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Introduction:
Radiolabeled exendin-4 (Ex4) derivatives are used to target the glucagon-like peptide-1 receptor (GLP-1R) for the clinical diagnosis of insulinomas, a rare type of neuroendocrine tumor. Gallium-68 is an ideal diagnostic nuclide for this application and a study evaluating an exendin-4-NODAGA conjugate is currently underway. However, i...
Citations
... Primary antibodies, optimally diluted, (Table 1) were applied overnight, washed in 50-mM Tris-HCl buffer (pH 7.5) containing 0.01% Tween-20 (Merck) and 100-mM sucrose (TBS-Ts), 15 counterstained with a horseradish peroxidase-conjugated polymer (Vector Laboratories; Burlingame, CA), washed, developed in 3,3′-diaminobenzidine (Dako; Glostrup, Denmark), lightly counterstained, and mounted. ...
Antigen-bearing proteins become progressively unavailable to immunodetection after prolonged storage of routine sections, exposed to a variety of agents, such as moisture, oxygen, and temperature. By proteomic analysis, the antigens are retained in the sections and definitely in the tissue block, pointing to fixation-independent, storage time–dependent protein modifications. Based on previous experience, we hypothesized that a combined exposure to a reducing agent and to chemicals favoring protein conformation changes would reverse the masking in aged sections. Disaccharides, lactose and sucrose, and a surfactant, added to a standard antigen retrieval buffer, reverse the negative changes in aged sections. Furthermore, they provide enhanced access to antigens in freshly cut sections, but not universally, revealing additional factors, besides heat and calcium chelation, required for antigen retrieval of individual proteins:
... Tissue staining. Multiplex immunohistochemistry was performed according to a previously published method [62][63][64] . Tissue sections (3 µm) were prepared from formalin-fixed paraffin-embedded human GBM samples (collected at the UZ/KU Leuven biobank according to protocols S59804, S61081 and S62248). ...
Glioblastomas are aggressive primary brain cancers that recur as therapy-resistant tumors. Myeloid cells control glioblastoma malignancy, but their dynamics during disease progression remain poorly understood. Here, we employed single-cell RNA sequencing and CITE-seq to map the glioblastoma immune landscape in mouse tumors and in patients with newly diagnosed disease or recurrence. This revealed a large and diverse myeloid compartment, with dendritic cell and macrophage populations that were conserved across species and dynamic across disease stages. Tumor-associated macrophages (TAMs) consisted of microglia- or monocyte-derived populations, with both exhibiting additional heterogeneity, including subsets with conserved lipid and hypoxic signatures. Microglia- and monocyte-derived TAMs were self-renewing populations that competed for space and could be depleted via CSF1R blockade. Microglia-derived TAMs were predominant in newly diagnosed tumors, but were outnumbered by monocyte-derived TAMs following recurrence, especially in hypoxic tumor environments. Our results unravel the glioblastoma myeloid landscape and provide a framework for future therapeutic interventions. Single-cell RNA-seq and CITE-seq were used to profile the glioblastoma immune landscape in humans and mice, revealing the diversity and dynamics of tumor macrophages as the disease progresses from initial diagnosis to recurrence.
... We also explored the use of TMAs for multiplex immunoassay and applied the Multiple Iteractive Labeling by Antibody Neodeposition (MILAN) technique, an assay involving repeated cycles of indirect immunofluorescence, image acquisition, and antibody removal [12,13]. We optimized the procedure for TMA sections and fluorescence microscopy. ...
... As all tumor samples are placed on a single TMA, the staining of all specimens can be performed at the same time under identical conditions, achieving highest experimental standards and saving assay volume. Moreover, recent advances in multiplex immunostaining techniques such as MILAN enable us to test multiple molecules on a single TMA slide [12], revealing the cellular composition, localization, and interactions between cells, as well as increasing the utility of very precious biological material. ...
