NPJ Systems Biology and Applications最新文献_第8页

Computational modeling of cancer cell metabolism along the catabolic-anabolic axes. 癌细胞代谢沿分解代谢-合成代谢轴的计算模型。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-10 DOI: 10.1038/s41540-025-00525-x

Javier Villela-Castrejon, Herbert Levine, Benny A Kaipparettu, José N Onuchic, Jason T George, Dongya Jia

{"title":"Computational modeling of cancer cell metabolism along the catabolic-anabolic axes.","authors":"Javier Villela-Castrejon, Herbert Levine, Benny A Kaipparettu, José N Onuchic, Jason T George, Dongya Jia","doi":"10.1038/s41540-025-00525-x","DOIUrl":"https://doi.org/10.1038/s41540-025-00525-x","url":null,"abstract":"Abnormal metabolism is a hallmark of cancer, this was initially recognized nearly a century ago through the observation of aerobic glycolysis in cancer cells. Mitochondrial respiration can also drive tumor progression and metastasis. However, it remains largely unclear the mechanisms by which cancer cells mix and match different metabolic modalities (oxidative/reductive) and leverage various metabolic ingredients (glucose, fatty acids, glutamine) to meet their bioenergetic and biosynthetic needs. Here, we formulate a phenotypic model for cancer metabolism by coupling master gene regulators (AMPK, HIF-1, MYC) with key metabolic substrates (glucose, fatty acids, and glutamine). The model predicts that cancer cells can acquire four metabolic phenotypes: a catabolic phenotype characterized by vigorous oxidative processes-O, an anabolic phenotype characterized by pronounced reductive activities-W, and two complementary hybrid metabolic states-one exhibiting both high catabolic and high anabolic activity-W/O, and the other relying mainly on glutamine oxidation-Q. Using this framework, we quantified gene and metabolic pathway activity by developing scoring metrics based on gene expression. We validated the model-predicted gene-metabolic pathway association and the characterization of the four metabolic phenotypes by analyzing RNA-seq data of tumor samples from TCGA. Strikingly, carcinoma samples exhibiting hybrid metabolic phenotypes are often associated with the worst survival outcomes relative to other metabolic phenotypes. Our mathematical model and scoring metrics serve as a platform to quantify cancer metabolism and study how cancer cells adapt their metabolism upon perturbations, which ultimately could facilitate an effective treatment targeting cancer metabolic plasticity.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"46"},"PeriodicalIF":3.5,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12065808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144023683","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

Patient-specific gene co-expression networks reveal novel subtypes and predictive biomarkers in lung adenocarcinoma. 患者特异性基因共表达网络揭示肺腺癌的新亚型和预测性生物标志物。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-09 DOI: 10.1038/s41540-025-00522-0

Patricio López-Sánchez, Federico Ávila-Moreno, Enrique Hernández-Lemus, Marieke L Kuijjer, Jesús Espinal-Enríquez

{"title":"Patient-specific gene co-expression networks reveal novel subtypes and predictive biomarkers in lung adenocarcinoma.","authors":"Patricio López-Sánchez, Federico Ávila-Moreno, Enrique Hernández-Lemus, Marieke L Kuijjer, Jesús Espinal-Enríquez","doi":"10.1038/s41540-025-00522-0","DOIUrl":"https://doi.org/10.1038/s41540-025-00522-0","url":null,"abstract":"Lung adenocarcinoma (LUAD) is a highly heterogenous and aggressive form of non-small cell lung cancer (NSCLC). The use of genome-wide gene co-expression networks (GCNs) has been paramount to describe changes in the transcriptional regulatory programs found between diseased and healthy states of LUAD. Recently, studies have shown that multiple cancerous phenotypes share a distinct GCN architecture, suggesting that network topology holds promise for understanding disease pathology. However, conventional GCN inference methods struggle to capture the inherent context-specificity within a patient population, thus flattening its heterogeneity. To address this issue, the use of single-sample network (SSN) modelling has emerged as a promising solution into studying heterogeneous traits of cancer through network-based approaches. Here, we reconstructed patient-specific GCNs (n=334) using the LIONESS equation and mutual information as the network inference method. Unsupervised analysis revealed six novel LUAD subtypes based on inter-patient network similarity, each with distinct network motifs reflecting unique biological programs. Supervised analysis, employing regularized Cox regression, identified 12 genes (CHRDL2, SPP2, VAC14, IRF5, GUCY1B1, NCS1, RRM2B, EIF5A2, CCDC62, CTCFL, XG, and TP53INP2) whose weighted degree in SSNs is predictive of patient survival in LUAD. These findings suggest that topological features of SSNs offer valuable insights into the context-specific nature of LUAD malignancy, highlighting the potential of SSN-based approaches for further research.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"44"},"PeriodicalIF":3.5,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12064794/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144029704","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 Python toolbox for neural circuit parameter inference. 神经电路参数推理的Python工具箱。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-09 DOI: 10.1038/s41540-025-00527-9

