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Metabolic stratification of human breast tumors reveal subtypes of clinical and therapeutic relevance

ISCIENCE 2023年第10期26卷 108059页

作者： Iqbal, Mohammad A. Siddiqui, Shumaila Smith, Kirk Singh, Prithvi Kumar, Bhupender Chouaib, Salem Chandrasekaran, Sriram Gulf Med Univ Thumbay Res Inst Precis Med Ajman U Arab Emirates Gulf Med Univ Coll Med Ajman U Arab Emirates CSIR Cent Drug Res Inst Lucknow Uttar Pradesh India Univ Michigan Dept Biomed Engn Ann Arbor MI 48109 USA Jamia Millia Islamia Ctr Interdisciplinary Res Basic Sci New Delhi India Univ Delhi Swami Shraddhanand Coll Dept Microbiol New Delhi India Univ Paris Saclay Fac Med INSERM UMR 1186Gustave RoussyEPHE Villejuif France Univ Michigan Program Chem Biol Ann Arbor MI 48109 USA Univ Michigan Rogel Canc Ctr Med Sch Ann Arbor MI 48109 USA

Extensive metabolic heterogeneity in breast cancers has limited the deployment of metabolic therapies. To enable patient stratification, we studied the metabolic landscape in breast cancers (similar to 3000 patients combined) and identified three subtypes with increasing degrees of metabolic deregulation. Subtype M1 was found to be dependent on bile-acid biosynthesis, whereas M2 showed reliance on methionine pathway, and M3 engaged fatty-acid, nucleotide, and glucose metabolism. The extent of metabolic alterations correlated strongly with tumor aggressiveness and patient outcome. This pattern was reproducible in independent datasets and using in vivo tumor metabolite data. Using machine-learning, we identified robust and generalizable signatures of metabolic subtypes in tumors and cell lines. Experimental inhibition of metabolic pathways in cell lines representing metabolic subtypes revealed subtype-specific sensitivity, therapeutically relevant drugs, and promising combination therapies. Taken together, metabolic stratification of breast cancers can thus aid in predicting patient outcome and designing precision therapies.

关键词： Medical informatics computational bioinformatics cancer

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FusionAI: Predicting fusion breakpoint from DNA sequence with deep learning

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ISCIENCE 2021年第10期24卷 103164页

作者： Kim, Pora Tan, Hua Liu, Jiajia Yang, Mengyuan Zhou, Xiaobo Univ Texas Hlth Sci Ctr Houston Sch Biomed Informat Houston TX 77030 USA Univ Texas Hlth Sci Ctr Houston McGovern Med Sch Houston TX 77030 USA Univ Texas Hlth Sci Ctr Houston Sch Dent Houston TX 77030 USA Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China Tongji Univ Sch Life Sci & Technol Shanghai 200092 Peoples R China

Identifying the molecular mechanisms related to genomic breakage is an important goal of cancer mechanism studies. Among diverse locations of structural variants, fusion genes, which have the breakpoints in the gene bodies and are typically identified from the split reads of RNA-seq data, can provide a highlighted structural variant resource for studying the genomic breakages with expression and potential pathogenic impacts. In this study, we developed FusionAI, which utilizes deep learning to predict gene fusion breakpoints based on DNA sequence and let us identify fusion breakage code and genomic context. FusionAI leverages the known fusion breakpoints to provide a prediction model of the fusion genes from the primary genomic sequences via deep learning, thereby helping researchers a more accurate selection of fusion genes and better understand genomic breakage.

关键词： genetics genomics computational bioinformatics artificial intelligence applications

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A physiologically based model of bile acid metabolism in mice

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ISCIENCE 2023年第10期26卷 107922页

作者： Kister, Bastian Viehof, Alina Rolle-Kampczyk, Ulrike Schwentker, Annika Treichel, Nicole Simone Jennings, Susan A. V. Wirtz, Theresa H. Blank, Lars M. Hornef, Mathias W. Bergen, Martin von Clavel, Thomas Kuepfer, Lars Univ Hosp RWTH Aachen Inst Syst Med Focus Organ Interact Aachen Germany Rhein Westfal TH Aachen Inst Appl Microbiol IAMB Aachen Biol & Biotechnol ABBt Aachen Germany Univ Hosp RWTH Aachen Inst Med Microbiol Funct Microbiome Res Grp Aachen Germany UFZ Helmholtz Ctr Environm Res Dept Mol Syst Biol Leipzig Germany Univ Hosp RWTH Aachen Inst Med Microbiol Aachen Germany Univ Hosp RWTH Aachen Dept Med 3 Aachen Germany German Ctr Integrat Biodivers Res iDiv Halle Jena Leipzig Leipzig Germany Univ Leipzig Inst Biochem Fac Life Sci Leipzig Germany