Soft tissue sarcoma (STS) is a heterogeneous family of rare mesenchymal tumors, characterized by histopathological and molecular diversity. Tissue microarray (TMA) is a tool that allows performing research in orphan diseases in a more efficient and cost-effective way. TMAs are paraffin blocks consisting of multiple small representative tissue cores from biological samples, for example, from multiple donors, diverse sites of disease, or multiple different diseases. In 2015, we began constructing TMAs using archival tumor material from STS patients. Specimens were well annotated in terms of histopathological diagnosis, treatment, and clinical follow-up of the tissue donors. Each TMA block contains duplicate or triplicate 1.0–1.5 mm tissue cores from representative tumor areas selected by sarcoma pathologists. The construction of TMAs was performed with TMA Grand Master (3DHistech). So far, we have established disease-specific TMAs from 7 STS subtypes: gastrointestinal stromal tumor (72 cases included in the array), alveolar soft part sarcoma (n = 12 + 47), clear cell sarcoma (n = 22 + 32), leiomyosarcoma (n = 55), liposarcoma (n = 42), inflammatory myofibroblastic tumor (n = 12 + 21), and alveolar rhabdomyosarcoma (n = 24). We also constructed a multisarcoma TMA covering a representative number of important histopathological subtypes on arrays for screening purposes, namely, angiosarcoma, dedifferentiated liposarcoma, pleomorphic liposarcoma, and myxoid liposarcoma, leiomyosarcoma, malignant peripheral nerve sheath tumor, myxofibrosarcoma, rhabdomyosarcoma, synovial sarcoma, and undifferentiated pleomorphic sarcoma, with 7–11 individual cases per subtype. We are currently expanding the list of TMAs with additional sarcoma entities, considering the heterogeneity of this family of tumors. Our extensive STS TMA platform is suitable for rapid and cost-effective morphological, immunohistochemical, and molecular characterization of the tumor as well as for the identification of potential novel diagnostic markers and drug targets. It is readily available for collaborative projects with research partners.
1. Introduction
Soft tissue sarcoma (STS) is a heterogeneous group of rare malignant tumors derived from mesenchymal progenitor cells, which are defined by various morphological, histopathological, and genetic characteristics [1, 2]. Tissue analysis, such as histology and immunohistochemistry (IHC), is essential for the clinical classification of sarcomas, treatment planning, and prognostic assessment. In the past few years, scientific progress in the complex field of STS has mainly been driven by the identification and implementation of novel prognostic and predictive markers, as illustrated by the success of kinase inhibitors treatments for gastrointestinal stromal tumors (GIST) [3], the use of epigenetic modifiers for epithelioid sarcomas with integrase interactor 1 loss [4], or the agnostic use of neurotrophic receptor tyrosine kinase (NTRK) inhibitors in sarcomas with specific gene fusions [5]. The approval of such drugs shows that the identification of novel biomarkers with diagnostic, prognostic, or predictive value, and a better understanding of the biology of an individual sarcoma subtype can rapidly translate into therapeutic relevance and improve the clinical outcome of patients. STS represents a family of at least 100 individual subtypes [1, 6], and all sarcomas together account for only 1% of all adult solid tumors [6]. Tissue collections are important to achieve further scientific progress and to gain a deeper insight into the biology of some sarcoma entities and the potential relevance of biomarkers. The use of archival sarcoma material for histopathology, immunohistochemical, and genetic studies is time-consuming, expensive, and labor-intensive, especially if a large number of cases are required for explorative studies.
Tissue microarray (TMA) can overcome some limitations of using conventional archival sarcoma tissue for research. TMA is a paraffin block consisting of many small representative tissue cores from patient samples in alignment of an array. This technology was first described by Kononen et al. in 1998 [7] but the concept can be traced back to 1986 when Battifora designed a “sausage block” by wrapping 1 mm thick rods of different specimens and embedding them afterwards in a paraffin block [8]. TMA can combine tissue from multiple donors with the same sarcoma subtype, multiple types of sarcoma from various donors, or longitudinal samples from the same donor. With modern TMAs, a large number of archival samples can be analyzed in parallel using tissue-based applications such as IHC, fluorescent in situ hybridization (FISH), or (multiplex) immunofluorescence. Such TMAs have potential advantages over conventional, single sample-based tissue analysis in terms of efficiency and cost-effectiveness of the work, especially when tissue is analyzed for research purposes. In 2015, the Laboratory of Experimental Oncology, KU Leuven, Leuven (Belgium) started establishing STS TMAs using left-over archival sarcoma tissue from patients treated at the University Hospitals in Leuven. Our primary aim was to create a ready-to-use TMA platform for sarcoma research. This article provides an overview on available TMAs and describes how they were constructed, examples of applications for translational research, and where we see potential advantages and limitations of this approach.
