Probes for CD68

Diffuse Large B-Cell Lymphoma (DLBCL) presents a high clinical and biological heterogeneity, and the tumor microenvironment chracteristics are important in its  progression. The aim of this study was to evaluate tumor T, B cells, macrophages and mast cells distribution in GBC and ABC DLBCL subgroups through a set of morphometric parameters allowing to provide a quantitative evaluation of the morphological features of the spatial patterns generated by these inflammatory cells.   Histological ABC and GCB samples were immunostained for CD4, CD8, CD68, CD 163, and tryptase in order to determine both percentage and position of positive cells in the tissue characterizing their spatial distribution. The results evidenced that cell patterns generated by CD4-, CD8-, CD68-, CD163- and tryptase-positive cell profiles exhibited a significantly higher uniformity index in ABC than in GCB subgroup. The positive-cell distributions appeared clustered in tissues from GCB, while in tissues from ABC such a feature was lower or absent. The combinations of spatial statistics-derived parameters can lead to better predictions of tumor cell infiltration than any classical morphometric method providing a more accurate description of the functional status of the tumor, useful for patient prognosis.

The tumor microenvironment evolves during malignant progression, with major changes in nonmalignant cells, cytokine networks, and the extracellular matrix (ECM). In this study, we aimed to understand how the ECM changes during neoplastic transformation of serous tubal intraepithelial carcinoma lesions (STIC) into high-grade serous ovarian cancers (HGSOC). Analysis of the mechanical properties of human fallopian tubes (FT) and ovaries revealed that normal FT and fimbria had a lower tissue modulus, a measure of stiffness, than normal or diseased ovaries. Proteomic analysis of the matrisome fraction between FT, fimbria, and ovaries showed significant differences in the ECM protein TGF beta induced (TGFBI, also known as βig-h3). STIC lesions in the fimbria expressed high levels of TGFBI, which was predominantly produced by CD163-positive macrophages proximal to STIC epithelial cells. In vitro stimulation of macrophages with TGFβ and IL4 induced secretion of TGFBI, whereas IFNγ/LPS downregulated macrophage TGFBI expression. Immortalized FT secretory epithelial cells carrying clinically relevant TP53 mutations stimulated macrophages to secrete TGFBI and upregulated integrin αvβ3, a putative TGFBI receptor. Transcriptomic HGSOC datasets showed a significant correlation between TGFBI expression and alternatively activated macrophage signatures. Fibroblasts in HGSOC metastases expressed TGFBI and stimulated macrophage TGFBI production in vitro. Treatment of orthotopic mouse HGSOC tumors with an anti-TGFBI antibody reduced peritoneal tumor size, increased tumor monocytes, and activated β3-expressing unconventional T cells. In conclusion, TGFBI may favor an immunosuppressive microenvironment in STICs that persists in advanced HGSOC. Furthermore, TGFBI may be an effector of the tumor-promoting actions of TGFβ and a potential therapeutic target. SIGNIFICANCE: Analysis of ECM changes during neoplastic transformation reveals a role for TGFBI secreted by macrophages in immunosuppression in early ovarian cancer.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with short overall survival; the standard of care (SoC) is chemotherapy. Immunotherapies in development aim to remodel the stroma by depleting immunosuppressive cell types or using T-cell redirection to kill tumor cells. To date, none of these methods have improved overall survival beyond SoC. Next generation immunotherapies that employ histopathology and molecular subtyping1 for target and patient selection may succeed. Here we leverage a spatial transcriptomics platform (Nanostring Digital Spatial Profiling, DSP) to reveal molecular signaling in tumoral and stromal cells in 57 PDAC patients using tumor microarrays (TMAs). This approach is rapid and clinically relevant as molecular and histology data can be easily bridged.MethodsTMAs generated from surgical resection tissue were commercially sourced. DSP was performed using the CTA RNA panel (1,800 target genes) using PanCK fluorescence for tumor/stroma segmentation. In parallel, slides were chromogenically stained for T-cells (CD3) and macrophages (CD68/CD163). Differential gene expression, gene signature and gene co-expression network analysis was performed using linear models in R.2 3ResultsDifferential gene expression analysis and correlation to IHC confirmed the DSP platform successfully profiled tumor and stromal compartments (figure 1). Immune cell signatures4 and pathway analysis revealed a heterogenous stromal environment. Using a fibroblast gene signature derived from single-cell RNAseq5 we found fibroblast density was positively correlated to PDGFR signaling and MHC-II expression but negatively correlated to B, CD4+ T and neutrophil cell levels (figure 2a). This finding supports the idea that atypical antigen presentation in cancer associated fibroblasts (CAFs) may be exploitable for immunotherapies.6 We constructed a co-expression network from in-situ stromal gene expression and used it to identify receptors coordinately expressed with the immunosuppressive macrophage marker CSF1R as a bispecific antibody partner (figure 2b).7 Classical macrophage markers were identified but also receptors with lesser-known functions in macrophages (TIM3/HAVCR2, FPR3, MS4A6A, LILRB4). Surveying target pairs in this method allows rapid, patient-specific confirmation in serial TMA sections with singleplex IHC or RNAscope.Abstact 928 Figure 1Segmentation strategy and validation of DSP (A) PanCK, CD68 and CD3 staining from two representative tumor cores; (B, C) correlation of gene transcripts in stroma to cell counts from chromogenic staining; (D) heatmap of selected genes differentially expressed in tumor and stroma (n=57 patients).Abstract 928 Figure 2Exploration of the stromal compartment in PDAC TMAs. (A) Heatmap of selected cell type and gene signatures from gene expression in the stroma, color represents single sample enrichment score using GSVA method; (B) a gene co-expression subnetwork in the stroma centered on CSF1R, edge thickness represents strength of correlation, green nodes have evidence for cell surface expression based on proteomic profiling.7ConclusionsIn this study we were able to recapitulate known PDAC biology using very small samples of primary tumors. The combination of TMAs and DSP enables a rapid validation of targets and hypothesis generation for bispecific parings. Further analysis of untreated (n=14) and post-adjuvant chemotherapy (n=26) patients using RNA DSP, IHC and bulk RNAseq is under way. Results from this cohort will enable an integrated histopathology and molecular approach to developing next-generation immunotherapies.ReferencesCollisson EA, Bailey P, Chang DK, Biankin AV. Molecular subtypes of pancreatic cancer. 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Cancer Discov 2019 August;9(8):1102-1123. Bausch-Fluck D, Hofmann A, Bock T, Frei AP, Cerciello F, Jacobs A, Moest H, Omasits U, Gundry RL, Yoon C, Schiess R, Schmidt A, Mirkowska P, Härtlová A, Van Eyk JE, Bourquin JP, Aebersold R, Boheler KR, Zandstra P, Wollscheid B. A mass spectrometric-derived cell surface protein atlas. PLoS One 2015 April 20;10(3):e0121314.Ethics ApprovalSpecimens were harvested from unused tissue after a surgical tumor resection procedure. A discrete legal consent form from both hospital and individuals was obtained by the commercial tissue vendor BioMax US for all samples analyzed in this abstract. All human tissues are collected under HIPPA approved protocols.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.