Bronchoalveolar lavage fluid reveals factors contributing to the efficacy of PD-1 blockade in lung cancer

Autor: Kentaro Masuhiro, Motohiro Tamiya, Kosuke Fujimoto, Shohei Koyama, Yujiro Naito, Akio Osa, Takashi Hirai, Hidekazu Suzuki, Norio Okamoto, Takayuki Shiroyama, Kazumi Nishino, Yuichi Adachi, Takuro Nii, Yumi Kinugasa-Katayama, Akiko Kajihara, Takayoshi Morita, Seiya Imoto, Satoshi Uematsu, Takuma Irie, Daisuke Okuzaki, Taiki Aoshi, Yoshito Takeda, Toru Kumagai, Tomonori Hirashima, Atsushi Kumanogoh
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: JCI Insight, Vol 7, Iss 9 (2022)
Druh dokumentu: article
ISSN: 2379-3708
DOI: 10.1172/jci.insight.157915
Popis: Bronchoalveolar lavage is commonly performed to assess inflammation and identify responsible pathogens in lung diseases. Findings from bronchoalveolar lavage might be used to evaluate the immune profile of the lung tumor microenvironment (TME). To investigate whether bronchoalveolar lavage fluid (BALF) analysis can help identify patients with non–small cell lung cancer (NSCLC) who respond to immune checkpoint inhibitors (ICIs), BALF and blood were prospectively collected before initiating nivolumab. The secreted molecules, microbiome, and cellular profiles based on BALF and blood analysis of 12 patients were compared with regard to therapeutic effect. Compared with ICI nonresponders, responders showed significantly higher CXCL9 levels and a greater diversity of the lung microbiome profile in BALF, along with a greater frequency of the CD56+ subset in blood T cells, whereas no significant difference in PD-L1 expression was found in tumor cells. Antibiotic treatment in a preclinical lung cancer model significantly decreased CXCL9 in the lung TME, resulting in reduced sensitivity to anti–PD-1 antibody, which was reversed by CXCL9 induction in tumor cells. Thus, CXCL9 might be associated with the lung TME microbiome, and the balance of CXCL9 and lung TME microbiome could contribute to nivolumab sensitivity in patients with NSCLC. BALF analysis can help predict the efficacy of ICIs when performed along with currently approved examinations.
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