2. Materials and Methods
2.1. Collection of Archival Tumor Tissue Blocks and Clinical Data
For the construction of TMAs, formalin-fixed (10% neutral buffered formalin for 24 hours), paraffin-embedded (FFPE) tumor blocks were collected from STS patients diagnosed at the University Hospitals Leuven (UZ Leuven), with left-over tissue archived in the Department of Pathology, UZ Leuven. We identified and retrieved relevant tumor blocks through the retrospective review of our sarcoma-specific clinical and research database (LECTOR), established and maintained by the Department of General Medical Oncology, UZ Leuven. The initial focus on certain sarcoma subtypes was primarily done with the purpose to match and support ongoing translational and clinical research projects in our group; in a second step, we started establishing TMAs from a variety of sarcomas to facilitate future translational research in the broader STS family of diseases. To enrich the collection with a sufficient number of cases from some ultrarare STS subtypes, a limited number of additional tumor blocks were collected from selected collaborating institutions: University Hospital Zürich (USZ), Zürich (Switzerland) and Leiden University Medical Center (LUMC), Leiden (The Netherlands). Furthermore, we utilized tissue blocks that were collected in the frame of the European Organisation of Research and Treatment of Cancer (EORTC) phase 2 trial 90101 “CREATE” [9–11], where left-over FFPE blocks from patients with clear cell sarcoma (CCSA), alveolar soft part sarcoma (ASPS), and inflammatory myofibroblastic tumor (IMFT) were centrally stored at a commercial biorepository, BioRep, Milan (Italy), for research purposes.
Apart from focusing on specific sarcoma subtypes, we applied the following criteria for selecting suitable donor tissue: available blocks with a sufficient amount of tumor tissue, without dehydration (to avoid brittle blocks) and depth of block at least 3 mm (to make sure a sufficient number of sections can be cut). All diagnoses were established or reviewed by sarcoma pathologists at UZ Leuven (RS) or LUMC (JVMGB) and confirmed by the presence of characteristic, immunohistological, or molecular markers if applicable, depending on the tumor type. The corresponding clinical data including pathological diagnosis, treatment, and clinical follow-up were extracted from LECTOR (UZ Leuven) and the CREATE-related trial database at EORTC, Brussels (Belgium). The collection and the analysis of pseudonymized clinical data and use of archival FFPE tumor samples were approved by the Medical Ethics Committee, UZ Leuven (reference numbers S51495, S59181). The collection of ASPS and IMFT cases from the archive of the Department of Pathology, Leiden University Medical Center, was approved with a waiver of consent by LUMC’s Medical Ethics Committee (B17.030).
2.2. Construction of TMA
Slides were cut from retrieved archival FFPE blocks, stained with hematoxylin and eosin (H&E), and assessed microscopically to evaluate the quality of tumor material. Selected high-quality blocks were sent to the Translational Research Unit (TRU), Institute of Pathology, University of Bern, Bern (Switzerland) or LUMC. The central facility made further H&E-stained sections which were digitally scanned for unbiased annotations of areas of interest. Cores of preselected diameter were made from these areas using CaseViewer 2.3 (3DHistech, Budapest, Hungary) (CJL) and reviewed by reference sarcoma pathologists (RS and JVMGB). The construction of TMAs was performed with the fully automated machine TMA Grand Master from 3DHistech, Budapest (Hungary). The TMA control software (TMA Grand Master package) was used to align images with corresponding donor blocks and to locate the annotated area. Two to three cores of 1.0 or 1.5 mm in diameter were automatically punched out from a donor block by the TMA machine according to the digital annotations. The cores were then relocated to a recipient block in a precise alignment. The annotated information and the corresponding location of cores were automatically archived and stored in a specific file. Subsequently, 4 μm sections were cut from the constructed TMA blocks, H&E-stained, and scanned for quality control purposes.
