Journal: American Journal of Cancer Research

Article Title: Upregulation of CYP1B1 by hypoxia is mediated by ERα activation in breast cancer cells

doi:

Figure Lengend Snippet: Analysis of HIF-1α and CYP1B1 expression in tissue microarray (TMA) samples from breast cancer patients. (A) Schematic diagram of the tumor stages of each breast tissue core. (B) Hematoxylin and eosin (H&E) staining images provided by the manufacturer. Immunofluorescence images of tumor microarrays (TMA) stained with anti-hypoxia-inducible factor-1 alpha (HIF-1α) (C) and anti-cytochrome P450 1B1 (CYP1B1) (D) antibodies. Images were acquired at 20X magnification using a Leica Thunder microscope. Whole tissue slide images were mosaic merged via LAS-X software. (E) Representative images of immunofluorescence analysis of HIF-1α (green) and CYP1B1 (green) in two slides of ER-negative and positive breast cancer TMA. Immunofluorescence images were acquired using a Leica Thunder microscope. (F) Scatter plots showing fluorescence intensity correlation analysis of HIF-1α and CYP1B1 in 64 ER-positive TMAs. (G) Violin plots of fluorescence intensities of HIF-1α and CYP1B1. Samples were classified into low (immunohistochemical [IHC] score: 1+, 2+) and high (IHC score: 3+) groups according to the estrogen receptor (ER) expression status of the TMA specification sheet, and the correlation between HIF-1α and CYP1B1 expression was analyzed. (H) Analysis of fluorescence intensity of CYP1B1 against HIF1α expression in ER-positive TMA. The fluorescence intensity of CYP1B1 was analyzed by classifying the fluorescence intensity of HIF1-α based on the top and bottom 25% ER expression. *, P<0.0001 versus ER-positive tumor tissue with low HIF1-α fluorescence intensity by Mann-Whitney test.

Article Snippet: Immunofluorescence analysis of tumor microarrays (TMAs) A human breast cancer tissue microarray (TMA, #BC081120e) containing 110 cases was purchased from Biomax (Rockville, MD).

Techniques: Expressing, Microarray, Staining, Immunofluorescence, Microscopy, Software, Fluorescence, Immunohistochemical staining, MANN-WHITNEY

Journal: Cancer Research

Article Title: Integrating AI-Powered Digital Pathology and Imaging Mass Cytometry Identifies Key Classifiers of Tumor Cells, Stroma, and Immune Cells in Non–Small Cell Lung Cancer

doi: 10.1158/0008-5472.CAN-23-1698

Figure Lengend Snippet: Multidimensional analysis of the NSCLC tumor ecosystem by IMC. A, Schematic representation of the IMC workflow on a formalin-fixed, paraffin-embedded tissue microarray. Key steps include staining with metal-tagged antibodies, spot-by-spot laser ablation, and acquisition by a mass cytometer. High dimensional images are reconstructed, processed, and segmented at both cellular and tissue level, generating data for further analyses. B, Heat map showing the mean values of key lineage markers adopted for cell cluster annotation. Proteins and cell phenotypes are ordered by hierarchical clustering with the Pearson correlation distance. Protein expression is color-coded from blue (lower) to red (higher) and scaled by column. C, Representative matched pictures of a NSCLC specimen showing pan-cytokeratin–positive tumor cells (left) and the tissue segmentation resulting from the machine learning pixel classifier (right). D, Spatial distribution and quantification of immune cell populations as the absolute cell number per mm 2 (left) or as a percentage of total immune cells (right) in the tumor and the stroma. E, Heat map showing the normalized marker expression in each macrophage cluster. Markers and cell clusters are ordered by hierarchical clustering according to Pearson correlation distance. Mean values of marker expression are represented and color-coded from blue (lower) to red (higher) and scaled by column. Color code indicates cluster identity. F and G, UMAP projections of macrophage cells ( n = 46733) from NSCLC tumors showing 20 clusters ( F ) or the cell distribution according to tissue segmentation ( G ). Each dot represents an individual cell. H, S100A8 + Mϕ infiltrate both the stroma and the tumor nests of NSCLC tissues. Representative pictures of the distribution of Mϕ (defined as CD68 + cells) and the subpopulation of S100A8 + Mϕ within tumor nests of a NSCLC tissue.

Article Snippet: Cohort 1 included 108 patients diagnosed with NSCLC, whose tumor specimen was spotted on a tissue microarray (TMA; LC2162–US Biomax), containing 209 cores.

Techniques: Formalin-fixed Paraffin-Embedded, Microarray, Staining, Cytometry, Expressing, Marker