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Phenochart

Manufactured by PerkinElmer
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Phenochart is a digital pathology software that enables the visualization and annotation of whole slide images. It provides tools for image management, analysis, and collaboration within a digital pathology workflow.

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Lab products found in correlation

4 6 diamidino 2 phenylindole (dapi), by Merck Group (3 mentions) Mantra quantitative pathology imaging system, by PerkinElmer (3 mentions) H 1400, by Vector Laboratories (2 mentions) Vectra3 multi spectral imaging microscope, by PerkinElmer (2 mentions) Inform software, by Akoya Biosciences (2 mentions) Hardset mounting media, by Vector Laboratories (2 mentions) Vectra polaris imaging system, by PerkinElmer (2 mentions) Vectra3 slide scanner, by PerkinElmer (2 mentions) Multispectral imaging system, by PerkinElmer (1 mentions) Inform software, by PerkinElmer (1 mentions) Bond rx, by Leica (1 mentions) Vectra polaris, by PerkinElmer (1 mentions) Vectra multispectral imaging system version 2, by PerkinElmer (1 mentions) Inform software version 2, by Akoya Biosciences (1 mentions) S3022, by Agilent Technologies (1 mentions) Vectra 3 quantitative pathology imaging system, by PerkinElmer (1 mentions) Opal 7 color fluorescent ihc kit, by PerkinElmer (1 mentions) Slc25a1 antibody, by Proteintech (1 mentions) 4 6 diamidino 2 phenylindole (dapi), by BestBio (1 mentions) F4 80, by Cell Signaling Technology (1 mentions)

Spelling variants of this product

Phenochart software (12 citations) Phenochart (v1.0) (2 citations)

22 protocols using phenochart

1

Multiplex Immunohistochemistry for Tumor Biomarkers

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Tissue sections were blocked with 3% hydrogen peroxide in TBST for 10 min and stained with a multiplex mIHC kit (Panovue, 10217100100). Briefly, the slides were incubated with MTSS1 antibody (CST, 93065) for 60 min, then incubated using the HRP–polymer detection system for 10 min for each step, before visualization using TSA 780 (1:100) for another 10 min. Following this, antigen retrieval was conducted to prepare slides for the next antibody. Using this TSA mIHC method, all samples were stained sequentially with the primary antibodies for PD-L1 (ABCAM, ab213524) visualized with TSA 570 (1:100), CD8A (ABCAM, ab17147) visualized with TSA 480 (1:100), GZMB (CST, 46890) visualized with TSA 690 (1:100), and the KRAS (ABCAM, ab180772) visualized with TSA 620 (1:100). Slides were counterstained with DAPI (Sigma, 1:1000) for nuclei visualization, and subsequently coverslipped using the Hardset mounting media (VectaShield, H-1400).
All tissue sections were imaged using the multispectral imaging system (PerkinElmer, Shanghai Kelin) under the appropriate fluorescent filters for multispectral analysis. A whole slide scan of the multiplex tissue sections produced multispectral fluorescent images visualized in Phenochart (PerkinElmer, Shanghai Kelin) at 200× magnification for further image analysis.
Wang Y., Jia Z., Liang C., He Y., Cong M., Wu Q., Tian P., He D., Miao X., Sun B., Yin Y., Peng C., Yao F., Fu D., Liang Y., Zhang P., Xiong H, & Hu G. (2023). MTSS1 curtails lung adenocarcinoma immune evasion by promoting AIP4-mediated PD-L1 monoubiquitination and lysosomal degradation. Cell Discovery, 9, 20.
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2

Quantitative Pathology Imaging of Tumor Immune Landscape

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Slides were scanned using the Automated Quantitative Pathology Imaging System (Vectra V.3.0.4, PerkinElmer) at an overview (4× magnification). Phenochart (V.1.0.9, PerkinElmer) was used to annotate multispectral images of tumor tissue to be scanned at 20× magnification. InForm software (V.2.4.2, PerkinElmer) was used for spectral unmixing of Opal fluorophores. Spectral unmixed images were digitally merged to create high magnification overviews of the tissue slides. Samples were assessed by a pathologist (ML/KG), and a region of interest (ROI) was selected containing the tumor and all surrounding stroma. Healthy tissue surrounding the tumor was excluded from the ROI. Tissue was segmented using InForm software to identify tumor regions (pan-cytokeratin positive areas). Due to the nature of the available tissue (ie, most samples were small biopsies), it was not possible to reliably identify an invasive margin, therefore we analyzed the lymphocyte infiltration per sample and no further distinction between tumor infiltrating lymphocytes or tumor excluded lymphocytes was made. HLA-ABC staining was converted to pseudo-3,3′-diaminobenzidine staining and scored for the absence of membranous expression of HLA-ABC.
van der Woude L.L., Gorris M.A., Wortel I.M., Creemers J.H., Verrijp K., Monkhorst K., Grünberg K., van den Heuvel M.M., Textor J., Figdor C.G., Piet B., Theelen W.S, & de Vries I.J. (2022). Tumor microenvironment shows an immunological abscopal effect in patients with NSCLC treated with pembrolizumab-radiotherapy combination. Journal for Immunotherapy of Cancer, 10(10), e005248.
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3