Alejandro Orozco Valero, Víctor Rodríguez-González, Noemi Montobbio, Miguel A Casal, Alejandro Tlaie, Francisco Pelayo, Christian Morillas, Jesús Poza, Carlos Gómez, Pablo Martínez-Cañada

{"title":"A Python toolbox for neural circuit parameter inference.","authors":"Alejandro Orozco Valero, Víctor Rodríguez-González, Noemi Montobbio, Miguel A Casal, Alejandro Tlaie, Francisco Pelayo, Christian Morillas, Jesús Poza, Carlos Gómez, Pablo Martínez-Cañada","doi":"10.1038/s41540-025-00527-9","DOIUrl":"https://doi.org/10.1038/s41540-025-00527-9","url":null,"abstract":"Computational research tools have reached a level of maturity that enables efficient simulation of neural activity across diverse scales. Concurrently, experimental neuroscience is experiencing an unprecedented scale of data generation. Despite these advancements, our understanding of the precise mechanistic relationship between neural recordings and key aspects of neural activity remains insufficient, including which specific features of electrophysiological population dynamics (i.e., putative biomarkers) best reflect properties of the underlying microcircuit configuration. We present ncpi, an open-source Python toolbox that serves as an all-in-one solution, effectively integrating well-established methods for both forward and inverse modeling of extracellular signals based on single-neuron network model simulations. Our tool serves as a benchmarking resource for model-driven interpretation of electrophysiological data and the evaluation of candidate biomarkers that plausibly index changes in neural circuit parameters. Using mouse LFP data and human EEG recordings, we demonstrate the potential of ncpi to uncover imbalances in neural circuit parameters during brain development and in Alzheimer's Disease.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"45"},"PeriodicalIF":3.5,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12064716/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047179","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

Effective integration of multi-omics with prior knowledge to identify biomarkers via explainable graph neural networks. 多组学与先验知识的有效整合，通过可解释的图神经网络识别生物标志物。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-08 DOI: 10.1038/s41540-025-00519-9

Rohit K Tripathy, Zachary Frohock, Hong Wang, Gregory A Cary, Stephen Keegan, Gregory W Carter, Yi Li

{"title":"Effective integration of multi-omics with prior knowledge to identify biomarkers via explainable graph neural networks.","authors":"Rohit K Tripathy, Zachary Frohock, Hong Wang, Gregory A Cary, Stephen Keegan, Gregory W Carter, Yi Li","doi":"10.1038/s41540-025-00519-9","DOIUrl":"https://doi.org/10.1038/s41540-025-00519-9","url":null,"abstract":"The rapid growth of multi-omics datasets and the wealth of biological knowledge necessitates the development of effective methods for their integration. Such methods are essential for building predictive models and identifying drug targets based on a limited number of samples. We propose a framework called GNNRAI for the supervised integration of multi-omics data with biological priors represented as knowledge graphs. Our framework leverages graph neural networks (GNNs) to model the correlation structures among features from high-dimensional 'omics data, which reduces the effective dimensions in data and enables us to analyze thousands of genes simultaneously using hundreds of samples. Furthermore, our framework incorporates explainability methods to elucidate informative biomarkers. We apply our framework to Alzheimer's disease (AD) multi-omics data, showing that the integration of transcriptomics and proteomics data with prior AD knowledge is effective, improving the prediction accuracy of AD status over single-omics analyses and highlighting both known and novel AD-predictive biomarkers.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"43"},"PeriodicalIF":3.5,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12062277/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144012929","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

