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A human breast atlas integrating single-cell proteomics and transcriptomics.
The breast is a dynamic organ whose response to physiological and pathophysiological conditions alters its disease susceptibility, yet the specific effects of these clinical variables on cell state remain poorly annotated. We present a unified, high-resolution breast atlas by integrating single-cell RNA-seq, mass cytometry, and cyclic immunofluorescence, encompassing a myriad of states. We define cell subtypes within the alveolar, hormone-sensing, and basal epithelial lineages, delineating associations of several subtypes with cancer risk factors, including age, parity, and BRCA2 germline mutation. Of particular interest is a subset of alveolar cells termed basal-luminal (BL) cells, which exhibit poor transcriptional lineage fidelity, accumulate with age, and carry a gene signature associated with basal-like breast cancer. We further utilize a medium-depletion approach to identify molecular factors regulating cell-subtype proportion in organoids. Together, these data are a rich resource to elucidate diverse mammary cell states.
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Single-cell transcriptomic analysis reveals crucial oncogenic signatures and its associative cell types involved in gastric cancer.
The intricate association of oncogenic markers negatively impacts accurate gastric cancer diagnosis and leads to the proliferation of mortality rate. Molecular heterogeneity is inevitable in determining gastric cancer's progression state with multiple cell types involved. Identification of pathogenic gene signatures is imperative to understand the disease's etiology. This study demonstrates a systematic approach to identifying oncogenic gastric cancer genes linked with different cell types. The raw counts of adjacent normal and gastric cancer samples are subjected to a quality control step. The dimensionality reduction and multidimensional clustering are performed using Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) techniques. The adjacent normal and gastric cancer sample cell clusters are annotated with the Human Primary Cell Atlas database using the "SingleR." Cellular state transition between the distinct groups is characterized using trajectory analysis. The ligand-receptor interaction between Vascular Endothelial Growth Factor (VEGF) and cell clusters unveils crucial molecular pathways in gastric cancer progression. Chondrocytes, Smooth muscle cells, and fibroblast cell clusters contain genes contributing to poor survival rates based on hazard ratio during survival analysis. The GC-related oncogenic signatures are isolated by comparing the gene set with the DisGeNET database. Twelve gastric cancer biomarkers (SPARC, KLF5, HLA-DRB1, IGFBP3, TIMP3, LGALS1, IGFBP6, COL18A1, F3, COL4A1, PDGFRB, COL5A2) are linked with gastric cancer and further validated through gene set enrichment analysis. Drug-gene interaction found PDGFRB, interacting with various anti-cancer drugs, as a potential inhibitor for gastric cancer. Further investigations on these molecular signatures will assist the development of precision therapeutics, promising longevity among gastric cancer patients.
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Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer.
BACKGROUND: Immuno-oncology (IO) therapies targeting the PD-1/PD-L1 axis, such as immune checkpoint inhibitor (ICI) antibodies, have emerged as promising treatments for early-stage breast cancer (ESBC). Despite immunotherapy's clinical significance, the number of benefiting patients remains small, and the therapy can prompt severe immune-related events. Current pathologic and transcriptomic predictions of IO response are limited in terms of accuracy and rely on single-site biopsies, which cannot fully account for tumor heterogeneity. In addition, transcriptomic analyses are costly and time-consuming. We therefore constructed a computational biomarker coupling biophysical simulations and artificial intelligence-based tissue segmentation of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRIs), enabling IO response prediction across the entire tumor. METHODS: By analyzing both single-cell and whole-tissue RNA-seq data from non-IO-treated ESBC patients, we associated gene expression levels of the PD-1/PD-L1 axis with local tumor biology. PD-L1 expression was then linked to biophysical features derived from DCE-MRIs to generate spatially- and temporally-resolved atlases (virtual tumors) of tumor biology, as well as the TumorIO biomarker of IO response. We quantified TumorIO within patient virtual tumors (n = 63) using integrative modeling to train and develop a corresponding TumorIO Score. RESULTS: We validated the TumorIO biomarker and TumorIO Score in a small, independent cohort of IO-treated patients (n = 17) and correctly predicted pathologic complete response (pCR) in 15/17 individuals (88.2% accuracy), comprising 10/12 in triple negative breast cancer (TNBC) and 5/5 in HR+/HER2- tumors. We applied the TumorIO Score in a virtual clinical trial (n = 292) simulating ICI administration in an IO-naïve cohort that underwent standard chemotherapy. Using this approach, we predicted pCR rates of 67.1% for TNBC and 17.9% for HR+/HER2- tumors with addition of IO therapy; comparing favorably to empiric pCR rates derived from published trials utilizing ICI in both cancer subtypes. CONCLUSION: The TumorIO biomarker and TumorIO Score represent a next generation approach using integrative biophysical analysis to assess cancer responsiveness to immunotherapy. This computational biomarker performs as well as PD-L1 transcript levels in identifying a patient's likelihood of pCR following anti-PD-1 IO therapy. The TumorIO biomarker allows for rapid IO profiling of tumors and may confer high clinical decision impact to further enable personalized oncologic care.
