Cargando…
Predicting response to neoadjuvant chemoradiotherapy in rectal cancer: from biomarkers to tumor models
Colorectal cancer (CRC) is a major contributor to cancer-associated morbidity worldwide and over one-third of CRC is located in the rectum. Neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection is commonly applied to treat locally advanced rectal cancer (LARC). In this review, we summa...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864271/ https://www.ncbi.nlm.nih.gov/pubmed/35222695 http://dx.doi.org/10.1177/17588359221077972 |
_version_ | 1784655425403092992 |
---|---|
author | Li, Moying Xiao, Qiyun Venkatachalam, Nachiyappan Hofheinz, Ralf-Dieter Veldwijk, Marlon R. Herskind, Carsten Ebert, Matthias P. Zhan, Tianzuo |
author_facet | Li, Moying Xiao, Qiyun Venkatachalam, Nachiyappan Hofheinz, Ralf-Dieter Veldwijk, Marlon R. Herskind, Carsten Ebert, Matthias P. Zhan, Tianzuo |
author_sort | Li, Moying |
collection | PubMed |
description | Colorectal cancer (CRC) is a major contributor to cancer-associated morbidity worldwide and over one-third of CRC is located in the rectum. Neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection is commonly applied to treat locally advanced rectal cancer (LARC). In this review, we summarize current and novel concepts of neoadjuvant therapy for LARC such as total neoadjuvant therapy and describe how these developments impact treatment response. Moreover, as response to nCRT is highly divergent in rectal cancers, we discuss the role of potential predictive biomarkers. We review recent advances in biomarker discovery, from a clinical as well as a histopathological and molecular perspective. Furthermore, the role of emerging predictive biomarkers derived from the tumor environment such as immune cell composition and gut microbiome is presented. Finally, we describe how different tumor models such as patient-derived cancer organoids are used to identify novel predictive biomarkers for chemoradiotherapy (CRT) in rectal cancer. |
format | Online Article Text |
id | pubmed-8864271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-88642712022-02-24 Predicting response to neoadjuvant chemoradiotherapy in rectal cancer: from biomarkers to tumor models Li, Moying Xiao, Qiyun Venkatachalam, Nachiyappan Hofheinz, Ralf-Dieter Veldwijk, Marlon R. Herskind, Carsten Ebert, Matthias P. Zhan, Tianzuo Ther Adv Med Oncol Review Colorectal cancer (CRC) is a major contributor to cancer-associated morbidity worldwide and over one-third of CRC is located in the rectum. Neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection is commonly applied to treat locally advanced rectal cancer (LARC). In this review, we summarize current and novel concepts of neoadjuvant therapy for LARC such as total neoadjuvant therapy and describe how these developments impact treatment response. Moreover, as response to nCRT is highly divergent in rectal cancers, we discuss the role of potential predictive biomarkers. We review recent advances in biomarker discovery, from a clinical as well as a histopathological and molecular perspective. Furthermore, the role of emerging predictive biomarkers derived from the tumor environment such as immune cell composition and gut microbiome is presented. Finally, we describe how different tumor models such as patient-derived cancer organoids are used to identify novel predictive biomarkers for chemoradiotherapy (CRT) in rectal cancer. SAGE Publications 2022-02-21 /pmc/articles/PMC8864271/ /pubmed/35222695 http://dx.doi.org/10.1177/17588359221077972 Text en © The Author(s), 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Review Li, Moying Xiao, Qiyun Venkatachalam, Nachiyappan Hofheinz, Ralf-Dieter Veldwijk, Marlon R. Herskind, Carsten Ebert, Matthias P. Zhan, Tianzuo Predicting response to neoadjuvant chemoradiotherapy in rectal cancer: from biomarkers to tumor models |
title | Predicting response to neoadjuvant chemoradiotherapy in rectal
cancer: from biomarkers to tumor models |
title_full | Predicting response to neoadjuvant chemoradiotherapy in rectal
cancer: from biomarkers to tumor models |
title_fullStr | Predicting response to neoadjuvant chemoradiotherapy in rectal
cancer: from biomarkers to tumor models |
title_full_unstemmed | Predicting response to neoadjuvant chemoradiotherapy in rectal
cancer: from biomarkers to tumor models |
title_short | Predicting response to neoadjuvant chemoradiotherapy in rectal
cancer: from biomarkers to tumor models |
title_sort | predicting response to neoadjuvant chemoradiotherapy in rectal
cancer: from biomarkers to tumor models |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864271/ https://www.ncbi.nlm.nih.gov/pubmed/35222695 http://dx.doi.org/10.1177/17588359221077972 |
work_keys_str_mv | AT limoying predictingresponsetoneoadjuvantchemoradiotherapyinrectalcancerfrombiomarkerstotumormodels AT xiaoqiyun predictingresponsetoneoadjuvantchemoradiotherapyinrectalcancerfrombiomarkerstotumormodels AT venkatachalamnachiyappan predictingresponsetoneoadjuvantchemoradiotherapyinrectalcancerfrombiomarkerstotumormodels AT hofheinzralfdieter predictingresponsetoneoadjuvantchemoradiotherapyinrectalcancerfrombiomarkerstotumormodels AT veldwijkmarlonr predictingresponsetoneoadjuvantchemoradiotherapyinrectalcancerfrombiomarkerstotumormodels AT herskindcarsten predictingresponsetoneoadjuvantchemoradiotherapyinrectalcancerfrombiomarkerstotumormodels AT ebertmatthiasp predictingresponsetoneoadjuvantchemoradiotherapyinrectalcancerfrombiomarkerstotumormodels AT zhantianzuo predictingresponsetoneoadjuvantchemoradiotherapyinrectalcancerfrombiomarkerstotumormodels |