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Journal: bioRxiv
Article Title: Tumor-associated mammary fibroblast matrices contain O-glycosylated oncofetal fibronectin
doi: 10.64898/2026.09.29.755525
Figure Lengend Snippet: A) The breast cancer tumor microenvironment contains a heterogeneous population of cells, including primary site and migrating metastatic cells that release soluble cytokine factors into the environment. Fibroblasts respond to environmental signals and become cancer-associated fibroblasts (CAFs), depositing an excess of ECM proteins, such as oncofetal fibronectin, which contributes to cancerous conditions. Oncofetal fibronectin is associated with epithelial-mesenchymal transition and multi-drug resistance in cancer cells. ECM-integrin binding can activate downstream signaling pathways that affect cancer cell phenotype; however, the mechanisms by which oncofetal fibronectin promotes cancer progression are not well understood. B) To recapitulate tumor soluble cues, media exposed to confluent HCC-1937 and MDA-MB-231 cells was collected. C) To provide a substrate of relevant bulk stiffness, polyacrylamide gels of healthy (2 kPa) and cancerous (20 kPa) adipose tissue were cast and functionalized with collagen. D) Human mammary fibroblasts (HMFs) were grown in tumor conditioned media and seeded on gels of relevant stiffness to model the tumor microenvironment that would promote a CAF phenotype. After 5 days of matrix deposition, samples were either assessed for HMF activation, decellularized for analysis of matrix microarchitecture, or decellularized and reseeded with cancer cells to evaluate the effect of tumor-associated matrices on cancer cell morphology.
Article Snippet: Additionally,
Techniques: Binding Assay, Protein-Protein interactions, Tissue, Activation Assay, Analysis, Morphology, Negative Control
Journal: bioRxiv
Article Title: Tumor-associated mammary fibroblast matrices contain O-glycosylated oncofetal fibronectin
doi: 10.64898/2026.09.29.755525
Figure Lengend Snippet: A) Representative maximum projection images of human mammary fibroblast (HMF) cell nuclei (blue), alpha smooth muscle actin (αSMA) (red), F-Actin (orange), total fibronectin (FN) (green) and the merged image of all channels for INC, cTCM, and mTCM groups. INC refers to HMFs cultured on 2 kPa polyacrylamide gels and fed with incubated low serum media not exposed to cancer cells. cTCM and mTCM HMFs were cultured on 20 kPa gels fed with tumor-conditioned media collected from HCC-1937 and MDA-MB-231 breast adenocarcinoma cells, respectively. Scale bars 50 μm. B) Average cell nuclei area of groups. Cell nuclei for each image were segmented using Cellpose and exported outlines were measured in ImageJ’s ROI manager to find the average cell nuclei area for the region of interest. Four regions of interest from five independent replicates were analyzed. C-E) αSMA, F-actin, and FN fluorescent signal coverage, respectively. Fluorescent signal area was determined by counting color-containing pixels in binarized maximum projection images of each channel. Each data point represents a region of interest from five independent replicates. F) Total FN alignment, quantified by CurveAlign after using CTFire’s curvelet-transform based extraction of fibers. Each data point represents a region of interest from five independent replicates. G) TGFβ1 concentration for each media type. Each data point is the average of three technical replicates, with three independent experiments tested for each media type. For all plots, error bars represent interquartile range and middle line represents median. Asterisks denote statistical significance after hypothesis testing: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 .
