No abstract

Purpose: Immunoscore is a prognostic tool defined to quantify in situ immune cell infiltrates, which appears to be superior to the tumor-node-metastasis (TNM) classification in colorectal cancer. In non-small cell lung cancer (NSCLC), no immunoscore has been established, but in situ tumor immunology is recognized as highly important. We have previously evaluated the prognostic impact of several immunological markers in NSCLC, yielding the density of stromal CD8 þ tumor-infiltrating lymphocytes (TIL) as the most promising candidate. Hence, we validate the impact of stromal CD8 þ TIL density as an immunoscore in NSCLC.Experimental Design: The prognostic impact of stromal CD8þ TILs was evaluated in four different cohorts from Norway and Denmark consisting of 797 stage I-IIIA NSCLC patients. The Tromso cohort (n ¼ 155) was used as training set, and the results were further validated in the cohorts from Bodo (n ¼ 169), Oslo (n ¼ 295), and Denmark (n ¼ 178). Tissue microarrays and clinical routine CD8 staining were used for all cohorts.Results: Stromal CD8 þ TIL density was an independent prognostic factor in the total material (n ¼ 797) regardless of the endpoint: disease-free survival (P < 0.001), disease-specific survival (P < 0.001), or overall survival (P < 0.001). Subgroup analyses revealed significant prognostic impact of stromal CD8 þ TIL density within each pathologic stage (pStage). In multivariate analysis, stromal CD8 þ TIL density and pStage were independent prognostic variables. Conclusions: Stromal CD8 þ TIL density has independent prognostic impact in resected NSCLC, adds prognostic impact within each pStage, and is a good candidate marker for establishing a TNM-Immunoscore.

One training dataset of 132 and two validation datasets of 62 and 94stage I-IV NSCLC patients were included. Interchangeability was assessed by performing a linear regression on CT and CBCT extracted features. A two-step correction was applied prior to model validation of a previously published radiomic signature. Results 13.3% (149 out of 1119) of the radiomic features, including all features of the previously published radiomic signature, showed an R above 0.85 between intermodal imaging techniques. For the radiomic signature, Kaplan-Meier curves were significantly different between groups with high and low prognostic value for both modalities. Harrell's concordance index was 0.69 for CT and 0.66 for CBCT models for dataset 1. Conclusions The results show that a subset of radiomic features extracted from CT and CBCT images are interchangeable using simple linear regression. Moreover, a previously developed radiomics signature has prognostic value for overall survival in three CBCT cohorts, showing the potential of CBCT radiomics to be used as prognostic imaging biomarker.