Stained slides were digitized using a multispectral slide imaging platform (Vectra Polaris; Akoya Biosciences, Marlborough, MA). Tumor surfaces were assessed using Inform software (v2.5.1, Akoya Biosciences) after manual annotation of the scanned slides by a pathologist and served to calculate the density of CD8+ T cells per sample after digital tissue segmentation and cell phenotyping (Inform software; Akoya Bioscience, v2.5.1).
Inform software
Manufactured by Akoya Biosciences
Sourced in United States
InForm software is a digital pathology platform developed by Akoya Biosciences. It is designed to enable the analysis and quantification of multiplex protein biomarkers in tissue samples.
Automatically generated - may contain errors
Lab products found in correlation
Vectra polaris, by Akoya Biosciences (5 mentions)
Phenochart software, by Akoya Biosciences (4 mentions)
Vectra polaris automated quantitative pathology imaging system, by Akoya Biosciences (4 mentions)
Halo software, by Indica Labs (4 mentions)
Prolong gold antifade reagent, by Thermo Fisher Scientific (3 mentions)
Vectra polaris imaging system, by Akoya Biosciences (2 mentions)
Phenoptrreports plug in, by Akoya Biosciences (2 mentions)
Vectra imaging system, by Akoya Biosciences (2 mentions)
4 6 diamidino 2 phenylindole (dapi), by Thermo Fisher Scientific (2 mentions)
Avidin biotin blocking system, by BioLegend (2 mentions)
Cd45.1 pe clone a20, by BioLegend (2 mentions)
Cd169 alexafluor488 3d6.112, by BioLegend (2 mentions)
B220 dylight650, by BioLegend (2 mentions)
F480 alexafluor488 bm8, by BioLegend (2 mentions)
Cd3e biotin, by BioLegend (2 mentions)
Streptavidin alexafluor750, by Thermo Fisher Scientific (2 mentions)
Igm cy5, by Jackson ImmunoResearch (2 mentions)
Opal polaris 7 color multiplex ihc kit, by Akoya Biosciences (2 mentions)
Opal polymer hrp ms rb, by Akoya Biosciences (2 mentions)
Bond max, by Leica (2 mentions)
52 protocols using inform software
1
Quantifying Tumor-Infiltrating CD8+ T Cells
2
Multiplex Immunohistochemistry Analysis of Liver Tumor
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The tumor score was determined by evaluating H&E‐stained liver sections. The degree of inflammatory cell infiltration and the mitotic rate were assessed using published methods.[46 (link),
47 (link)
] Immunostaining was performed using antibodies included CD4 (D7D2Z) rabbit monoclonal antibody, CD8α (D4W2Z) XP rabbit monoclonal antibody, and F4/80 (D2S9R) XP rabbit monoclonal antibody (Cell Signaling Technology), following a published protocol.[48 (link)
] During the multiplex optimization process, evaluations were conducted and made adjustments to antibody‐Opal dye pairings, concentrations, and their order within the panel. This optimization included assessing signal‐to‐noise ratios, ensuring that the positive stain's signal intensity exceeded the background by a ratio greater than 10:1. Additionally, signal balance was addressed by maintaining a signal intensity range of ≈10–30 normalized counts for each fluorophore. These adjustments were carried out using the inForm software by Akoya Biosciences.[48 (link)
] Subsequently, multiplexed fluorescence images of the liver sections were analyzed utilizing QuPath version 0.2.3.
47 (link)
] Immunostaining was performed using antibodies included CD4 (D7D2Z) rabbit monoclonal antibody, CD8α (D4W2Z) XP rabbit monoclonal antibody, and F4/80 (D2S9R) XP rabbit monoclonal antibody (Cell Signaling Technology), following a published protocol.[48 (link)
] During the multiplex optimization process, evaluations were conducted and made adjustments to antibody‐Opal dye pairings, concentrations, and their order within the panel. This optimization included assessing signal‐to‐noise ratios, ensuring that the positive stain's signal intensity exceeded the background by a ratio greater than 10:1. Additionally, signal balance was addressed by maintaining a signal intensity range of ≈10–30 normalized counts for each fluorophore. These adjustments were carried out using the inForm software by Akoya Biosciences.[48 (link)
] Subsequently, multiplexed fluorescence images of the liver sections were analyzed utilizing QuPath version 0.2.3.