Multiplexed Immunohistochemistry Analysis

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Immunohistochemical protocols were performed using 4 mm thick sections, mCD8 antibody (Cell Signaling) as primary antibody. All slides were stained by Bond RX fully automated staining device (LEICA), scanned by Vectra Polaris (Perkin Elmer), and analyzed by Phenochart and InForm (Perkin Elmer) according to the manufacturer’s protocol. The anti-mPD-L1, anti-Pan-CK, anti-mCD8, anti-mFoxp3, anti-mPD-1 and anti-mGranzyme B antibodies were applied for multiplex immunohistochemistry. The InForm software was used for analysis tissue and cell segmentation. The individual cells including target expression were integrated and converted by R (V.3.6.1). The converted matrix files were analyzed for deconvoluted results by FlowJo software (V.10.6.2).
Pyo K.H., Lim S.M., Park C.W., Jo H.N., Kim J.H., Yun M.R., Kim D., Xin C.F., Lee W., Gheorghiu B., Hong M.H., Kim H.R., Shim H.S., Jang M., Lee S.S, & Cho B.C. (2020). Comprehensive analyses of immunodynamics and immunoreactivity in response to treatment in ALK-positive non-small-cell lung cancer. Journal for Immunotherapy of Cancer, 8(2), e000970.
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4

Multiplex Fluorescent Imaging for Tissue Analysis

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ESCC tissue microarrays that underwent multiplex fluorescent staining for each fluorophore were imaged using Vectra Multispectral Imaging System version 2 (Perkin Elmer, USA) under the appropriate fluorescent filters (green for Opal 570, blue for Opal 540 and DAPI) to yield the spectral library required for multispectral analysis. A whole slide scan of the multiplex tissue sections produced multispectral fluorescent images visualized in Phenochart (Perkin Elmer, USA) and imaging at 20 × power for further analysis. Analysis of the multispectral images was conducted using inForm image analysis (Perkin Elmer, USA). Representative images of each sample used to establish tissue segmentation, which was applied to batch analysis of all high-power multispectral images. The positivity threshold of each marker was then determined and recorded for further data analysis.
Zheng S., Liu T., Li L., Liu Q., Huang C., Liang Y., Tan Y., Zhang L, & Lu X. (2023). SLC1A5, unrelated to prognosis, was associated with CD8+ T-cell exclusion in the tumor microenvironment of squamous cell carcinoma. Heliyon, 9(3), e14571.
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5

Tissue Segmentation and Cell Phenotyping

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Slides were imaged using a Vectra microscope. Whole slide scans were performed using the ×10 objective lens. ROIs were selected with fixed-size stamps in Phenochart (PerkinElmer), based on the previously acquired whole slide scan images. 1 × 1 (669 × 500 µm; ×20 object lens) stamp was used for the Margin and 2 × 2 (1338 × 1000 µm) for the Core, Edge, and Normal. As many viable regions as possible in each specimen were selected with minimal overlap. Acquired images (n = 1800) were analyzed with inForm for tissue-component segmentation of tumor-cell (AE1AE3+) and stroma (AE1AE3–) regions and cell phenotyping. Density of cells in each ROI was calculated by combining the cell counts from all images and normalizing by the total area (cell/mm2).
Huang Y.K., Wang M., Sun Y., Di Costanzo N., Mitchell C., Achuthan A., Hamilton J.A., Busuttil R.A, & Boussioutas A. (2019). Macrophage spatial heterogeneity in gastric cancer defined by multiplex immunohistochemistry. Nature Communications, 10, 3928.
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6

Quantitative Pathology Imaging of FFPE Tissues

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The stained FFPE tissue sections were scanned using the Mantra quantitative pathology imaging system (PerkinElmer, Waltham, MA, USA) to obtain bright field and fluorescence images of the whole slides. Two pathologists observed the scanned pathological images using Phenochart (PerkinElmer) software and segmented the tumor core (TC) and normal (N) regions. The tumor core region and the normal region are not directly adjacent but are separated by the invasion margin (IM, the region between the two is approximately 1–1.5 mm wide). Subsequently, a fixed-size stamp (930 × 700 μm; × 20 objective lens) was used to select the representative region of interest (ROI) in the tumor center and normal regions. As many nonoverlapping ROIs as possible were chosen in each slice. Two pathologists were responsible for controlling the quality of the stained regions to ensure that all ROIs were within a suitable range of signal intensity.
Jia K., Chen Y., Sun Y., Hu Y., Jiao L., Ma J., Yuan J., Qi C., Li Y., Gong J., Gao J., Zhang X., Li J., Zhang C, & Shen L. (2022). Multiplex immunohistochemistry defines the tumor immune microenvironment and immunotherapeutic outcome in CLDN18.2-positive gastric cancer. BMC Medicine, 20, 223.
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7

