[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-333387-105":59,"doc-detail-333387-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","personalized-analysis-of-human-cancer-multi-omics-for-precision-oncology","Personalized analysis of human cancer multi-omics for precision oncology","","Multi-omics technologies that integrate genomics, proteomics, and transcriptomics provide deep insights into cancer biology. Differential analysis is a core computational task that compares molecular differences between cancerous and normal tissues, yet population-based methods often ignore heterogeneity among individual tumors. This limitation motivates tailored differential analysis algorithms that target patient-specific variations and enable a more refined understanding of disease mechanisms. A review summarizes principles of individualized techniques, evaluates their performance on cancer multi-omics data, and discusses potential clinical applications.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/personalized-analysis-of-human-cancer-multi-omics-for-precision-oncology/333387/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/personalized-analysis-of-human-cancer-multi-omics-for-precision-oncology/333387.png","ImageObject",300,407,{"name":92,"@type":93},"Aurora","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",14,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Why do population-level multi-omics differential analysis methods fall short for precision oncology?","Question",{"text":113,"@type":114},"They tend to overlook heterogeneity unique to individual tumors, which can miss critical patient-specific molecular traits needed for precision medicine.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What is the key idea behind individualized differential analysis methods?",{"text":118,"@type":114},"They focus on disruptions in relative expression orderings (REOs) of gene pairs, which are assumed stable in normal tissue but reversed in diseased samples.",{"name":120,"@type":111,"acceptedAnswer":121},"How does individualized analysis help identify biologically relevant differences for patients?",{"text":122,"@type":114},"By assessing reversal patterns in individual diseased samples, the approach pinpoints differentially expressed genes and other dysregulated molecular features that can support personalized therapeutic strategies.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},333387,1790188938,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":39,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":46,"preview_page_count":4},4810365810221,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Computational and Structural Biotechnology Journal 23 (2024) 2049–2056  \nContents lists available at ScienceDirect  \nComputational and Structural Biotechnology Journal  \njournal [homepage:](homepage: www.elsevier.com/locate/csbj)[ www.elsevier.com/locate/csbj](homepage: www.elsevier.com/locate/csbj)  \n| Personalized analysis of human cancer multi-omics for precision oncology   Jiaao Li a, c, 1, Jingyi Tian a, c, 1, Yachen Liu b, c, Zan Liu a, b, c, Mengsha Tong a, b, c, *\u003Cbr>a State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian 361102, China b National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian 361102, China\u003Cbr>c School of Informatics, Xiamen University, Xiamen 316000, China |  |  |\n| --- | --- | --- |\n| A R T I C L E I N F O |  | A B S T R A C T |\n| Keywords:\u003Cbr>Precision oncology\u003Cbr>Multi-omics\u003Cbr>Individualized analysis |  | Multi-omics technologies, encompassing genomics, proteomics, and transcriptomics, provide profound insights into cancer biology. A fundamental computational approach for analyzing multi-omics data is differential analysis, which identifies molecular distinctions between cancerous and normal tissues. Traditional methods, however, often fail to address the distinct heterogeneity of individual tumors, thereby neglecting crucial patientspecific molecular traits. This shortcoming underscores the necessity for tailored differential analysis algorithms, which focus on particular patient variations. Such approaches offer a more nuanced understanding of cancer biology and are instrumental in pinpointing personalized therapeutic strategies. In this review, we summarize the principles of current individualized techniques. We also review their efficacy in analyzing cancer multi-omics data and discuss their potential applications in clinical practice. |\n\n1. Introduction  \nThe investigation of human cancer using multi-omics methodologies has emerged as a pivotal area of research, seeking to elucidate cancer mechanisms by integrating diverse biological dimensions. This approach merges data from genomics, epigenomics, transcriptomics, and proteomics to forge a comprehensive molecular portrait of cancer [1]. Genomic analysis focuses on DNA alterations, including mutations and copy number variations, primarily utilizing whole-genome sequencing [2]. Epigenomic research delves into DNA methylation and histone modifications, shedding light on gene regulation [3]. Transcriptomics examines RNA transcripts to reveal gene expression patterns, predominantly through RNA sequencing [4]. Proteomics, employing methods such as mass spectrometry, examines the complete protein set in a sample, thus reflecting the actual functional molecules [5].  \nDifferential analysis is one of the most commonly performed tasks for multi-omics data. Currently, most of these methods were designed for the population-level, offering insights into variances between distinct groups such as tumor and normal samples. The T-test [6] is a statistical method utilized for hypothesis testing to detect differences between continuous data that are approximately normally distributed and have  \nequal variances. DESeq2 [7] identifies differentially expressed genes using a negative binomial distribution model, necessitating biological replicates in the experimental samples to ensure result accuracy. Similarly, edgeR [8] also applies a negative binomial distribution model to identify differentially expressed genes. It accounts for variance in gene expression levels to calculate normalized expression values for each gene across various sample groups.  \nHowever, conventional population-level analysis methods often overlook the heterogeneity unique to individual tumors, thereby neglecting patient-specific molecular traits. Therefore, several studies have shifted their focus towards the heterogeneity and individual differences among patien","cbCaic8A77mOY4ry","https://ap.wps.com/l/cbCaic8A77mOY4ry","pdf",2283448,"English","# Introduction\n## Multi-omics integration in cancer research\n## Population-level differential analysis methods\n## Motivation for individualized differential analysis\n## Principles based on relative expression orderings (REOs)\n## Patient-specific identification of dysregulated features","[{\"question\":\"Why do population-level multi-omics differential analysis methods fall short for precision oncology?\",\"answer\":\"They tend to overlook heterogeneity unique to individual tumors, which can miss critical patient-specific molecular traits needed for precision medicine.\"},{\"question\":\"What is the key idea behind individualized differential analysis methods?\",\"answer\":\"They focus on disruptions in relative expression orderings (REOs) of gene pairs, which are assumed stable in normal tissue but reversed in diseased samples.\"},{\"question\":\"How does individualized analysis help identify biologically relevant differences for patients?\",\"answer\":\"By assessing reversal patterns in individual diseased samples, the approach pinpoints differentially expressed genes and other dysregulated molecular features that can support personalized therapeutic strategies.\"}]","Personalized analysis of human cancer multi-omics for precision oncology | PDF",1790002211]