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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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Figure 8

Heatmaps for differential gene expression.

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Heatmaps for differential gene expression.
Heatmaps for differential gen...
Heatmaps for differential gene expression in select transcriptional regulators, coinhibitory and costimulatory molecules, and cytokines and chemokines as well as their cognate receptors associated with exhaustion among the 6 groups in indicated cell types. Significance was set at P < 0.05, adjusted P < 0.1, and absolute log2 fold change >1. Moderated t-statistic from the limma package, with Benjamini and Hochberg’s adjustment for multiple testings.

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