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Predicting drug responses based on individual transcriptomic profiles holds promise for refining prognosis and advancing precision medicine. Although many studies have endeavored to predict the responses of known drugs to novel transcriptomic profiles, research into predicting responses for newly discovered drugs remains sparse. In this study, we introduce scDrug+, a comprehensive pipeline that seamlessly integrates single-cell analysis with drug-response prediction. Importantly, scDrug+ is equipped to predict the response of new drugs by analyzing their molecular structures. The open-source tool is available as a Docker container, ensuring ease of deployment and reproducibility. It can be accessed at https://github.com/ailabstw/scDrugplus.
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Perfilação da Expressão Gênica , Análise de Célula Única , Transcriptoma , Análise de Célula Única/métodos , Humanos , Transcriptoma/genética , Perfilação da Expressão Gênica/métodos , Estrutura Molecular , Reprodutibilidade dos Testes , Software , Descoberta de Drogas/métodosRESUMO
BACKGROUND: Interstitial lung disease (ILD) is the primary cause of mortality in systemic sclerosis (SSc), an autoimmune disease characterized by tissue fibrosis. SSc-related ILD (SSc-ILD) occurs more frequently in females aged 30-55 years, whereas idiopathic pulmonary fibrosis (IPF) is more prevalent in males aged 60-75 years. SSc-ILD occurs earlier than IPF and progresses rapidly. FCN1, FABP4, and SPP1 macrophages are involved in the pathogenesis of lung fibrosis; SPP1 macrophages demonstrate upregulated expression in both SSc-ILD and IPF. To identify the differences between SSc-ILD and IPF using single-cell analysis, clarify their distinct pathogeneses, and propose directions for prevention and treatment. METHODS: We performed single-cell RNA sequencing on NCBI Gene Expression Omnibus (GEO) databases GSE159354 and GSE212109, and analyzed lung tissue samples across healthy controls, IPF, and SSc-ILD. The primary measures were the filtered genes integrated with batch correction and annotated cell types for distinguishing patients with SSc-ILD from healthy controls. We proposed an SSc-ILD pathogenesis using cell-cell interaction inferences, and predicted transcription factors regulating target genes using SCENIC. Drug target prediction of the TF gene was performed using Drug Bank Online. RESULTS: A subset of macrophages activates the MAPK signaling pathway under oxidative stress. Owing to the lack of inhibitory feedback from ANNEXIN and the autoimmune characteristics, this leads to an earlier onset of lung fibrosis compared to IPF. During initial lung injury, fibroblasts begin to activate the IL6 pathway under the influence of SPP1 alveolar macrophages, but IL6 appears unrelated to other inflammatory and immune cells. This may explain why tocilizumab (an anti-IL6-receptor antibody) only preserves lung function in patients with early SSc-ILD. Finally, we identified BCLAF1 and NFE2L2 as influencers of MAPK activation in macrophages. Metformin downregulates NFE2L2 and could serve as a repurposed drug candidate. CONCLUSIONS: SPP1 alveolar macrophages play a role in the profibrotic activity of IPF and SSc-ILD. However, SSc-ILD is influenced by autoimmunity and oxidative stress, leading to the continuous activation of MAPK in macrophages. This may result in an earlier onset of lung fibrosis than in IPF. Such differences could serve as potential research directions for early prevention and treatment.
