NPJ Systems Biology and Applications最新文献_第3页

Identifying genes underlying parallel evolution of stromal resistance to placental and cancer invasion. 鉴定基质抗胎盘和癌症侵袭平行进化的基因。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-22 DOI: 10.1038/s41540-025-00577-z

Yasir Suhail, Wenqiang Du, Junaid Afzal, Günter P Wagner, Kshitiz

{"title":"Identifying genes underlying parallel evolution of stromal resistance to placental and cancer invasion.","authors":"Yasir Suhail, Wenqiang Du, Junaid Afzal, Günter P Wagner, Kshitiz","doi":"10.1038/s41540-025-00577-z","DOIUrl":"https://doi.org/10.1038/s41540-025-00577-z","url":null,"abstract":"Stromal regulation of cancer dissemination is well recognized, however causal genes remain unidentified. We previously demonstrated that epitheliochorial species have acquired stromal resistance to placental invasion, correlating with reduced rate of cancer malignancies, identifying stromal genes correlating with depth of placental invasion called ELI (Evolved Levels of Invasibility) genes. Similarly, decidualization of human endometrial fibroblasts confers resistance to placental invasion. We hypothesized that both trajectories may convergently use similar pathways, providing an opportunity to identify stromal genes regulating epithelial invasion. We created a gene-set ELI-D1 (ELI-Decidual 1), putatively underlying stromal vulnerability to invasion. ELI-D1 were negatively enriched in T1-T2 stage transition in many human cancers, typically preceding dissemination. We also identified candidate transcriptional regulators underlying variation in ELI-D1 genes across eutherians, functionally showing Nr2f6, and JDP2 can regulate stromal resistance to invasion in human fibroblasts. Our comparative approach provides us with a gene-set linked to stromal vulnerability in human cancers.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"95"},"PeriodicalIF":3.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144962966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A cell type and state specific gene regulation network inference method for immune regulatory analysis. 一种用于免疫调节分析的细胞类型和状态特异性基因调控网络推断方法。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-13 DOI: 10.1038/s41540-025-00564-4

Xiong Li, Kun Rao, Chuang Chen, Yuejin Zhang, Juan Zhou, Xu Meng, Yi Hua, Jie Li, Haowen Chen

{"title":"A cell type and state specific gene regulation network inference method for immune regulatory analysis.","authors":"Xiong Li, Kun Rao, Chuang Chen, Yuejin Zhang, Juan Zhou, Xu Meng, Yi Hua, Jie Li, Haowen Chen","doi":"10.1038/s41540-025-00564-4","DOIUrl":"10.1038/s41540-025-00564-4","url":null,"abstract":"The gene regulatory network inference method based on bulk sequencing data not only confuses different types of cells, but also ignores the phenomenon of network dynamic changes with cell state. Single cell transcriptome sequencing technology provides data support for constructing cell type and state specific gene regulatory networks. This study proposes a method for inferring cell type and state specific gene regulatory networks based on scRNA-seq data, called inferCSN. Firstly, inferCSN infers pseudo temporal information from scRNA-seq data and reorders cells based on this information. Because of the uneven distribution of cells in pseudo temporal information, the regulatory relationship tends to lean towards the high-density areas of cells. Therefore, based on the cell state, we divide the cells into different windows to eliminate the temporal information differences caused by cell density. Then, a sparse regression model, combined with reference network information, is used to construct a cell type-specific regulatory network (CSN) for each window. The experimental results on both simulated and real scRNA-seq datasets show that inferCSN outperforms other methods in multiple performance metrics. In addition, experimental results on datasets of different types (such as steady-state and linear datasets) and scales (different cell and gene numbers) show that inferCSN is robust. To further demonstrate the effectiveness and application prospects of inferCSN, we analyzed the gene regulatory network of T cells in different states and different tumor subclons within the tumor microenvironment, and we found that comparing the regulatory networks in different states can reveal immune suppression related signaling pathways.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"94"},"PeriodicalIF":3.5,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12350830/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144847977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Altered dynamic functional connectivity and reduced higher order information interaction in Parkinson's patients with hyposmia. 帕金森低氧症患者动态功能连接改变和高阶信息交互减少。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-13 DOI: 10.1038/s41540-025-00574-2

