Cell lines are valuable resources as model for human biology and translational medicine. It is thus important to explore the concordance between the expression in various cell lines vis-à-vis human native and disease tissues. In this study, we investigate the expression of all human protein-coding genes in more than 1,000 human cell lines representing 27 cancer types by a genome-wide transcriptomics analysis. The cell line gene expression is compared with the corresponding profiles in various tissues, organs, single-cell types and cancers. Here, we present the expression for each cell line and give guidance for the most appropriate cell line for a given experimental study. In addition, we explore the cancer-related pathway and cytokine activity of the cell lines to aid human biology studies and drug development projects. All data are presented in an open access cell line section of the Human Protein Atlas to facilitate the exploration of all human protein-coding genes across these cell lines.

Significance: Cardiovascular diseases remain the leading cause of death worldwide, with atherosclerosis being the most common source of clinical events. Metabolic changes with aging associate with concurrent increased risk of both type 2 diabetes and cardiovascular disease, with the former further raising the risk of the latter. The activity of a selective type of autophagy, chaperone-mediated autophagy (CMA), decreases with age or upon dietary excesses. Here we study whether reduced CMA activity increases risk of atherosclerosis in mouse models. We have identified that CMA is up-regulated early in response to proatherogenic challenges and demonstrate that reduced systemic CMA aggravates vascular pathology in these conditions. We also provide proof-of-concept support that CMA up-regulation is an effective intervention to reduce atherosclerosis severity and progression.

Background: While single‐omics analyses on human atherosclerotic plaque have been very useful to map stage‐ or disease‐related differences in expression, they only partly capture the array of changes in this tissue and suffer from scale‐intrinsic limitations. In order to better identify processes associated with intraplaque hemorrhage and plaque instability, we therefore combined multiple omics into an integrated model.Methods: In this study, we compared protein and gene makeup of low‐ versus high‐risk atherosclerotic lesion segments from carotid endarterectomy patients, as judged from the absence or presence of intraplaque hemorrhage, respectively. Transcriptomic, proteomic, and peptidomic data of this plaque cohort were aggregated and analyzed by DIABLO, an integrative multivariate classification and feature selection method.Results: We identified a protein‐gene associated multiomics model able to segregate stable, nonhemorrhaged from vulnerable, hemorrhaged lesions at high predictive performance (AUC >0.95). The dominant component of this model correlated with αSMA⁻PDGFRα⁺fibroblast‐like cell content (p = 2.4E‐05) and Arg1⁺macrophage content (p = 2.2E‐04) and was driven by serum response factor (SRF), possibly in a megakaryoblastic leukemia‐1/2 (MKL1/2) dependent manner. Gene set overrepresentation analysis on the selected key features of this model pointed to a clear cardiovascular disease signature, with overrepresentation of extracellular matrix synthesis and organization, focal adhesion, and cholesterol metabolism terms, suggestive of the model's relevance for the plaque vulnerability. Finally, we were able to corroborate the predictive power of the selected features in several independent mRNA and proteomic plaque cohorts.Conclusions: In conclusion, our integrative omics study has identified an intraplaque hemorrhage‐associated cardiovascular signature that provides excellent stratification of low‐ from high‐risk carotid artery plaques in several independent cohorts. Further study revealed suppression of an SRF‐regulated disease network, controlling lesion stability, in vulnerable plaque, which can serve as a scaffold for the design of targeted intervention in plaque destabilization.

Evidence is emerging for the role of intestinal tryptophan metabolism in the development of inflammatory bowel disease (IBD). In order to identify the role of altered intestinal tryptophan metabolism in IBD pathogenesis, a meta-analysis of the transcriptome was performed to identify differentially expressed genes involved in the tryptophan metabolism pathways in intestinal biopsies of IBD as compared to non-IBD controls. Moreover, a systematic review of the metabolome was performed to identify the concurrent changes in tryptophan metabolites. Integration of the transcriptome and metabolome identified various alterations in intestinal tryptophan metabolism during active disease in IBD patients, including decreased intestinal tryptophan absorption, enhanced kynurenine pathway, increased interstitial serotonin availability, changed indole pathway, and activated aryl hydrocarbon receptor signaling. Therefore, a network of intestinal tryptophan metabolism pathways in IBD could be established, helping to assess the potential of genes and metabolites involved in these pathways as diagnostic markers and targets for IBD management.