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Doenças Pulmonares Intersticiais , Macrófagos , Escleroderma Sistêmico , Humanos , Escleroderma Sistêmico/complicações , Escleroderma Sistêmico/patologia , Escleroderma Sistêmico/genética , Macrófagos/metabolismo , Doenças Pulmonares Intersticiais/complicações , Feminino , Masculino , Pessoa de Meia-Idade , Adulto , Fibrose Pulmonar Idiopática/complicações , Fibrose Pulmonar Idiopática/patologia , Idoso , Regulação da Expressão Gênica , Análise de Célula Única , Pulmão/patologiaRESUMO
Mitochondrial division inhibitor 1 (Mdivi-1) is a well-known synthetic compound aimed at inhibiting dynamin-related protein 1 (Drp1) to suppress mitochondrial fission, making it a valuable tool for studying mitochondrial dynamics. However, its specific effects beyond Drp1 inhibition remain to be confirmed. In this study, we employed integrative proteomics and phosphoproteomics to delve into the molecular responses induced by Mdivi-1 in SK-N-BE(2)C cells. A total of 3070 proteins and 1945 phosphorylation sites were identified, with 880 of them represented as phosphoproteins. Among these, 266 proteins and 97 phosphorylation sites were found to be sensitive to the Mdivi-1 treatment. Functional enrichment analysis unveiled their involvement in serine biosynthesis and extrinsic apoptotic signaling pathways. Through targeted metabolomics, we observed that Mdivi-1 enhanced intracellular serine biosynthesis while reducing the production of C24:1-ceramide. Within these regulated phosphoproteins, dynamic dephosphorylation of proteasome subunit alpha type 3 serine 250 (PSMA3-S250) occurred after Mdivi-1 treatment. Further site-directed mutagenesis experiments revealed that the dephosphorylation-deficient mutant PSMA3-S250A exhibited a decreased cell survival. This research confirms that Mdivi-1's inhibition of mitochondrial division leads to various side effects, ultimately influencing cell survival, rather than solely targeting Drp1 inhibition.
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Multiômica , Neuroblastoma , Humanos , Apoptose , Fosfoproteínas , Serina , Neuroblastoma/tratamento farmacológico , Neuroblastoma/genéticaRESUMO
Neuroblastoma, a childhood cancer affecting the sympathetic nervous system, continues to challenge the development of potent treatments due to the limited availability of druggable targets for this aggressive illness. Recent investigations have uncovered that phosphoglycerate dehydrogenase (PHGDH), an essential enzyme for de novo serine synthesis, serves as a non-oncogene dependency in high-risk neuroblastoma. In this study, we show that homoharringtonine (HHT) acts as a PHGDH inhibitor, inducing intricate alterations in cellular metabolism, and thus providing an efficient treatment for neuroblastoma. We have experimentally verified the reliance of neuroblastoma on PHGDH and employed molecular docking, thermodynamic evaluations, and X-ray crystallography techniques to determine the bond interactions between HHT and PHGDH. Administering HHT to treat neuroblastoma resulted in effective cell elimination in vitro and tumor reduction in vivo. Metabolite and functional assessments additionally disclosed that HHT treatment suppressed de novo serine synthesis, initiating intricate metabolic reconfiguration and oxidative stress in neuroblastoma. Collectively, these discoveries highlight the potential of targeting PHGDH using HHT as a potent approach for managing high-risk neuroblastoma.
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Neuroblastoma , Fosfoglicerato Desidrogenase , Humanos , Criança , Mepesuccinato de Omacetaxina , Simulação de Acoplamento Molecular , Inibidores Enzimáticos , Neuroblastoma/tratamento farmacológico , SerinaRESUMO
BACKGROUND: The nuclear factor kappa B (NFκB) regulatory pathways downstream of tumor necrosis factor (TNF) play a critical role in carcinogenesis. However, the widespread influence of NFκB in cells can result in off-target effects, making it a challenging therapeutic target. Ensemble learning is a machine learning technique where multiple models are combined to improve the performance and robustness of the prediction. Accordingly, an ensemble learning model could uncover more precise targets within the NFκB/TNF signaling pathway for cancer therapy. METHODS: In this study, we trained an ensemble learning model on the transcriptome profiles from 16 cancer types in the TCGA database to identify a robust set of genes that are consistently associated with the NFκB/TNF pathway in cancer. Our model uses cancer patients as features to predict the genes involved in the NFκB/TNF signaling pathway and can be adapted to predict the genes for different cancer types by switching the cancer type of patients. We also performed functional analysis, survival analysis, and a case study of triple-negative breast cancer to demonstrate our model's potential in translational cancer medicine. RESULTS: Our model accurately identified genes regulated by NFκB in response to TNF in cancer patients. The downstream analysis showed that the identified genes are typically involved in the canonical NFκB-regulated pathways, particularly in adaptive immunity, anti-apoptosis, and cellular response to cytokine stimuli. These genes were found to have oncogenic properties and detrimental effects on patient survival. Our model also could distinguish patients with a specific cancer subtype, triple-negative breast cancer (TNBC), which is known to be influenced by NFκB-regulated pathways downstream of TNF. Furthermore, a functional module known as mononuclear cell differentiation was identified that accurately predicts TNBC patients and poor short-term survival in non-TNBC patients, providing a potential avenue for developing precision medicine for cancer subtypes. CONCLUSIONS: In conclusion, our approach enables the discovery of genes in NFκB-regulated pathways in response to TNF and their relevance to carcinogenesis. We successfully categorized these genes into functional groups, providing valuable insights for discovering more precise and targeted cancer therapeutics.
