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Development of a novel prognostic prediction model using mitochondrial-related genes and single-cell sequencing data for colorectal carcinoma.
BACKGROUND: Colorectal carcinoma (CRC) is a prevalent malignancy worldwide. Due to suboptimal screening practices, CRC is frequently diagnosed at an advanced stage. The role of mitochondrial abnormalities in the advancement of CRC is significant, but the prognostic effect of mitochondrial genes remains unclear. Recent research emphasizes mitochondrial dysfunction's key role in oncogenesis and cancer progression. Mitochondria are vital for cellular metabolism, energy production, and regulating processes like apoptosis, redox homeostasis, and signal transduction. Their dysfunction causes metabolic reprogramming, heightened oxidative stress, and cell death resistance. Though mitochondrial abnormalities link to CRC's aggressive phenotypes, the prognostic value of a comprehensive set of mitochondrial genes remains unclear, leaving a critical knowledge gap. The primary objective of this study was to systematically investigate the prognostic potential of mitochondrial genes in CRC and to develop a novel, reliable risk-scoring model. We aimed to identify key mitochondrial genes associated with patient survival, construct a predictive signature, and validate its efficacy in independently prognosticating overall survival (OS). METHODS: This study used single-cell RNA sequencing (scRNA-seq) data of CRC tissues from The Cancer Genome Atlas (TCGA), and a comprehensive set of 1,650 mitochondrial genes from MitoCarta 3.0. A differential gene expression analysis, gene set enrichment analysis (GSEA), pathway analysis, and Cox proportional hazards regression analysis were conducted. RESULTS: The Cox regression analysis identified five mitochondrial genes (i.e., CPT2, ACSL6, MOCS1, TERT, and PTRH1). These five genes were used to establish a reliable risk-scoring system. Patients with elevated risk scores had more severe clinical manifestations and worse survival outcomes. These results were corroborated in an external validation set (GSE17536 cohort). A predictive model was developed based on these genes that had robust predictive capabilities with areas under the curve (AUCs) of 0.75, 0.77, and 0.78 in the prediction of the 1-, 3-, and 5-year OS of CRC patients, respectively. Additionally, the correlation between the risk score and immune microenvironment characteristics (e.g., immune infiltration patterns, stromal/immune scores) further substantiated the predictive power of the model. CONCLUSIONS: This study established a novel prognostic model for CRC based on mitochondrial genes, thereby extending the understanding of the disease's progression. Subsequent studies should seek to validate these findings within a broader cohort of patients and explore the potential therapeutic roles of the identified mitochondrial genes in the management of CRC.
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Expression of targets of the RNA-binding protein AUF-1 in human airway epithelium indicates its role in cellular senescence and inflammation.
INTRODUCTION: The RNA-binding protein AU-rich-element factor-1 (AUF-1) participates to posttranscriptional regulation of genes involved in inflammation and cellular senescence, two pathogenic mechanisms of chronic obstructive pulmonary disease (COPD). Decreased AUF-1 expression was described in bronchiolar epithelium of COPD patients versus controls and in vitro cytokine- and cigarette smoke-challenged human airway epithelial cells, prompting the identification of epithelial AUF-1-targeted transcripts and function, and investigation on the mechanism of its loss. RESULTS: RNA immunoprecipitation-sequencing (RIP-Seq) identified, in the human airway epithelial cell line BEAS-2B, 494 AUF-1-bound mRNAs enriched in their 3'-untranslated regions for a Guanine-Cytosine (GC)-rich binding motif. AUF-1 association with selected transcripts and with a synthetic GC-rich motif were validated by biotin pulldown. AUF-1-targets' steady-state levels were equally affected by partial or near-total AUF-1 loss induced by cytomix (TNFα/IL1β/IFNγ/10 nM each) and siRNA, respectively, with differential transcript decay rates. Cytomix-mediated decrease in AUF-1 levels in BEAS-2B and primary human small-airways epithelium (HSAEC) was replicated by treatment with the senescence- inducer compound etoposide and associated with readouts of cell-cycle arrest, increase in lysosomal damage and senescence-associated secretory phenotype (SASP) factors, and with AUF-1 transfer in extracellular vesicles, detected by transmission electron microscopy and immunoblotting. Extensive in-silico and genome ontology analysis found, consistent with AUF-1 functions, enriched RIP-Seq-derived AUF-1-targets in COPD-related pathways involved in inflammation, senescence, gene regulation and also in the public SASP proteome atlas; AUF-1 target signature was also significantly represented in multiple transcriptomic COPD databases generated from primary HSAEC, from lung tissue and from single-cell RNA-sequencing, displaying a predominant downregulation of expression. DISCUSSION: Loss of intracellular AUF-1 may alter posttranscriptional regulation of targets particularly relevant for protection of genomic integrity and gene regulation, thus concurring to airway epithelial inflammatory responses related to oxidative stress and accelerated aging. Exosomal-associated AUF-1 may in turn preserve bound RNA targets and sustain their function, participating to spreading of inflammation and senescence to neighbouring cells.