Sneha Ray, Navkiran Kalsi, Henning Boecker, Neeraj Upadhyay, Rajanikant Panda

{"title":"Altered dynamic functional connectivity and reduced higher order information interaction in Parkinson's patients with hyposmia.","authors":"Sneha Ray, Navkiran Kalsi, Henning Boecker, Neeraj Upadhyay, Rajanikant Panda","doi":"10.1038/s41540-025-00574-2","DOIUrl":"10.1038/s41540-025-00574-2","url":null,"abstract":"Hyposmia, a common non-motor symptom in Parkinson's disease (PD) linked to reduced odor sensitivity, is associated with brain structural and functional changes, but dynamic brain activity and altered regional information exchange remain underexplored, limiting insight into underlying brain states. We selected 15 PD patients with severe hyposmia (PD-SH), 15 PD patients with normal cognition (PD-CN), and 15 healthy controls (HC). Using functional MRI, we assessed the brain's spatiotemporal connectivity (brain-state) alterations, and the brain's capacity for higher-order information exchange (synergy and redundancy). A dynamic brain state with complex-long-range connections was significantly reduced in PD-SH and PD-CN, compared to HC. Brain-states consisting of modular-clusters in sensorimotor and frontal areas occurred more frequently in PD-SH than in PD-CN and HC. Higher-order information flow was reduced in PD patients, with PD-SH showing a greater reduction in synergetic information flow in frontal, insula, and left sensory-motor. These findings suggest potential discriminative biomarkers for PD-SH.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"93"},"PeriodicalIF":3.5,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12350643/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144847978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Causality-aware graph neural networks for functional stratification and phenotype prediction at scale. 用于功能分层和大规模表型预测的因果关系感知图神经网络。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-12 DOI: 10.1038/s41540-025-00567-1

Charalampos P Triantafyllidis, Ricardo Aguas

{"title":"Causality-aware graph neural networks for functional stratification and phenotype prediction at scale.","authors":"Charalampos P Triantafyllidis, Ricardo Aguas","doi":"10.1038/s41540-025-00567-1","DOIUrl":"10.1038/s41540-025-00567-1","url":null,"abstract":"We employ a computational framework that integrates mathematical programming and Graph Neural Networks (GNNs) to elucidate functional phenotypic heterogeneity in disease by classifying entire pathways under various conditions of interest. Our approach combines two distinct, yet seamlessly integrated, modeling schemes. First, we leverage Prior Knowledge Networks (PKNs) to reconstruct gene networks from genomic and transcriptomic data. We demonstrate how this can be achieved through mathematical programming optimization and provide examples using comprehensive, established databases. We then tailor GNNs to classify each network as a single data point at graph-level, using various node embeddings and edge attributes. These networks may vary in their biological or molecular annotations, which serve as a labeling scheme for their supervised classification. We apply the framework to the human DNA damage and repair pathway using the TP53 regulon in a pancancer study across cell lines and tumor samples to classify Gene Regulatory Networks (GRNs) across different TP53 mutation types. This approach allows us to identify mutations with distinguishable functional profiles that can be related to specific phenotypes, thus providing a data-driven pipeline for genotype-to-phenotype translation. This scalable approach enables the classification of diverse conditions within the multi-factorial nature of diseases and disentangles their polygenic complexity by revealing new functional patterns through a causal representation.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"92"},"PeriodicalIF":3.5,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12343938/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144835881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding the role of toggle genes in chronic lymphocytic leukemia proliferation. 了解toggle基因在慢性淋巴细胞白血病增殖中的作用。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-11 DOI: 10.1038/s41540-025-00575-1

Olga Sirbu, Gunjan Agarwal, Alessandro Giuliani, Kumar Selvarajoo

{"title":"Understanding the role of toggle genes in chronic lymphocytic leukemia proliferation.","authors":"Olga Sirbu, Gunjan Agarwal, Alessandro Giuliani, Kumar Selvarajoo","doi":"10.1038/s41540-025-00575-1","DOIUrl":"10.1038/s41540-025-00575-1","url":null,"abstract":"Cancer cell populations, such as chronic lymphocytic leukemia (CLL), are characterized by aberrant proliferation and plasticity: cells may switch between states so increasing population heterogeneity. Previous works have shown that gene expression noise can impact cell-state transition. To gain better insights into transcriptome-wide expression dynamics and the effect of noise on state transition, here we investigate RNA-Seq data of proliferative (PC) and non-proliferative (NPC) CLL cells. Various data analytics were applied to the whole transcriptome, switch-like toggle (ON/OFF) genes, temporal differentially expressed (DE) genes, and randomly selected genes. Collectively, we identified 2713 temporal DE genes (DESeq2 with 4-fold, p < 0.05) and 1704 toggle genes shaping the differentiation process over a period of 96 h, with 604 overlapping genes between them. Despite their lower numbers compared to DE, toggle genes contributed significantly to gene expression noise in both cell types. Toggle gene analyses revealed the enrichment of genes involved in processes such as G-alpha signaling and muscle contraction as proliferation related RHO-GTPase, interleukin and chemokine signaling, and lymphoid cell communication. Thus, toggle genes, although being random ON/OFF genes, show gene expression functional variability. These results suggest that toggle genes play an important role in shaping cell population plasticity.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"91"},"PeriodicalIF":3.5,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12340104/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generalized linear modeling of flow cytometry data to analyze immune responses in tuberculosis vaccine research. 流式细胞术数据的广义线性建模以分析结核病疫苗研究中的免疫反应。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-10 DOI: 10.1038/s41540-025-00572-4

Pablo Maldonado, Taru S Dutt, Amanda Hitpas, Brendan Podell, G Brooke Anderson, Marcela Henao-Tamayo

