Non-invasive CT imaging biomarker to predict immunotherapy response in gastric cancer : a multicenter study
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ..
BACKGROUND: Despite remarkable benefits have been provided by immune checkpoint inhibitors in gastric cancer (GC), predictions of treatment response and prognosis remain unsatisfactory, making identifying biomarkers desirable. The aim of this study was to develop and validate a CT imaging biomarker to predict the immunotherapy response in patients with GC and investigate the associated immune infiltration patterns.
METHODS: This retrospective study included 294 GC patients who received anti-PD-1/PD-L1 immunotherapy from three independent medical centers between January 2017 and April 2022. A radiomics score (RS) was developed from the intratumoral and peritumoral features on pretreatment CT images to predict immunotherapy-related progression-free survival (irPFS). The performance of the RS was evaluated by the area under the time-dependent receiver operating characteristic curve (AUC). Multivariable Cox regression analysis was performed to construct predictive nomogram of irPFS. The C-index was used to determine the performance of the nomogram. Bulk RNA sequencing of tumors from 42 patients in The Cancer Genome Atlas was used to investigate the RS-associated immune infiltration patterns.
RESULTS: Overall, 89 of 294 patients (median age, 57 years (IQR 48-66 years); 171 males) had an objective response to immunotherapy. The RS included 13 CT features that yielded AUCs of 12-month irPFS of 0.787, 0.810 and 0.785 in the training, internal validation, and external validation 1 cohorts, respectively, and an AUC of 24-month irPFS of 0.805 in the external validation 2 cohort. Patients with low RS had longer irPFS in each cohort (p<0.05). Multivariable Cox regression analyses showed RS is an independent prognostic factor of irPFS. The nomogram that integrated the RS and clinical characteristics showed improved performance in predicting irPFS, with C-index of 0.687-0.778 in the training and validation cohorts. The CT imaging biomarker was associated with M1 macrophage infiltration.
CONCLUSION: The findings of this prognostic study suggest that the non-invasive CT imaging biomarker can effectively predict immunotherapy outcomes in patients with GC and is associated with innate immune signaling, which can serve as a potential tool for individual treatment decisions.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
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| Enthalten in: |
Journal for immunotherapy of cancer - 11(2023), 11 vom: 21. Nov. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Huang, Weicai [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarkers |
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| Anmerkungen: |
Date Completed 10.01.2024 Date Revised 15.03.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1136/jitc-2023-007807 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM366703102 |
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| 500 | |a Date Revised 15.03.2024 | ||
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| 520 | |a © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. | ||
| 520 | |a BACKGROUND: Despite remarkable benefits have been provided by immune checkpoint inhibitors in gastric cancer (GC), predictions of treatment response and prognosis remain unsatisfactory, making identifying biomarkers desirable. The aim of this study was to develop and validate a CT imaging biomarker to predict the immunotherapy response in patients with GC and investigate the associated immune infiltration patterns | ||
| 520 | |a METHODS: This retrospective study included 294 GC patients who received anti-PD-1/PD-L1 immunotherapy from three independent medical centers between January 2017 and April 2022. A radiomics score (RS) was developed from the intratumoral and peritumoral features on pretreatment CT images to predict immunotherapy-related progression-free survival (irPFS). The performance of the RS was evaluated by the area under the time-dependent receiver operating characteristic curve (AUC). Multivariable Cox regression analysis was performed to construct predictive nomogram of irPFS. The C-index was used to determine the performance of the nomogram. Bulk RNA sequencing of tumors from 42 patients in The Cancer Genome Atlas was used to investigate the RS-associated immune infiltration patterns | ||
| 520 | |a RESULTS: Overall, 89 of 294 patients (median age, 57 years (IQR 48-66 years); 171 males) had an objective response to immunotherapy. The RS included 13 CT features that yielded AUCs of 12-month irPFS of 0.787, 0.810 and 0.785 in the training, internal validation, and external validation 1 cohorts, respectively, and an AUC of 24-month irPFS of 0.805 in the external validation 2 cohort. Patients with low RS had longer irPFS in each cohort (p<0.05). Multivariable Cox regression analyses showed RS is an independent prognostic factor of irPFS. The nomogram that integrated the RS and clinical characteristics showed improved performance in predicting irPFS, with C-index of 0.687-0.778 in the training and validation cohorts. The CT imaging biomarker was associated with M1 macrophage infiltration | ||
| 520 | |a CONCLUSION: The findings of this prognostic study suggest that the non-invasive CT imaging biomarker can effectively predict immunotherapy outcomes in patients with GC and is associated with innate immune signaling, which can serve as a potential tool for individual treatment decisions | ||
| 650 | 4 | |a Multicenter Study | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Biomarkers, Tumor | |
| 650 | 4 | |a Immunotherapy | |
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| 700 | 1 | |a Xiong, Wenjun |e verfasserin |4 aut | |
| 700 | 1 | |a Tang, Lei |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Chuanli |e verfasserin |4 aut | |
| 700 | 1 | |a Yuan, Qingyu |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Cheng |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Kangneng |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Zepang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Taojun |e verfasserin |4 aut | |
| 700 | 1 | |a Han, Zhen |e verfasserin |4 aut | |
| 700 | 1 | |a Feng, Hao |e verfasserin |4 aut | |
| 700 | 1 | |a Liang, Xiaokun |e verfasserin |4 aut | |
| 700 | 1 | |a Zhong, Yonghong |e verfasserin |4 aut | |
| 700 | 1 | |a Deng, Haijun |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Lequan |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Yikai |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Shen, Lin |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Guoxin |e verfasserin |4 aut | |
| 700 | 1 | |a Jiang, Yuming |e verfasserin |4 aut | |
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