BACKGROUND:Understanding the proteomic-level heterogeneity of the tumor microenvironment (TME) in colorectal cancer (CRC) is crucial due to its well-known heterogeneity. While heterogenous CRC has been extensively characterized at the molecular subtype level, research into the functional heterogeneity of fibroblasts, particularly their relationship with extracellular matrix (ECM) alterations, remains limited. Addressing this gap is essential for a comprehensive understanding of CRC progression and the development of targeted therapies. METHODS:24 tissue samples from 21 CRC patients, along with adjacent normal tissues (NAT), were collected and decellularized using a detergent-based method to enrich the ECM component. Proteomic analysis of ECM-enriched samples was performed using tandem mass tag (TMT) spectrometry, followed by statistical analysis including differential expression protein (DEP) analysis. Single-cell RNA sequencing (scRNA-Seq) data from public datasets were integrated and analyzed to delineate cell states within the TME. Bulk tissue RNA-Seq and bioinformatics analysis, including consensus molecular subtype (CMS) classification and single-cell level deconvolution of TCGA bulk RNA-seq data, were conducted to further explore gene expression patterns and TME composition. RESULTS:Differential cellular origin of the NAT and tumorous ECM proteins were identified, revealing 110 ECM proteins enriched in NAT and 28 ECM proteins in tumor tissues. Desmoplastic and WNT5A+ inflammatory fibroblasts were indicated as the sources of tumor-enriched ECM proteins, while ADAMDEC1+ expressing fibroblasts and PI16+ expressing fibroblast were identified as the sources of NAT-enriched ECM proteins. Deconvolution of bulk RNA-seq of CRC tissues discriminated CMS-specific fibroblast state, reflecting the biological traits of each CMS subtype. Specially, seven ECM genes specific to mesenchymal subtype (CMS4), including PI16+ fibroblast-related 4 genes (SFRP2, PRELP, OGN, SRPX) and desmoplastic fibroblast-related 3 genes (THBS2, CTHRC1, BGN), showed a significant association with poorer survival in patient with CRC. CONCLUSION:We conducted an extracellular matrix (ECM)-focused profiling of the TME by integrating quantitative proteomics with single-cell RNA sequencing (scRNA-seq) data from CRC patients. We identified the ECM proteins of NAT and tumor tissue, and established a cell-matrisome database. We defined mesenchymal subtype-specific molecules associated with specific fibroblast subtypes showing a significant association with poorer survival in patients with CRC. Our ECM-focused profiling of tumor stroma provides new insights as indicators for biological processes and clinical endpoints.

Alternative splicing contributes to complex traits, but whether this differs in trait-relevant cell types across diverse genetic ancestries is unclear. Here we describe cell-type-specific, sex-biased and ancestry-biased alternative splicing in similar to 1 M peripheral blood mononuclear cells from 474 healthy donors from the Asian Immune Diversity Atlas. We identify widespread sex-biased and ancestry-biased differential splicing, most of which is cell-type-specific. We identify 11,577 independent cis-splicing quantitative trait loci (sQTLs), 607 trans-sGenes and 107 dynamic sQTLs. Colocalization between cis-eQTLs and trans-sQTLs revealed a cell-type-specific regulatory relationship between HNRNPLL and PTPRC. We observed an enrichment of cis-sQTL effects in autoimmune and inflammatory disease heritability. Specifically, we functionally validated an Asian-specific sQTL disrupting the 5 ' splice site of TCHP exon 4 that putatively modulates the risk of Graves' disease in East Asian populations. Our work highlights the impact of ancestral diversity on splicing and provides a roadmap to dissect its role in complex diseases at single-cell resolution.

Lack of diversity and proportionate representation in genomics datasets and databases contributes to inequity in healthcare outcomes globally[1][1],[2][2]. The relationships of human diversity with biological and biomedical phenotypes are pervasive[3][3], yet remain understudied, particularly in a single-cell genomics context. Here we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA-sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 healthy donors and 6 controls, spanning 7 population groups across 5 countries. AIDA is one of the largest healthy blood datasets in terms of number of cells, and also the most diverse in terms of number of population groups. Though population groups are frequently compared at the continental level, we identified a pervasive impact of sub-continental diversity on cellular and molecular properties of immune cells. These included cell populations and genes implicated in disease risk and pathogenesis as well as those relevant for diagnostics. We detected single-cell signatures of human diversity not apparent at the level of cell types, as well as modulation of the effects of age and sex by self-reported ethnicity. We discovered functional genetic variants influencing cell type-specific gene expression, including context-dependent effects, which were under-represented in analyses of non-Asian population groups, and which helped contextualise disease-associated variants. We validated our findings using multiple independent datasets and cohorts. AIDA provides fundamental insights into the relationships of human diversity with immune cell phenotypes, enables analyses of multi-ancestry disease datasets, and facilitates the development of precision medicine efforts in Asia and beyond. ### Competing Interest Statement The authors have declared no competing interest. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3

Identification of optimal target antigens that distinguish cancer cells from normal surrounding tissue cells remains a key challenge in chimeric antigen receptor (CAR) cell therapy for tumors with intratumoral heterogeneity. In this study, we dissected tissue complexity to the level of individual cells through the construction of a single-cell expression atlas that integrates ~1.4 million tumor, tumor-infiltrating normal and reference normal cells from 412 tumors and 12 normal organs. We used a two-step screening method using random forest and convolutional neural networks to select gene pairs that contribute most to discrimination between individual malignant and normal cells. Tumor coverage and specificity are evaluated for the AND, OR and NOT logic gates based on the combinatorial expression pattern of the pairing genes across individual single cells. Single-cell transcriptome-coupled epitope profiling validates the AND, OR and NOT switch targets identified in ovarian cancer and colorectal cancer.

Chronic alcohol consumption often induces hepatic steatosis but rarely causes severe inflammation in Kupffer cells (KCs) despite the increased hepatic influx of lipopolysaccharide (LPS), suggesting the presence of a veiled tolerance mechanism. In addition to LPS, the liver is affected by several gut-derived neurotransmitters through the portal blood, but the effects of catecholamines on KCs have not been clearly explored in alcohol-associated liver disease (ALD). Hence, we investigated the regulatory roles of catecholamine on inflammatory KCs under chronic alcohol exposure. We discovered that catecholamine levels were significantly elevated in the cecum, portal blood, and liver tissues of chronic ethanol-fed mice. Increased catecholamines induced mitochondrial translocation of cytochrome P450 2E1 in perivenous hepatocytes expressing the β2-adrenergic receptor (ADRB2), leading to the enhanced production of growth differentiation factor 15 (GDF15). Subsequently, GDF15 profoundly increased ADRB2 expression in adjacent inflammatory KCs to facilitate catecholamine/ADRB2-mediated apoptosis. Single-cell RNA sequencing of KCs confirmed the elevated expression of Adrb2 and apoptotic genes after chronic ethanol intake. Genetic ablation of Adrb2 or hepatic Gdf15 robustly decreased the number of apoptotic KCs near perivenous areas, exacerbating alcohol-associated inflammation. Consistently, we found that blood and stool catecholamine levels and perivenous GDF15 expression were increased in patients with early-stage ALD along with an increase in apoptotic KCs. Our findings reveal a novel protective mechanism against ALD, in which the catecholamine/GDF15 axis plays a critical role in KC apoptosis, and identify a unique neuro-metabo-immune axis between the gut and liver that elicits hepatoprotection against alcohol-mediated pathogenic challenges.

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a dataset of ~360,000 cells. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of finely phenotyped immune cell types, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. Our multitissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis, and antigen receptor sequencing.