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Distinct Sarcoma Microenvironments Predict Benefit from Addition of Pembrolizumab to Preoperative Radiotherapy and Surgery in SU2C-SARC032.
The addition of pembrolizumab to preoperative radiotherapy (RT) improved disease-free survival (DFS) for patients with stage III undifferentiated pleomorphic sarcoma (UPS) and dedifferentiated/pleomorphic liposarcoma (LPS) in the randomized SU2C-SARC032 trial. To precisely identify patients who benefit from pembrolizumab and RT, we performed comprehensive multi-omics profiling of pre- and post-treatment tumor and blood samples, including bulk RNA-seq, flow cytometry, and cytometry by time of flight. Additionally, we built a single-cell RNA-seq atlas spanning 65,786 cells from UPS and LPS to recover single-cell states in bulk tumor samples using digital cytometry. Two opposing tumor microenvironments (TMEs), immune-cold sarcoma ecotype 1 (SE1) and immune-hot sarcoma immune class E (SIC E), benefited from pembrolizumab. Pembrolizumab combined with RT depleted PD-1+ exhausted T cells in SIC E sarcomas and increased effector memory CD4+ T cells in SE1 sarcomas with an overall increase in CD8+ early activated T cells, CD4+ follicular helper T cells, and T cell receptor diversity. Matrix-remodeling stromal and epithelial-like sarcoma cell programs were associated with worse outcomes and diminished with pembrolizumab and RT. Our findings identify different mechanisms of response to pembrolizumab in localized, high-risk UPS/LPS and suggest that sarcoma TME signatures may identify patients most likely to benefit from adding pembrolizumab to preoperative RT.
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Recognition of immune-related tumor antigens and immune subtypes for mRNA vaccine development in lung adenocarcinoma.
BACKGROUND: There are currently no treatments targeting the immune microenvironment (TME) as an extension of immunotherapy. Our research aims to provide guidance for the development of immune-related mRNA vaccines and the identification of immune subtypes for vaccine treatment in lung adenocarcinoma (LUAD). METHODS: HTRNA-Seq and single cell RNA-seq data were obtained from The Cancer Genome Atlas (TCGA) and Gene-Expression Omnibus (GEO, GSE87340, GSE140343, GSE148071) databases. Immune checkpoints (ICP) were used as criteria to differentiate immune subtypes and immune resistance score (IRS) system is constructed by ssGSEA to judge the immune microenvironment status of patients. RESULTS: Two overexpressed tumor-specific antigens, including ZC3H12D and TXNDC5, were found to be associated with both disease-free survival (DFS) and overall survival (OS). In addition, the expression of two genes correlated with antigen-presenting cell (APC) infiltration and tumor purity. Subsequently, the immune subtype of the patient was defined by constructing an IRS scoring system. The lower the IRS, the stronger the immune response in the TME. This result was verified in external datasets and at the single-cell level. CONCLUSIONS: ZC3H12D and TXNDC5 are potential tumor-specific antigens for developing mRNA vaccines in LUAD. Importantly, patients with low IRS are more suitable for the use of immunotherapy and vaccines. Our research enhances understanding of TME features and guides more effective immunotherapy strategies.