Article Snippet: Additionally,
Techniques: Cell Culture, Incubation, Counting, Extraction, Concentration Assay
Journal: bioRxiv
Article Title: Tumor-associated mammary fibroblast matrices contain O-glycosylated oncofetal fibronectin
doi: 10.64898/2026.09.29.755525
Figure Lengend Snippet: A and E) Representative maximum projection images of HCC-1937 and MDA-MB-231 cells, respectively, reseeded onto INC and respective tumor-associated matrices; cell nuclei (blue), F-actin (cyan), oFN (red), and merged image of all channels are displayed. Scale bars 50 μm. B and F) Cell area of HCC-1937 and MDA-MB-231 cells, respectively. Combined nuclei and F-actin channel images were segmented using Cellpose and area of exported cell outlines were measured in ImageJ. Each data point represents a single cell. C and G) Circularity of HCC-1937 and MDA-MB-231 cells, respectively, measured from cell outlines. Each data point represents a single cell. D and H) Colocalization of F-actin and oFN signals for HCC-1937 and MDA-MB-231 samples, respectively. Displayed colocalization coefficient is the Mander’s M1 value, which is the fraction of F-actin signal overlapping with oFN signal. Each data point is one region of interest from three independent replicates. For all plots, error bars represent interquartile range and middle line represents median. Asterisks denote statistical significance after hypothesis testing: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Article Snippet: Additionally,
Techniques: Single Cell
Journal: Journal of Experimental & Clinical Cancer Research : CR
Article Title: NRGN inhibits CD8⁺ T cell effector function by downregulating MHC-I expression through the FMR1–IRF8 axis in hepatocellular carcinoma
doi: 10.1186/s13046-026-03783-7
Figure Lengend Snippet: Tumor-intrinsic NRGN suppresses MHC-I antigen presentation to evade CD8⁺ T cell immune surveillance in HCC. A Representative images of orthotopic liver tumors in C57BL/6 mice following NRGN manipulation, with or without CD8⁺ T cell exhaustion ( n = 5). B - F Quantification of mouse survival ( B ), tumor weight ( C ), tumor volume ( D ), liver weight ( E ), and liver weight/body weight ratio ( F ) in the orthotopic HCC model. G , H Western blot analysis of MHC-I expression in Huh7 ( G ) and Hep3B ( H ) cells after NRGN manipulation ( n = 3). I , J Flow cytometry analysis of cell surface MHC-I levels in Huh7 ( I ) and Hep3B ( J ) cells following NRGN intervention ( n = 3). K , L Western blot analysis of H-2Kb and β2m expression in Hep-53.4 cells following NRGN overexpression ( K ) or knockdown ( L ) ( n = 3). M , N Flow cytometry analysis of cell surface H-2Kb levels in Hep-53.4 cells following NRGN overexpression ( M ) or knockdown ( N ) ( n = 3). O Representative images of orthotopic liver tumors in C57BL/6 mice generated with Nrgn-knockdown Hep-53.4 cells ( n = 5). P - R Quantification of mouse survival ( P ), tumor weight ( Q ), and tumor volume ( R ) in the Nrgn-knockdown orthotopic HCC model. S TUNEL staining of tumor tissues to assess apoptosis levels ( n = 5). T - V Immunofluorescence analysis of differential expression of NRGN and β2m in tumor tissues ( n = 5). W Flow cytometry analysis of CD8⁺ T cell activation status in different experimental groups ( n = 5). X Flow cytometry analysis of tumor cell surface H-2Kb expression levels in different experimental groups ( n = 5). * P < 0.05; ** P < 0.01; *** P < 0.001; **** P < 0.0001; ns, not significant
Article Snippet: HEK-293T cells and human HCC cell lines Huh7, Hep3B, Hep1-6 and murine cytotoxic T-cell line CTLL-2 were obtained from the American Type Culture Collection (ATCC), and the
Techniques: Immunopeptidomics, Western Blot, Analysis, Expressing, Flow Cytometry, Over Expression, Knockdown, Generated, TUNEL Assay, Staining, Immunofluorescence, Quantitative Proteomics, Activation Assay
Journal: Translational Oncology
Article Title: Integrating spatial and single-cell transcriptomics via machine learning to characterize efferocytosis in hepatocellular carcinoma prognosis and immunotherapy
doi: 10.1016/j.tranon.2026.102801
Figure Lengend Snippet: Identification and multi-level validation of TPI1 as a pivotal prognostic driver. (A) Lollipop chart showing the selection frequency of feature genes across 101 machine learning models, identifying TPI1 as a high-frequency core gene. (B) Univariate Cox regression analysis of candidate genes; TPI1 exhibited the most substantial Hazard Ratio (HR), characterizing it as a preeminent risk factor. (C) Expression profiling of TPI1 across malignant versus paracancerous tissues within the TCGA-LIHC discovery cohort (upper) and GSE14520 validation cohort (lower). (D) Kaplan-Meier overall survival curves comparing patients with high and low TPI1 expression in the TCGA-LIHC (top) and GSE14520 (bottom) cohorts. (E) Relative mRNA expression levels of TPI1 in the immortalized human hepatocyte line (MIHA) and HCC cell lines (Huh7, SMMC-7721) determined by RT-qPCR. (F) Representative Western blot images (left) and densitometric quantification (right) of TPI1 protein levels in MIHA, Huh7, and SMMC-7721 cells. GAPDH served as the internal loading control. Data are expressed as mean ± SD. ** P < 0.01, *** P < 0.001.
Article Snippet: The
Techniques: Biomarker Discovery, Selection, Expressing, Quantitative RT-PCR, Western Blot, Control