Multiplex Immunohistochemistry of FFPE Tissues

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All data and images shown in this paper were conducted by mfIHC, except for those in Additional file 1: Figure S1. This staining was performed based on the manufacturer’s protocol (PerkinElmer, Opal® Kit) to visualize 8 specific cell markers (Additional file 1: Table S2). The specific experimental operation steps are reflected in Additional file 1.
The stained FFPE tissue sections were scanned using a Vectra microscope. Next, regions of interest (ROIs) were selected with fixed-size stamps (931 × 698 µm; 20× object lens) in Phenochart (PerkinElmer), based on the acquired whole slide scan images. Six filter cubes were used for each image capture, including DAPI (368–461 nm), 480 (450–500 nm), FITC (494–536 nm), CY3 (550–570 nm), CY5 (627–694 nm), and Texas Red (588–616 nm). Three ROIs of 0.65 mm2 were selected for each tumor core in order to cover the entire tumor core as much as possible, then each ROIs were scanned at 200× magnification using a Ventana Image Viewer with the same exposure times.
Li B., Guo Y., Yi Y., Huang Z., Ren Y., Wang H, & Yang L. (2023). Non-spatial and spatial heterogeneity revealed a suppressive immune feature of Siglec-15 in lung adenocarcinomas. Journal of Translational Medicine, 21, 599.
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8

Quantitative Pathology Imaging of FFPE Tissues

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The stained FFPE tissue sections were scanned using the Mantra quantitative pathology imaging system (PerkinElmer, Waltham, MA, USA) to obtain bright field and fluorescence images of the whole slides. Two pathologists observed the scanned pathological images using Phenochart (PerkinElmer) software and segmented the tumor core (TC) and normal (N) regions. The tumor core region and the normal region are not directly adjacent but are separated by the invasion margin (IM, the region between the two is approximately 1–1.5 mm wide). Subsequently, a fixed-size stamp (930 × 700 μm; × 20 objective lens) was used to select the representative region of interest (ROI) in the tumor center and normal regions. As many nonoverlapping ROIs as possible were chosen in each slice. Two pathologists were responsible for controlling the quality of the stained regions to ensure that all ROIs were within a suitable range of signal intensity.
Jia K., Chen Y., Sun Y., Hu Y., Jiao L., Ma J., Yuan J., Qi C., Li Y., Gong J., Gao J., Zhang X., Li J., Zhang C, & Shen L. (2022). Multiplex immunohistochemistry defines the tumor immune microenvironment and immunotherapeutic outcome in CLDN18.2-positive gastric cancer. BMC Medicine, 20, 223.
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9

Quantitative Pathology Imaging Workflow

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Images were acquired using the Mantra Quantitative Pathology Imaging System (PerkinElmer, Waltham, MA). The multi-spectral images were visualised in a Phenochart. Briefly, representative ROIs were chosen by two specialist pathologists, and multiple fields of view were acquired at 20× for further analysis. The ROIs were defined as follows: normal tissue adjacent to the tumour (N), the area within the specimen but not within the tumour; IM, the area at the interface of tumour and normal tissues (approximately 1–1.5 mm; depth defined by the size of the microscopy field); TC, -the tumour centre ROIs were selected with fixed-size stamps in a Phenochart (PerkinElmer), based on the previously acquired whole-slide scan images. A1 × 1 (930 × 700 µm; ×20 object lens) stamp was used. As many viable regions as possible in each specimen were selected with minimal overlap. All processed data were subjected to quality control (QC) by a pathologist, with the subsequent exclusion of the inappropriate regions from the analysis as well as the confirmation of outlier results.
Chen Y., Jia K., Sun Y., Zhang C., Li Y., Zhang L., Chen Z., Zhang J., Hu Y., Yuan J., Zhao X., Li Y., Gong J., Dong B., Zhang X., Li J, & Shen L. (2022). Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment. Nature Communications, 13, 4851.
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10

Spatial Mapping of Cell Phenotypes

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Stained slides were scanned using the Vectra3 Multi-Spectral Imaging Microscope with Vectra and Phenochart software (Perkin Elmer). Every available TMA core was imaged as a 3x3 composite image to capture almost the entire core in one image. The scanned images were analyzed in inForm software version 2.3 (Akoya). The inForm software is trained to identify individual cells within the TMA core by hematoxylin staining and intensity, average cell size, and cell splitting algorithms. Brown DAB staining that overlapped with hematoxylin staining was identified by the software as being a nuclear staining, while staining without overlap with the nuclear signal was considered cytoplasmic. In this way, nuclear versus cytoplasmic staining was differentiated. An average of 11,000 cells were counted per TMA core.
Fernandez A.I., Geng X., Chaldekas K., Harris B., Duttargi A., Berry V.L., Berry D.L., Mahajan A., Cavalli L.R., Győrffy B., Tan M, & Riggins R.B. (2019). The orphan nuclear receptor estrogen-related receptor beta (ERRβ) in triple-negative breast cancer. Breast cancer research and treatment, 179(3), 585-604.
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