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A radiomic signature model to predict the chemoradiation-induced alteration in tumor-infiltrating CD8+ cells in locally advanced rectal cancer.
Jeon, Seung Hyuck; Lim, Yu Jin; Koh, Jaemoon; Chang, Won Ick; Kim, Sehui; Kim, Kyubo; Chie, Eui Kyu.
Affiliation
  • Jeon SH; Department of Radiation Oncology, Seoul National University College of Medicine, Seoul, Republic of Korea; Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
  • Lim YJ; Department of Radiation Oncology, Kyung Hee University College of Medicine, Kyung Hee University Medical Center, Seoul, Republic of Korea.
  • Koh J; Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Chang WI; Department of Radiation Oncology, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Kim S; Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Kim K; Department of Radiation Oncology, Ewha Womans University College of Medicine, Seoul, Republic of Korea.
  • Chie EK; Department of Radiation Oncology, Seoul National University College of Medicine, Seoul, Republic of Korea; Institute of Radiation Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea. Electronic address: ekchie93@snu.ac.kr.
Radiother Oncol ; 162: 124-131, 2021 09.
Article in En | MEDLINE | ID: mdl-34265357
ABSTRACT
BACKGROUND AND

PURPOSE:

Regarding the altered tumor immune status following cytotoxic treatment, this study aims to develop a radiomic signature to predict CD8+ tumor-infiltrating lymphocyte (TIL) density changes in chemoradiotherapy (CRT) of rectal cancer. MATERIALS AND

METHODS:

We used the magnetic resonance imaging (MRI) and immunohistochemistry data before and after neoadjuvant CRT. The discovery datasets consisted of pre-CRT dataset A1 (n = 113), post-CRT datasets A2 (n = 32; predominance of tumor) and A3 (n = 20; pure fibrosis). The developed model was validated in dataset B (n = 28). Thirty-eight radiomic features from T2-weighted MRI scans were incorporated into the least absolute shrinkage and selection operator method.

RESULTS:

In pre-CRT dataset A1, the area under the receiver operating characteristic curve (AUC) values of radiomic score for predicting CD8+ TILs were 0.760 and 0.729 for training and validation subsets, respectively. A significant correlation was observed between the signature and CD8+ TIL density in the post-CRT dataset A2 (Pearson's R = -0.372, P = 0.036), whereas no association was found in dataset A3 (Pearson's R = -0.069, P = 0.77). The association was also observed in the validation dataset B (Pearson's R = -0.374, P = 0.049). In dataset A2, the radiomic score difference predicted changes in CD8+ TIL density (AUC = 0.824).

CONCLUSION:

We established the MRI-derived radiomic signature for predicting CRT-induced alterations in CD8+ TILs. This study suggests the clinical utility of radiomics-immunophenotype modeling to evaluate tumor immune status following neoadjuvant chemoradiation in rectal cancer.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Rectal Neoplasms / Chemoradiotherapy Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Radiother Oncol Year: 2021 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Rectal Neoplasms / Chemoradiotherapy Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Radiother Oncol Year: 2021 Type: Article