinoma [abstract] . In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2529.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 464-464
    Abstract: Estrogen (ER) and/or progesterone (PR) receptor-positive, early breast cancer benefits from targeted therapy via long-term estrogen deprivation. Valid treatment options include the selective ER modulator tamoxifen (TAM) that interferes with estrogen-binding at the ER, and aromatase inhibitors (AI) that block the enzyme aromatase to prevent the conversion of androgens to estrogen. Both treatment principles are in clinical use however fail in about one third of the patients. The choice of endocrine treatment is currently not well supported by predictive tumor markers. Gene expression signatures covering critical breast cancer pathways were tested to predict TAM and AI associated outcomes in a prospectively collected postmenopausal, hormone-receptor positive, early breast cancer cohort (IKP211; 1200 patients, median follow up 5.5 years; DRKS00000605). RNA was extracted from formalin-fixed paraffin-embedded tumor sections of 631 patients and subjected to gene expression profiling with 770 genes across 23 key breast cancer pathways/processes (NanoString®BC360 panel) including the prognostic PAM50 signature for intrinsic subtype classification. Signatures were measured with the nCounter Digital Analyzer system (Nanostring) and revealed 60% Luminal A, 31% Luminal B, 6% HER2 enriched and 3% Basal-like tumor subtypes. Predefined signature scores (Nanostring) or single gene expression scores were analyzed in relation to breast cancer recurrence-free survival (EFS). PAM50 subtype designation and its derived Genomic Risk Score (ROR) were strongly associated with EFS of patients treated with AI (Log Rank P & lt;0.05 all comparisons) but not in patients treated with mono-TAM. Preliminary data show that higher levels of FOXA1 and androgen receptor (AR) gene expression are both associated with longer EFS in patients with AI therapy. Likewise, increased (mutant-like) p53 signaling was prognostic for shorter EFS (Log Rank P & lt;0.05). These relations were not observed in patients treated with TAM or with a switch treatment regimen. A trend for longer EFS linked to an increased anti-tumor immune activity, as deduced by cytotoxic cell abundance and activity, was observed in a subgroup of mainly TAM treated patients. Our preliminary data suggest that gene expression signatures pertaining to FOXA1 and AR signaling, p53 and anti-tumor immune activity may define subgroups of patients with different outcomes and may aid in future personalized treatment concepts for hormone-sensitive postmenopausal early breast cancer. Citation Format: Werner Schroth, Reiner Hoppe, Florian Büttner, Stefan Winter, Siarhei Kandabarau, Jörg Kumbrink, Heather A. Brauer, Peter Fritz, Matthias Schwab, Thomas Mürdter, Hiltrud Brauch. Gene expression signatures for the prediction of endocrine treatment outcome in early-stage luminal breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 464.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 1632-1632
    Abstract: Introduction: Kidney cancer is the 12th most common cancer world-wide with 338.000 newly diagnosed cases in 2012, according to the World Cancer Research Fund International. With around 70-80%, clear cell renal cell carcinomas (ccRCC) make up the vast majority of kidney cancers. Advanced and metastatic ccRCCs are marked by poor survival rates despite the availability of targeted therapies. Currently several immunotherapeutic approaches, including checkpoint-blocking antibodies and dendritic cell vaccines are undergoing clinical investigations. In this study we identified tumor-associated peptides which could be used in cancer vaccines to improve treatment of patients with advanced ccRCC. Methods: To identify suitable peptides for cancer vaccines we set up a tissue collection of paired tumors and normal kidney tissues from 60 ccRCC patients. From these tissues, HLA molecules were isolated by affinity chromatography and bound peptides analyzed by mass spectrometry. HLA ligand profiles of tissues excised from various organ sites of non-ccRCC patients were used to complement the data. Based on these analyses, Egl nine homolog 3 (EGLN3) was selected as a candidate for peptide vaccination and further investigated in our own data cohort comprising the 60 ccRCC patients. Therefore, mRNA and protein expression, as well as DNA methylation data were collected and correlated with HLA ligandomics and clinical data. In addition, we integrated RNA-Seq, DNA methylation, somatic mutation and clinical data from a ccRCC patient cohort from The Cancer Genome Atlas in our analyses. Finally, EGLN3 function was