3
Multiplex IF Staining of TMAs
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Tissues of tissue microarray (TMA) were sliced into sections with 9 µm thickness and mounted onto glass slices. Multiplex immunofluorescent staining was performed on TMAs using Opal 7‐Color IHC kits (Akoya Biosciences, Hopkinton, MA) according to the manufacturer's instructions. Briefly, sections were deparaffinized using xylene and progressively hydrated by ethanol ending with a distilled water wash. Microwave treatment was performed in AR6 buffer for antigen retrieval. Then slides were sequentially stained with the following primary antibodies and fluorescent dyes: anti‐CD31 (1:50, #ab9498, Abcam)/Opal‐520, Anti‐phospho‐FGFR4 (1:200, #PA5105531, Invitrogen)/Opal‐620, anti‐pan‐cytokeratin (1:100, #ab86734, Abcam)/Opal‐690. For each molecule being detected, slides were incubated with the specific primary and secondary antibody, followed by Opal fluorophore solution and incubated for 10 min at room temperature. Afterward, microwave treatment was performed again to remove the specific primary antibody. Steps were repeated for subsequent primary antibodies to achieve multiplex IF staining. After antibody staining, slides were incubated in DAPI solution for 5 min at room temperature, washed several times, and then mounted with coverslips. Digital images of all cores of TMA were acquired using the Vectra Polaris Imaging System and analyzed by inForm software (Akoya Biosciences).
4
Automated Quantification of Neutrophil Extracellular Traps
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Evaluation of NETs was performed using an Automated Quantitative Pathology Imaging System (Vectra Polaris, Akoya Biosciences). Tissue imaging and spectral unmixing were performed using inForm software (version 2.4.8, Akoya Biosciences). Image analysis was then performed using the open-source digital pathology software QuPath version 0.2.3 and ImageJ Software, an open-source Java-based image processing software. Measurement workflow and scoring have been previously described (42 (link)). In short, neutrophils were identified by the costaining with CD15 and MPO. NETs were detected based on the costaining with CD15, MPO, and H3Cit. An ImageJ software plugin was developed and validated to accurately calculate the percentage area of neutrophils and NETs for each TMA spot (42 (link)).
5
Multiplex Immunofluorescence Imaging of Tumor Microenvironment
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Multispectral imaging (MSI) was performed using the basic protocol described in Wickenhauser et al. [66 (link)]. Two multiplex panels with different mAbs and opal-dye combinations were used. The first panel included anti-PD-L1 clone E1L3N (Cell Signaling E1L3N, 1:150) in combination with Opal690, anti-Foxp3 clone 236A/E/ (Abcam, 1:00) with Opal540, anti-CD3 clone SP7 (ThermoFisher SP7, 1:100) with Opal570, anti-CD163 clone MRQ-26 (Cell Marque, 1:50) with Opal620 and anti-panCK Ab AE1/AE3 (Dako, 1:150) with Opal520. The second panel comprised anti-TIM-3 (Abcam, ab241332, 1:1000) with Opal 520, anti-PD-1 (Biocare Medical, NAT105, 1:50) with Opal 540, anti-CD8 (DAKO, C8/144b, 1:50) with Opal 570, anti-TIGIT (Biozol, USC-PAN056HU01-1, 1:50) with Opal 620, anti-CD69 (Abcam, ab233396, 1:50) with Opal 650 and anti-HLA-G (Abcam, clone 4H84, 1:100) with Opal 690. After counterstaining with DAPI (Akoya Biosciences, Marlborough, MA), the sections were mounted and scanned with the Vectra Polaris System (Akoya Biosciences, Marlborough, MA) and a mean of 18 regions of interest (ROIs) per slide were taken with a 20 × zoom. The inForm software (Version 2.4.10, Akoya Biosciences) was employed to perform cell segmentation and phenotyping. PhenoptrReports scripts were used within R to evaluate the frequency and density of the different cell types as well as their interspatial relationships.
6
Multiplex Immunofluorescence Profiling of Colorectal Cancer
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Two panels of antibodies were used to perform mIF on CRC TMAs (n=787). On panel 1, a fully automated mIF assay was developed on the Ventana Discovery Ultra autostainer platform (Roche Tissue Diagnostics, software version RUO Discovery Universal V21.00.0019). Staining was performed on 4 µm thick sections of previously constructed TMAs with the optimised antibodies (Table S1 ). A negative control slide was used on each staining run to rule out non-specific staining. Whole slide images were captured at 10x magnification using the PhenoImager HT multispectral slide scanner (Akoya Biosciences V1.0.13), TMA maps were applied using Phenochart software (Akoya Biosciences V1.1.0), and core images were captured at 20x magnification. Core images were spectrally unmixed using Inform software (Akoya Biosciences, software version 2.5.1).
mIF panel 2 was stained using an autostainer (Thermofisher) with optimised antibodies (Table S1 ). The slides were scanned by NanoZoomer S60 digital slide scanner (Hamamatsu, USA) with 20x magnification. TMA maps were applied for further analysis. Visiopharm (version 2021.02.5.10297), a digital precision pathology software, was used to perform the analysis. The percent positive cells of total cells detected for each marker were calculated (Figure S1 ).
