Development and validation of the immune signature to predict distant metastasis in patients with nasopharyngeal carcinoma.

J Immunother Cancer

Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong Province, People's Republic of China

Published: April 2020

Background: The tumor immune microenvironment has clinicopathological significance in predicting prognosis and therapeutic efficacy. We aimed to develop an immune signature to predict distant metastasis in patients with nasopharyngeal carcinoma (NPC).

Methods: Using multiplexed quantitative fluorescence, we detected 17 immune biomarkers in a primary screening cohort of 54 NPC tissues presenting with/without distant metastasis following radical therapy. The LASSO (least absolute shrinkage and selection operator) logistic regression model used statistically significant survival markers in the training cohort (n=194) to build an immune signature. The prognostic and predictive accuracy of it was validated in an external independent group of 304 patients.

Results: Eight statistically significant markers were identified in the screening cohort. The immune signature consisting of four immune markers (PD-L1+ CD163+, CXCR5, CD117) in intratumor was adopted to classify patients into high and low risk in the training cohort and it showed a high level of reproducibility between different batches of samples (r=0.988 for intratumor; p<0.0001). High-risk patients had shorter distant metastasis-free survival (HR 5.608, 95% CI 2.619 to 12.006; p<0.0001) and progression-free survival (HR 2.798, 95% CI 1.498 to 5.266; p=0·001). The C-indexes which reflected the predictive capacity in training and validation cohort were 0.703 and 0.636, respectively. Low-risk patients benefited from induction chemotherapy plus concurrent chemoradiotherapy (IC+CCRT) (HR 0.355, 95% CI 0.147 to 0.857; p=0·021), while high-risk patients did not (HR 1.329, 95% CI 0.543 to 3.253; p=0·533). To predict the individual risk of distant metastasis, nomograms with the integration of both immune signature and clinicopathological risk factors were developed.

Conclusions: The immune signature provided a reliable estimate of distant metastasis risk in patients with NPC and might be applied to identify the cohort which benefit from IC+CCRT.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204817PMC
http://dx.doi.org/10.1136/jitc-2019-000205DOI Listing

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