[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-331257-105":59,"doc-detail-331257-en":130},{"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":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","prognostic-genome-and-transcriptome-signatures-in-colorectal-cancers-read-online-free","Prognostic genome and transcriptome signatures in colorectal cancers - read online free","","Colorectal cancer arises from somatic genomic alterations that disrupt driver genes in core cancer pathways. This study integrates whole-genome and transcriptome analyses of 1,063 primary colorectal cancers from a population-based cohort with long-term follow-up to evaluate functional and prognostic effects of cancer-causing mutations. The work identifies early and late driver gene mutations, pathway co-mutation patterns, and multiple colorectal-cancer-specific mutational processes linked to survival, and defines five prognostic expression subtypes with distinct molecular features. Microsatellite-instable tumors split into two classes with differing hypoxia and immune/stromal infiltration, supporting individualized therapy planning.",{"@graph":69,"@context":122},[70,84,105],{"@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/prognostic-genome-and-transcriptome-signatures-in-colorectal-cancers-read-online-free/331257/",{"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/prognostic-genome-and-transcriptome-signatures-in-colorectal-cancers-read-online-free/331257.png","ImageObject",300,407,{"name":92,"@type":93},"Theodore","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-27","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What dataset and cohort were used to study colorectal cancer prognostic signatures?","Question",{"text":112,"@type":113},"Whole genomes and transcriptomes were analyzed for 1,063 primary colorectal cancers in a population-based cohort with long-term follow-up, using patient-matched tumor and control samples.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were driver gene mutations and their timing characterized?",{"text":117,"@type":113},"Across 96 mutated driver genes, the study observed two patterns of pathway co-mutations and used timing analyses to identify nine early and three late driver gene mutation events.",{"name":119,"@type":110,"acceptedAnswer":120},"What prognostic models emerged from gene expression and how did they relate to mutations?",{"text":121,"@type":113},"Gene expression classification produced five prognostic subtypes with distinct molecular features, which were in part explained by underlying genomic alterations. Prognostic mutations and expression subtypes may support individualized therapy approaches.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},331257,1790189387,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"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":145,"preview_page_count":4},7971461740886,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","Article  \n\n| Prognostic genome and transcriptome signatures in colorectal cancers |  |  |\n| --- | --- | --- |\n| [https://doi.org/10.1038/s41586-024-07769-3](https://doi.org/10.1038/s41586-024-07769-3)\u003Cbr>Received: 24 April 2023 Accepted: 1 July 2024 Published online: 7 August 2024 Open access\u003Cbr> Check for updates | Luís Nunes1,10,11, Fuqiang Li2,3,4,11, Meizhen Wu2,3,4,11, Tian Luo2,3,4,11, Klara Hammarström1, Emma Torell1, Ingrid Ljuslinder5, Artur Mezheyeuski1, Per-Henrik Edqvist1,\u003Cbr>Anna Löfgren-Burström6, Carl Zingmark6, Sofia Edin6, Chatarina Larsson1, Lucy Mathot1, Erik Osterman1, Emerik Osterlund1, Viktor Ljungström1, Inês Neves1, Nicole Yacoub1, Unnur Guðnadóttir1, Helgi Birgisson7, Malin Enblad7, Fredrik Ponten1, Richard Palmqvist6, Xun Xu2, Mathias Uhlén8,9, Kui Wu2,3,4,12✉, Bengt Glimelius1,12✉, Cong Lin2,3,4,12✉ &\u003Cbr>Tobias Sjöblom1,12✉\u003Cbr>Colorectal cancer is caused by a sequence of somatic genomic alterations affecting driver genes in core cancer pathways1. Here, to understand the functional and prognostic impact of cancer-causing somatic mutations, we analysed the whole genomes and transcriptomes of 1,063 primary colorectal cancers in a populationbased cohort with long-term follow-up. From the 96 mutated driver genes, 9 were not previously implicated in colorectal cancer and 24 had not been linked to any cancer. Two distinct patterns of pathway co-mutations were observed, timing analyses identified nine early and three late driver gene mutations, and several signatures of colorectal-cancer-specific mutational processes were identified. Mutations in WNT, EGFRandTGFβ pathway genes, the mitochondrial CYB gene and 3 regulatory elements along with 21 copy-number variations and the COSMIC SBS44 signature correlated with survival. Gene expression classification yielded five prognostic subtypes with distinct molecular features, in part explained by underlying genomic alterations. Microsatellite-instable tumours divided into two classes with different levels of hypoxia and infiltration of immune and stromal cells. To our knowledge, this study constitutes the largest integrated genome and transcriptome analysis of colorectal cancer, and interlinks mutations, gene expression and patient outcomes. The identification of prognostic mutations and expression subtypes can guide future efforts to individualize colorectal cancer therapy. |  |\n| Colorectal cancer (CRC) is the third most common and the second |  | understanding ofCRC pathogenesis, identify driver events and find |\n| deadliest tumour type in both sexes, with 1,900,000 new cases and |  | prognostic features, we analysed whole genomes along with tumour |\n| 900,000 deaths annually. About 20% of patients have metastatic dis- |  | transcriptomes in a large, population-based CRC cohort with clinical |\n| ease already at diagnosis, and another 20% will develop metastases later2. From exome3–7and whole-genome8–10sequencing, the mutational |  | outcomes. |\n| landscape of CRC is best characterized in coding regions, whereas non-coding regions remain understudied. Approximately 80–85% of |  | Mutational landscape |\n| CRCsareclassified as copy-number altered microsatellite stable (MSS), 10–16% as highly mutated with microsatellite instability (MSI) and 1–2% |  | We obtained high-quality whole-genome sequences (average 53-fold coverage) from patient-matched tumour and unaffected control sam- |\n| as ultramutated resulting from somatic POLE mutations4,11. The MSI status predicts response to checkpoint inhibitors12, whereas KRAS, |  | ples along with tumour transcriptome sequence (average 30 million paired reads; Supplementary Table 1) from 1,063 out of 1,126 CRC |\n| NRASand BRAF mutations predict poor response to EGFR-targeted |  | cases. Of the 1,063 CRCs, 943 were primary tumour surgical specimens |\n| therapies13. The WNT, EGFR–KRAS–BRAF, PIK3CA, TGFβ and p53 path- |  | and 120 were primary tumour biopsies. Control samples were taken |\n| ways are regulated by mutations inCRC1, a","cbCaimNNVWC3HnTK","https://ap.wps.com/l/cbCaimNNVWC3HnTK","pdf",8957552,32,"English","# Mutational landscape\n## Pathway co-mutation and timing analyses\n## Survival-associated signatures and copy-number variation\n## Prognostic gene-expression subtypes\n## Microsatellite instability tumor classes","[{\"question\":\"What dataset and cohort were used to study colorectal cancer prognostic signatures?\",\"answer\":\"Whole genomes and transcriptomes were analyzed for 1,063 primary colorectal cancers in a population-based cohort with long-term follow-up, using patient-matched tumor and control samples.\"},{\"question\":\"How were driver gene mutations and their timing characterized?\",\"answer\":\"Across 96 mutated driver genes, the study observed two patterns of pathway co-mutations and used timing analyses to identify nine early and three late driver gene mutation events.\"},{\"question\":\"What prognostic models emerged from gene expression and how did they relate to mutations?\",\"answer\":\"Gene expression classification produced five prognostic subtypes with distinct molecular features, which were in part explained by underlying genomic alterations. Prognostic mutations and expression subtypes may support individualized therapy approaches.\"}]","Prognostic genome and transcriptome signatures in colorectal cancers - read online free | PDF",1789992437,81]