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NF-kappa B , Neoplasias de Mama Triplo Negativas , Humanos , NF-kappa B/genética , NF-kappa B/metabolismo , Neoplasias de Mama Triplo Negativas/tratamento farmacológico , Fator de Necrose Tumoral alfa/genética , Fator de Necrose Tumoral alfa/uso terapêutico , Transdução de Sinais/genética , Carcinogênese , Aprendizado de MáquinaRESUMO
Conserved residues in protein homolog sequence alignments are structurally or functionally important. For intrinsically disordered proteins or proteins with intrinsically disordered regions (IDRs), however, alignment often fails because they lack a steric structure to constrain evolution. Although sequences vary, the physicochemical features of IDRs may be preserved in maintaining function. Therefore, a method to retrieve common IDR features may help identify functionally important residues. We applied unsupervised contrastive learning to train a model with self-attention neuronal networks on human IDR orthologs. Parameters in the model were trained to match sequences in ortholog pairs but not in other IDRs. The trained model successfully identifies previously reported critical residues from experimental studies, especially those with an overall pattern (e.g., multiple aromatic residues or charged blocks) rather than short motifs. This predictive model can be used to identify potentially important residues in other proteins, improving our understanding of their functions. The trained model can be run directly from the Jupyter Notebook in the GitHub repository using Binder (mybinder.org). The only required input is the primary sequence. The training scripts are available on GitHub (https://github.com/allmwh/IFF). The training datasets have been deposited in an Open Science Framework repository (https://osf.io/jk29b).
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Proteínas Intrinsicamente Desordenadas , Humanos , Proteínas Intrinsicamente Desordenadas/química , Alinhamento de Sequência , Aprendizado de Máquina , Modelos Moleculares , Conformação ProteicaRESUMO
ABSTARCT: Ectopic ATP synthase on the plasma membrane (eATP synthase) has been found in various cancer types and is a potential target for cancer therapy. However, whether it provides a functional role in tumor progression remains unclear. Here, quantitative proteomics reveals that cancer cells under starvation stress express higher eATP synthase and enhance the production of extracellular vesicles (EVs), which are vital regulators within the tumor microenvironment. Further results show that eATP synthase generates extracellular ATP to stimulate EV secretion by enhancing P2X7 receptor-triggered Ca2+ influx. Surprisingly, eATP synthase is also located on the surface of tumor-secreted EVs. The EVs-surface eATP synthase increases the uptake of tumor-secreted EVs in Jurkat T-cells via association with Fyn, a plasma membrane protein found in immune cells. The eATP synthase-coated EVs uptake subsequently represses the proliferation and cytokine secretion of Jurkat T-cells. This study clarifies the role of eATP synthase on EV secretion and its influence on immune cells.
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Vesículas Extracelulares , Neoplasias , Vesículas Extracelulares/metabolismo , Transporte Biológico , Trifosfato de Adenosina/metabolismo , Neoplasias/metabolismoRESUMO
Ectopic ATP synthase complex (eATP synthase), located on cancer cell surface, has been reported to possess catalytic activity that facilitates the generation of ATP in the extracellular environment to establish a suitable microenvironment and to be a potential target for cancer therapy. However, the mechanism of intracellular ATP synthase complex transport remains unclear. Using a combination of spatial proteomics, interaction proteomics, and transcriptomics analyses, we find ATP synthase complex is first assembled in the mitochondria and subsequently delivered to the cell surface along the microtubule via the interplay of dynamin-related protein 1 (DRP1) and kinesin family member 5B (KIF5B). We further demonstrate that the mitochondrial membrane fuses to the plasma membrane in turn to anchor ATP syntheses on the cell surface using super-resolution imaging and real-time fusion assay in live cells. Our results provide a blueprint of eATP synthase trafficking and contribute to the understanding of the dynamics of tumor progression.