Bile acid (BA) metabolism is a complex system that includes a wide variety of primary and secondary, as well as conjugated and unconjugated BAs that undergo continuous enterohepatic circulation (EHC). Alterations in both composition and dynamics of BAs have been associated with various diseases. However, a mechanistic understanding of the relationship between altered BA metabolism and related diseases is lacking. computational modeling may support functional analyses of the physiological processes involved in the EHC of BAs along the gut-liver axis. In this study, we developed a physiologically based model of murine BA metabolism describing synthesis, hepatic and microbial transformations, systemic distribution, excretion, and EHC of BAs at the whole-body level. For model development, BA metabolism of specific pathogen-free (SPF) mice was characterized in vivo by measuring BA levels and composition in various organs, expression of transporters along the gut, and cecal microbiota composition. We found significantly different BA levels between male and female mice that could only be explained by adjusted expression of the hepatic enzymes and transporters in the model. Of note, this finding was in agreement with experimental observations. The model for SPF mice could also describe equivalent experimental data in germ-free mice by specifically switching off microbial activity in the intestine. The here presented model can therefore facilitate and guide functional analyses of BA metabolism in mice, e.g., the effect of pathophysiological alterations on BA metabolism and translation of results from mouse studies to a clinically relevant context through cross-species extrapolation.

关键词： Physiology Microbiome computational bioinformatics

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Computerized tertiary lymphoid structures density on H&E-images is a prognostic biomarker in resectable lung adenocarcinoma

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ISCIENCE 2023年第9期26卷 107635页

作者： Wang, Yumeng Lin, Huan Yao, Ningning Chen, Xiaobo Qiu, Bingjiang Cui, Yanfen Liu, Yu Li, Bingbing Han, Chu Li, Zhenhui Zhao, Wei Wang, Zimin Pan, Xipeng Lu, Cheng Liu, Jun Liu, Zhenbing Liu, Zaiyi Guilin Univ Elect Technol Sch Comp Sci & Informat Secur Guilin 541004 Peoples R China Southern Med Univ Guangdong Prov Peoples Hosp Guangdong Acad Med Sci Dept Radiol Guangzhou 510080 Peoples R China Guangdong Prov Key Lab Artificial Intelligence Med Guangzhou 510080 Peoples R China Shanxi Med Univ Shanxi Prov Canc Hosp Shanxi Hosp Canc HospDept RadiobiolChinese Acad Med Sci Taiyuan 030013 Peoples R China Kunming Med Univ Affiliated Hosp 3 Yunnan Canc Hosp Yunnan Canc CtrDept Thoracic Surg 1 Kunming 650118 Peoples R China Guangdong Cardiovasc Inst Guangzhou 510080 Peoples R China South China Univ Technol Sch Med Guangzhou 510006 Peoples R China Ganzhou Municipal Hosp Ganzhou Hosp Guangdong Prov Peoples Hosp Dept Pathol 49 Dagong Rd Ganzhou 341000 Peoples R China Southern Med Univ Guangdong Prov Peoples Hosp Med Res Inst Guangdong Acad Med Sci Guangzhou 510080 Peoples R China Kunming Med Univ Affiliated Hosp 3 Yunnan Canc Hosp Yunnan Canc CtrDept Radiol Kunming 650118 Peoples R China Cent South Univ Xiangya Hosp 2 Dept Radiol Changsha 410011 Peoples R China

The increased amount of tertiary lymphoid structures (TLSs) is associated with a favorable prognosis in patients with lung adenocarcinoma (LUAD). However, evaluating TLSs manually is an experience-dependent and time-consuming process, which limits its clinical application. In this multi-center study, we developed an automated computational workflow for quantifying the TLS density in the tumor region of routine hematoxylin and eosin (H&E)-stained whole-slide images (WSIs). The association between the computerized TLS density and disease-free survival (DFS) was further explored in 802 patients with resectable LUAD of three cohorts. Additionally, a Cox proportional hazard regression model, incorporating clinicopathological variables and the TLS density, was established to assess its prognostic ability. The computerized TLS density was an independent prognostic biomarker in patients with resectable LUAD. The integration of the TLS density with clinicopathological variables could support individualized clinical decision-making by improving prognostic stratification.