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Construction of molecular signatures based on the co-expression network of NECSO-related gene TRPM4 and its prognostic value in hepatocellular carcinoma.
BACKGROUND: Hepatocellular carcinoma (HCC) demonstrates significant prognostic variability that is not entirely accounted for by traditional staging systems. Necrosis by sodium overload (NECSO) is an emerging programmed cell death pathway, but its clinical relevance in HCC remains undefined. Therefore, this study aimed to identify TRPM4-associated core genes, develop and validate a prognostic signature, and investigate its relationship with the tumor immune microenvironment, tumor mutational burden, and single-cell expression patterns in HCC. METHODS: We integrated transcriptomic, clinical, and mutational datasets from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (n=421) and Gene Expression Omnibus (GEO) cohorts (n=115) to identify genes co-expressed with TRPM4-a key NECSO mediator-and those differentially expressed in HCC. A prognostic signature was developed using least absolute shrinkage and selection operator (LASSO)-Cox regression and validated through survival analysis, time-dependent receiver operating characteristic (ROC) curves, and multivariate Cox regression analysis. The immune landscape was characterized using CIBERSORT, somatic mutation data were used to calculate tumor mutational burden (TMB) and assess its correlation with the risk score, and single-cell RNA sequencing (scRNA-seq) resolved cell-type-specific expression patterns. RESULTS: From 294 TRPM4-associated core genes, we identified an 11-gene signature (BRSK1, MMP1, GRIN2D, GP6, MYOM2, N4BP3, CCDC112, TSEN54, MAP3K9, SPP1, B3GNT4) that independently predicted overall survival (OS) (hazard ratio =5.419, P<0.001) with areas under the curve (AUCs) of 0.779, 0.693, and 0.701 at 1, 3, and 5 years. These values were superior or comparable to conventional clinicopathologic variables after direct comparison. High-risk patients exhibited an immunosuppressive microenvironment, characterized by enrichment of M0 macrophage, a higher M2/M1 ratio (P<0.001) and distinct immune checkpoint profiles. When integrated with TMB, the prognostic stratification was further refined: high-TMB/high-risk patients had poorest outcomes (median OS, 15.3 months), while low-TMB/low-risk patients had the most favorable survival (median OS, 68.7 months). Single-cell analysis revealed that MMP1 was induced in cancer-associated fibroblasts (CAFs) and SPP1 was downregulated in macrophages, single-cell risk scores confirmed TAFs and macrophages as the main contributors to the prognostic model. CONCLUSIONS: The TRPM4-centered 11-gene signature provides robust and independent prognostic stratification in HCC by integrating immune, mutational, and single-cell features. This signature serves as a potential tool for prognostic evaluation and may help inform immunotherapeutic strategies for HCC.
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A spatiotemporal single-cell atlas of porcine development reveals regulatory dynamics and cellular targets of domestication.