2.3. Immunohistochemistry
For a typical immunohistochemical study, TMA sections were pretreated with Ultra Clear (VWR, Pennsylvania, US) and 100% ethanol for deparaffinization and dehydration, and were incubated in a solution of methanol (Acros Organics, New Jersey, US) with hydrogen peroxidase (Merck, New Jersey, US) for blocking endogenous peroxidase. Antigen retrieval was achieved by sections incubated in 10 mM citrate buffer (pH 6.0) in a preheated water bath at 95°C for 30 minutes, followed by the incubation of protein block serum-free (DAKO A/S X0909, Glostrup, Denmark). For the purpose of comparison between whole tumor tissue section and TMA, immunostaining was performed with phospho-p44/42 mitogen-activated protein kinase antibody (pMAPK, Cell Signaling Technology #4370, Massachusetts, US) and phospho-AKT antibody (pAKT, Cell Signaling Technology #9271) at 4°C overnight. For target screening in multiple STS subtypes, immunostaining was performed with human platelet-derived growth factor receptor beta (PDGFR-B) antibody (R&D AF385, Minneapolis, US) at room temperature for one hour. Visualization was done by 3,3′-Diaminobenzidine Substrate Chromogen System (DAKO A/S K34681), following instructions from the manufacturer. After counterstaining with hematoxylin (VWR), slides were dehydrated in series of 100% ethanol solution and mounted. The stained slides were automatically scanned and evaluated blindly and independently by two investigators using Olympus BX43 microscopy and cellSens software (Olympus, Tokyo, Japan). Scoring was done according to scoring intensity: 0 (negative), 1 (weakly positive), 2 (moderately positive), and 3 (strongly positive). For cases with more than one available core on the TMA, a mathematical mean was recorded as the final result.
2.4. Multiple Iteractive Labeling by Antibody Neodeposition
We also explored the use of TMAs for multiplex immunoassay and applied the Multiple Iteractive Labeling by Antibody Neodeposition (MILAN) technique, an assay involving repeated cycles of indirect immunofluorescence, image acquisition, and antibody removal [12, 13]. We optimized the procedure for TMA sections and fluorescence microscopy. Deparaffinization and dehydration were performed as described above, followed by antigen retrieval with Tris-EDTA (pH = 9). Multicolor immunofluorescent staining was achieved using an antibody cocktail made by 1 : 50 dilution of primary antibodies, which were selected from different host species or different subclass of immunoglobulin G (IgG) (Supplementary Table S1). TMA sections were incubated with cocktail antibody solution at 4°C overnight. Corresponding fluorophore-conjugated secondary antibodies (1 : 200 dilution) were sequentially administrated to the TMAs at room temperature for one hour, followed by fluorescence counterstaining with 4′,6-diamidino-2-phenylindole (DAPI, Thermo Fisher Scientific, Massachusetts, US) and mounting with dissolvable medium. After image acquisition, the coverslip was removed by incubation in washing solution, and antibodies were removed with preheated stripping buffer (2-mercaptoethanol and sodium dodecyl sulphate, Sigma-Aldrich, Missouri, US) at 56°C for 30 minutes with horizontal shaking. After this, the next cycle could be applied with different combinations of primary and fluorophore-conjugated antibodies. The number and sequence of cycles were determined by the potential expression level of interested targets and to minimize the possible impact of tissue loss during the experiment (Supplementary Table S1). In the current manuscript, we present the combined use of TMAs and MILAN as an illustration of the potential use of this technique for characterization of the tumor microenvironment in ASPS, one of the few sarcoma subtypes tending to respond to immune checkpoint modulation in the clinic. In this experiment, we performed multiplex staining for immune checkpoints, markers for tumor-infiltrating lymphocytes, and tumor-specific molecules (Supplementary Table S1). Immunofluorescence staining was scored blindly in the previously defined order by the investigator (CJL) and was assessed as a categorical variable based on the percentage of cells expressing targeted molecules. The targeted molecules and corresponding evaluation criteria were the following: cell membrane expression on multiplex immunofluorescence of the markers programmed cell death protein 1, programmed cell death protein ligand 1, cytotoxic T lymphocyte-associated protein 4, CD3, CD4, CD8, CD14, CD56, CD68, and major histocompatibility complex class I/II were considered as positive. For transcription factor E3 (TFE3, ASPS specific molecule), nuclear expression was considered as positive [14]. Both cytoplasmic and nuclear expressions of forkhead box protein P3 were defined as positive [15]. The proportion of cells was scored as 0 (no cells stained), 1 (1–10% of stained cells), 2 (10–30% of stained cells), or 3 (>30% of stained cells).
