AUTHOR=Gao Yuzhen , Chen Shipeng , Vafaei Somayeh , Zhong Xiaoli TITLE=Tumor-Infiltrating Immune Cell Signature Predicts the Prognosis and Chemosensitivity of Patients With Pancreatic Ductal Adenocarcinoma JOURNAL=Frontiers in Oncology VOLUME=10 YEAR=2020 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2020.557638 DOI=10.3389/fonc.2020.557638 ISSN=2234-943X ABSTRACT=Objective

Tumor-infiltrating immune cells might add a predictive value for the prognostic stratification of patients with pancreatic ductal adenocarcinoma (PDAC) and chemotherapy response. We aimed to develop a prognostic model based on the tumor-infiltrating immune cell signature to improve the prediction of survival and chemotherapy benefits of patients with PDAC.

Methods

The abundance of tumor-infiltrating immune cells for 661 patients with PDAC from four different cohorts with survival data was collected in the training cohorts. Cox regression analysis and meta-analysis of immune cells were conducted to generate the tumor immune cell score (TICS) for prognostic stratification. Other two independent cohorts including 188 patients were then used to validate the model. Those patients who underwent chemotherapy were used to further analyze the value of TICS for predicting the chemotherapy response. Furthermore, the difference in the somatic mutations and immune-related molecules between the TICS subgroups was analyzed.

Results

6 out of 28 immune cells were found to be significantly associated with PDAC prognosis in the training cohorts (all P < 0.05). The developed TICS could significantly predict the PDAC survival and chemotherapy benefit both in the training and the external validation cohorts (log-rank test, P < 0.05). Significant differences were found in different TICS subgroups in terms of the immune characteristics, checkpoint genes, and tumor mutational burden. Functional and pathway analyses further proved that the TICS was significantly related to the tumor immunity response in patients with PDAC.

Conclusion

TICS might be used to predict PDAC patients with a better survival and greater chemotherapy benefit.