Journal: Clinical and Molecular Hepatology

Article Title: COLEC12 high tumor-associated macrophages orchestrate lenvatinib resistance and cancer stemness in hepatocellular carcinoma via paracrine NRG1-HER2/HER3 signaling

doi: 10.3350/cmh.2025.1059

Figure Lengend Snippet: NRG1 mediates COLEC12 high TAM-induced stemness and therapeutic resistance. (A) Overlap of genes upregulated in COLEC12 OE macrophages with the THPA secretome. Heatmap of the top 20 induced genes. qRT-PCR, immunoblot, and ELISA confirm increased NRG1 expression and secretion in COLEC12 OE THP-1 macrophages (n=3). (B) COLEC12 OE CM increases lenvatinib resistance in Huh7 cells, whereas NRG1 knockdown reverses this effect, as shown by IC50, CCK-8 proliferation, colony formation, and apoptosis assays (n=3). (C) Subcutaneous Huh7 xenografts (n=6) and orthotopic liver models were treated with intratumoral or intraperitoneal injections of Vector-CM, COLEC12 OE -CM, or COLEC12 OE +shNRG1#1-CM with/without lenvatinib, showing tumor images, volumes, weights, and liver/body weight ratios (n=6). (D) qRT-PCR of SOX2/OCT4/CD44/CD133 in Huh7 under indicated CM (n=3). Tumorsphere formation under indicated CM (n=3). (E) Limiting dilution assays in vitro (M, n=3) and in vivo (N, n=6 per group), showing stem cell or tumor-initiating frequencies. Data are presented mean±standard error of the mean. Two group comparisons used Student’s t-test; multiple groups used one-way ANOVA; tumor initiation used Kruskal–Wallis. NRG1, Neuregulin 1; COLEC12, Collectin Subfamily Member 12; THPA, The Human Protein Atlas ; CM, conditioned medium; COLEC12 OE , COLEC12-overexpressing. * P <0.05, ** P <0.01, *** P <0.001. Source data available.

Article Snippet: We integrated COLEC12 OE macrophage transcriptomic data with the secretome dataset from The Human Protein Atlas (THPA) to identify potential mediators of COLEC12 high macrophage–induced stemness in HCC.

Techniques: Quantitative RT-PCR, Western Blot, Enzyme-linked Immunosorbent Assay, Expressing, Knockdown, CCK-8 Assay, Plasmid Preparation, In Vitro, In Vivo

Journal: Journal of Proteome Research

Article Title: Automated Mag-Net Enrichment Unlocks Deep and Cost-Effective LC–MS Plasma Proteomics

doi: 10.1021/acs.jproteome.5c00420

Figure Lengend Snippet: Enriched and neat plasma proteins cluster into four main groups based on protein intensities. Cluster 1 contains proteins found in neat plasma and shared across all methods, while Cluster 2 consists of proteins identified in all five enrichment methods. Cluster 3 includes proteins with medium intensity, mostly detected in all methods except ENRICHiST and neat. Cluster 4 consists primarily of low-intensity proteins. Each cluster is enriched with distinct Gene Ontology terms, cellular localizations, and tissue associations. (A) Hierarchical clustering of proteins detected in at least 10% of all samples, based on log 2 intensity. (B) Enrichment analysis of proteins in each cluster with the PANTHER GO-Slim databases , for cellular components and biological processes. Results were first filtered to retain terms with over 2-fold enrichment and a minimum of ten proteins per term. The top five terms with the lowest FDR values were selected for each cluster. (C) Subcellular location of proteins in each cluster based on The Human Protein Atlas (HPA) annotations. Only the top 20 locations are shown. The inset highlights the top five secretome annotations among all identified proteins. (D) Number of proteins annotated as tissue-enriched in the HPA transcriptomics data set. The 20 tissues with the highest total count of tissue-enriched proteins are shown.

Article Snippet: The subcellular location of proteins, gene-level RNA expression data, single cell-type expression data, and the human secretome annotations were downloaded from the Human Protein Atlas (HPA, version 24.0, proteinatlas.org ).

Techniques: Clinical Proteomics, Transcriptomics