Cargando…

Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics

BACKGROUND: Significant intertumoral heterogeneity exists as antitumor treatment is introduced. Heterogeneous therapeutic responses are conventionally evaluated by imaging examinations based on Response Evaluation Criteria in Solid Tumors (RECIST); nevertheless, there are increasing recognitions tha...

Descripción completa

Detalles Bibliográficos
Autores principales: Lv, Jiawei, Wu, Chenfei, Li, Junyan, Chen, Foping, He, Shiwei, He, Qingmei, Zhou, Guanqun, Ma, Jun, Sun, Ying, Wei, Denghui, Lin, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9396864/
https://www.ncbi.nlm.nih.gov/pubmed/35996151
http://dx.doi.org/10.1186/s12916-022-02463-5
_version_ 1784772013252935680
author Lv, Jiawei
Wu, Chenfei
Li, Junyan
Chen, Foping
He, Shiwei
He, Qingmei
Zhou, Guanqun
Ma, Jun
Sun, Ying
Wei, Denghui
Lin, Li
author_facet Lv, Jiawei
Wu, Chenfei
Li, Junyan
Chen, Foping
He, Shiwei
He, Qingmei
Zhou, Guanqun
Ma, Jun
Sun, Ying
Wei, Denghui
Lin, Li
author_sort Lv, Jiawei
collection PubMed
description BACKGROUND: Significant intertumoral heterogeneity exists as antitumor treatment is introduced. Heterogeneous therapeutic responses are conventionally evaluated by imaging examinations based on Response Evaluation Criteria in Solid Tumors (RECIST); nevertheless, there are increasing recognitions that they do not fully capture patient clinical benefits. Currently, there is a paucity of data regarding the clinical implication of biological responses assessed by liquid biopsy of on-treatment circulating tumor DNA (ctDNA). Here, we investigated whether biological response evaluated by ctDNA kinetics added critical information to the RECIST, and whether integrating on-treatment biological response information refined risk stratification of cancer patients. METHODS: In this population-based cohort study, we included 821 patients with Epstein-Barr virus (EBV)-associated nasopharynx of head and neck cancer (NPC) receiving sequential neoadjuvant chemotherapy (NAC) and chemoradiotherapy (CRT), who had pretreatment and on-treatment cfEBV DNA and magnetic resonance imaging (MRI) surveillance. Biological responses evaluated by cfEBV DNA were profiled and compared with conventional MRI-based RECIST evaluation. The inverse probability weighting (IPW)-adjusted survival analysis was performed for major survival endpoints. The Cox proportional hazard regression [CpH]-based model was developed to predict the on-treatment ctDNA-based individualized survival. RESULTS: Of 821 patients, 71.4% achieved complete biological response (cBR) upon NAC completion. RECIST-based response evaluations had 25.3% discordance with ctDNA-based evaluations. IPW-adjusted survival analysis revealed that cfEBV DNA(post-NAC) was a preferential prognosticator for all endpoints, especially for distant metastasis. In contrast, radiological response was more preferentially associated with locoregional recurrence. Intriguingly, cfEBV DNA(post-NAC) further stratified RECIST-responsive and non-responsive patients; RECIST-based non-responsive patients with cBR still derived substantial clinical benefits. Moreover, detectable cfEBV DNA(post-NAC) had 83.6% prediction sensitivity for detectable post-treatment ctDNA, which conferred early determination of treatment benefits. Finally, we established individualized risk prediction models and demonstrated that introducing on-treatment ctDNA significantly refined risk stratification. CONCLUSIONS: Our study helps advance the implementation of ctDNA-based testing in therapeutic response evaluation for a refined risk stratification. The dynamic and refined risk profiling would tailor future liquid biopsy-based risk-adapted personalized therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-022-02463-5.
format Online
Article
Text
id pubmed-9396864
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-93968642022-08-24 Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics Lv, Jiawei Wu, Chenfei Li, Junyan Chen, Foping He, Shiwei He, Qingmei Zhou, Guanqun Ma, Jun Sun, Ying Wei, Denghui Lin, Li BMC Med Research Article BACKGROUND: Significant intertumoral heterogeneity exists as antitumor treatment is introduced. Heterogeneous therapeutic responses are conventionally evaluated by imaging examinations based on Response Evaluation Criteria in Solid Tumors (RECIST); nevertheless, there are increasing recognitions that they do not fully capture patient clinical benefits. Currently, there is a paucity of data regarding the clinical implication of biological responses assessed by liquid biopsy of on-treatment circulating tumor DNA (ctDNA). Here, we investigated whether biological response evaluated by ctDNA kinetics added critical information to the RECIST, and whether integrating on-treatment biological response information refined risk stratification of cancer patients. METHODS: In this population-based cohort study, we included 821 patients with Epstein-Barr virus (EBV)-associated nasopharynx of head and neck cancer (NPC) receiving sequential neoadjuvant chemotherapy (NAC) and chemoradiotherapy (CRT), who had pretreatment and on-treatment cfEBV DNA and magnetic resonance imaging (MRI) surveillance. Biological responses evaluated by cfEBV DNA were profiled and compared with conventional MRI-based RECIST evaluation. The inverse probability weighting (IPW)-adjusted survival analysis was performed for major survival endpoints. The Cox proportional hazard regression [CpH]-based model was developed to predict the on-treatment ctDNA-based individualized survival. RESULTS: Of 821 patients, 71.4% achieved complete biological response (cBR) upon NAC completion. RECIST-based response evaluations had 25.3% discordance with ctDNA-based evaluations. IPW-adjusted survival analysis revealed that cfEBV DNA(post-NAC) was a preferential prognosticator for all endpoints, especially for distant metastasis. In contrast, radiological response was more preferentially associated with locoregional recurrence. Intriguingly, cfEBV DNA(post-NAC) further stratified RECIST-responsive and non-responsive patients; RECIST-based non-responsive patients with cBR still derived substantial clinical benefits. Moreover, detectable cfEBV DNA(post-NAC) had 83.6% prediction sensitivity for detectable post-treatment ctDNA, which conferred early determination of treatment benefits. Finally, we established individualized risk prediction models and demonstrated that introducing on-treatment ctDNA significantly refined risk stratification. CONCLUSIONS: Our study helps advance the implementation of ctDNA-based testing in therapeutic response evaluation for a refined risk stratification. The dynamic and refined risk profiling would tailor future liquid biopsy-based risk-adapted personalized therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-022-02463-5. BioMed Central 2022-08-23 /pmc/articles/PMC9396864/ /pubmed/35996151 http://dx.doi.org/10.1186/s12916-022-02463-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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.
spellingShingle Research Article
Lv, Jiawei
Wu, Chenfei
Li, Junyan
Chen, Foping
He, Shiwei
He, Qingmei
Zhou, Guanqun
Ma, Jun
Sun, Ying
Wei, Denghui
Lin, Li
Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics
title Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics
title_full Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics
title_fullStr Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics
title_full_unstemmed Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics
title_short Improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor DNA kinetics
title_sort improving on-treatment risk stratification of cancer patients with refined response classification and integration of circulating tumor dna kinetics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9396864/
https://www.ncbi.nlm.nih.gov/pubmed/35996151
http://dx.doi.org/10.1186/s12916-022-02463-5
work_keys_str_mv AT lvjiawei improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT wuchenfei improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT lijunyan improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT chenfoping improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT heshiwei improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT heqingmei improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT zhouguanqun improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT majun improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT sunying improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT weidenghui improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics
AT linli improvingontreatmentriskstratificationofcancerpatientswithrefinedresponseclassificationandintegrationofcirculatingtumordnakinetics