Loading…

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, P...

Full description

Saved in:
Bibliographic Details
Published in:Signal transduction and targeted therapy 2023-04, Vol.8 (1), p.160-160, Article 160
Main Authors: Liu, Yihan, Wu, Wantao, Cai, Changjing, Zhang, Hao, Shen, Hong, Han, Ying
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c541t-58e7d3973dcd29239294a287f9678ba09d3dc54dbaa1c2284c52a28657d202483
cites cdi_FETCH-LOGICAL-c541t-58e7d3973dcd29239294a287f9678ba09d3dc54dbaa1c2284c52a28657d202483
container_end_page 160
container_issue 1
container_start_page 160
container_title Signal transduction and targeted therapy
container_volume 8
creator Liu, Yihan
Wu, Wantao
Cai, Changjing
Zhang, Hao
Shen, Hong
Han, Ying
description Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.
doi_str_mv 10.1038/s41392-023-01419-2
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_8c4da95fefc84a8b8117348e70c99ee1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_8c4da95fefc84a8b8117348e70c99ee1</doaj_id><sourcerecordid>2799932163</sourcerecordid><originalsourceid>FETCH-LOGICAL-c541t-58e7d3973dcd29239294a287f9678ba09d3dc54dbaa1c2284c52a28657d202483</originalsourceid><addsrcrecordid>eNp9kstu1DAUhiMEolXpC7BAkdiwCfga22wQqrhUqgRIsLbO2CcZjzJ2sDMVfXvcppSWBStb_v_z-dya5jklrynh-k0RlBvWEcY7QgU1HXvUHDMiTcd7Lh_fux81p6XsCCG050pJ8bQ54ooIqZk6br59hSVgXDqPOVyib39hTGOGYWn3yeNU2hBbB9FhbpctZpiv3rYLum1MUxoDlhaib2Gep-AqKcXyrHkywFTw9PY8aX58_PD97HN38eXT-dn7i85JQZdOalSeG8W988ywWosRwLQaTK_0BojxVZHCbwCoY0wLJ1nVe6k8I0xoftKcr1yfYGfnHPaQr2yCYG8eUh4t5CW4Ca12woORAw5OC9AbTanioiZAnDGItLLeraz5sNmjd7UhGaYH0IdKDFs7pktLCTFKK1EJr24JOf08YFnsPhSH0wQR06FYpgnpmaDy2vryH-suHXKsvbJMGWM4q4OqLra6XE6lZBzusqHEXm-AXTfA1g2wNxtgWQ16cb-Ou5A_864GvhpKleKI-e_f_8H-Bphbu6E</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2799932163</pqid></control><display><type>article</type><title>Patient-derived xenograft models in cancer therapy: technologies and applications</title><source>Publicly Available Content Database</source><source>PubMed Central</source><source>Springer Nature - nature.com Journals - Fully Open Access</source><creator>Liu, Yihan ; Wu, Wantao ; Cai, Changjing ; Zhang, Hao ; Shen, Hong ; Han, Ying</creator><creatorcontrib>Liu, Yihan ; Wu, Wantao ; Cai, Changjing ; Zhang, Hao ; Shen, Hong ; Han, Ying</creatorcontrib><description>Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.</description><identifier>ISSN: 2059-3635</identifier><identifier>ISSN: 2095-9907</identifier><identifier>EISSN: 2059-3635</identifier><identifier>DOI: 10.1038/s41392-023-01419-2</identifier><identifier>PMID: 37045827</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/67/1059 ; 631/67/70 ; Animals ; Cancer ; Cancer Research ; Cancer therapies ; Cell Biology ; Chemotherapy ; Clinical trials ; Deep learning ; Drug resistance ; Heterografts ; Humans ; Immunotherapy ; Internal Medicine ; Medicine ; Medicine &amp; Public Health ; Mice ; Neoplasms - drug therapy ; Neoplasms - genetics ; Oncology ; Pathology ; Patients ; Review ; Review Article ; Xenografts</subject><ispartof>Signal transduction and targeted therapy, 2023-04, Vol.8 (1), p.160-160, Article 160</ispartof><rights>The Author(s) 2023</rights><rights>2023. The Author(s).</rights><rights>The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c541t-58e7d3973dcd29239294a287f9678ba09d3dc54dbaa1c2284c52a28657d202483</citedby><cites>FETCH-LOGICAL-c541t-58e7d3973dcd29239294a287f9678ba09d3dc54dbaa1c2284c52a28657d202483</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2799932163/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2799932163?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37045827$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Yihan</creatorcontrib><creatorcontrib>Wu, Wantao</creatorcontrib><creatorcontrib>Cai, Changjing</creatorcontrib><creatorcontrib>Zhang, Hao</creatorcontrib><creatorcontrib>Shen, Hong</creatorcontrib><creatorcontrib>Han, Ying</creatorcontrib><title>Patient-derived xenograft models in cancer therapy: technologies and applications</title><title>Signal transduction and targeted therapy</title><addtitle>Sig Transduct Target Ther</addtitle><addtitle>Signal Transduct Target Ther</addtitle><description>Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.