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Mitocôndrias , Neoplasias , Humanos , Mitocôndrias/metabolismo , Membrana Celular/metabolismo , Membranas Mitocondriais/metabolismo , Neoplasias/metabolismo , Trifosfato de Adenosina/metabolismo , Microambiente TumoralRESUMO
Gene regulatory networks govern complex gene expression programs in various biological phenomena, including embryonic development, cell fate decisions and oncogenesis. Single-cell techniques are increasingly being used to study gene expression, providing higher resolution than traditional approaches. However, inferring a comprehensive gene regulatory network across different cell types remains a challenge. Here, we propose to construct context-dependent gene regulatory networks (CDGRNs) from single-cell RNA sequencing data utilizing both spliced and unspliced transcript expression levels. A gene regulatory network is decomposed into subnetworks corresponding to different transcriptomic contexts. Each subnetwork comprises the consensus active regulation pairs of transcription factors and their target genes shared by a group of cells, inferred by a Gaussian mixture model. We find that the union of gene regulation pairs in all contexts is sufficient to reconstruct differentiation trajectories. Functions specific to the cell cycle, cell differentiation or tissue-specific functions are enriched throughout the developmental process in each context. Surprisingly, we also observe that the network entropy of CDGRNs decreases along differentiation trajectories, indicating directionality in differentiation. Overall, CDGRN allows us to establish the connection between gene regulation at the molecular level and cell differentiation at the macroscopic level.
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Desenvolvimento Embrionário , Redes Reguladoras de Genes , Diferenciação Celular/genética , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismo , Perfilação da Expressão GênicaRESUMO
Circular permutation (CP) is a protein sequence rearrangement in which the amino- and carboxyl-termini of a protein can be created in different positions along the imaginary circularized sequence. Circularly permutated proteins usually exhibit conserved three-dimensional structures and functions. By comparing the structures of circular permutants (CPMs), protein research and bioengineering applications can be approached in ways that are difficult to achieve by traditional mutagenesis. Most current CP detection algorithms depend on structural information. Because there is a vast number of proteins with unknown structures, many CP pairs may remain unidentified. An efficient sequence-based CP detector will help identify more CP pairs and advance many protein studies. For instance, some hypothetical proteins may have CPMs with known functions and structures that are informative for functional annotation, but existing structure-based CP search methods cannot be applied when those hypothetical proteins lack structural information. Despite the considerable potential for applications, sequence-based CP search methods have not been well developed. We present a sequence-based method, SeqCP, which analyzes normal and duplicated sequence alignments to identify CPMs and determine candidate CP sites for proteins. SeqCP was trained by data obtained from the Circular Permutation Database and tested with nonredundant datasets from the Protein Data Bank. It shows high reliability in CP identification and achieves an AUC of 0.9. SeqCP has been implemented into a web server available at: http://pcnas.life.nthu.edu.tw/SeqCP/.
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Single-cell RNA sequencing (scRNA-seq) technology allows massively parallel characterization of thousands of cells at the transcriptome level. scRNA-seq is emerging as an important tool to investigate the cellular components and their interactions in the tumor microenvironment. scRNA-seq is also used to reveal the association between tumor microenvironmental patterns and clinical outcomes and to dissect cell-specific effects of drug treatment in complex tissues. Recent advances in scRNA-seq have driven the discovery of biomarkers in diseases and therapeutic targets. Although methods for prediction of drug response using gene expression of scRNA-seq data have been proposed, an integrated tool from scRNA-seq analysis to drug discovery is required. We present scDrug as a bioinformatics workflow that includes a one-step pipeline to generate cell clustering for scRNA-seq data and two methods to predict drug treatments. The scDrug pipeline consists of three main modules: scRNA-seq analysis for identification of tumor cell subpopulations, functional annotation of cellular subclusters, and prediction of drug responses. scDrug enables the exploration of scRNA-seq data readily and facilitates the drug repurposing process. scDrug is freely available on GitHub at https://github.com/ailabstw/scDrug.