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Intercellular communication atlas reveals Oprm1 as a neuroprotective factor for retinal ganglion cells.
The progressive death of mature neurons often results in neurodegenerative diseases. While the previous studies have mostly focused on identifying intrinsic mechanisms controlling neuronal survival, the extracellular environment also plays a critical role in regulating cell viability. Here we explore how intercellular communication contributes to the survival of retinal ganglion cells (RGCs) following the optic nerve crush (ONC). Although the direct effect of the ONC is restricted to the RGCs, we observed transcriptomic responses in other retinal cells to the injury based on the single-cell RNA-seq, with astrocytes and Müller glia having the most interactions with RGCs. By comparing the RGC subclasses with distinct resilience to ONC-induced cell death, we found that the high-survival RGCs tend to have more ligand-receptor interactions with other retinal cells, suggesting that these RGCs are intrinsically programmed to foster more communication with their surroundings. Furthermore, we identified the top 47 interactions that are stronger in the high-survival RGCs, likely representing neuroprotective interactions. We performed functional assays on one of the receptors, μ-opioid receptor (Oprm1), a receptor known to play roles in regulating pain, reward, and addictive behavior. Although Oprm1 is preferentially expressed in intrinsically photosensitive retinal ganglion cells (ipRGC), its neuroprotective effect could be transferred to multiple RGC subclasses by selectively overexpressing Oprm1 in pan-RGCs in ONC, excitotoxicity, and glaucoma models. Lastly, manipulating Oprm1 activity improved visual functions or altered pupillary light response in mice. Our study provides an atlas of cell-cell interactions in intact and post-ONC retina, and a strategy to predict molecular mechanisms controlling neuroprotection, underlying the principal role played by extracellular environment in supporting neuron survival.
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Mechanisms of synergistic regulation of the tumor microenvironment by fibroblasts and keratinocytes in esophageal squamous cell carcinoma.
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a highly invasive malignant tumor, and its tumor microenvironment (TME) plays a pivotal role in disease progression and treatment resistance. As key components of the TME, fibroblasts and keratinocytes are hypothesized to synergistically regulate tumor biological behavior. METHODS: This study integrated single-cell transcriptomic data with bulk RNA-seq data from ESCC to investigate the interaction mechanisms between fibroblasts and keratinocytes within the tumor microenvironment. Rigorous quality control, standardization, and clustering analyses were performed on the single-cell data, identifying ten distinct cell subpopulations, including fibroblasts and keratinocytes. The proportions and expression profile differences of these two cell types were compared between experimental and control groups. Cell-cell communication analysis deciphered ligand-receptor pairs and associated signaling pathways governing intercellular interactions. Molecular subtyping of The Cancer Genome Atlas (TCGA) cohort samples was subsequently performed using non-negative matrix factorization (NMF) based on interaction-specific genes. A multi-gene prognostic model was constructed via least absolute shrinkage and selection operator (LASSO) regression, and its predictive efficacy was evaluated. Finally, functional enrichment, immune microenvironment assessment, and differential expression analyses revealed differences in biological functions and immune infiltration patterns across distinct risk subtypes. RESULTS: By integrating the gene expression profiles of these two cell types, a novel molecular classification system was successfully established, enabling the stratification of ESCC patients into C1(high-risk) and C2(low-risk) subtypes with marked differences in survival outcomes. Patients classified as subtype C2 had a median survival of 3.8 months, significantly longer than the 1.8 months observed in the high-risk subtype C1, highlighting the substantial clinical relevance of this classification. Further analysis revealed that the high-risk cohort exhibited significant enrichment in metabolism-related pathways, such as endocytosis and glyceride metabolism, whereas the low-risk cohort was predominantly associated with pathways involved in cell junctions and structural maintenance. Mechanistically, the interaction between these two cell types jointly promotes the reprogramming of the tumor immune microenvironment by regulating immune cell infiltration, HLA molecule expression, and immune checkpoint activity. Furthermore, the study identified key genes, including SLIT2 and SFRP1, which display cell-type-specific expression patterns in ESCC and hold potential as prognostic biomarkers or therapeutic targets. This research provides novel insights into the regulatory mechanisms of the ESCC tumor microenvironment, laying a theoretical foundation for the development of precision therapeutic strategies targeting the tumor microenvironment. CONCLUSION: This study elucidates the synergistic regulatory mechanisms between fibroblasts and keratinocytes within the tumor microenvironment of ESCC. These findings offer a novel theoretical foundation for molecular classification, prognosis prediction, and precision treatment of ESCC.