关键词： Health informatics computational bioinformatics cancer

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FishGET: A fish gene expression and transcriptome database with improved accuracy and visualization

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ISCIENCE 2023年第4期26卷 106539页

作者： Guo, Cheng Duan, You Ye, Weidong Zhang, Wanting Cheng, Yingyin Shi, Mijuan Xia, Xiao-Qin Chinese Acad Sci Inst Hydrobiol Wuhan 430072 Peoples R China Sichuan Univ West China Univ Hosp 2 West China Inst Women & Childrens Hlth Joint Lab Lung Dev & Related Dis Chengdu Peoples R China Fudan Univ Sch Life Sci Chengdu Peoples R China Univ Chinese Acad Sci Coll Adv Agr Sci Beijing Peoples R China Chinese Acad Sci Innovat Acad Seed Design Beijing 100101 Peoples R China Sichuan Univ Key Lab Birth Defects & Related Dis Women & Childr Minist Educ Chengdu 610041 Peoples R China Sichuan Univ NHC Key Lab Chronobiol Chengdu Peoples R China

With the rapid expansion of transcriptome studies in many fishes, a great number of RNA-seq data have been published, allowing for a more systematic understanding of the general profiles and details of gene expression in fish. FishGET is dedicated to gathering and curating fish RNA-seq data to discover more new RNAs, including mRNA and lncRNA, thereby getting a more complete reference transcriptome and providing more comprehensive and accurate transcriptome annotations. We obtained a total of 1362 RNA-seq paired-end data of 8 fishes from 97 different studies, and then we performed transcript assembly, meta-assembly, weighted gene co-expression network analysis (WGCNA), functional annotations, neighbor location annotation, lncRNA type annotation, homology annotation. To promote research into fish genes at the transcriptional level, we developed a user-friendly web interface that allows users to view all information and makes use of multiple types of dynamic interactive visualization services.

关键词： computational bioinformatics Ichthyology Transcriptomics

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Topologically associating domain underlies tissue specific expression of long intergenic non-coding RNAs

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ISCIENCE 2023年第5期26卷 106640页

作者： Hamba, Yu Kamatani, Takashi Miya, Fuyuki Boroevich, Keith A. Tsunoda, Tatsuhiko Univ Tokyo Grad Sch Sci Dept Biol Sci Lab Med Sci Math Tokyo 1130033 Japan RIKEN Lab Med Sci Math Ctr Integrat Med Sci Yokohama 2300045 Japan Tokyo Med & Dent Univ M&D Data Sci Ctr Dept AI Technol Dev Tokyo 1010062 Japan Tokyo Med & Dent Univ Hosp Div Precis Canc Med Tokyo 1138519 Japan Keio Univ Dept Med Div Pulm Med Sch Med Tokyo 1608582 Japan Keio Univ Ctr Med Genet Sch Med Tokyo 1608582 Japan Univ Tokyo Grad Sch Frontier Sci Dept Computat Biol & Med Sci Chiba 2778562 Japan

Accumulating evidence indicates that long intergenic non-coding RNAs (lincR-NAs) show more tissue-specific expression patterns than protein-coding genes (PCGs). However, although lincRNAs are subject to canonical transcriptional regulation like PCGs, the molecular basis for the specificity of their expression patterns remains unclear. Here, using expression data and coordinates of topo-logically associating domains (TADs) in human tissues, we show that lincRNA loci are significantly enriched in the more internal region of TADs compared to PCGs and that lincRNAs within TADs have higher tissue specificity than those outside TADs. Based on these, we propose an analytical framework to interpret transcriptional status using lincRNA as an indicator. We applied it to hypertrophic cardiomyopathy data and found disease-specific transcriptional regulation: ectopic expression of keratin at the TAD level and derepression of myocyte dif-ferentiation-related genes by E2F1 with down-regulation of LINC00881. Our re-sults provide understanding of the function and regulation of lincRNAs according to genomic structure.

关键词： computational bioinformatics Expression study Genomic analysis

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Aging affects circadian clock and metabolism and modulates timing of medication

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ISCIENCE 2021年第4期24卷 102245页

作者： Sadria, Mehrshad Layton, Anita T. Univ Waterloo Dept Appl Math Waterloo ON Canada Univ Waterloo Cheriton Sch Comp Sci Dept Biol Waterloo ON Canada Univ Waterloo Sch Pharm Waterloo ON Canada

Aging is associated with impairments in the circadian rhythms, and with energy deregulation that affects multiple metabolic pathways. The goal of this study is to unravel the complex interactions among aging, metabolism, and the circadian clock. We seek to identify key factors that inform the liver circadian clock of cellular energy status and to reveal the mechanisms by which variations in food intake may disrupt the clock. To address these questions, we develop a comprehensive mathematical model that represents the circadian pathway in the mouse liver, together with the insulin/IGF-1 pathway, mTORC1, AMPK, NAD+, and the NAD+ -consuming factor SIRT1. The model is age-specific and can simulate the liver of a young mouse or an aged mouse. Simulation results suggest that the reduced NAD+ and SIRT1 bioavailability may explain the shortened circadian period in aged rodents. Importantly, the model identifies the dosing schedules for maximizing the efficacy of anti-aging medications.

