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Background: PD-L1 immunohistochemistry (IHC) staining is currently accepted as the gold-standard biomarker for immune therapy in advanced non-small cell lung cancer (NSCLC). However, the use of various antibodies and cut-offs as well as certain degree of subjectivity in pathological evaluation has overshadowed the clear-cut predictive performance of PD-L1 expression. Multiplexed technologies can be of help in this setting providing an objective measurement of PD-L1 levels. On the other hand, gene expression signatures incorporating not only PD-L1 but also other components of the stroma might better capture the immune-context of the molecular heterogeneity of NSCLC tumors. nCounter gene expression technology is an alternative method to measure PD-L1 gene expression by digital counting proving a direct measurement of mRNA levels. Methods: A 7-gene ‘immune signature’ comprising CD4, CD8, programmed cell death-1 (PD-1), programmed death-ligand 1 (PD-L1), interferon gamma (IFNG), granzyme M (GZMM) and forkhead box P3 (FOXP3) were included in a customized nCounter panel (NanoString Technologies), used in our institution on a routine basis to simultaneously screen for relevant oncogenic-drivers (ALK, ROS1, RET, NTRK1 gene fusions and METΔ14 mutation). Total RNA obtained from formalin-fixed paraffin embedded (FFPE) samples was used for PD-L1 digital counting (nCounter) which was normalised with six housekeeping genes (ACTB, MRPL19, PSMC4, RPLP0, SF3A1, GAPDH) and compared with PD-L1 protein IHC evaluation using whole tissue section with 22C3 monoclonal mouse anti-PD-L1 antibody measured on tumor cells. Results: A total of 425 FFPE samples from advanced NSCLC were analyzed with the nCounter panel. Among them, 25 samples were not evaluable (5.9%). PD-L1 IHC was available for 163 FFPE samples and were compared with nCounter PD-L1 expression results. By IHC, 63/163 samples (38.65%) were scored as negative for PD-L1 protein expression, whereas 100/163 (61.35%) were evaluated as positive. Among positive, 62 (38.04%) and 38 (23.31%) presented a moderate (≥ 1-49%) and high PD-L1 staining (≥50%) respectively. Using an appropriate cut-off value (IHC≥1%), PD-L1 mRNA expression levels correlated with PD-L1 IHC evaluation with a 76% of concordance and a 0.755 Cohen’s kappa (confidence interval 95% 0.651- 0.858). Unsupervised clustering across of mRNA expression data from 395 samples using the seven-immune-related genes and correlations between each immune gene were performed and a high correlation was found between PD-1 and FOXP3 (r=0.9) and PD-1 with GZMM (r=0.8). Conclusions: PD-L1 mRNA gene expression shows promising in predicting PD-L1 protein expression in NSCLC. Further clinical validation is ongoing to confirm if PD-L1 gene expression by nCounter can be an alternative to IHC to select patients’ candidates for immune check-point inhibitors. Citation Format: Cristina Teixido, Elba Marin, Cristina Aguado, Laia Pare, Ana Gimenez-Capitan, Sandra Lopez-Prades, Andres Felipe Cardona, Carlos Cabrera, Elena Gonzalvo, Laura Lopez, Ruth Roman, Daniel Martinez, Ivana Sullivan, Pedro Jares, Aleix Prat, Miguel Angel Molina-Vila, Noemi Reguart. Concordance of mRNA expression (nCounter) and protein expression (IHC) for the detection of PD-L1 in patients with advanced non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 131.

Introduction: A large group of lymph node-positive breast cancer patients receive neoadjuvant chemotherapy and subsequently undergo axillary lymph node dissection. It has been previously proposed that axillary lymph node dissection may be avoided-and it's associated reduced morbidity-in patients showing pathologic complete response. Therefore, the purpose of this study was to develop a nomogram to predict axillary node pathologic response to neoadjuvant chemotherapy in breast cancer patients in order to guide the surgical treatment decision-making process for this group of patients. Methods: A cross-sectional, secondary data study was carried out between 2013-2016 on 222 lymph node-positive breast cancer patients who received neoadjuvant chemotherapy followed by locoregional management, including axillary lymph node dissection. Logistic regression analysis was performed to determine the association of the axillary pathologic complete response with the different clinical and pathological variables. Variables found to be statistically significantly associated with axillary pCR (pathologic complete response) were used to create the logistic regression model and the nomogram in pre-menopausal patients. Axillary pCR was defined as absence of residual disease in the breast and of micro-metastasis in axillary lymph nodes. Samples with isolated tumor cells were considered as positive for residual disease. Results: a total of 222 patients were included, of which 131 were premenopausal at the time of diagnosis. Axillary pathologic complete response was observed in 55.7% (73 of 131) of patients, and was significantly associated with estrogen receptor (ER) negative tumors (OR 2.59, 95%CI 1.21-5.53), progesterone receptor (PR) negative tumors (OR 2.63, 95%CI 1.28-5.38), and Her2 positive tumors (OR 0.40, 95%CI 0.19-0.84), for which a significant correlation with increased probability of achieving axillary pathologic complete response was evidenced. Conclusion: The performance of this model to predict axillary pCR in pre-menopausal patients was weak, and therefore the decision to avoid surgical axillary dissection should not be based solely on the developed nomogram. However, further studies may lead to validation of this model.