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      Tumor organoids: applications in cancer modeling and potentials in precision medicine

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          Abstract

          Cancer is a top-ranked life-threatening disease with intratumor heterogeneity. Tumor heterogeneity is associated with metastasis, relapse, and therapy resistance. These factors contribute to treatment failure and an unfavorable prognosis. Personalized tumor models faithfully capturing the tumor heterogeneity of individual patients are urgently needed for precision medicine. Advances in stem cell culture have given rise to powerful organoid technology for the generation of in vitro three-dimensional tissues that have been shown to more accurately recapitulate the structures, specific functions, molecular characteristics, genomic alterations, expression profiles, and tumor microenvironment of primary tumors. Tumoroids in vitro serve as an important component of the pipeline for the discovery of potential therapeutic targets and the identification of novel compounds. In this review, we will summarize recent advances in tumoroid cultures as an excellent tool for accurate cancer modeling. Additionally, vascularization and immune microenvironment modeling based on organoid technology will also be described. Furthermore, we will summarize the great potential of tumor organoids in predicting the therapeutic response, investigating resistance-related mechanisms, optimizing treatment strategies, and exploring potential therapies. In addition, the bottlenecks and challenges of current tumoroids will also be discussed in this review.

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          Ahmedin Jemal, Lindsey A Torre, Rebecca Siegel … (2018)
          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            Breast cancer statistics, 2019

            Carol DeSantis, Jiemin Ma, Mia Gaudet … (2019)
            This article is the American Cancer Society's biennial update on female breast cancer statistics in the United States, including data on incidence, mortality, survival, and screening. Over the most recent 5-year period (2012-2016), the breast cancer incidence rate increased slightly by 0.3% per year, largely because of rising rates of local stage and hormone receptor-positive disease. In contrast, the breast cancer death rate continues to decline, dropping 40% from 1989 to 2017 and translating to 375,900 breast cancer deaths averted. Notably, the pace of the decline has slowed from an annual decrease of 1.9% during 1998 through 2011 to 1.3% during 2011 through 2017, largely driven by the trend in white women. Consequently, the black-white disparity in breast cancer mortality has remained stable since 2011 after widening over the past 3 decades. Nevertheless, the death rate remains 40% higher in blacks (28.4 vs 20.3 deaths per 100,000) despite a lower incidence rate (126.7 vs 130.8); this disparity is magnified among black women aged <50 years, who have a death rate double that of whites. In the most recent 5-year period (2013-2017), the death rate declined in Hispanics (2.1% per year), blacks (1.5%), whites (1.0%), and Asians/Pacific Islanders (0.8%) but was stable in American Indians/Alaska Natives. However, by state, breast cancer mortality rates are no longer declining in Nebraska overall; in Colorado and Wisconsin in black women; and in Nebraska, Texas, and Virginia in white women. Breast cancer was the leading cause of cancer death in women (surpassing lung cancer) in four Southern and two Midwestern states among blacks and in Utah among whites during 2016-2017. Declines in breast cancer mortality could be accelerated by expanding access to high-quality prevention, early detection, and treatment services to all women.
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              Human organoids: model systems for human biology and medicine

              Jihoon Kim, Bon-Kyoung Koo, Juergen A. Knoblich (2020)
              The historical reliance of biological research on the use of animal models has sometimes made it challenging to address questions that are specific to the understanding of human biology and disease. But with the advent of human organoids — which are stem cell-derived 3D culture systems — it is now possible to re-create the architecture and physiology of human organs in remarkable detail. Human organoids provide unique opportunities for the study of human disease and complement animal models. Human organoids have been used to study infectious diseases, genetic disorders and cancers through the genetic engineering of human stem cells, as well as directly when organoids are generated from patient biopsy samples. This Review discusses the applications, advantages and disadvantages of human organoids as models of development and disease and outlines the challenges that have to be overcome for organoids to be able to substantially reduce the need for animal experiments.
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                Author and article information

                Contributors
                Hanxiao Xu: 935123566@qq.com
                Dechao Jiao: jiaodechao007@126.com
                Aiguo Liu: drliuaiguo@163.com
                Kongming Wu:
                ORCID: http://orcid.org/0000-0003-2499-1032
                kmwu_lab@163.com
                Journal
                Journal ID (nlm-ta): J Hematol Oncol
                Journal ID (iso-abbrev): J Hematol Oncol
                Title: Journal of Hematology & Oncology
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1756-8722
                Publication date (Electronic): 12 May 2022
                Publication date PMC-release: 12 May 2022
                Publication date Collection: 2022
                Volume: 15
                Electronic Location Identifier: 58
                Affiliations
                [1 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, Department of Pediatrics, Tongji Hospital of Tongji Medical College, , Huazhong University of Science and Technology, ; Wuhan, 430030 China
                [2 ]GRID grid.412633.1, ISNI 0000 0004 1799 0733, Department of Interventional Radiology, , The First Affiliated Hospital of Zhengzhou University, ; Zhengzhou, 450052 China
                [3 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, Department of Oncology, Tongji Hospital of Tongji Medical College, , Huazhong University of Science and Technology, ; Wuhan, 430030 China
                Author information
                http://orcid.org/0000-0003-2499-1032
                Article
                Publisher ID: 1278
                DOI: 10.1186/s13045-022-01278-4
                PMC ID: 9103066
                PubMed ID: 35551634
                SO-VID: 0e9725dc-e037-4487-a09a-5e2a43d3b2ac
                Copyright © © The Author(s) 2022
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 8 February 2022
                Date accepted : 28 April 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81874120
                Award ID: 82073370
                Award Recipient :
                Categories
                Subject: Review
                Custom metadata
                issue-copyright-statement © The Author(s) 2022

                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: organoid,patient-derived xenografts,cancer,tumor microenvironment,therapy response prediction,drug discovery
                Data availability:
                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: organoid, patient-derived xenografts, cancer, tumor microenvironment, therapy response prediction, drug discovery

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