Abstract
3015 Background: Use of antibiotics (ATB) alters the gut microbiota composition and decreases bacterial diversity. Pre-clinical evidences demonstrated the impact of the microbiota in the efficacy of immune checkpoint blockades (ICB) in cancer. Interaction between ATB and ICB has not been extensively investigated in cancer patients (pts). Our study evaluated the effect of ATB in cancer pts treated with PD-1/PD-L1 inhibitors. Methods: We conducted a retrospective analysis of pts treated with PD-1/PD-L1 inhibitors for advanced Renal Cell Carcinoma (RCC), Urothelial Cancer (UC) and Non-Small Cell Lung Cancer (NSCLC) and data on ATB use were collected. ATB(+)/(-) groups were defined as pts treated or not with ATB before (2 months period) or within the first month of ICB. PFS and OS were compared between both groups among all pts and then according to tumor site. Statistical analyses were performed using the Kaplan-Meier method. Cox regression analyses were performed separately for each cancer type adjusting for its specific risk factors. Results: Among 175 pts included, 51 (29%) received ATB (mostly beta-lactamases and fluoroquinolones). ATB(+) group had shorter PFS and OS when compared to ATB(-) group: 3.4 vs. 5.2 months, p < 0.013, and 12.2 vs. 20.8 months, p < 0.001, respectively. According to tumor type, ATB(+) group translated into decrease OS (7.0 vs. 13.8 months, p < 0.038) in NSCLC. In RCC and UC pts, ATB (+) group had shorter PFS when compared to ATB(-) group (4.3 vs. 7.4 months, p < 0.013 and 1.8 vs. 4.3 months, p = 0.048, respectively). The negative impact of ATB was maintained after multivariate analyses adjusting for risk factors in each tumor type. Conclusions: ATB prescription preceding or concomitant to the first injection of PD-1/PD-L1 inhibitors impaired the outcome in patients with advanced cancers. This reduction in efficacy seems to be independent of classical prognostic factors in RCC, UC and NSCLC. These data should be validated in larger cohort. In addition, the role of gut composition to explain this interaction is ongoing, as well as novel diagnosis tools based on microbiota to predict response/resistance to ICB.
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