analyzed in 2D and 3D kidney carcinoma cell culture systems. Results: 16 different peptides from EGLN3 were detected in 32 of the 60 analyzed tumor samples, with the most frequent peptide found in tumors of 10 different patients. Only two of the peptides were also detected in normal kidney or other non-ccRCC tissues, rendering EGLN3 peptides promising candidates to be used in ccRCC-directed vaccines. Most of our patients were HLA A*02:01 positive, however using NetMHCpan (http://www.cbs.dtu.dk/services/NetMHCpan/) only one of the peptides identified by HLA ligandomics was also predicted to be a strong binder for that particular HLA molecule. Expression of EGLN3 mRNA was not different in patients with and without HLA-presented peptides. Generally, EGLN3 mRNA expression was strongly induced in ccRCC tumors compared to normal kidney (p & lt;10-6), whereas protein levels remained mainly unchanged in most patients. Functional investigations in different RCC cell culture models indicated involvement of EGLN3 in regulation of apoptosis and cell cycle progression. Conclusion: Advanced ccRCC is marked by poor survival rates due to ineffective therapeutic options. Peptides from EGLN3, as well as other ccRCC-exclusive peptides could represent activators of the immune system to specifically fight ccRCC tumors. The function and targetability of EGLN3 remains to be investigated. Citation Format: Anna Reustle, Moreno Di Marco, Florian Büttner, Stefan Winter, Daniel Kowalewski, Linus Backert, Steffen Rausch, Joerg Hennenlotter, Marcus Scharpf, Falko Fend, Arnulf Stenzl, Jens Bedke, Matthias Schwab, Elke Schaeffeler. Identification and analysis of EGLN3 as tumor-associated peptide in ccRCC [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 1632. doi:10.1158/1538-7445.AM2017-1632
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 5
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2017
    In:  Cancer Research Vol. 77, No. 13_Supplement ( 2017-07-01), p. 474-474
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 474-474
    Abstract: Long-term estrogen deprivation with tamoxifen or aromatase inhibitors (AI) is the basic principle of endocrine treatment of ER-positive breast cancer. Acquired resistance is however a major obstacle in treatment success. Based on clinical observations and in vitro as well as animal in vivo experiments it has been suggested that tumor cell clones evolve over time and become vulnerable to E2-induced apoptosis, thereby potentially providing a promising second line treatment option. In vitro, this vulnerability is mimicked in the AI-resistant breast cancer models MCF-7:5C and MCF-7:2A, which during long-term E2-deprivation reconfigure their survival signaling including endoplasmic reticulum, oxidative and inflammatory stress related pathways. E2-stimulation of these cells initiates an unfolded protein response which in turn triggers apoptosis through the intrinsic and subsequently extrinsic pathway (Jordan VC 2015). Recently, we identified miRNA profiles matching the biology of AI resistance and vulnerability to E2-induced apoptosis (Hoppe R et al. 2016). Here we investigate the modulatory role of miRNAs in E2-induced apoptosis through the identification of their global expression changes in E2-stimulated 5C and 2A models compared to MCF-7:WS8 reference. Each cell line was treated with 10-9 M E2 or vehicle over a 72h time course (6, 12, 24, 72 h). miRNA profiles were generated using Affymetrix GeneChip miRNA2.0 arrays. At each time point relative miRNA expression changes (E2/control) were evaluated resulting in a total of 72 (5C), 104 (2A) and 94 (WS8) differentially expressed miRNAs (FC & gt; 1.5 or & lt; 1/1.5, Pt-test & lt; 0.05). Differential expression analyses between consecutive time points revealed 16 (5C), 43 (2A) and 27 (WS8) miRNAs (maximum absolute FC difference & gt; 1.5, PF-test & lt; 0.05). Differential area under the curve (dAUC) analyses at 6-72, 6-24, and 24-72 h mined the overall, early, and late-responding miRNAs of the different phenotypes (Ppermutation test & lt; 0.05). Representative early down-regulated miRNA candidates potentially modulating E2-induced apoptosis in 5C cells are miR-543 and miR-432 of the DLK1-DIO3 locus on Chr. 14q32.31. Late responding up-regulated miRNA candidates are miR-150* and miR-149* the low expression of which in tumor tissues registered in The Cancer Genome Atlas (miRNA-Seq v. 3.1.17.0) was associated with worse outcome in all PAM50 breast cancer subtypes and Lum B, respectively (HR = 2.1, 95% CI: 1.4-3.2; P = 0.00017; HR = 6.8, 95% CI: 1.5-3.0; P = 0.0036). We are currently in the process to subject respective miRNA sets to functional enrichment analyses (KEGG, GO) and to correlate E2-responsive miRNA candidates with respective transcriptome signatures. In summary, we will present miRNAs matching to the biological processes inherent to E2-induced apoptosis. These may serve as potential targets for the amplification of the apoptotic trigger upon E2-treatment. Citation Format: Reiner Hoppe, Ping Fan, Stefan Winter, Florian Büttner, V. Craig Jordan, Hiltrud B. Brauch. Estrogen-responsive miRNAs as modulators of E2-induced apoptosis in AI-resistant breast cancer [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 474. doi:10.1158/1538-7445.AM2017-474