3. Results
3.1. Tissue Donor Characteristics and Tumor Blocks
Between April 2015 and March 2020, 459 selected STS FFPE blocks, originating from patients who had undergone surgery or biopsy procedures, were retrieved from archives of UZ Leuven and collaborating institutions (USZ provided 4 cases of CCSA; LUMC donated 4 cases of ASPS and 5 cases of IMFT). These samples originated from a total of 328 individual patients, with a male-to-female ratio of 0.97 and a median age of the patients at sarcoma diagnosis of 58 years (range 0–95). The majority of donor samples were collected from a primary tumor (41%) or a metastatic lesion (40%), followed by local recurrence (16%). The selected samples originated mainly from abdominal or chest sites (58%), extremities (22%), trunk (7%), or head and neck (6%). The most common subtypes of STS included were leiomyosarcoma (LMS, 31%), GIST (17%), CCSA (8%), alveolar rhabdomyosarcoma (ARMS, 7%), dedifferentiated liposarcoma (DDLPS, 6%), myxoid/round cell liposarcoma (MLPS, 6%), pleomorphic liposarcoma (PLPS, 4%), well-differentiated liposarcoma (WDLPS, 4%), ASPS (3%), IMFT (3%), angiosarcoma (2%), malignant peripheral nerve sheath tumor (MPNST, 2%), myxofibrosarcoma (2%), rhabdomyosarcoma (RMS, 2%), synovial sarcoma (SynSa, 2%), and undifferentiated pleomorphic sarcoma (UPS, 2%). The characteristics of each tumor type are summarized in Supplementary Table S2.
In addition, 102 available archival tissue samples from 100 individual donors with ASPS, CCSA, or IMFT, who participated in EORTC trial 90101, were used for TMA construction, with a male-to-female ratio of 1.29 and a median age at diagnosis of the patients with these rare sarcomas of 33 years (range 1–77). The majority of these samples were collected from a primary tumor (71%) or a metastatic lesion (27%). These orphan sarcomas are known to be potentially driven by specific molecular alterations, and the presence of the according genetic hallmark was therefore determined by FISH and/or IHC as part of the original study protocol [16–18]. Specific translocations were confirmed by the presence of a rearrangement of TFE3 in ASPS (89% of cases) and rearrangement of Ewing sarcoma breakpoint region 1 (EWSR1) in CCSA (88%). Anaplastic lymphoma kinase (ALK) rearrangement and/or immunopositivity was analyzed in IMFT (62%) (Supplementary Table S3).