关键词： Physiology computational bioinformatics Complex System Biology

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TranSNPs: A class of functional SNPs affecting mRNA translation potential revealed by fraction-based allelic imbalance

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ISCIENCE 2021年第12期24卷 103531页

作者： Valentini, Samuel Marchioretti, Caterina Bisio, Alessandra Rossi, Annalisa Zaccara, Sara Romanel, Alessandro Inga, Alberto Univ Trento Dept Cellular Computat & Integrat Biol CIBIO I-38123 Trento Italy Univ Padua Dept Biomed Sci DBS I-35131 Padua Italy Cornell Univ Weill Med Coll New York NY 10065 USA

Few studies have explored the association between SNPs and alterations in mRNA translation potential. We developed an approach to identify SNPs that can mark allele-specific protein expression levels and could represent sources of inter-individual variation in disease risk. Using MCF7 cells under different treatments, we performed polysomal profiling followed by RNA sequencing of total or polysome-associated mRNA fractions and designed a computational approach to identify SNPs showing a significant change in the allelic balance between total and polysomal mRNA fractions. We identified 147 SNPs, 39 of which located in UTRs. Allele-specific differences at the translation level were confirmed in transfected MCF7 cells by reporter assays. Exploiting breast cancer data from TCGA we identified UTR SNPs demonstrating distinct prognosis features and altering binding sites of RNA-binding proteins. Our approach produced a catalog of tranSNPs, a class of functional SNPs associated with allele-specific translation and potentially endowed with prognostic value for disease risk.

关键词： Molecular mechanism of gene regulation computational bioinformatics Transcriptomics

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Quantifying the impact of physical activity on future glucose trends using machine learning

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ISCIENCE 2022年第3期25卷 103888页

作者： Tyler, Nichole S. Mosquera-Lopez, Clara Young, Gavin M. El Youssef, Joseph Castle, Jessica R. Jacobs, Peter G. Oregon Hlth & Sci Univ Artificial Intelligence Med Syst AIMS Lab Dept Biomed Engn Portland OR 97232 USA Oregon Hlth & Sci Univ Harold Schnitzer Diabet Hlth Ctr Div Endocrinol Portland OR 97239 USA

Prevention of hypoglycemia (glucose <70 mg/dL) during aerobic exercise is a major challenge in type 1 diabetes. Providing predictions of glycemic changes during and following exercise can help people with type 1 diabetes avoid hypoglycemia. A unique dataset representing 320 days and 50,000 + time points of glycemic measurements was collected in adults with type 1 diabetes who participated in a 4 arm crossover study evaluating insulin-pump therapies, whereby each participant performed eight identically designed in-clinic exercise studies. We demonstrate that even under highly controlled conditions, there is considerable intra-participant and inter-participant variability in glucose outcomes during and following exercise. Participants with higher aerobic fitness exhibited significantly lower minimum glucose and steeper glucose declines during exercise. Adaptive, personalized machine learning (ML) algorithms were designed to predict exercise-related glucose changes. These algorithms achieved high accuracy in predicting the minimum glucose and hypoglycemia during and following exercise sessions, for all fitness levels.

关键词： Physiology Biocomputational method computational bioinformatics

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Activation of gene expression by detergent-like protein domains

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ISCIENCE 2021年第9期24卷 103017页

作者： Broyles, Bradley K. Gutierrez, Andrew T. Maris, Theodore P. Coil, Daniel A. Wagner, Thomas M. Wang, Xiao Kihara, Daisuke Class, Caleb A. Erkine, Alexandre M. Butler Univ Coll Pharm & Hlth Sci Indianapolis IN 46208 USA Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

The mechanisms by which transcriptional activation domains ( tADs) initiate eukaryotic gene expression have been an enigma for decades because most tADs lack specificity in sequence, structure, and interactions with targets. Machine learning analysis of data sets of tAD sequences generated in vivo elucidated several functionality rules: the functional tAD sequences should (i) be devoid of or depleted with basic amino acid residues, (ii) be enriched with aromatic and acidic residues, (iii) be with aromatic residues localized mostly near the terminus of the sequence, and acidic residues localized more internally within a span of 20-30 amino acids, (iv) be with both aromatic and acidic residues preferably spread out in the sequence and not clustered, and (v) not be separated by occasional basic residues. These and other more subtle rules are not absolute, reflecting absence of a tAD consensus sequence, enormous variability, and consistent with surfactant-like tAD biochemical properties. The findings are compatible with the paradigm-shifting nucleosome detergent mechanismof gene expression activation, contributing to the development of the liquid-liquid phase separation model and the biochemistry of near-stochastic functional allosteric interactions.

关键词： Biological sciences Molecular biology bioinformatics computational bioinformatics gene activation transcriptional regulation IDR machine learning neural network chromatin nucleosome

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