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Microbial communities are massively resident in the human body, yet dysbiosis has been reported to correlate with many diseases, including various cancers. Most studies focus on the gut microbiome, while the bacteria that participate in tumor microenvironments on site remain unclear. Previous studies have acquired the bacteria expression profiles from RNA-seq, whole genome sequencing, and whole exon sequencing in The Cancer Genome Atlas (TCGA). However, small-RNA sequencing data were rarely used. Using TCGA miRNA sequencing data, we evaluated bacterial abundance in 32 types of cancer. To uncover the bacteria involved in cancer, we applied an analytical process to align unmapped human reads to bacterial references and developed the BIC database for the transcriptional landscape of bacteria in cancer. BIC provides cancer-associated bacterial information, including the relative abundance of bacteria, bacterial diversity, associations with clinical relevance, the co-expression network of bacteria and human genes, and their associated biological functions. These results can complement previously published databases. Users can easily download the result plots and tables, or download the bacterial abundance matrix for further analyses. In summary, BIC can provide information on cancer microenvironments related to microbial communities. BIC is available at: http://bic.jhlab.tw/.
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Bases de Dados Factuais , Microbiota , Neoplasias , Microambiente Tumoral , Humanos , Bactérias/genética , Bactérias/metabolismo , Microbioma Gastrointestinal/genética , Microbiota/genética , MicroRNAs/genética , Neoplasias/microbiologia , RNA Ribossômico 16S/genéticaRESUMO
Tissue-resident macrophages are essential to protect from pathogen invasion and maintain organ homeostasis. The ability of thymic macrophages to engulf apoptotic thymocytes is well appreciated, but little is known about their ontogeny, maintenance, and diversity. Here, we characterized the surface phenotype and transcriptional profile of these cells and defined their expression signature. Thymic macrophages were most closely related to spleen red pulp macrophages and Kupffer cells and shared the expression of the transcription factor (TF) SpiC with these cells. Single-cell RNA sequencing (scRNA-Seq) showed that the macrophages in the adult thymus are composed of two populations distinguished by the expression of Timd4 and Cx3cr1. Remarkably, Timd4+ cells were located in the cortex, while Cx3cr1+ macrophages were restricted to the medulla and the cortico-medullary junction. Using shield chimeras, transplantation of embryonic thymuses, and genetic fate mapping, we found that the two populations have distinct origins. Timd4+ thymic macrophages are of embryonic origin, while Cx3cr1+ macrophages are derived from adult hematopoietic stem cells. Aging has a profound effect on the macrophages in the thymus. Timd4+ cells underwent gradual attrition, while Cx3cr1+ cells slowly accumulated with age and, in older mice, were the dominant macrophage population in the thymus. Altogether, our work defines the phenotype, origin, and diversity of thymic macrophages.
Assuntos
Macrófagos , Timo , Camundongos , Animais , Timo/metabolismo , Timócitos , Células-Tronco Hematopoéticas , FenótipoRESUMO
The small nucleolar RNA host gene 1 (SNHG1) is a novel oncogenic long non-coding RNA (lncRNA) aberrantly expressed in different tumor types. We previously found highly expressed SNHG1 was associated with poor prognosis and MYCN status in neuroblastoma (NB). However, the molecular mechanisms of SNHG1 in NB are still unclear. Here, we disrupted endogenous SNHG1 in the MYCN-amplified NB cell line SK-N-BE(2)C using the CRISPR/Cas9 system and demonstrated the proliferation and colony formation ability of SNHG1-knowndown cells were suppressed. The transcriptome analysis and functional assays of SNHG1-knockdown cells revealed SNHG1 was involved in various biological processes including cell growth, migration, apoptosis, cell cycle, and reactive oxygen species (ROS). Interestingly, the expression of core regulatory circuitry (CRC) transcription factors in MYCN-amplified NB, including PHOX2B, HAND2, GATA3, ISL1, TBX1, and MYCN, were decreased in SNHG1-knockdown cells. The chromatin-immunoprecipitation sequencing (ChIP-seq) and transposase-accessible chromatin using sequencing (ATAC-seq) analyses showed that chromatin status of these CRC members was altered, which might stem from interactions between SNHG1 and HDAC1/2. These findings demonstrate that SNHG1 plays a crucial role in maintaining NB identity via chromatin regulation and reveal the function of the lncRNA SNHG1 in NB.
