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The review traces historical obstacles such as weak early-stage miRNA signature specificity, inconsistent biomarker panels, and cancer heterogeneity. It then highlights high-throughput profiling, bioinformatics, and machine-learning integration of multi-omics data to enhance diagnostic accuracy. Remaining challenges include the need for standardized protocols and clarifying the complex miRNA interplay in cancer biology.",{"@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/micrornas-circulating-biomarkers-for-the-early-detection-of-imperceptible-cancers-via-biosensor-and-machine-learning-advances/332199/",{"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/micrornas-circulating-biomarkers-for-the-early-detection-of-imperceptible-cancers-via-biosensor-and-machine-learning-advances/332199.png","ImageObject",300,407,{"name":92,"@type":93},"Maeve","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-07","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is early detection difficult for many cancers described in the review?","Question",{"text":112,"@type":113},"Early-stage tumors are often asymptomatic because of limited systemic effects and metastases. The review also notes a lack of specific and sensitive screening tests that follow standardized parameters, causing delayed accurate detection.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which cancer types are highlighted as having unique early-diagnosis challenges?",{"text":117,"@type":113},"The review specifically discusses pancreatic cancer, non-small cell lung cancer (NSCLC), liver cancer, and central nervous system (CNS) tumors. It links each to factors such as asymptomatic onset, vague symptoms, and limitations of common screening and diagnostic approaches.",{"name":119,"@type":110,"acceptedAnswer":120},"How do high-throughput and machine-learning advances support miRNA-based early detection?",{"text":121,"@type":113},"High-throughput technologies enable comprehensive detection and profiling of miRNA signatures related to early-stage cancers. The review also describes how bioinformatics and machine-learning can integrate multi-omics data to improve the accuracy and reliability of miRNA-based diagnostic assays.","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},332199,1790383776,{"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":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":39,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":46,"preview_page_count":4},5909877438554,"https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272","Oncogene [www.nature.com/onc](www.nature.com/onc)  \nREVIEW ARTICLE OPEN   \nMicroRNAs: circulating biomarkers for the early detection of imperceptible cancers via biosensor and machine-learning advances  \nGavin A. D. Metcalf1 ✉  \n© The Author(s) 2024  \n|  |  |  |\n| --- | --- | --- |\n|  | This review explores the topic of microRNAs (miRNAs) for improved early detection of imperceptible cancers, with potential to advance precision medicine and improve patient outcomes. Historical research exploring miRNA’s role in cancer detection collectively revealed initial hurdles in identifying specific miRNA signatures for early-stage and difficult-to-detect cancers. Early studies faced challenges in establishing robust biomarker panels and overcoming the heterogeneity of cancer types. Despite this, recent developments have supported the potential of miRNAs as sensitive and specific biomarkers for early cancer detection as well as having demonstrated remarkable potential as diagnostic tools for imperceptible cancers, such as those with elusive symptoms or challenging diagnostic criteria. This review discusses the advent of high-throughput technologies that have enabled comprehensive detection and profiling of unique miRNA signatures associated with early-stage cancers. Furthermore, advancements in bioinformatics and machine-learning techniques are considered, exploring the integration of multi-omics data which have potential to enhance both the accuracy and reliability of miRNA-based cancer detection assays. Finally, perspectives on the continuing development on technologies as well as discussion around challenges that remain, such as the need for |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n| standardised protocols and addressing the complex interplay of miRNAs in cancer biology are conferred. |  |  |\n|  | Oncogene (2024) 43:2135–2142; [https://doi.org/10.1038/s41388-024-03076-3](https://doi.org/10.1038/s41388-024-03076-3) |  |\n|  |  |  |\n\nCHALLENGES IN EARLY DETECTION OF DIFFICULT-TO-DETECT CANCERS  \nCurrent trajectories suggest that global cancer cases will reach over 35 million by 2050 [1] and that almost half of all cancer cases that were diagnosed in England in 2018 were at advanced stages (3 and 4) [2] . This highlights the urgency of early detection in order to attempt to reduce the burden this will inevitably cause on patients, their social support network, healthcare systems, as well as local and global economies.  \nHowever, despite this pressing need, early detection poses many challenges. The lack of systemic effects due to the small size of primary tumours, or metastases, in early stages of development often leads to the asymptomatic nature of disease progression. In addition, the reported lack of specific and sensitive screening tests that follow standardised testing parameters collectively contribute to delayed accurate detection.  \nCertain well-documented cancers present unique challenges in diagnosis, including pancreatic, non-small cell lung cancer (NSCLC), liver, and central nervous system (CNS) tumours. All aforementioned cancers share the challenge of being asymptomatic in early stages of development, and often present with vague and non-specific symptoms as the disease advances [3–7] . The deep-seated retroperitoneal location of the pancreas frequently hinders early detection of cancer through common screening methods. In addition to this, there are no widely adopted reliable screening tests [8] . NSCLC has limited effective  \nscreening tools applicable to high-risk groups, high false positive rates in common imaging techniques along with invasive diagnostic biopsy procedures posing significant risks, especially in light of the recent pandemic [9, 10] . The early detection of Liver cancers is complicated by cirrhosis masking key diagnostic symptoms, imaging limitations when considering small lesions due to poor arterial phase hyperenhancement of contrast ag","cbCaid4xrIQeFDWN","https://ap.wps.com/l/cbCaid4xrIQeFDWN","pdf",754442,"English","# Challenges in early detection of difficult-to-detect cancers\n## Early detection urgency and key barriers\n## Cancer-specific diagnostic challenges\n# MicroRNAs (miRNAs)\n## Definition, length, and discovery\n## Mechanisms of extracellular survival and release","[{\"question\":\"Why is early detection difficult for many cancers described in the review?\",\"answer\":\"Early-stage tumors are often asymptomatic because of limited systemic effects and metastases. The review also notes a lack of specific and sensitive screening tests that follow standardized parameters, causing delayed accurate detection.\"},{\"question\":\"Which cancer types are highlighted as having unique early-diagnosis challenges?\",\"answer\":\"The review specifically discusses pancreatic cancer, non-small cell lung cancer (NSCLC), liver cancer, and central nervous system (CNS) tumors. It links each to factors such as asymptomatic onset, vague symptoms, and limitations of common screening and diagnostic approaches.\"},{\"question\":\"How do high-throughput and machine-learning advances support miRNA-based early detection?\",\"answer\":\"High-throughput technologies enable comprehensive detection and profiling of miRNA signatures related to early-stage cancers. The review also describes how bioinformatics and machine-learning can integrate multi-omics data to improve the accuracy and reliability of miRNA-based diagnostic assays.\"}]","MicroRNAs: circulating biomarkers for the early detection of imperceptible cancers via biosensor and machine-learning advances | PDF",1789997290]