{"title":"Generalized linear modeling of flow cytometry data to analyze immune responses in tuberculosis vaccine research.","authors":"Pablo Maldonado, Taru S Dutt, Amanda Hitpas, Brendan Podell, G Brooke Anderson, Marcela Henao-Tamayo","doi":"10.1038/s41540-025-00572-4","DOIUrl":"10.1038/s41540-025-00572-4","url":null,"abstract":"Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) kills ~1.3 million people annually. Accordingly, vaccines and sophisticated analytical tools are necessary to evaluate their effectiveness. To address these challenges, we created a Generalized Linear Model (GLM) framework to evaluate high-dimensional flow cytometry data and the multivariable influences on immune responses, accommodating proportional and non-normal data, and violations of assumptions set by classical statistical evaluations. In naïve mice vaccinated with BCG boosted with ID93-GLA-SE, we used GLMs to assess the impact of sex, vaccination, and days post-infection on probabilities of immune cell phenotypes following Mtb challenge. We demonstrate enhanced T cell responses in the lung following BCG + ID93-GLA-SE compared to BCG or ID93-GLA-SE alone, with notable sex differences in humoral immunity. This framework highlights GLMs in assessing complex datasets while enhancing our comprehension of independent continuous and categorical variables on vaccine efficacy, and serves as a foundation for deeper, more complex scenarios.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"90"},"PeriodicalIF":3.5,"publicationDate":"2025-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335546/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144812165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Breast cancer is detectable from peripheral blood using machine learning over T cell receptor repertoires. 利用T细胞受体谱的机器学习从外周血中检测乳腺癌。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-08 DOI: 10.1038/s41540-025-00573-3

Miriam Zuckerbrot-Schuldenfrei, Ari Raphael, Alona Zilberberg, Sol Efroni

{"title":"Breast cancer is detectable from peripheral blood using machine learning over T cell receptor repertoires.","authors":"Miriam Zuckerbrot-Schuldenfrei, Ari Raphael, Alona Zilberberg, Sol Efroni","doi":"10.1038/s41540-025-00573-3","DOIUrl":"10.1038/s41540-025-00573-3","url":null,"abstract":"The immune system's defense abilities rely on the diversity of T and B lymphocytes. T Cell Receptors (TCRs) are generated through V(D)J recombination, where distinct genetic elements combine and undergo modifications, creating extensive variability. In breast cancer, the most frequently diagnosed cancer in women, early detection sometimes helps with highly effective and potentially curative treatment. The TCR repertoire may provide information about tumor status. To test this, we investigated the peripheral blood TCR repertoire and its association with tumor status. We collected blood samples from 98 women, including patients and healthy donors. Following TCR profiling, machine learning of these data was able to show an association between TCR profiles and breast cancer presence or absence with high accuracy (average AUC of 0.96). Our findings imply the immune system retains tumor-relevant, TCR-related, signals detectable in blood. This information could potentially benefit future derivatives from this knowledge, either in the field of detection or treatment.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"89"},"PeriodicalIF":3.5,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12334664/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144804393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A statistical framework for detecting therapy-induced resistance from drug screens. 从药物筛选中检测治疗性耐药性的统计框架。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-06 DOI: 10.1038/s41540-025-00560-8

Chenyu Wu, Einar Bjarki Gunnarsson, Jasmine Foo, Kevin Leder

引用次数: 0

A computational framework for inferring species dynamics and interactions with applications in microbiota ecology. 推断物种动态和相互作用的计算框架与微生物群生态学的应用。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-05 DOI: 10.1038/s41540-025-00568-0

Yuanwei Xu, Georgios V Gkoutos

{"title":"A computational framework for inferring species dynamics and interactions with applications in microbiota ecology.","authors":"Yuanwei Xu, Georgios V Gkoutos","doi":"10.1038/s41540-025-00568-0","DOIUrl":"10.1038/s41540-025-00568-0","url":null,"abstract":"We present MBPert, a generic computational framework for inferring species interactions and predicting dynamics in time-evolving ecosystems from perturbation and time-series data. In this work, we contextualize the framework in microbial ecosystem modeling by coupling a modified generalized Lotka-Volterra formulation with machine learning optimization. Unlike traditional methods that rely on gradient matching, MBPert leverages numerical solutions of differential equations and iterative parameter estimation to robustly capture microbial dynamics. The framework is assessed within the context of two experimental scenarios: (i) paired before-and-after measurements under targeted perturbations, and (ii) longitudinal time-series data with time-dependent perturbations. Extensive simulation studies, benchmarking on standardized MTIST datasets, and application to Clostridium difficile infection in mice and repeated antibiotic perturbations of human gut micribiota, demonstrate that MBPert accurately recapitulates species interactions and predicts system dynamics. Our results highlight MBPert as a powerful and flexible tool for mechanistic insight into microbiota ecology, with broad potential applicability to other complex dynamical systems.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"87"},"PeriodicalIF":3.5,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12325733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144789630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-modal clustering reveals event-free patient subgroup in colorectal cancer survival. 多模态聚类揭示结直肠癌无事件患者亚组生存率。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-02 DOI: 10.1038/s41540-025-00557-3

Nikita Janakarajan, Guillaume Larghero, María Rodríguez Martínez

引用次数: 0