An in silico approach deciphering the commensal dynamics in the cutaneous milieu. 一种破译皮肤环境中共生动力学的计算机方法。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-07 DOI: 10.1038/s41540-025-00524-y

Sumathi Kalankariyan, Anjana Thottapillil, Abha Saxena, Manoj Srivatsn S, Vinitha Kadamkode, Renu Kapoor, Rupak Mitra, Janhavi Raut, K V Venkatesh

{"title":"An in silico approach deciphering the commensal dynamics in the cutaneous milieu.","authors":"Sumathi Kalankariyan, Anjana Thottapillil, Abha Saxena, Manoj Srivatsn S, Vinitha Kadamkode, Renu Kapoor, Rupak Mitra, Janhavi Raut, K V Venkatesh","doi":"10.1038/s41540-025-00524-y","DOIUrl":"https://doi.org/10.1038/s41540-025-00524-y","url":null,"abstract":"The skin microbiota, particularly coagulase-negative staphylococci (CoNS) such as S. epidermidis, plays a crucial role in maintaining skin health and immunity. S. epidermidis, a predominant commensal species, interacts intimately with keratinocytes to regulate immune responses and antimicrobial defence mechanisms. Metabolic byproducts like short-chain fatty acids (SCFAs) influence keratinocyte activation, while cell wall components engage Toll-like receptors (TLRs) to modulate inflammation. These interactions are fundamental for preserving skin homeostasis and combating pathogenic invaders. Our comprehensive mathematical model, integrating commensal dynamics, immune responses, and skin microenvironment variables, provides insights into these intricate interactions. The model delves into the complexities of skin scenarios and perturbations, aiming to understand the colonization dynamics of S. epidermidis and its influence on skin barrier functions. It examines how disruptions in key factors such as AMP, growth factor-mediated repair pathways, and filaggrin mutations influence the behaviour of the system. The study depicts the skin microenvironment as a highly dynamic one, highlighting the critical role of S. epidermidis and capturing its role in barrier dysfunction caused by internal and external factors. By offering insights into skin barrier function and immune responses, the model illuminates key interactions of commensals within the skin microenvironment which can ultimately benefit skin health.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"42"},"PeriodicalIF":3.5,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12058978/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144034185","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

Neural mechanisms balancing accuracy and flexibility in working memory and decision tasks. 平衡工作记忆和决策任务的准确性和灵活性的神经机制。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-05-07 DOI: 10.1038/s41540-025-00520-2

Han Yan, Jin Wang

{"title":"Neural mechanisms balancing accuracy and flexibility in working memory and decision tasks.","authors":"Han Yan, Jin Wang","doi":"10.1038/s41540-025-00520-2","DOIUrl":"https://doi.org/10.1038/s41540-025-00520-2","url":null,"abstract":"The living system follows the principles of physics, yet distinctive features, such as adaptability, differentiate it from conventional systems. The cognitive functions of decision-making (DM) and working memory (WM) are crucial for animal adaptation, but the underlying mechanisms are still unclear. To explore the mechanism underlying DM and WM functions, here we applied a general non-equilibrium landscape and flux approach to a biophysically based model that can perform decision-making and working memory functions. Our findings reveal that DM accuracy improved with stronger resting states in the circuit architecture with selective inhibition. However, the robustness of working memory against distractors was weakened. To address this, an additional non-selective input during the delay period of decision-making tasks was proposed as a mechanism to gate distractors with minimal increase in thermodynamic cost. This temporal gating mechanism, combined with the selective-inhibition circuit architecture, supports a dynamical modulation that emphasizes the robustness or flexibility to incoming stimuli in working memory tasks according to the cognitive task demands. Our approach offers a quantitative framework to uncover mechanisms underlying cognitive functions grounded in non-equilibrium physics.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"41"},"PeriodicalIF":3.5,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12059158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144037551","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

Biochemical implementation of acceleration sensing and PIDA control. 生化实现加速度传感和PIDA控制。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-26 DOI: 10.1038/s41540-025-00514-0