mIF panel 2 was stained using an autostainer (Thermofisher) with optimised antibodies (
7
Automated Multiplex Immunofluorescence Imaging
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Automated mIF was performed as previously described (Giraldo et al. 2018 (link); Davis et al. 2020 (link)). Briefly, slides were heated and dewaxed to remove any paraffin. Antigen retrieval was performed using ER2 followed by washing steps. Nonspecific staining was blocked using Blocking/Ab Diluent (Akoya Biosciences) followed by the first primary antibody (see position 1 in Supplemental Table S3 ). The corresponding polymer was applied followed by the tyramide signal amplification dye (Opal Automation Multiplex IHC Kit; Akoya Biosciences). Slides were heated to strip the primary antibody and polymer, washed, and blocked again. The process was repeated for positions 2–6. After the last step of antibody striping, the slides were stained for DAPI and coverslipped using ProLong Diamond Antifade Mountant (Life Technologies).
Slides were scanned using the Vectra Polaris Quantitative Pathology Imaging System (Akoya Biosciences). A 10× (1 µm/px) whole-slide scan was acquired and used as a guide to select 20 high power field (HPF) for 20× image acquisition. These 20× HPF images were processed in Inform software (Akoya Biosciences) and exported to images with QPTIFF format.
Slides were scanned using the Vectra Polaris Quantitative Pathology Imaging System (Akoya Biosciences). A 10× (1 µm/px) whole-slide scan was acquired and used as a guide to select 20 high power field (HPF) for 20× image acquisition. These 20× HPF images were processed in Inform software (Akoya Biosciences) and exported to images with QPTIFF format.
8
Automated Quantitative Pathology Imaging
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Whole slide scans were imaged on the Vectra 3.0 Automated Quantitative Pathology Imaging System (Akoya) using the 20× objective. We randomly selected 12 multispectral image regions each slide using Phenochart software (Akoya Biosciences) at 40× magnification, which were then analyzed with inForm software (v2.4.10, Akoya) to unmix adjacent fluorochromes, subtract autofluorescence, segment the tissue into tumor and stroma regions, segment the cells into nuclear, cytoplasmic, and membrane compartments, and to phenotype the cells according to morphology and cell marker expression based on either their PD-L1 status or their expression of CD68, CD11c, and CK (CD68−CD11c−CK− cells were defined as “other”). Independent projects were created to phenotype each cellular marker, then merged, consolidated, and analyzed in R Studio using the phenoptrReports plug-in (Akoya Biosciences) to quantify the total number of PD-L1+ cells that overlapped CD68/CD11c/CK/other cells. We also used phenoptrReports to quantify entire-cell PD-L1 expression in each phenotype category in all 23 samples. Use of human samples was approved by IRB of University of Colorado AMC (COMIRB Protocol 16-2436).
9
Quantifying Murine Hepatic Lymphatics
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LVD is defined as the area of the lymphatics divided by the defined tissue area. For lymphatic density in murine livers, regions portal tracts were selected and images were exported in tiff format after unmixing in Inform software (Akoya Biosciences, Marlborough, MA. Lymphatics were colored in using the color tool and the whole 1800 × 1500 area was opened with ImageJ version 1.52T (National Institutes of Health, Bethesda, MD). The image was converted into an 8-bit image and the threshold was adjusted so only the drawn lymphatic area was seen. The analyze particles function was used to determine the area of the lymphatics. Area of lymphatics in each portal triad was then divided by the area of the portal triad (∼0.7 mm2) to calculate lymphatic vessel density per portal area. Approximately 5 portal areas were calculated per liver tissue section (∼70 mm2) in 2-5 mice per group from 2 different experiments.
10
Quantifying c-Myc and G9a Expression in HCC Tissues
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Tissues were fixed in 4% paraformaldehyde immediately after isolation and embedded in paraffin. Tissue sections of 4 μm thickness were stained for immunohistochemistry. Ten HCC‐PDX tissues and a tissue microarray (TMA) of 77 human liver cancer patients (OutdoBiotech, Shanghai, China) were serially stained using the Opal workflow (Akoya Biosciences, Marlborough, MA, USA) with c‐Myc primary antibody (1 : 200, Abcam) for 1 h followed by HRP‐conjugated secondary antibody and tyramide signal amplification (TSA) by fluorescein isothiocyanate (FITC). Tissues were subsequently stained with G9a primary antibody (Abcam), and the same TSA system was applied using Cyanine 5 (Cy5) as the fluorescent stain. DAPI was used as the nuclear counterstain. Image acquisition and signal quantification analysis of the tissues were performed using the Vectra imaging system (Akoya Biosciences) and inForm software (Akoya Biosciences) respectively. Tissues were categorised into low and high expression using the first and third quartile mean intensities as thresholds respectively.
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