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UBTD1 Drives Ovarian Cancer Progression via Mutation-Associated Alterations, Stromal Microenvironment Remodeling, and TNF/AP-1 Signaling.
BACKGROUND: The ubiquitin domain-containing protein 1 (UBTD1) is involved in protein homeostasis and cell cycle regulation, and emerging evidence suggests its role in tumor biology. However, its function in ovarian cancer (OC) remains unclear. OC is highly lethal due to late diagnosis, metastasis, and platinum resistance. This study is aimed at investigating the role of UBTD1 in OC by integrating single-cell transcriptomics, mutation and HRD-related analyses, tumor microenvironment evaluation, and experimental validation. METHODS: We examined UBTD1 expression, prognosis, somatic mutation features, and immune microenvironment characteristics utilizing public databases, such as the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Single-cell RNA-seq data were analyzed using Seurat, hdWGCNA, and CopyKAT to characterize UBTD1-associated malignant-cell states and inferred CNV burden. Based on the median UBTD1 expression, TCGA-OV samples were divided into high and low expression groups to compare mutation spectra, DNA repair pathway activity, stromal scores, and immune cell infiltration. Functional assays were performed in A2780 and SK-OV-3 cell lines following lentiviral shRNAs-mediated UBTD1 knockdown. RNA sequencing and rescue experiments were used to explore downstream pathways. RESULTS: Integrated single-cell and TCGA-OV analyses revealed that UBTD1-low tumors were enriched for genomic instability-related features, including increased inferred CNV burden and higher tumor mutation burden. By comparison, UBTD1-high tumors showed increased stromal scores and modest enrichment of selected immune-cell populations, including macrophages and neutrophils. Experimentally, UBTD1 was upregulated in OC and associated with poor prognosis. UBTD1 knockdown inhibited malignant phenotypes, enhanced cisplatin sensitivity, promoted apoptosis, and suppressed TNF/AP-1/FOS-related signaling. FOS overexpression partially reversed the effects of UBTD1 silencing. CONCLUSIONS: UBTD1 expression defines distinct mutation and microenvironmental states in OC and functionally promotes malignant phenotypes, potentially through TNF/AP-1/FOS-related signaling.
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Single-cell atlas of peripheral blood mononuclear cells from pregnant women.
BACKGROUND: During pregnancy, mother-child interactions trigger a variety of subtle changes in the maternal body, which may be reflected in the status of peripheral blood mononuclear cells (PBMCs). Although these cells are easy to access and monitor, a PBMC atlas for pregnant women has not yet been constructed. METHODS: We applied single-cell RNA sequencing (scRNA-seq) to profile 198,356 PBMCs derived from 136 pregnant women (gestation weeks 6 to 40) and a control cohort. We also used scRNA-seq data to establish a transcriptomic clock and thereby predicted the gestational age of normal pregnancy. RESULTS: We identified reconfiguration of the peripheral immune cell phenotype during pregnancy, including interferon-stimulated gene upregulation, activation of RNA splicing-related pathways and immune activity of cell subpopulations. We also developed a cell-type-specific model to predict gestational age of normal pregnancy. CONCLUSIONS: We constructed a single-cell atlas of PBMCs in pregnant women spanning the entire gestation period, which should help improve our understanding of PBMC composition turnover in pregnant women.
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Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication.
BACKGROUND: Immunotherapy has emerged as a potent clinical approach for cancer treatment, but only subsets of cancer patients can benefit from it. Targeting lactate metabolism (LM) in tumor cells as a method to potentiate anti-tumor immune responses represents a promising therapeutic strategy. METHODS: Public single-cell RNA-Seq (scRNA-seq) cohorts collected from patients who received immunotherapy were systematically gathered and scrutinized to delineate the association between LM and the immunotherapy response. A novel LM-related signature (LM.SIG) was formulated through an extensive examination of 40 pan-cancer scRNA-seq cohorts. Then, multiple machine learning (ML) algorithms were employed to validate the capacity of LM.SIG for immunotherapy response prediction and survival prognostication based on 8 immunotherapy transcriptomic cohorts and 30 The Cancer Genome Atlas (TCGA) pan-cancer datasets. Moreover, potential targets for immunotherapy were identified based on 17 CRISPR datasets and validated via in vivo and in vitro experiments. RESULTS: The assessment of LM was confirmed to possess a substantial relationship with immunotherapy resistance in 2 immunotherapy scRNA-seq cohorts. Based on large-scale pan-cancer data, there exists a notably adverse correlation between LM.SIG and anti-tumor immunity as well as imbalance infiltration of immune cells, whereas a positive association was observed between LM.SIG and pro-tumorigenic signaling. Utilizing this signature, the ML model predicted immunotherapy response and prognosis with an AUC of 0.73/0.80 in validation sets and 0.70/0.87 in testing sets respectively. Notably, LM.SIG exhibited superior predictive performance across various cancers compared to published signatures. Subsequently, CRISPR screening identified LDHA as a pan-cancer biomarker for estimating immunotherapy response and survival probability which was further validated using immunohistochemistry (IHC) and spatial transcriptomics (ST) datasets. Furthermore, experiments demonstrated that LDHA deficiency in pancreatic cancer elevated the CD8+ T cell antitumor immunity and improved macrophage antitumoral polarization, which in turn enhanced the efficacy of immunotherapy. CONCLUSIONS: We unveiled the tight correlation between LM and resistance to immunotherapy and further established the pan-cancer LM.SIG, holds the potential to emerge as a competitive instrument for the selection of patients suitable for immunotherapy.
