Lukmon M Raji, Monowarul M Siddique, Margaret S Bohm, Joseph F Pierre, Mary C Playdon, Scott A Summers, Bing Li, Katherine L Cook, E Angela Murphy, Liza Makowski
{"title":"Murine Models of Obesity-Related Cancer Risk.","authors":"Lukmon M Raji, Monowarul M Siddique, Margaret S Bohm, Joseph F Pierre, Mary C Playdon, Scott A Summers, Bing Li, Katherine L Cook, E Angela Murphy, Liza Makowski","doi":"10.1158/1940-6207.CAPR-24-0545","DOIUrl":null,"url":null,"abstract":"<p><p>Obesity is a global menace that has impacted over 14% of adults worldwide and over a third of Americans. Importantly, obesity is associated with an increased risk of over 13 types of cancer and worse outcomes, including increased mortality. This review focuses on the importance of considering obesity and metabolic dysfunction in cancer risk as part of the National Cancer Institute's funded consortium known as the Metabolic Dysfunction and Cancer Risk Program (MeDOC). It describes previous and ongoing mouse models used in studies conducted by MeDOC consortium members, as well as other relevant studies. Most cancer studies examine tumor progression, metastasis, or recurrence, which are consequences following tumor onset; however, this approach does not consider risk per se. To truly model cancer risk, parameters to measure include the quantification of cancer onset, measured as incidence or latency. Investigators must be cognizant of many factors in study design, including the choice of cancer model and genetic strain. Preclinical approaches addressing risk typically include genetically engineered mouse models or the administration of irritants or carcinogens. We also discuss the transplantation of cells or tumors such as allografts or xenografts, with a focus on tumor rejection or regression to approximate cancer risk, not cancer progression. Herein, we highlight two cancers, breast and colorectal cancer, where risk is associated with obesity and discussed varied murine model approaches, as well as key findings that explore cancer risk, prevention, or interception.</p>","PeriodicalId":72514,"journal":{"name":"Cancer prevention research (Philadelphia, Pa.)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer prevention research (Philadelphia, Pa.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1158/1940-6207.CAPR-24-0545","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Obesity is a global menace that has impacted over 14% of adults worldwide and over a third of Americans. Importantly, obesity is associated with an increased risk of over 13 types of cancer and worse outcomes, including increased mortality. This review focuses on the importance of considering obesity and metabolic dysfunction in cancer risk as part of the National Cancer Institute's funded consortium known as the Metabolic Dysfunction and Cancer Risk Program (MeDOC). It describes previous and ongoing mouse models used in studies conducted by MeDOC consortium members, as well as other relevant studies. Most cancer studies examine tumor progression, metastasis, or recurrence, which are consequences following tumor onset; however, this approach does not consider risk per se. To truly model cancer risk, parameters to measure include the quantification of cancer onset, measured as incidence or latency. Investigators must be cognizant of many factors in study design, including the choice of cancer model and genetic strain. Preclinical approaches addressing risk typically include genetically engineered mouse models or the administration of irritants or carcinogens. We also discuss the transplantation of cells or tumors such as allografts or xenografts, with a focus on tumor rejection or regression to approximate cancer risk, not cancer progression. Herein, we highlight two cancers, breast and colorectal cancer, where risk is associated with obesity and discussed varied murine model approaches, as well as key findings that explore cancer risk, prevention, or interception.