3.2. Overview of Currently Available TMAs
In an ongoing effort, we have created a current total of 10 STS subtype-specific TMAs, including two TMAs each from ASPS (12 and 47 cases per array), CCSA (22 and 32), and IMFT (12 and 21), as well as one TMA each from GIST (72), LMS (55), LPS (43), and ARMS (21). For screening purposes, we have also constructed a multisarcoma TMA covering 10 characteristic, clinically relevant subtypes of STS, combining 7–11 individual cases of angiosarcoma, DDLPS, PLPS, MLPS, LMS, MPNST, myxofibrosarcoma, RMS, SynSa, and UPS on one array. A detailed overview of the current status of our TMA platform with basic description of the individual array features is presented in Table 1. Additional TMAs from solitary fibrous tumor (SFT), angiosarcoma, and SynSa are currently under construction or in preparation, to match ongoing translational research in our group. Some TMAs (e.g., UZL_TMA_CCSA) were constructed in a way to combine tissue from the same donor taken at different stages of the disease, that is, material collected from the primary tumor, a local recurrence, and a metastatic lesion, to allow for important longitudinal biological studies. Other TMAs combine different histological subtypes, for example, four well-known variants of adipocytic sarcomas on one array for comparative studies (e.g., UZL_PT_TMA_LPS) or one disease combining cases with diverse molecular drivers on one TMA (e.g., UZL_PT_TMA_GIST) (Table 2). The created panel of TMAs is linked with extensive, well-structured clinical information from the according donors.
Institutions that contributed samples
Name of tissue microarrays
Soft tissue sarcoma subtypes included
Number of cases
Number of blocks
Number of cores per block
Core size (mm)
UZ Leuven and collaborating institutions
UZL_PT_TMA_multiple subtype STS
Angiosarcoma
7
7
2
1.0
Dedifferentiated liposarcoma
10
10
Pleomorphic liposarcoma
10
10
Myxoid liposarcoma
10
10
Leiomyosarcoma
9
9
Malignant peripheral nerve sheath tumor
10
10
Myxofibrosarcoma
11
11
Rhabdomyosarcoma
7
7
Synovial sarcoma
10
10
Undifferentiated pleomorphic sarcoma
9
9
UZL_PT_TMA_CCSA
Clear cell sarcoma
22
35
2
1.0
UZL_PT_TMA_ASPS
Alveolar soft part sarcoma
12
16
3
1.5
UZL_PT_TMA_IMFT
Inflammatory myofibroblastic tumor
12
12
3
1.5
UZL_PT_TMA_ARMS
Alveolar rhabdomyosarcoma
21
34
2
1.0
UZL_PT_TMA_LMS
Leiomyosarcoma
55
131
2
1.0
UZL_PT_TMA_GIST
Gastrointestinal stromal tumor
72
76
2
1.0
UZL_PT_TMA_LPS
Well-differentiated liposarcoma
14
20
3
1.0
Dedifferentiated liposarcoma
11
16
Pleomorphic liposarcoma
6
7
Myxoid liposarcoma
10
19
UZL_PT_TMA_SFT
Solitary fibrous tumor
Under construction
UZL_PT_TMA_ANGS
Angiosarcoma
In preparation
UZL_PT_TMA_SYNSA
Synovial sarcoma
In preparation
EORTC phase 2 trial 90101 (CREATE)
CREATE_TMA_CCSA
Clear cell sarcoma
32
32
3
1.5
CREATE_TMA_ASPS
Alveolar soft part sarcoma
47
49
3
1.5
CREATE_TMA_IMFT
Inflammatory myofibroblastic tumor
21
21
3
1.5
EORTC: European Organisation for Research and Treatment of Cancer
... Finally, only a selection of potential immune/ senescence biomarkers was evaluated; for instance, data on PD-L1 expression and other immune checkpoint and activation markers on the tumor are not yet available. An extensive multiplex immunohistochemistry analysis, using the newly developed 'Multiple Iterative Labeling by Antibody Neodeposition (MILAN)' technique 47 and including a multitude of additional immunerelated tumor markers is currently ongoing. These in depth analyses will allow us to characterise in more detail the phenotype and functional status of immune subsets of the tumor infiltrate, coexpression of immune markers and the local interactions between different cell types in the tumor microenvironment. ...
Objectives:
Aging is associated with altered immune function and chronic low-grade inflammation, referred to as immunosenescence. As breast cancer is an age-related disease, the impact of aging on tumor immune responses may have important consequences. However, effects of immunosenescence on breast tumor immune infiltration remain largely unknown.