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Genetic and cellular architecture of breast cancer risk across ancestries.
BACKGROUND: Breast cancer genome-wide association studies (GWAS) have identified more than 200 susceptibility loci, but most studies are dominated by European and East Asian populations. METHODS: We analyzed breast cancer GWAS summary statistics from African (AFR), East Asian (EAS), European (EUR), and Hispanic/Latina (H/L) samples (159,297 cases and 212,102 controls). We estimated logit-scale SNP-based heritability, polygenicity, and cross-ancestry genetic correlation, partitioned heritability across functional annotations, and integrated GWAS results with the Tabula Sapiens single-cell atlas using scDRS+. RESULTS: The logit-scale heritability of breast cancer ranged from h2=0.47 (SE = 0.07) in EAS to AFR h2=0.61 (SE = 0.10), with no significant differences across ancestries (p = 0.63). The model-implied number of non-null susceptibility SNPs in the sparse normal-mixture effect-size model also varied from 4,446 (SE = 3,100) in EAS to 8,308 (SE = 2,751) in AFR, but differences were not significant across ancestries (p = 0.55). Cross-sample genetic correlations varied, with the strongest correlation between EUR and EAS (ρ=0.79, SE = 0.08) and weakest between AFR and H/L (ρ=0.26, SE = 0.24). Regulatory annotations were enriched for breast cancer heritability across samples. Integration with single-cell expression profiles implicated ancestry-shared associations with innate immune, secretory epithelial, and stromal cell types. CONCLUSION: These results indicate substantial cross-ancestry sharing of breast cancer polygenic architecture, highlight a consistent contribution of regulatory variation, and identify convergent cellular contexts that motivate functional follow-up and inform expectations for the transferability and attainable performance of common-variant risk prediction across populations.
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Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia.
Sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli to the central nervous system. Single-cell RNA sequencing has provided insights into the diversity of sensory ganglia cell types in rodents, nonhuman primates, and humans, but it remains difficult to compare cell types across studies and species. We thus constructed harmonized atlases of the DRG and TG that describe and facilitate comparison of 18 neuronal and 11 non-neuronal cell types across six species and 31 datasets. We then performed single-cell/nucleus RNA sequencing of DRG from both human and the highly regenerative axolotl and found that the harmonized atlas also improves cell type annotation, particularly of sparse neuronal subtypes. We observed that the transcriptomes of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The resources presented here can guide future studies in comparative transcriptomics, simplify cell-type nomenclature differences across studies, and help prioritize targets for future analgesic development.
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Decoding plant cell types across species: A blueprint for gene discovery.
Uncovering plant cell types and regulatory genes across species has long been a challenge. Writing in Cell, Xue et al. present single-cell atlases for six vascular plants and identify conserved "cell-type foundational genes." These enable cross-species annotation, speeding up discoveries in plant and evolutionary biology and ultimately supporting crop improvement.
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ATLAS-seq: a microfluidic single-cell TCR screen for antigen-reactive TCRs.
Discovering antigen-reactive T cell receptors (TCRs) is central to developing effective engineered T cell immunotherapies. However, the conventional technologies for isolating antigen-reactive TCRs (i.e., major histocompatibility complex (MHC) multimer staining) focus on high-affinity interactions between the TCR and MHC-antigen complex, and may fail to identify TCRs with high efficacy for activating T cells. Here, we develop a microfluidic single-cell screening method for antigen-reactive T cells named ATLAS-seq (Aptamer-based T Lymphocyte Activity Screening and SEQuencing). This technology isolates and characterizes activated T cells via an aptamer-based fluorescent molecular sensor, which monitors the cytotoxic cytokine IFNγ secretion from single T cells upon antigen stimulation, followed by single-cell RNA and single-cell TCR sequencing. We use ATLAS-seq to screen TCRs reactive to cytomegalovirus (CMV) or prostate specific antigen (PSA) from peripheral blood mononuclear cells (PBMCs). ATLAS-seq identifies distinct TCR clonotype populations with higher T cell activation levels compared to TCRs recovered by MHC multimer staining. Select TCR clonotypes from ATLAS-seq are more efficient in target cell killing than those from MHC multimer staining. Collectively, ATLAS-seq provides an efficient and broadly applicable technology to screen antigen-reactive TCRs for engineered T cell immunotherapy.
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Single cells tell it all.
A new single-cell atlas of gene expression provides insights into the patterning of the neural plate of mice.
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A Multimodal Omics Framework to Empower Target Discovery for Cardiovascular Regeneration.
Ischaemic heart disease is a global healthcare challenge with high morbidity and mortality. Early revascularisation in acute myocardial infarction has improved survival; however, limited regenerative capacity and microvascular dysfunction often lead to impaired function and the development of heart failure. New mechanistic insights are required to identify robust targets for the development of novel strategies to promote regeneration. Single-cell RNA sequencing (scRNA-seq) has enabled profiling and analysis of the transcriptomes of individual cells at high resolution. Applications of scRNA-seq have generated single-cell atlases for multiple species, revealed distinct cellular compositions for different regions of the heart, and defined multiple mechanisms involved in myocardial injury-induced regeneration. In this review, we summarise findings from studies of healthy and injured hearts in multiple species and spanning different developmental stages. Based on this transformative technology, we propose a multi-species, multi-omics, meta-analysis framework to drive the discovery of new targets to promote cardiovascular regeneration.
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An atlas for hemocytes in an insect.
Single-cell RNA sequencing has revealed distinct subpopulations of hemocytes in fruit fly larvae.