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MicroRNAs , Neuroblastoma , RNA Longo não Codificante , Linhagem Celular Tumoral , Proliferação de Células/genética , Cromatina , Regulação Neoplásica da Expressão Gênica , Histona Desacetilase 1/metabolismo , Histona Desacetilase 2 , Humanos , MicroRNAs/genética , Proteína Proto-Oncogênica N-Myc/genética , Proteína Proto-Oncogênica N-Myc/metabolismo , Neuroblastoma/genética , Neuroblastoma/patologia , RNA Longo não Codificante/genética , RNA Longo não Codificante/metabolismo , RNA Nucleolar Pequeno , Espécies Reativas de Oxigênio/metabolismo , Transposases/metabolismoRESUMO
Post-COVID-19 pulmonary fibrosis (PCPF) is a long-term complication that appears in some COVID-19 survivors. However, there are currently limited options for treating PCPF patients. To address this problem, we investigated COVID-19 patients' transcriptome at single-cell resolution and combined biological network analyses to repurpose the drugs treating PCPF. We revealed a novel gene signature of PCPF. The signature is functionally associated with the viral infection and lung fibrosis. Further, the signature has good performance in diagnosing and assessing pulmonary fibrosis. Next, we applied a network-based drug repurposing method to explore novel treatments for PCPF. By quantifying the proximity between the drug targets and the signature in the interactome, we identified several potential candidates and provided a drug list ranked by their proximity. Taken together, we revealed a novel gene expression signature as a theragnostic biomarker for PCPF by integrating different computational approaches. Moreover, we showed that network-based proximity could be used as a framework to repurpose drugs for PCPF.
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BACKGROUND: Recently, non-coding RNAs are of growing interest, and more scientists attach importance to research on their functions. Long non-coding RNAs (lncRNAs) are defined as non-protein coding transcripts longer than 200 nucleotides. We already knew that lncRNAs are related to cancers and will be dysregulated in them. But most of their functions are still left to further study. A mechanism of RNA regulation, known as competing endogenous RNAs (ceRNAs), has been proposed to explain the complex relationships among mRNAs and lncRNAs by competing for binding with shared microRNAs (miRNAs). METHODS: We proposed an analysis framework to construct the association networks among lncRNA, mRNA, and miRNAs based on their expression patterns and decipher their network modules. RESULTS: We collected a large-scale gene expression dataset of 1,061 samples from breast invasive carcinoma (BRCA) patients, each consisted of the expression profiles of 4,359 lncRNAs, 16,517 mRNAs, and 534 miRNAs, and applied the proposed analysis approach to interrogate them. We have uncovered the underlying ceRNA modules and the key modulatory lncRNAs for different subtypes of breast cancer. CONCLUSIONS: We proposed a modulatory analysis to infer the ceRNA effects among mRNAs and lncRNAs and performed functional analysis to reveal the plausible mechanisms of lncRNA modulation in the four breast cancer subtypes. Our results might provide new directions for breast cancer therapeutics and the proposed method could be readily applied to other diseases.