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A single-cell genomic atlas for the effects of chronic ethanol exposure in the mouse dorsal striatum.
Alcohol use disorder (AUD) is characterized by compulsive drinking, which is thought to be mediated by effects of chronic intermittent ethanol exposure on the dorsal striatum, the input nucleus of the basal ganglia. Despite significant efforts to understand the impact of ethanol on the dorsal striatum, the rich diversity of striatal cell types and multitude of ethanol targets expressed by them necessitates an unbiased, discovery-based approach. In this study, we used single-nuclei RNA-sequencing (snRNA-seq; n = 86,715 cells) to examine the impact of chronic intermittent ethanol exposure on the dorsal striatum in C57BL/6 male and female mice. We detected 462 differentially expressed genes at FDR < 0.05, the majority of which were mapped to spiny projection neurons (SPNs), the most prominent cell type in the striatum. Gene co-expression network analysis and functional annotation of differentially expressed genes revealed down-regulation of postsynaptic intracellular signaling cascades in SPNs. Inflammation-related genes were down-regulated across many neuronal and non-neuronal cell types. Gene set enrichment analyses also pointed to altered states of rare cell types, including the induction of angiogenesis-related genes in vascular cells. A gene module down-regulated specifically in canonical SPNs was enriched for calcium-signaling genes and components of glutamatergic synapses, as well as for genes associated with genetic risk for AUD. Genetic perturbations of six of this module's hub genes - Foxp1, Bcl11b, Pde10a, Rarb, Rgs9, and Itgr1 - had causal effects on its expression in the mouse striatum and/or on the broader set of differentially expressed genes in alcohol-exposed mice. These data provide important clues as to the impact of ethanol on striatal biology and provide a key resource for future investigation.
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Whole-animal multiplexed single-cell RNA-seq reveals transcriptional shifts across Clytia medusa cell types.
We present an organism-wide, transcriptomic cell atlas of the hydrozoan medusa Clytia hemisphaerica and describe how its component cell types respond to perturbation. Using multiplexed single-cell RNA sequencing, in which individual animals were indexed and pooled from control and perturbation conditions into a single sequencing run, we avoid artifacts from batch effects and are able to discern shifts in cell state in response to organismal perturbations. This work serves as a foundation for future studies of development, function, and regeneration in a genetically tractable jellyfish species. Moreover, we introduce a powerful workflow for high-resolution, whole-animal, multiplexed single-cell genomics that is readily adaptable to other traditional or nontraditional model organisms.
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m6A demethylase-driven reprogramming of leukemia-associated macrophages predicts improved outcomes in acute myeloid leukemia.
