Single-sample enrichment analysis identified predictive biomarker candidates for nivolumab in patients with non-small cell lung cancer.
Authors: Tomoiki Aiba, Chieko Hattori, Jun Sugisaka, Hisashi Shimizu, Hirotaka Ono, Yutaka Domeki, Ryohei Saito, Sachiko Kawana, Yousuke Kawashima, Keisuke Terayama, Yukihiro Toi, Atsushi Nakamura, Shinsuke Yamanda, Yuichiro Kimura, Yutaka Suzuki, Atsushi Niida, Shunichi Sugawara
Journal: Journal of Clinical Oncology (2021)

e21097 Background: Although anti-PD-1/PD-L1 monotherapy has achieved clinical success in non-small cell lung cancer (NSCLC), definitive predictive biomarkers remain to be elucidated. We assumed that by combining gene expression signatures with patient clinical data, we could identify a novel promising biomarker to predict response to anti-PD-1/PD-L1 monotherapy in NSCLC patients. Moreover, the characterization of these signatures will help us to decipher the complexity of tumor-immune interactions and better understand the tumor microenvironment (TME) that favors clinical response to nivolumab monotherapy. Methods: From clinically annotated NSCLC patients (n = 40) with nivolumab monotherapy in the second- or later-line settings, we prospectively collected tumor tissues and peripheral blood mononuclear cells (PBMCs) before first dose of nivolumab and PBMCs after first 4 or 5 doses of nivolumab. All tumor tissue and PBMC samples obtained were applied to whole-transcriptome sequencing (RNA-seq). We extracted transcriptomic datasets of lung adenocarcinoma (LUAD) (n = 20) and lung squamous cell carcinoma (LUSC) (n = 18) from the results, separately analyzed each histological subtype. To elucidate biological processes associated with clinical outcomes, we performed a supervised gene set enrichment analysis (GSEA) approach and an unsupervised single sample scoring approach. Results: In LUAD, we observed that gene sets related to interferon (type I and II) signaling (‘IFN signatures’) and antigen processing and presentation (‘APP signatures’) were significantly enriched in pre-treatment PBMCs of responders. IFN and APP signatures, which are closely related to each other, functionally cooperate to activate anti-tumor immune response. The enrichment of IFN and APP signatures provides the possibility that responders have a pre-existing anti-tumor immunity prior to nivolumab monotherapy. In LUSC, neither IFN nor APP signatures were enriched in pre-treatment tumor tissues and PBMCs of responders. Instead, gene sets related to the regulation of the TME (‘TME signatures’) are significantly enriched in pre-treatment tumor tissues of non-responders. The enrichment of TME signatures suggested that non-responders have an extremely immunosuppressive TME. These findings highlighted that responsive LUAD inherently have a high immunogenicity to elicit effective anti-tumor responses, whereas responsive LUSC have a similar level of immunogenicity as non-responsive LUSC but are free from an extremely immunosuppressive TME. Conclusions: We found that nivolumab enhanced anti-tumor immunity in patients with LUAD in a quite different way from patients with LUSC. Our study provides a blueprint for innovating combinational immunotherapy and supporting patient selection and treatment strategies on long-term clinical outcomes.