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Purpose: Chemo-radiotherapy (CRT) is the standard treatment for non-metastatic anal squamous cell carcinomas (ASCC). Despite excellent results for T1-2 stages, relapses still occur in around 35% of locally advanced tumors. Recent strategies focus on treatment intensification, but could benefit from a better patient selection. Our goal was to assess the prognostic value of pre-therapeutic MRI radiomics on 2-year disease control (DC). Methods: We retrospectively selected patients with non-metastatic ASCC treated at the CHU Bordeaux and in the French FFCD0904 multicentric trial. Radiomic features were extracted from T2-weighted pre-therapeutic MRI delineated sequences. After random division between training and testing sets on a 2:1 ratio, univariate and multivariate analysis were performed on the training cohort to select optimal features. The correlation with 2-year DC was assessed using logistic regression models, with AUC and accuracy as performance gauges, and the prediction of disease-free survival using Cox regression and Kaplan-Meier analysis. Results: A total of 82 patients were randomized in the training (n = 54) and testing sets (n = 28). At 2 years, 24 patients (29%) presented relapse. In the training set, two clinical (tumor size and CRT length) and two radiomic features (FirstOrder_Entropy and GLCM_JointEnergy) were associated with disease control in univariate analysis and included in the model. The clinical model was outperformed by the mixed (clinical and radiomic) model in both the training (AUC 0.758 versus 0.825, accuracy of 75.9% versus 87%) and testing (AUC 0.714 versus 0.898, accuracy of 78.6% versus 85.7%) sets, which led to distinctive high and low risk of disease relapse groups (HR 8.60, p = 0.005). Conclusion: A mixed model with two clinical and two radiomic features was predictive of 2-year disease control after CRT and could contribute to identify high risk patients amenable to treatment intensification with view of personalized medicine.

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Background: TILs and iGES are associated with pathologic complete response (pCR) and relapse-free survival (RFS) in HER2+ breast cancer, however they have typically not been compared. Here we examine the prognostic value of iGES vs. TILs, alone and together, in two different HER2+ neoadjuvant trials: the chemotherapy plus HER2targeting trial C40601, and the all-biologic trial PAMELA.Methods: Gene expression profiling by mRNA sequencing (RNAseq) and TILs (per 2014 TILs working group) as a continuous variable were assessed on 230 C40601 and 139 PAMELA pre-treatment samples. iGES scores were calculated by extracting the median expression of all genes within a signature. Association with pCR and RFS was studied by logistic regression and Cox analyses. To compare the goodness of fit of different models, we used the Akaike Information Criterion (AIC). To compare the prognostic ability of two nested models, we used the Likelihood-Ratio test (LRT).Results: Every 1% increase in TILs was associated with a significant 1% increase in the odds of pCR in C40601 (odds ratio [OR] 1.01, p < 0.01) and a 2% increase in PAMELA (OR 1.02, p ¼ 0.04). TILs were not associated with RFS at 7 years in C40601 (Hazard ratio [HR] 0.99, p ¼ 0.21). Of the 210 iGES tested, 130 (61.9%) were correlated with TILs across the 2 trials (p < 0.05), and 13 iGES were also significantly associated with higher pCR rates in both studies (ORs range 1.05-2.33, p < 0.05). 11 of 13 iGES outperformed TILs for pCR prediction, 7 of which were B-cell-related iGES. In a multivariate Cox model including clinical factors and PAM50 subtype, 8 of these iGES, but not TILS, were independently associated with RFS (iGES HRs range 0.56-0.72, p values < 0.05; TILs HR 0.99, p ¼ 0.38).Conclusions: In C40601 and PAMELA, multiple, mostly B-cell-related, iGES performed better than TILs for pCR prediction. In C40601, TILs did not provide additional RFS information to clinical parameters, subtype, and multiple GES. When both TILs and iGES are available, the prognostic value of RNA-based signatures is superior.

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