BACKGROUND: N6-methyladenosine (m6A) is a dynamic mRNA modification influencing transcript fate and cellular identity, especially in cancer. While oncogenic roles of m6A regulators in AML cells are known, their impact on the leukemic immune microenvironment is unclear. METHODS: In this study, we constructed a single-cell atlas of macrophages in AML by integrating publicly available scRNA-seq datasets from 129 patient cohorts. Data were batch-corrected using Seurat and Harmony. Macrophage subpopulations were identified, and the expression and activity of 29 m6A regulators were analyzed. Pseudotime analysis (Monocle3), cell-cell communication (CellChat), and pathway enrichment (Metascape) analyses were performed to explore m6A-related functional programs. Survival analysis was conducted using Kaplan-Meier curves. RT-qPCR was used to verify the correlation between m6A regulatory molecules and prognosis. RESULTS: Our findings indicated that m6A regulators are associated with macrophage fate. Writer-high macrophages showed enhanced proliferation and differentiation, maintaining monocyte-like features. Eraser-high macrophages remodeled macrophage function toward an M1-like, pro-inflammatory and antigen-presenting state. Reader-high macrophages drove macrophages toward an immunosuppressive, M2-like phenotype, while m6A-deficient cells exhibit features of functional exhaustion. Survival analysis based on bulk RNA-seq data further revealed that m6A-regulated macrophage profiles were associated with distinct prognostic stratification in AML patients. RT-qPCR analysis of macrophages isolated from clinical AML samples further validated these findings, showing that patients with favorable prognosis exhibited significantly higher expression levels of erasers compared to those with poor prognosis. CONCLUSION: These results highlight m6A system's role in macrophage reprogramming and suggest that targeting m6A regulators in macrophages may serve as a potential basis for prognostic stratification and a promising therapeutic strategy in AML.
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In silico analysis identifies a putative cell-of-origin for BRAF fusion-positive cerebellar pilocytic astrocytoma.
Childhood cancers are increasingly recognized as disorders of cellular development. This study sought to identify the cellular and developmental origins of cerebellar pilocytic astrocytoma, the most common brain tumor of childhood. Using publicly available gene expression data from pilocytic astrocytoma tumors and controlling for driver mutation, a set of developmental-related genes which were overexpressed in cerebellar pilocytic astrocytoma was identified. These genes were then mapped onto several developmental atlases in order to identify normal cells with similar gene expression patterns and the developmental trajectory of those cells was interrogated. Eight known neuro-developmental genes were identified as being expressed in cerebellar pilocytic astrocytoma. Mapping those genes or their orthologs onto mouse neuro-developmental atlases identified overlap in their expression within the ventricular zone of the cerebellar anlage. Further analysis with a single cell RNA-sequencing atlas of the developing mouse cerebellum defined this overlap as occurring in ventricular zone progenitor cells at the division point between GABA-ergic neuronal and glial lineages, a developmental trajectory which closely mirrors that previously described to occur within pilocytic astrocytoma cells. Furthermore, ventricular zone progenitor cells and their progeny exhibited evidence of MAPK pathway activation, the paradigmatic oncogenic cascade known to be active in cerebellar pilocytic astrocytoma. Gene expression from developing human brain atlases recapitulated the same anatomic localizations and developmental trajectories as those found in mice. Taken together, these data suggest this population of ventricular zone progenitor cells as the cell-of-origin for BRAF fusion-positive cerebellar pilocytic astrocytoma.
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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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Single-Cell RNA-seq Reveals a Developmental Hierarchy Super-Imposed Over Subclonal Evolution in the Cellular Ecosystem of Prostate Cancer.
Prostate cancer (PCa) is a complex disease. An ongoing accumulation of mutations results in increased genetic diversity, with the tumor acquiring distinct subclones. However, non-genetic intra-tumoral heterogeneity, the cellular differentiation state and the interplay between subclonal evolution and transcriptional heterogeneity are poorly understood. Here, the authors perform single-cell RNA sequencing from 14 untreated PCa patients. They create an extensive cell atlas of the PCa patients and mapped developmental states onto tumor subclonal evolution. They identify distinct subclones across PCa patients and then stratify tumor cells into four transcriptional subtypes, EMT-like (subtype 0), luminal A-like (subtype 1), luminal B/C-like (subtype 2), and basal-like (subtype 3). These subtypes are hierarchically organized into stem cell-like and differentiated status. Strikingly, multiple subclones within a single primary tumor present with distinct combinations of preferential subtypes. In addition, subclones show different communication strengths with other cell types within the tumor ecosystem, which may modulate the distinct transcriptional subtypes of the subclones. Notably, by integrating TCGA data, they discover that both tumor cell transcriptional heterogeneity and cellular ecosystem diversity correlate with features of a poor prognosis. Collectively, their study provides the analysis of subclonal and transcriptional heterogeneity and its implication for patient prognosis.