</description><subject>631/67/1059</subject><subject>631/67/70</subject><subject>Animals</subject><subject>Cancer</subject><subject>Cancer Research</subject><subject>Cancer therapies</subject><subject>Cell Biology</subject><subject>Chemotherapy</subject><subject>Clinical trials</subject><subject>Deep learning</subject><subject>Drug resistance</subject><subject>Heterografts</subject><subject>Humans</subject><subject>Immunotherapy</subject><subject>Internal Medicine</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>Mice</subject><subject>Neoplasms - drug therapy</subject><subject>Neoplasms - genetics</subject><subject>Oncology</subject><subject>Pathology</subject><subject>Patients</subject><subject>Review</subject><subject>Review Article</subject><subject>Xenografts</subject><issn>2059-3635</issn><issn>2095-9907</issn><issn>2059-3635</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kstu1DAUhiMEolXpC7BAkdiwCfga22wQqrhUqgRIsLbO2CcZjzJ2sDMVfXvcppSWBStb_v_z-dya5jklrynh-k0RlBvWEcY7QgU1HXvUHDMiTcd7Lh_fux81p6XsCCG050pJ8bQ54ooIqZk6br59hSVgXDqPOVyib39hTGOGYWn3yeNU2hBbB9FhbpctZpiv3rYLum1MUxoDlhaib2Gep-AqKcXyrHkywFTw9PY8aX58_PD97HN38eXT-dn7i85JQZdOalSeG8W988ywWosRwLQaTK_0BojxVZHCbwCoY0wLJ1nVe6k8I0xoftKcr1yfYGfnHPaQr2yCYG8eUh4t5CW4Ca12woORAw5OC9AbTanioiZAnDGItLLeraz5sNmjd7UhGaYH0IdKDFs7pktLCTFKK1EJr24JOf08YFnsPhSH0wQR06FYpgnpmaDy2vryH-suHXKsvbJMGWM4q4OqLra6XE6lZBzusqHEXm-AXTfA1g2wNxtgWQ16cb-Ou5A_864GvhpKleKI-e_f_8H-Bphbu6E</recordid><startdate>20230412</startdate><enddate>20230412</enddate><creator>Liu, Yihan</creator><creator>Wu, Wantao</creator><creator>Cai, Changjing</creator><creator>Zhang, Hao</creator><creator>Shen, Hong</creator><creator>Han, Ying</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7X7</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20230412</creationdate><title>Patient-derived xenograft models in cancer therapy: technologies and applications</title><author>Liu, Yihan ; Wu, Wantao ; Cai, Changjing ; Zhang, Hao ; Shen, Hong ; Han, Ying</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c541t-58e7d3973dcd29239294a287f9678ba09d3dc54dbaa1c2284c52a28657d202483</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>631/67/1059</topic><topic>631/67/70</topic><topic>Animals</topic><topic>Cancer</topic><topic>Cancer Research</topic><topic>Cancer therapies</topic><topic>Cell Biology</topic><topic>Chemotherapy</topic><topic>Clinical trials</topic><topic>Deep learning</topic><topic>Drug resistance</topic><topic>Heterografts</topic><topic>Humans</topic><topic>Immunotherapy</topic><topic>Internal Medicine</topic><topic>Medicine</topic><topic>Medicine &amp; Public Health</topic><topic>Mice</topic><topic>Neoplasms - drug therapy</topic><topic>Neoplasms - genetics</topic><topic>Oncology</topic><topic>Pathology</topic><topic>Patients</topic><topic>Review</topic><topic>Review Article</topic><topic>Xenografts</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Yihan</creatorcontrib><creatorcontrib>Wu, Wantao</creatorcontrib><creatorcontrib>Cai, Changjing</creatorcontrib><creatorcontrib>Zhang, Hao</creatorcontrib><creatorcontrib>Shen, Hong</creatorcontrib><creatorcontrib>Han, Ying</creatorcontrib><collection>SpringerOpen</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Biological Sciences</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Signal transduction and targeted therapy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Yihan</au><au>Wu, Wantao</au><au>Cai, Changjing</au><au>Zhang, Hao</au><au>Shen, Hong</au><au>Han, Ying</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Patient-derived xenograft models in cancer therapy: technologies and applications</atitle><jtitle>Signal transduction and targeted therapy</jtitle><stitle>Sig Transduct Target Ther</stitle><addtitle>Signal Transduct Target Ther</addtitle><date>2023-04-12</date><risdate>2023</risdate><volume>8</volume><issue>1</issue><spage>160</spage><epage>160</epage><pages>160-160</pages><artnum>160</artnum><issn>2059-3635</issn><issn>2095-9907</issn><eissn>2059-3635</eissn><abstract>Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>37045827</pmid><doi>10.1038/s41392-023-01419-2</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2059-3635
ispartof Signal transduction and targeted therapy, 2023-04, Vol.8 (1), p.160-160, Article 160
issn 2059-3635
2095-9907
2059-3635
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_8c4da95fefc84a8b8117348e70c99ee1
source Publicly Available Content Database; PubMed Central; Springer Nature - nature.com Journals - Fully Open Access
subjects 631/67/1059
631/67/70
Animals
Cancer
Cancer Research
Cancer therapies
Cell Biology
Chemotherapy
Clinical trials
Deep learning
Drug resistance
Heterografts
Humans
Immunotherapy
Internal Medicine
Medicine
Medicine & Public Health
Mice
Neoplasms - drug therapy
Neoplasms - genetics
Oncology
Pathology
Patients
Review
Review Article
Xenografts
title Patient-derived xenograft models in cancer therapy: technologies and applications
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T21%3A07%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Patient-derived%20xenograft%20models%20in%20cancer%20therapy:%20technologies%20and%20applications&rft.jtitle=Signal%20transduction%20and%20targeted%20therapy&rft.au=Liu,%20Yihan&rft.date=2023-04-12&rft.volume=8&rft.issue=1&rft.spage=160&rft.epage=160&rft.pages=160-160&rft.artnum=160&rft.issn=2059-3635&rft.eissn=2059-3635&rft_id=info:doi/10.1038/s41392-023-01419-2&rft_dat=%3Cproquest_doaj_%3E2799932163%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c541t-58e7d3973dcd29239294a287f9678ba09d3dc54dbaa1c2284c52a28657d202483%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2799932163&rft_id=info:pmid/37045827&rfr_iscdi=true