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 6
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2016
    In:  Cancer Research Vol. 76, No. 14_Supplement ( 2016-07-15), p. 1073-1073
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 1073-1073
    Abstract: The blockade of E2 signaling by either tamoxifen or aromatase inhibitors (AI) is the standard treatment of patients with estrogen receptor (ER)-positive breast cancer. However, acquired resistance to antiestrogen therapies remains a big clinical challenge. The in vitro breast cancer models MCF-7:5C and MCF-7:2A mimic clinical AI resistance in that they grow under tamoxifen, but can rapidly regress with E2 due to the reconfiguration of survival signaling known as E2-inducible apoptosis. This principle is currently explored in clinical trials in order to develop strategies to overcome endocrine resistance. To better understand the biology of AI resistance we previously ascertained a wide range of alterations of stress related pathways including the accumulation of endoplasmic reticulum stress, oxidative stress, and inflammatory stress that occur prior to E2-induced apoptosis (Ariazi et al. 2011; Fan et al. 2013, 2015; Sweeney et al. 2014). In this current work we investigated miRNA expression profiles of the 5C and 2A models (both compared to MCF-7:WS8 reference) in order to further elucidate the molecular scenario that characterizes the AI resistance phenotypes and their susceptibility to E2-induced apoptosis. Using Affymetrix GeneChip miRNA2.0 arrays we identified 184 miRNAs differentially expressed between 2A and 5C (FC & gt; 1.5 or & lt; 1/1.5, P & lt; 0.05). Of these, 30 miRNAs were specific for 2A, 99 for 5C, and 55 overlapped. Common miRNAs include upregulated oncogenic miRNAs of the miR-17-92 cluster (Chr. 13q31) and the paralogous 106a-363 cluster (Chr. X), as well as downregulated tumor suppressive miRNAs such as miR-342-5p. Thirty-four miRNAs that cluster at Chr. 14q32 were overexpressed in 5C cells and highly correlate with the downregulated miR-99a and miR-125b (Chr. 21q21). At the clinical level based on data from The Cancer Genome Atlas (miRNA-Seq v. 3.1.17.0), low expression of miR-31 was associated with poor (HR = 3.0, 95% CI: 1.9-4.8; Padj = 8.7E-5), and low miR-222 expression was associated with better outcome (HR = 0.3, 95% CI: 0.1-0.6; Padj. = 4.4E-3). As miR-31 expression is high and miR-222 expression is low in 5C cells compared to the MCF-7:WS8 reference, we suggest protective roles. Functions of miRNAs were deciphered via analyses of their predicted targets (CLIP-confirmed). Using KEGG and GO databases functional enrichment analyses of 5C and 2A specific miRNA sets revealed pathways associated with cell proliferation for both models including insulin, mTOR, and ErbB signaling as well as immune response and metabolism associated pathways. While the 2A specific miRNA set revealed additional metabolic pathways, the 5C specific miRNA set points to pathways involved in apoptosis. Thus, we confirmed the biological processes inherent to AI resistance and provide critical evidence for miRNA profiles as an important regulatory principle in these AI resistance models. Citation Format: Reiner Hoppe, Ping Fan, Florian Büttner, Stefan Winter, Heather Cunliffe, V. Craig Jordan, Hiltrud B. Brauch. Modulation of aromatase inhibitor resistance by miRNAs in breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1073.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 7
    In: Genome Medicine, Springer Science and Business Media LLC, Vol. 14, No. 1 ( 2022-09-15)
