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Fig. 4 | Molecular Cancer

Fig. 4

From: Cellular organization and molecular differentiation model of breast cancer-associated fibroblasts

Fig. 4

Analysis of patient-derived fibroblasts. a Basic statistics of single-cell gene expression profiles of patient-derived fibroblasts isolated from invasive, ERα-positive breast cancer and according normal tissue. Graphs represent frequency of selected gene targets in percentage as bars and average gene expression levels given as log2-transformed relative quantities depicted as dots. Error bars represent SEM (*p-value < 0.05 ANOVA, NF: normal fibroblast, CAF: cancer-associated fibroblast). b (Left panel) Principal component analysis (PCA) of 152 individual normal (n = 77, blue dots) and cancer-associated fibroblasts (n = 75, red triangles). (Right panel) Plot represents the gene loadings for the PCA. Principal component projection of the genes illustrates the contribution of each gene to the scores of PC2 and PC3. Groups of genes are indicated as follows; orange: epithelial, red: fibroblast markers, purple: chemokines, green: transcription factors, blue: proliferation markers, grey: breast cancer-specific stem cell markers, black: pluripotency. Identified gene clusters of cell line model are highlighted with gene cluster A divided into two (A1, A2) whereas gene cluster E is absent. c PCA depicting combined mean-centered datasets of single-cell gene expression of CAF model and patient-derived fibroblasts based on ten genes with potential fibroblast activation-predictive qualities. d PCAs of subgroups/differentiation states and applying patient-derived normal (left panel) and cancer-associated fibroblast (middle panel) single-cell data as test set. Patient data was normalized due to variable global expression levels by autoscaling data per cell. (Right panel) According gene loadings for PCAs

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