{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T16:14:45Z","timestamp":1779207285683,"version":"3.51.4"},"reference-count":26,"publisher":"American Society for Clinical Investigation","issue":"10","license":[{"start":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T00:00:00Z","timestamp":1778803200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,15]]},"abstract":"<jats:p>\n                    Immune checkpoint inhibitors (ICIs) have improved patient outcomes substantially in non\u2013small cell lung cancer (NSCLC). Despite considerable effort, our understanding of the features that predict for immunotherapy response and resistance in patients remains incomplete. In this issue of the\n                    <jats:italic>JCI<\/jats:italic>\n                    , Isomoto and colleagues utilized a multiplex IHC platform to profile the spatial organization of the lung cancer tumor immune microenvironment, enabling the identification of spatial immune features that correlate with immunotherapy efficacy. This study enhances our knowledge of the spatial organization of features impacting ICI efficacy by identifying a three-variable spatial composite \u2014 including CD73 upregulation in\n                    <jats:italic>EGFR<\/jats:italic>\n                    -mutant NSCLC \u2014 that substantially outperforms PD-L1 expression in predicting immunotherapy efficacy. Moreover, it establishes spatial proteomic profiling as a platform for generating therapeutic hypotheses that are actionable and mechanistic in NSCLC.\n                  <\/jats:p>","DOI":"10.1172\/jci206316","type":"journal-article","created":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T15:53:00Z","timestamp":1779205980000},"source":"Crossref","is-referenced-by-count":0,"title":["Understanding immune checkpoint inhibitor efficacy through spatial decoding of the lung cancer tumor immune microenvironment"],"prefix":"10.1172","volume":"136","author":[{"given":"Tao","family":"Zou","sequence":"first","affiliation":[{"name":"Hamon Center for Therapeutic Oncology Research,"},{"name":"Department of Internal Medicine,"},{"name":"Department of Immunology,"},{"name":"Harold C. Simmons Comprehensive Cancer Center, and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7776-0767","authenticated-orcid":true,"given":"John D.","family":"Minna","sequence":"additional","affiliation":[{"name":"Hamon Center for Therapeutic Oncology Research,"},{"name":"Department of Internal Medicine,"},{"name":"Harold C. Simmons Comprehensive Cancer Center, and"},{"name":"Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"232","published-online":{"date-parts":[[2026,5,15]]},"reference":[{"key":"B1","unstructured":"World Health Organization. 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