    Abstract: Renal cell carcinoma (RCC) is a heterogeneous disease comprising histologically defined subtypes. For therapy selection, precise subtype identification and individualized prognosis are mandatory, but currently limited. Our aim was to refine subtyping and outcome prediction across main subtypes, assuming that a tumor is composed of molecular features present in distinct pathological subtypes. Methods Individual RCC samples were modeled as linear combination of the main subtypes (clear cell (ccRCC), papillary (pRCC), chromophobe (chRCC)) using computational gene expression deconvolution. The new molecular subtyping was compared with histological classification of RCC using the Cancer Genome Atlas (TCGA) cohort ( n  = 864; ccRCC: 512; pRCC: 287; chRCC: 65) as well as 92 independent histopathologically well-characterized RCC. Predicted continuous subtypes were correlated to cancer-specific survival (CSS) in the TCGA cohort and validated in 242 independent RCC. Association with treatment-related progression-free survival (PFS) was studied in the JAVELIN Renal 101 ( n  = 726) and IMmotion151 trials ( n  = 823). CSS and PFS were analyzed using the Kaplan–Meier and Cox regression analysis. Results One hundred seventy-four signature genes enabled reference-free molecular classification of individual RCC. We unambiguously assign tumors to either ccRCC, pRCC, or chRCC and uncover molecularly heterogeneous tumors (e.g., with ccRCC and pRCC features), which are at risk of worse outcome. Assigned proportions of molecular subtype-features significantly correlated with CSS (ccRCC ( P  = 4.1E − 10), pRCC ( P  = 6.5E − 10), chRCC ( P  = 8.6E − 06)) in TCGA. Translation into a numerical RCC-R(isk) score enabled prognosis in TCGA ( P  = 9.5E − 11). Survival modeling based on the RCC-R score compared to pathological categories was significantly improved ( P  = 3.6E − 11). The RCC-R score was validated in univariate ( P  = 3.2E − 05; HR = 3.02, 95% CI: 1.8–5.08) and multivariate analyses including clinicopathological factors ( P  = 0.018; HR = 2.14, 95% CI: 1.14–4.04). Heterogeneous PD-L1-positive RCC determined by molecular subtyping showed increased PFS with checkpoint inhibition versus sunitinib in the JAVELIN Renal 101 ( P  = 3.3E − 04; HR = 0.52, 95% CI: 0.36 − 0.75) and IMmotion151 trials ( P  = 0.047; HR = 0.69, 95% CI: 0.48 − 1). The prediction of PFS significantly benefits from classification into heterogeneous and unambiguous subtypes in both cohorts ( P  = 0.013 and P  = 0.032). Conclusion Switching from categorical to continuous subtype classification across most frequent RCC subtypes enables outcome prediction and fosters personalized treatment strategies.
    Type of Medium: Online Resource
    ISSN: 1756-994X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2484394-5
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  • 8
    In: Cells, MDPI AG, Vol. 11, No. 20 ( 2022-10-19), p. 3289-
    Abstract: Since their initial description by Elie Metchnikoff, phagocytes have sparked interest in a variety of biologic disciplines. These important cells perform central functions in tissue repair and immune activation as well as tolerance. Myeloid cells can be immunoinhibitory, particularly in the tumor microenvironment, where their presence is generally associated with poor patient prognosis. These cells are highly adaptable and plastic, and can be modulated to perform desired functions such as antitumor activity, if key programming molecules can be identified. Human clear cell renal cell carcinoma (ccRCC) is considered immunogenic; yet checkpoint blockades that target T cell dysfunction have shown limited clinical efficacy, suggesting additional layers of immunoinhibition. We previously described “enriched-in-renal cell carcinoma” (erc) DCs that were often found in tight contact with dysfunctional T cells. Using transcriptional profiling and flow cytometry, we describe here that ercDCs represent a mosaic cell type within the macrophage continuum co-expressing M1 and M2 markers. The polarization state reflects tissue-specific signals that are characteristic of RCC and renal tissue homeostasis. ErcDCs are tissue-resident with increasing prevalence related to tumor grade. Accordingly, a high ercDC score predicted poor patient survival. Within the profile, therapeutic targets (VSIG4, NRP1, GPNMB) were identified with promise to improve immunotherapy.
    Type of Medium: Online Resource
    ISSN: 2073-4409
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2661518-6
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  • 9
    In: Journal of Proteome Research, American Chemical Society (ACS), Vol. 16, No. 2 ( 2017-02-03), p. 933-944
    Type of Medium: Online Resource
    ISSN: 1535-3893 , 1535-3907
    Language: English
    Publisher: American Chemical Society (ACS)
    Publication Date: 2017
    detail.hit.zdb_id: 2065254-9
    SSG: 12
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  • 10
    In: Oncotarget, Impact Journals, LLC, Vol. 7, No. 44 ( 2016-11-01), p. 71235-71254
    Type of Medium: Online Resource
    ISSN: 1949-2553
    URL: Issue
    Language: English
    Publisher: Impact Journals, LLC
    Publication Date: 2016
    detail.hit.zdb_id: 2560162-3
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