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Usage Information

Immune reprogramming via PD-1 inhibition enhances early-stage lung cancer survival
Geoffrey J. Markowitz, Lauren S. Havel, Michael J.P. Crowley, Yi Ban, Sharrell B. Lee, Jennifer S. Thalappillil, Navneet Narula, Bhavneet Bhinder, Olivier Elemento, Stephen T.C. Wong, Dingcheng Gao, Nasser K. Altorki, Vivek Mittal
Geoffrey J. Markowitz, Lauren S. Havel, Michael J.P. Crowley, Yi Ban, Sharrell B. Lee, Jennifer S. Thalappillil, Navneet Narula, Bhavneet Bhinder, Olivier Elemento, Stephen T.C. Wong, Dingcheng Gao, Nasser K. Altorki, Vivek Mittal
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Research Article Immunology Oncology

Immune reprogramming via PD-1 inhibition enhances early-stage lung cancer survival

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Abstract

Success of immune checkpoint inhibitors in advanced non-small-cell lung cancer (NSCLC) has invigorated their use in the neoadjuvant setting for early-stage disease. However, the cellular and molecular mechanisms of the early immune responses to therapy remain poorly understood. Through an integrated analysis of early-stage NSCLC patients and a Kras mutant mouse model, we show a prevalent programmed cell death 1/programmed cell death 1 ligand 1 (PD-1/PD-L1) axis exemplified by increased intratumoral PD-1+ T cells and PD-L1 expression. Notably, tumor progression was associated with spatiotemporal modulation of the immune microenvironment with dominant immunosuppressive phenotypes at later phases of tumor growth. Importantly, PD-1 inhibition controlled tumor growth, improved overall survival, and reprogrammed tumor-associated lymphoid and myeloid cells. Depletion of T lymphocyte subsets demonstrated synergistic effects of those populations on PD-1 inhibition of tumor growth. Transcriptome analyses revealed T cell subset–specific alterations corresponding to degree of response to the treatment. These results provide insights into temporal evolution of the phenotypic effects of PD-1/PD-L1 activation and inhibition and motivate targeting of this axis early in lung cancer progression.

Authors

Geoffrey J. Markowitz, Lauren S. Havel, Michael J.P. Crowley, Yi Ban, Sharrell B. Lee, Jennifer S. Thalappillil, Navneet Narula, Bhavneet Bhinder, Olivier Elemento, Stephen T.C. Wong, Dingcheng Gao, Nasser K. Altorki, Vivek Mittal

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Usage data is cumulative from December 2024 through December 2025.

Usage JCI PMC
Text version 1,010 219
PDF 99 21
Figure 511 6
Supplemental data 221 22
Citation downloads 73 0
Totals 1,914 268
Total Views 2,182
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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