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Hu Q, Wang Y, Yao S, Mao Y, Liu L, Li Z, Chen Y, Zhang S, Li Q, Zhao Y, Fan X, Cui Y, Zhao K, Liu Z. Desmoplastic Reaction Associates with Prognosis and Adjuvant Chemotherapy Response in Colorectal Cancer: A Multicenter Retrospective Study. Cancer Res Commun 2023; 3:1057-1066. [PMID: 37377615 PMCID: PMC10269709 DOI: 10.1158/2767-9764.crc-23-0073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 04/26/2023] [Accepted: 05/23/2023] [Indexed: 06/29/2023]
Abstract
Desmoplastic reaction (DR) is one of many tumor-host interactions and is associated with the overall survival (OS) of patients with colorectal cancer. However, the clinical significance of DR requires further study in large multicenter cohorts and its predictive value in adjuvant chemotherapy (ACT) response remains unclear. Here, a total of 2,225 patients with colorectal cancer from five independent institutions were divided into primary (N = 1,012 from two centers) and validation (N = 1,213 from three centers) cohorts. DR was classified as immature, middle, or mature depending on the presence of myxoid stroma and hyalinized collagen bundles at the invasive front of the primary tumor. OS among different subgroups were compared, and the correlations of DR type with tumor-infiltrating lymphocytes (TILs) within stroma, tumor stroma ratio (TSR), and Stroma AReactive Invasion Front Areas (SARIFA) were also analyzed. In the primary cohort, patients with mature DR had the highest 5-year survival rate. These findings were confirmed in validation cohort. In addition, for stage II colorectal cancer, patients classified as non-mature DR would benefit from ACT compared with surgery alone. Furthermore, immature and middle DR were more associated with high TSR, less distribution of TILs within stroma and positive SARIFA compared with mature. Taken together, these data suggest that DR is a robust-independent prognostic factor for patients with colorectal cancer. For patients with stage II colorectal cancer, non-mature DR could be a potential marker for recognizing high-risk patients who may benefit from ACT. Significance DR has the potential to identify patients with high-risk colorectal cancer and predict the efficacy of adjuvant chemotherapy in patients with stage II colorectal cancer. Our findings support reporting DR types as additional pathologic parameters in clinical practice for more precise risk stratification.
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Affiliation(s)
- Qingru Hu
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, P.R. China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, P.R. China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, P.R. China
| | - Yiting Wang
- Department of Pathology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, P.R. China
| | - Su Yao
- Department of Pathology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, P.R. China
| | - Yun Mao
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, P.R. China
| | - Liu Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, P.R. China
| | - Zhenhui Li
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, P.R. China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, P.R. China
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, P.R. China
| | - Yonghe Chen
- Department of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, P.R. China
| | - Shenyan Zhang
- Department of Pathology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, P.R. China
| | - Qian Li
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, P.R. China
- School of Medicine, South China University of Technology, Guangzhou, P.R. China
| | - Yingnan Zhao
- School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, P.R. China
| | - Xinjuan Fan
- Department of Pathology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, P.R. China
| | - Yanfen Cui
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, P.R. China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, P.R. China
- Department of Radiology, Shanxi Cancer Hospital, Shanxi Medical University, Taiyuan, P.R. China
| | - Ke Zhao
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, P.R. China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, P.R. China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, P.R. China
| | - Zaiyi Liu
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, P.R. China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, P.R. China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, P.R. China
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