Fig 2: BIAS for integrative image analysis and automated LMD single-cell isolation.a, AI-driven nucleus and cytoplasm segmentation of normal-appearing and cancer cells and tissue using BIAS. b, We benchmarked the accuracy of its segmentation approach using the F1 metric and compared results to three additional methods—M1 is unet4nuclei6, M2 is CellProfiler8 and M3 is Cellpose7—while OUR refers to nucleAIzer3. Bars show mean F1 scores with s.e.m.; n = 10 independent images for melanoma tissue and (U2OS) cells, and n = 20 for salivary gland tissue. Visual representation of the segmentation results: green areas correspond to true positive, blue to false positive and red to false negative. c, BIAS serves as the interface between the scanning and an LMD microscope, allowing high-accuracy transfers of cell contours between the microscopes. Illustration of cutting offset with respect to the object of interest and optimal path finding. d, Practical illustration of the functions in the upper panel. e, Immunofluorescence staining of the human fallopian tube epithelium with FOXJ1 and EpCAM antibodies, detecting ciliated and epithelial cells, respectively. Left panel: Ciliated (FOXJ1-positive) and secretory (FOXJ1-negative) cells. Right panel: Cell classification based on FOXJ1 intensity. Class 1 (FOXJ1-positive) and class 2 (FOXJ1-negative); magnification factor = ×387. f, PCA of FOXJ1-positive and FOXJ1-negative cell proteomes. g, Heat map of known protein markers for secretory and ciliated cells. Protein levels are z-scored. Asterisks represent imputed data. The marker list was derived from the Human Protein Atlas20 project and based on literature mining. h, Volcano plot of the pairwise proteomic comparison between FOXJ1-positive and FOXJ1-negative cells. Cell-type-specific marker proteins are highlighted in green and turquoise, and black represents potential novel marker proteins. Significant enriched cell-type-specific proteins are displayed above the black lines (two-sided t-test, FDR < 0.05, s0 = 0.1, n = 4 biological replicates).

Fig 3: DVP applied to archival tissue of a rare salivary gland carcinoma.a, Immunohistochemical staining of normal salivary gland stained for the cell adhesion protein EpCAM. Supervised (random forest) ML was trained to identify acinar (green) and duct cells (turquoise). Scale bar = 20µm. b, Quantitative proteomic comparison between acinar and duct cells from tissue in A with known cell type specific markers highlighted (https://bit.ly/3iOK8Qf). c, Relative protein levels of selected pathways that were significantly higher in acinar or duct cells. d, Unsupervised hierarchical clustering of acinar and duct cell proteomes from two different patients together with acinar cell carcinoma cells. Note that normal acinar cells of two different tissues clustered together. Duct cells clustered furthest away. Prior to clustering, protein levels from different sample groups (duct cell tissue #1, acinar cell tissue #1, acinar cell tissue #2, carcinoma tissue #2) were averaged and z-scored. Bar on the left shows differentially expressed pathways from panel b with acini and duct specific proteins in green and turquoise, respectively.

Fig 4: Anti-tumor capability of epithelial cell adhesion molecule-chimeric antigen receptor-T (EpCAM-CAR-T) at the in vitro level. A) The cytotoxicity of EpCAM-CAR-T cells against SKOV3 cells was analyzed by Real Time Cell Analysis assay. B) Levels of Interferon-γ (IFNγ) released by EpCAM-CAR-T cells analyzed by ELISA after incubated with ovarian cancer (OC) cells for 24 hr. Untransduced T cells were used as NC-T. Error bars denote the s.e.m., and the results were compared with two-way ANOVA test. ***P<0.001.

Fig 5: Expression of epithelial cell adhesion molecule (EpCAM) on ovarian cancer samples and cell lines. A) EpCAM expression was detected in ovarian cancer (OC) and the para-cancerous tissue, scale bar=100 µm. B) The surface expression of EpCAM on OC cell line SKOV3 detected by flow cytometry.