Specific fibroblast markers and in-depth heterogeneity analysis are currently lacking, hindering functional studies in cardiovascular diseases (CVD). Here, we established cell-type markers and heterogeneity in murine and human arteries and studied the adventitial fibroblast response to CVD and its risk factors hypercholesterolemia and aging. Murine aorta scRNA-seq analysis of adventitial mesenchymal cells identified fibroblast-specific markers. Immunohistochemistry and flow cytometry validated platelet-derived growth factor receptor alpha (PDGFRA) and dipeptidase 1 (DPEP1) across human and murine aorta, carotid, and femoral arteries, while traditional markers such as cluster of differentiation (CD)90 and vimentin also marked transgelin + vascular smooth muscle cells. Next, pseudotime analysis showed multiple fibroblast clusters differentiating along trajectories. Three trajectories, marked by CD55 (Cd55+), Cxcl chemokine 14 (Cxcl14+) and lysyl oxidase (Lox+), were reproduced in an independent RNAseq dataset. Gene ontology analysis showed divergent functional profiles of the three trajectories, related to vascular development, antigen presentation and/or collagen fibril organization, respectively. Trajectory-specific genes included significantly more genes with known genome-wide associations (GWAS) to CVD than expected by chance, implying a role in CVD. Indeed, differential regulation of fibroblast clusters by CVD risk factors was shown in adventitia of aged C57BL/6J mice, and mildly hypercholesterolemic LDLR-KO mice on chow by flow cytometry. The expansion of collagen-related CXCL14 + and LOX + fibroblasts in aged and hypercholesterolemic aortic adventitia respectively, coincided with increased adventitial collagen. Immunohistochemistry, bulk, and single-cell transcriptomics of human carotid and aorta specimens emphasized translational value as CD55+, CXCL14 + and LOX + fibroblasts were observed in healthy and atherosclerotic specimens. Also, trajectory-specific gene sets differentially correlated to human atherosclerotic plaque traits. We provide two adventitial fibroblast-specific markers, PDGFRA and DPEP1, and demonstrate fibroblast heterogeneity in health and cardiovascular disease in humans and mice. Biological relevance is evident from regulation of fibroblast clusters by age and hypercholesterolemia in vivo, associations with human atherosclerotic plaque traits, and enrichment of genes with a GWAS for CVD.

Introduction: Macrophages and T cells play crucial roles in liver physiology, but their functional diversity in hepatocellular carcinoma (HCC) remains largely unknown.Methods: Two bulk RNA-sequencing (RNA-seq) cohorts for HCC were analyzed using gene co-expression network analysis. Key gene modules and networks were mapped to single-cell RNA-sequencing (scRNA-seq) data of HCC. Cell type fraction of bulk RNA-seq data was estimated by deconvolution approach using single-cell RNA-sequencing data as a reference. Survival analysis was carried out to estimate the prognosis of different immune cell types in bulk RNA-seq cohorts. Cell-cell interaction analysis was performed to identify potential links between immune cell types in HCC.Results: In this study, we analyzed RNA-seq data from two large-scale HCC cohorts, revealing a major and consensus gene co-expression cluster with significant implications for immunosuppression. Notably, these genes exhibited higher enrichment in liver macrophages than T cells, as confirmed by scRNA-seq data from HCC patients. Integrative analysis of bulk and single-cell RNA-seq data pinpointed SPP1⁺ macrophages as an unfavorable cell type, while VCAN⁺ macrophages, C1QA⁺ macrophages, and CD8⁺ T cells were associated with a more favorable prognosis for HCC patients. Subsequent scRNA-seq investigations and in vitro experiments elucidated that SPP1, predominantly secreted by SPP1⁺ macrophages, inhibits CD8⁺ T cell proliferation. Finally, targeting SPP1 in tumor-associated macrophages through inhibition led to a shift towards a favorable phenotype.Discussion: This study underpins the potential of SPP1 as a translational target in immunotherapy for HCC.