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Poster Discussion session - Basic science

3759 - Identification of a Radio-Immune Signature with High Prognostic Value in Surgically Resected NSCLC

Date

29 Sep 2019

Session

Poster Discussion session - Basic science

Presenters

Giulia Mazzaschi

Citation

Annals of Oncology (2019) 30 (suppl_5): v797-v815. 10.1093/annonc/mdz269

Authors

G. Mazzaschi1, F. Quaini2, G. Milanese3, L. Gnetti4, G. Bocchialini2, L. Ampollini2, R. Minari5, M. Silva3, N. Sverzellati3, G. Roti2, M. Tiseo1

Author affiliations

  • 1 Medical Oncology Unit, University Hospital of Parma, 43126 - Parma/IT
  • 2 Medicine And Surgery, University of Parma, 43126 - Parma/IT
  • 3 Radiology, University of Parma, 43126 - Parma/IT
  • 4 Pathology, Azienda Ospedaliera di Parma, 43126 - Parma/IT
  • 5 Medicine And Surgery, AOU di Parma, 43126 - Parma/IT

Resources

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Abstract 3759

Background

The role of radiomics against clinical and histologic standard has been repeatedly demonstrated, although the integration of high-throughput imaging into a multidimensional prediction model is still in its early dawn. Thus, the aim of the present study was to determine whether CT-derived radiomic features (CT-RFs) might intercept the landscaped arrangement of the tumor immune microenvironment (TIME), offering a novel non-invasive assessment of prognostic factors in NSCLC.

Methods

A cohort of 100 (70 training and 30 validation) surgically resected NSCLC was investigated. TIME was classified according to PD-L1 and Tumor Infiltrating Lymphocytes (TILs) levels and further defined as hot, intermediate or cold by the relative contribution of effector and suppressor phenotypes. Extracted CT-RFs were correlated to TIME profiles and ROC curves were used to test the accuracy of the radiomic predictor. The impact of integrated radio-immune parameters on clinical outcome was estimated by Kaplan Meier method.

Results

Patient-specific tissue immune profiles were reflected by a strong correlation between CT-RFs and TIME parameters (U-Mann Whitney Test). Cluster Tendency and GrayLevelNonUniformity were upregulated in PD-L1high and TILs rich tumors (p < 0.01), while Skewness and Coarseness were correlated to PD-L1low and TILs poor (p < 005) samples, respectively. Among 13 CT extracted features distinctive of hot TIME (hCT-RFs), the most significantly upregulated were Energy, Busyness, and Entropy (p < 0.01), underlining the heterogeneous nature of inflamed NSCLC. Conversely, cold TIME-related features (cCT-RFs) showed a restricted variability being essentially confined to LowGrayLevelEmphasis (p < 0.001). When hCT-RFs and cCT-RFs were entered together in a multivariate logistic regression model, a highly specific and sensitive radiomic predictor of hot (1.00 AUC, p < 0.001) and cold (0.92 AUC, p = 0.001) TIME was revealed. Strikingly, a progressive decrease in OS and DFS (Kaplan Meier, p < 0.001) was documented, respectively, in hot, intermediate and cold NSCLC as defined by the radio-immune model.

Conclusions

Specific TIME profiles inscribe radiomic features resulting in a radio-immune signature with prognostic impact on NSCLC.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

University of Parma.

Funding

University of Parma.

Disclosure

All authors have declared no conflicts of interest.

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