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Neoplasias da Mama , MicroRNAs , RNA Longo não Codificante , Neoplasias da Mama/genética , Feminino , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Humanos , MicroRNAs/genética , MicroRNAs/metabolismo , RNA Longo não Codificante/genética , RNA Longo não Codificante/metabolismo , RNA Mensageiro/genética , RNA Mensageiro/metabolismoRESUMO
The tumor microenvironment (TME), which comprises cellular and noncellular components, is involved in the complex process of cancer development. Emerging evidence suggests that mesenchymal stem cells (MSCs), one of the vital regulators of the TME, foster tumor progression through paracrine secretion. However, the comprehensive phosphosignaling pathways that are mediated by MSC-secreting factors have not yet been fully established. In this study, we attempt to dissect the MSC-triggered mechanism in lung cancer using quantitative phosphoproteomics. A total of 1958 phosphorylation sites are identified in lung cancer cells stimulated with MSC-conditioned medium. Integrative analysis of the identified phosphoproteins and predicted kinases demonstrates that MSC-conditioned medium functionally promotes the proliferation and migration of lung cancer via the ERK/phospho-c-Fos-S374 pathway. Recent studies have reported that extracellular ATP accumulates in the TME and stimulates the P2X7R on the cancer cell membrane via purinergic signaling. We observe that ectopic ATP synthase is located on the surface of MSCs and excreted extracellular ATP into the lung cancer microenvironment to trigger the ERK/phospho-c-Fos-S374 pathway, which is consistent with these previous findings. Our results suggest that ectopic ATP synthase on the surface of MSCs releases extracellular ATP into the TME, which promotes cancer progression via activation of the ERK/phospho-c-Fos-S374 pathway.
Assuntos
Neoplasias Pulmonares , Células-Tronco Mesenquimais , Trifosfato de Adenosina/metabolismo , Movimento Celular/fisiologia , Proliferação de Células , Meios de Cultivo Condicionados/farmacologia , Humanos , Neoplasias Pulmonares/metabolismo , Células-Tronco Mesenquimais/metabolismo , Microambiente TumoralRESUMO
Single-cell RNA sequencing (scRNA-seq) approach can broadly and specifically evaluate the individual cells with minimum detection bias. To explore the individual compositional and transcriptional alteration of intestinal leukocytes in the Dual Specificity Phosphatase six knockout (D6KO) mice, we performed a scRNA-seq followed by the cell type annotation based on ImmGen database. Composition assessments found that D6KO-derived intestinal leukocytes tend to stay inactivate or immature status. The enrichment analysis showed that D6KO-derived intestinal leukocytes are less sensitive to microbes. The mod PhEA phenotypic analysis showed that the D6KO leukocytes may link to not only immune-associated but also diverse previously non-immune-related diseases. Integrating our dataset with the published dataset GSE124880 generated a comprehensive dataset for exploring intestinal immunity. Down-regulation of Ccl17 gene was found in the D6KO-derived dendritic cells. Our results demonstrated the advantage of applying scRNA-seq for dissecting the individual alteration of intestinal leukocytes, particularly in the D6KO mice at a naive state.
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Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been rapidly spreading worldwide, causing hundreds of millions of infections. Despite the development of vaccines, insufficient protection remains a concern. Therefore, the screening of drugs for the treatment of coronavirus disease 2019 (COVID-19) is reasonable and necessary. This study utilized bioinformatics for the selection of compounds approved by the U.S. Food and Drug Administration with therapeutic potential in this setting. In addition, the inhibitory effect of these compounds on the enzyme activity of transmembrane protease serine 2 (TMPRSS2), papain-like protease (PLpro), and 3C-like protease (3CLpro) was evaluated. Furthermore, the capability of compounds to attach to the spike-receptor-binding domain (RBD) was considered an important factor in the present assessment. Finally, the antiviral potency of compounds was validated using a plaque reduction assay. Our funnel strategy revealed that tamoxifen possesses an anti-SARS-CoV-2 property owing to its inhibitory performance in multiple assays. The proposed time-saving and feasible strategy may accelerate drug screening for COVID-19 and other diseases.
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Mitochondria are crucial organelles that provide energy via oxidative phosphorylation in eukaryotic cells and also have critical roles in growth, division, and the cell cycle, as well as the rapid adaptation required to meet the metabolic needs of the cell. Mitochondrial processes are highly dynamic; fusion and fission can vary with cell type, cellular context, and stress levels. Accumulating evidence demonstrates that an imbalance in mitochondrial dynamics leads to death in numerous types of human cancer cells. Therefore, modulating mitochondrial dynamics could be a therapeutic target. In this review, we provide an overview of the protein interaction networks involved in mitochondrial dynamics as effective and feasible drug targets and discuss the related potential therapeutic strategies for cancer.