Methods:
This exploratory study investigated a broad panel of immune/senescence markers in peripheral blood and in the tumor microenvironment of young, middle-aged and old patients diagnosed with early invasive luminal (hormone-sensitive, HER2-negative) breast cancer. In the old group, G8-scores were computed as a correlate for clinical frailty.
Results:
Significant age-related changes in plasma levels of several inflammatory mediators (IL-1α, IP-10, IL-8, MCP-1, CRP), immune checkpoint markers (Gal-9, sCD25, TIM-3, PD-L1), IGF-1 and circulating miRs (miR-18a, miR-19b, miR-20, miR-155, miR-195 and miR-326) were observed. Shifts were observed in distinct peripheral blood mononuclear cell populations, particularly naive CD8+ T-cells. At the tumor level, aging was associated with lower total lymphocytic infiltration, together with decreased abundance of several immune cell markers, especially CD8. The relative fractions of cell subsets in the immune infiltrate were also altered. Clinical frailty was associated with higher frequencies of exhausted/senescent (CD27-CD28- and/or CD57+) terminally differentiated CD8+ cells in the blood and with increased tumor infiltration by FOXP3+ cells.
Conclusion:
Aging and frailty are associated with profound changes of the blood and tumor immune profile in luminal breast cancer, pointing to a different interplay between tumor cells, immune cells and inflammatory mediators at higher age.
... An updated list of validated antibodies is published and updated. 6 For retinoic acid receptor related orphan receptor C (RORC), we directly assessed the effect of the stripping buffer by extending the incubation time to be equivalent to the cumulative exposure during 4 or 10 staining and stripping cycles (as previously published 3 ) ( Figure 1) and we confirmed that epitopes which survive the first cycle will not be affected by numerous subsequent staining and stripping cycles. ...
... 3 µm sections were processed for indirect IHC or multiple labeling as previously described in detail 24,25 and Supplementary Data. ...
Reactivation of the anti-tumor response has shown substantial progress in aggressive tumors such as melanoma and lung cancer. Data on less common histotypes are scanty. Immune checkpoint inhibitor therapy has been applied to few cases of uterine leiomyosarcomas, of which the immune cell composition was not examined in detail. We analyzed the inflammatory infiltrate of 21 such cases in high-dimensional, single cell phenotyping on routinely processed tissue. T-lymphoid cells displayed a composite phenotype common to all tumors, suggestive of antigen-exposure, acute and chronic exhaustion. To the contrary, myelomonocytic cells had case-specific individual combinations of phenotypes and subsets. We identified five distinct monocyte-macrophage cell types, some not described before, bearing immunosuppressive molecules (TIM3, B7H3, VISTA, PD1, PDL1). Detailed in situ analysis of routinely processed tissue yields comprehensive information about the immune status of sarcomas. The method employed provides equivalent information to extractive single-cell technology, with spatial contexture and a modest investment.
The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future. In this Review, the authors discuss the latest advances in profiling multiple molecular modalities from single cells, including genomic, transcriptomic, epigenomic and proteomic information. They describe the diverse strategies for separately analysing different modalities, how the data can be computationally integrated, and approaches for obtaining spatially resolved data.
Multiplex imaging technologies are increasingly used for single-cell phenotyping and spatial characterization of tissues; however, transparent methods are needed for comparing the performance of platforms, protocols and analytical pipelines. We developed a python software, mplexable, for reproducible image processing and utilize Jupyter notebooks to share our optimization of signal removal, antibody specificity, background correction and batch normalization of the multiplex imaging with a focus on cyclic immunofluorescence (CyCIF). Our work both improves the CyCIF methodology and provides a framework for multiplexed image analytics that can be easily shared and reproduced.
Recent single-cell technologies have enabled researchers to simultaneously assess the transcriptomes and other modalities of thousands of cells within their spatial context. Here, we have summarized available single-cell methods for dissociated tissues and tissue slides with respect to the specifics of microglial biology. We have focused on next-generation-based technologies. We review the potential of these single-cell sequencing methods and newer multiomics approaches to extend the understanding of microglia function beyond the status quo.