Emmanouil Alexis, Sebastián Espinel-Ríos, Ioannis G Kevrekidis, José L Avalos

引用次数: 0

The Virtual Parkinsonian patient. 虚拟帕金森病人。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-26 DOI: 10.1038/s41540-025-00516-y

Marianna Angiolelli, Damien Depannemaecker, Hasnae Agouram, Jean Régis, Romain Carron, Marmaduke Woodman, Letizia Chiodo, Paul Triebkorn, Abolfazl Ziaeemehr, Meysam Hashemi, Alexandre Eusebio, Viktor Jirsa, Pierpaolo Sorrentino

{"title":"The Virtual Parkinsonian patient.","authors":"Marianna Angiolelli, Damien Depannemaecker, Hasnae Agouram, Jean Régis, Romain Carron, Marmaduke Woodman, Letizia Chiodo, Paul Triebkorn, Abolfazl Ziaeemehr, Meysam Hashemi, Alexandre Eusebio, Viktor Jirsa, Pierpaolo Sorrentino","doi":"10.1038/s41540-025-00516-y","DOIUrl":"https://doi.org/10.1038/s41540-025-00516-y","url":null,"abstract":"This study investigates the influence of the pharmacological nigrostriatal dopaminergic stimulation on the entire brain by analyzing EEG and deep electrodes, placed near the subthalamic nuclei, from 10 Parkinsonian patients before (OFF) and after (ON) L-Dopa administration. We characterize large-scale brain dynamics as the spatio-temporal spreading of aperiodic bursts. We then simulate the effects of L-Dopa utilizing a novel neural-mass model that includes the local dopamine concentration. Whole-brain dynamics are simulated for different dopaminergic tones, generating predictions for the expected dynamics, to be compared with empirical EEG and deep electrode data. To this end, we invert the model and infer the most likely dopaminergic tone from empirical data, correctly identifying a higher Dopaminergic tone in the ON-state, and a lower dopaminergic tone in the OFF-state, for each patient. In conclusion, we successfully infer the dopaminergic tone by integrating anatomical and functional knowledge into physiological predictions, using solid ground truth to validate our findings.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"40"},"PeriodicalIF":3.5,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12033322/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144029743","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 multidisciplinary approach towards modeling of a virtual human lung. 多学科方法对虚拟人肺建模。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-18 DOI: 10.1038/s41540-025-00517-x

Timothy Lam, Henry T Quach, Lauren Hall, Maria Abou Chakra, Amy P Wong

引用次数: 0

Exploring the role of EMT in ovarian cancer progression using a multiscale mathematical model. 利用多尺度数学模型探讨EMT在卵巢癌进展中的作用。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-17 DOI: 10.1038/s41540-025-00508-y

Samuel Oliver, Michael Williams, Mohit Kumar Jolly, Deyarina Gonzalez, Gibin Powathil

{"title":"Exploring the role of EMT in ovarian cancer progression using a multiscale mathematical model.","authors":"Samuel Oliver, Michael Williams, Mohit Kumar Jolly, Deyarina Gonzalez, Gibin Powathil","doi":"10.1038/s41540-025-00508-y","DOIUrl":"https://doi.org/10.1038/s41540-025-00508-y","url":null,"abstract":"Epithelial-to-mesenchymal transition (EMT) plays a key role in the progression of cancer tumours, significantly reducing the success of treatment. EMT occurs when a cell undergoes phenotypical changes, resulting in enhanced drug resistance, higher cell plasticity, and increased metastatic abilities. Here, we employ a 3D agent-based multiscale modelling framework using PhysiCell to explore the role of EMT over time in two cell lines, OVCAR-3 and SKOV-3. This approach allows us to investigate the spatiotemporal progression of ovarian cancer and the impacts of the conditions in the microenvironment. OVCAR-3 and SKOV-3 cell lines possess highly contrasting tumour layouts, allowing a wide range of different tumour dynamics and morphologies to be tested and studied. Along with performing sensitivity analysis on the model, simulation results capture the biological observations and trends seen in tumour growth and development, thus helping to obtain further insights into OVCAR-3 and SKOV-3 cell line dynamics.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"36"},"PeriodicalIF":3.5,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12006308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144023723","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