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This study systematically examines age-dependent occurrence rates for 23 carcinoma types, characterizing their age-dependent distribution shapes, the determinants of peak occurrence ages, and gender differences. Using SEER data, the analysis identifies two ADOR distribution types: mostly unimodal and a subset bimodal. Modeling attributes the first type to stem-cell divisions and required bloodborne growth factors, while the second type includes viral infection for the first peak. Additional results link organ iron levels to sex disparities and implicate sex hormones as key determinants of onset age.",{"@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/elucidation-of-factors-affecting-the-age-dependent-cancer-occurrence-rates/329787/",{"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/elucidation-of-factors-affecting-the-age-dependent-cancer-occurrence-rates/329787.png","ImageObject",300,407,{"name":92,"@type":93},"Aurelia","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-07","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"How many carcinoma types are analyzed, and what is the focus of the study?","Question",{"text":112,"@type":113},"The study analyzes 23 carcinoma types and focuses on their age-dependent distribution patterns, the determinants of peak occurrence ages, and gender differences.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What are the two types of age-dependent occurrence rate (ADOR) distributions identified from SEER reports?",{"text":117,"@type":113},"The SEER-based analysis identifies two ADOR distribution types: most cancer types are unimodal, while a few are bimodal with an additional peak.",{"name":119,"@type":110,"acceptedAnswer":120},"What explanations are proposed for the unimodal versus bimodal ADOR patterns?",{"text":121,"@type":113},"The first ADOR type is explained using two age-dependent parameters involving stem-cell divisions and availability of subtype-specific bloodborne growth factors, while for the second type the first peak is attributed to viral infection and the second peak follows the same stem-cell/growth-factor mechanism.","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},329787,1790197851,{"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":34,"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},1099514068365,"https://ap-avatar.wpscdn.com/avatar/10000253d8d9f28188e?x-image-process=image/resize,m_fixed,w_180,h_180&k=1794309523707217728","Article  \nElucidation of Factors Affecting the Age-Dependent Cancer Occurrence Rates  \nJun Xiao 1,2, Yangkun Cao 2,3, Xuan Li 1,2, Long Xu 2, Zhihang Wang 1,2, Zhenyu Huang 1,2, Xuechen Mu 2,4, Yinwei Qu 1,2, * and Ying Xu 2, *  \nAcademic Editor: ImanTavassoly  \nReceived: 24 November 2024  \nRevised: 24 December 2024  \nAccepted: 29 December 2024  \nPublished: 31 December 2024  \nCitation: Xiao, J.; Cao, Y.; Li, X.; Xu, L.; Wang, Z.; Huang, Z.; Mu, X.; Qu, Y.; Xu, Y. Elucidation of Factors Affecting the Age-Dependent Cancer Occurrence Rates. Int. J. Mol. Sci. 2025, 26, 275. [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)ijms26010275  \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://creativecommons.org/](https://creativecommons.org/)[ ](https://creativecommons.org/)[licenses/by/4.0/](licenses/by/4.0/)) .  \n1 College of Computer Science and Technology, Jilin University, Changchun 130012, China; [xiaojun20@mails.jlu.edu.cn](xiaojun20@mails.jlu.edu.cn) (J.X.); [xuanli0518@gmail.com](xuanli0518@gmail.com) (X.L.); [zhihang22@mails.jlu.edu.cn](zhihang22@mails.jlu.edu.cn) (Z.W.); [zhenyuh19@mails.jlu.edu.cn](zhenyuh19@mails.jlu.edu.cn) (Z.H.)  \n2 Systems Biology Laboratory for Metabolic Reprogramming, School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China; [caoyk20@mails.jlu.edu.cn](caoyk20@mails.jlu.edu.cn) (Y.C.);  \n[xul6@sustech.edu.cn](xul6@sustech.edu.cn) (L.X.); [m250921296@gmail.com](m250921296@gmail.com) (X.M.)  \n3 School of Artificial Intelligence, Jilin University, Changchun 130012, China  \n4 School of Mathematics, Jilin University, Changchun 130012, China  \n* Correspondence: [quyw21@mails.jlu.edu.cn](quyw21@mails.jlu.edu.cn) (Y.Q.); [xuy9@sustech.edu.cn](xuy9@sustech.edu.cn) (Y.X.)  \nAbstract: Cancer occurrence rates exhibit diverse age-related patterns, and understanding them may shed new and important light on the drivers of cancer evolution. This study systematically analyzes the age-dependent occurrence rates of 23 carcinoma types, focusing on their age-dependent distribution patterns, the determinants of peak occurrence ages, and the significant difference between the two genders. According to the SEER reports, these cancer types have two types of age-dependent occurrence rate (ADOR) distributions, with most having a unimodal distribution and a few having a bimodal distribution. Our modeling analyses have revealed that (1) the first type can be naturally and simply explained using two age-dependent parameters: the total number of stem cell divisions inan organ from birth to the current age and the availability levels of bloodborne growth factors specifically needed by the cancer (sub)type, and (2) for the second type, the first peak is due to viral infection, while the second peak can be explained as in (1) for each cancer type. Further analyses indicate that (i) the iron level in an organ makes the difference between the male and female cancer occurrence rates, and (ii) the levels of sex hormones are the key determinants in the onset age of multiple cancer types. This analysis deepensour understanding of the dynamics of cancer evolution shared by diverse cancer types and provides new insights that are useful for cancer prevention and therapeutic strategies, thereby addressing critical gaps in the current paradigm of oncological research.  \nKeywords: cancer occurrence; Fenton reaction; growth signal; cell cycle; viral infection  \n1. Introduction  \nThe systematic examination of the age-dependent occurrence rates for different cancer types given in the SEER reports [1,2] revealed that (1) the vast majority of the cancer types each have an age-dependent unimodal distribution for the occurrence rate, namely the occurrence rate going up with age until it reaches a peak age and then going down with ","cbCaikihDYy2kYLL","https://ap.wps.com/l/cbCaikihDYy2kYLL","pdf",4853912,27,"English","# Abstract\n# Introduction","[{\"question\":\"How many carcinoma types are analyzed, and what is the focus of the study?\",\"answer\":\"The study analyzes 23 carcinoma types and focuses on their age-dependent distribution patterns, the determinants of peak occurrence ages, and gender differences.\"},{\"question\":\"What are the two types of age-dependent occurrence rate (ADOR) distributions identified from SEER reports?\",\"answer\":\"The SEER-based analysis identifies two ADOR distribution types: most cancer types are unimodal, while a few are bimodal with an additional peak.\"},{\"question\":\"What explanations are proposed for the unimodal versus bimodal ADOR patterns?\",\"answer\":\"The first ADOR type is explained using two age-dependent parameters involving stem-cell divisions and availability of subtype-specific bloodborne growth factors, while for the second type the first peak is attributed to viral infection and the second peak follows the same stem-cell/growth-factor mechanism.\"}]","Elucidation of Factors Affecting the Age-Dependent Cancer Occurrence Rates | PDF",1789985625,68]