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This work addresses the limited evidence connecting glycosphingolipid metabolism with pancreatic cancer by analyzing single-cell sequencing data and quantifying single-cell metabolism using the scMetabolism pipeline. A prognostic epithelial glycosphingolipid gene signature predicts survival, immune response, mutation patterns, and chemotherapy reaction in pancreatic adenocarcinoma cohorts, supporting stratification by risk.",{"@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/single-cell-rna-sequencing-analysis-reveals-metabolic-changes-in-epithelial-glycosphingolipids-and-establishes-a-prognostic-risk-model-for-pancreatic-cancer-article/330831/",{"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/single-cell-rna-sequencing-analysis-reveals-metabolic-changes-in-epithelial-glycosphingolipids-and-establishes-a-prognostic-risk-model-for-pancreatic-cancer-article/330831.png","ImageObject",300,407,{"name":92,"@type":93},"Violet","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-23","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main objective of this study?","Question",{"text":112,"@type":113},"To clarify how epithelial glycosphingolipid metabolism relates to pancreatic cancer and to develop a prognostic risk model based on a gene signature.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the metabolic analysis performed?",{"text":117,"@type":113},"The study used a single-cell sequencing dataset, applied the scMetabolism computational pipeline to quantify single-cell metabolism, and derived a prognostic gene signature from differential expressed genes.",{"name":119,"@type":110,"acceptedAnswer":120},"What does the prognostic model indicate for patient outcomes?",{"text":121,"@type":113},"Patients are stratified into high- and low-risk groups by median risk score, and the high-risk group shows worse survival across multiple cohorts, along with distinct mutation and immune characteristics.","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},330831,1790177933,{"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":29,"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":36,"preview_page_count":4},4398048950312,"https://ap-avatar.wpscdn.com/avatar/400002538284de19e3c?_k=1778320343897328908","diagnostics  \nArticle  \nSingle-Cell RNA Sequencing Analysis Reveals Metabolic Changes in Epithelial Glycosphingolipids and Establishes a Prognostic Risk Model for Pancreatic Cancer  \nQinwen Ba, Xiong Wang , Hui Hu  and Yanjun Lu *  \nCitation: Ba, Q.; Wang, X.; Hu, H.; Lu, Y. Single-Cell RNA Sequencing Analysis Reveals Metabolic Changes in Epithelial Glycosphingolipids and Establishes a Prognostic Risk Model for Pancreatic Cancer. Diagnostics 2024, 14, 1094. [https://doi.org/](https://doi.org/)[ ](https://doi.org/)[10.3390/diagnostics14111094](10.3390/diagnostics14111094)  \nReceived: 15 April 2024  \nRevised: 17 May 2024  \nAccepted: 21 May 2024  \nPublished: 24 May 2024  \nCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \nDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China  \n* [Correspondence: yanjunlu@tjh.tjmu.edu.cn](Correspondence: yanjunlu@tjh.tjmu.edu.cn); Tel.: +86-027-83665470  \nAbstract: Objective: Metabolic reprogramming serves as a distinctive feature of cancer, impacting proliferation and metastasis, with aberrant glycosphingolipid expression playing a crucial role in malignancy. Nevertheless, limited research has investigated the connection between glycosphingolipid metabolism and pancreatic cancer. Methods: This study utilized a single-cell sequencing dataset to analyze the cell composition in pancreatic cancer tissues and quantified single-cell metabolism using a newly developed computational pipeline called scMetabolism. A gene signature developed from the differential expressed genes (DEGs), related to epithelial cell glycosphingolipid metabolism, was established to forecast patient survival, immune response, mutation status, and reaction to chemotherapy with pancreatic adenocarcinoma (PAAD) . Results: The single-cell sequencing analysis revealed a significant increase in epithelial cell proportions in PAAD, with high glycosphingolipid metabolism occurring in the cancerous tissue. A six-gene signature prognostic model based on abnormal epithelial glycosphingolipid metabolism was created and confirmed using publicly available databases. Patients with PAAD were divided into high-and low-risk categories according to the median risk score, with those in the high-risk group demonstrating a more unfavorable survival outcome in all three cohorts, with higher rates of gene mutations (e.g., KRAS, CDKN2A), increased levels of immunosuppressive cells (macrophages, Th2 cells, regulatory T cells), and heightened sensitivity to Acetalax and Selumetinlb. Conclusions: Abnormal metabolism of glycosphingolipids in epithelial cells may promote the development of PAAD. A model utilizing a gene signature associated with epithelial glycosphingolipids metabolism has been established, serving as a valuable indicator for the prognostic stratification of patients with PAAD.  \nKeywords: pancreatic cancer; glycosphingolipids; risk model; single-cell RNA sequencing  \n1. Introduction  \nPancreatic cancer is considered one of the most lethal types of cancer globally, showing a five-year survival rate of under 5% for all stages [1] . Chemotherapy remains the primary treatment for pancreatic cancer patients, but only a minority benefit from it as most develop rapid and common chemoresistance, leading to a poor prognosis [2] . Therefore, developing reliable prognostic biomarkers for patient stratification and treatment is crucial.  \nRecent evidence highlights that abnormal metabolism in cancer cells is not just a hallmark but also a root cause of tumors [3] . Malignant cells alter metabolic pathways to support their survival, uncontrolled growth, and divis","cbCaiqlB5c2OjDKN","https://ap.wps.com/l/cbCaiqlB5c2OjDKN","pdf",8201957,16,"English","# Abstract\n# Introduction\n## Background and clinical need\n## Metabolism in pancreatic cancer and therapeutic relevance\n## Role of single-cell RNA sequencing","[{\"question\":\"What is the main objective of this study?\",\"answer\":\"To clarify how epithelial glycosphingolipid metabolism relates to pancreatic cancer and to develop a prognostic risk model based on a gene signature.\"},{\"question\":\"How was the metabolic analysis performed?\",\"answer\":\"The study used a single-cell sequencing dataset, applied the scMetabolism computational pipeline to quantify single-cell metabolism, and derived a prognostic gene signature from differential expressed genes.\"},{\"question\":\"What does the prognostic model indicate for patient outcomes?\",\"answer\":\"Patients are stratified into high- and low-risk groups by median risk score, and the high-risk group shows worse survival across multiple cohorts, along with distinct mutation and immune characteristics.\"}]","Single-Cell RNA Sequencing Analysis Reveals Metabolic Changes in Epithelial Glycosphingolipids and Establishes a Prognostic Risk Model for Pancreatic Cancer - Article | PDF",1789990368]