Systematic characterization of cellular gene expression in livestock tissues during development is essential for understanding the regulation of complex traits. Despite the comprehensive profiling of cell atlases in livestock, a dynamic view of tissue development remains lacking. Here, using both single-cell and single-nucleus RNA sequencing, we present a comprehensive single-cell transcriptomic landscape of 252,033 cells/nuclei, mapping 83 distinct cell types across five pig tissues from prenatal to postnatal developmental stages. Our findings highlight the coordinated remodeling of tissue architecture through stem/progenitor cell proliferation, lineage specification, and functional maturation during organogenesis. We identified key transcription factors and regulatory networks that drive lineage-specific and spatiotemporally dynamic transcriptional programs. Developmental trajectory analysis identified a conserved bifurcated transcriptional organization of immune cells, accompanied by dynamic changes in transcription factors associated with immune cell maturation. Integrative analysis utilizing multi-omic, single-cell, and pig population genomics data identified a muscle-specific enhancer of the MYOT gene as a target of artificial selection, underlying meat-quality divergence between Asian and European pig breeds. Moreover, cross-species comparison between pigs and humans revealed conserved cell types, underscoring the evolutionary link. In summary, the comprehensive pig developmental cell atlas serves as a key resource for understanding livestock development, provides insights for precision breeding, and highlights the value of the reference pig cell atlas as a powerful resource for biomedical research.
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Early role for a Na+,K+-ATPase (ATP1A3) in brain development.
Osmotic equilibrium and membrane potential in animal cells depend on concentration gradients of sodium (Na+) and potassium (K+) ions across the plasma membrane, a function catalyzed by the Na+,K+-ATPase α-subunit. Here, we describe ATP1A3 variants encoding dysfunctional α3-subunits in children affected by polymicrogyria, a developmental malformation of the cerebral cortex characterized by abnormal folding and laminar organization. To gain cell-biological insights into the spatiotemporal dynamics of prenatal ATP1A3 expression, we built an ATP1A3 transcriptional atlas of fetal cortical development using mRNA in situ hybridization and transcriptomic profiling of ∼125,000 individual cells with single-cell RNA sequencing (Drop-seq) from 11 areas of the midgestational human neocortex. We found that fetal expression of ATP1A3 is most abundant to a subset of excitatory neurons carrying transcriptional signatures of the developing subplate, yet also maintains expression in nonneuronal cell populations. Moving forward a year in human development, we profiled ∼52,000 nuclei from four areas of an infant neocortex and show that ATP1A3 expression persists throughout early postnatal development, most predominantly in inhibitory neurons, including parvalbumin interneurons in the frontal cortex. Finally, we discovered the heteromeric Na+,K+-ATPase pump complex may form nonredundant cell-type-specific α-β isoform combinations, including α3-β1 in excitatory neurons and α3-β2 in inhibitory neurons. Together, the developmental malformation phenotype of affected individuals and single-cell ATP1A3 expression patterns point to a key role for α3 in human cortex development, as well as a cell-type basis for pre- and postnatal ATP1A3-associated diseases.
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Decoding cytarabine-induced damage in the prepubertal testis: A multi-omics atlas of ecosystem and inheritance.
Pediatric leukemia therapies can compromise future fertility, particularly in prepubertal boys who cannot bank sperm. We used dose-response histology, endocrine and sperm analyses, bulk and single-cell RNA-seq, and metabolomics to map cytarabine (Ara-C) injury in prepubertal mouse testes. Ara-C caused seminiferous-tubule disruption, hormone suppression, sperm loss, spermatogonial depletion linked to ferroptosis and replication arrest, stress remodeling of Sertoli and Leydig cells, and altered intercellular signaling centered on Sertoli hubs. Unexposed F1 offspring retained inflammatory, nucleotide, and energy-metabolism changes, suggesting intergenerational imprinting after paternal exposure. These findings define cell-type-specific vulnerabilities in the developing testis and nominate redox balance, ferroptosis, Sertoli stress pathways, Leydig inflammatory signaling, and niche communication as targets for fertility-preserving strategies during pediatric chemotherapy.
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A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients.
BACKGROUND: The molecular underpinnings of organ dysfunction in severe COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we perform single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. RESULTS: We identify hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells, and a central role in a pro-fibrotic TGFβ signaling cell-cell communications network. Integrated analysis and comparisons with healthy controls reveal extensive changes in the cellular composition and expression states in COVID-19 liver, providing the underpinning of hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis characteristic of COVID-19 cholangiopathy. We also observe Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition is dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. CONCLUSIONS: Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.