The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Temporal and spatial discordance of programmed cell death-ligand 1 expression and lymphocyte tumor infiltration between paired primary lesions and brain metastases in lung cancer
Open accessAbstract
BACKGROUND: The dynamics of PD-L1 expression may limit its use as a tissue-based predictive biomarker. We sought to expand our understanding of the dynamics of PD-L1 expression and tumor-infiltrating lymphocytes (TILs) in patients with lung cancer-related brain metastases. EXPERIMENTAL DESIGN: Paired primary lung cancers and brain metastases were identified and assessed for PD-L1 and CD3 expression by immunohistochemistry. Lesions with 5% or greater PD-L1 expression were considered positive. Agreement statistics and the χ(2) or Fisher's exact test were used for analysis. RESULTS: We analyzed 146 paired lesions from 73 cases. There was disagreement of tumor cell PD-L1 expression in 10 cases (14%, κ = 0.71), and disagreement of TIL PD-L1 expression in 19 cases (26%, κ = 0.38). Most paired lesions with discordant tumor cell expression of PD-L1 were obtained 6 or more months apart. When specimens were categorized using a proposed tumor microenvironment categorization scheme based on PD-L1 expression and TILs, there were significant changes in the classifications because many of the brain metastases lacked either PD-L1 expression, tumor lymphocyte infiltration or both even when they were present in the primary lung cancer specimens (P = 0.009). CONCLUSIONS: We identified that there are significant differences between the tumor microenvironment of paired primary lung cancers and brain metastases. When physicians decide to treat patients with lung cancer with a PD-1 or PD-L1 inhibitor, they must do so in the context of the spatial and temporal heterogeneity of the tumor microenvironment.
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PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F.-A., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E.-M., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,845
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
Wanchoo, R., Karam, S., Uppal, N. N., Barta, V. S., Deray, G., Devoe, C., Launay-Vacher, V., Jhaveri, K. D., & on behalf of Cancer and Kidney International Network Workgroup on Immune Checkpoint Inhibitors (2017) · American Journal of Nephrology · doi:10.1159/000455014 · Cited by 15,256
The blockade of immune checkpoints in cancer immunotherapy
Pardoll, D. M. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3239 · Cited by 13,838
Circos: An information aesthetic for comparative genomics
Krzywinski, M., Schein, J., Birol, İ., Connors, J., Gascoyne, R., Horsman, D., Jones, S. J., & Marra, M. A. (2009) · Genome Research · doi:10.1101/gr.092759.109 · Cited by 10,964
Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer
Borghaei, H., Paz-Ares, L., Horn, L., Spigel, D. R., Steins, M., Ready, N. E., Chow, L. Q., Vokes, E. E., Felip, E., Holgado, E., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1507643 · Cited by 9,335
Nivolumab versus Docetaxel in Advanced Squamous-Cell Non–Small-Cell Lung Cancer
Brahmer, J., Reckamp, K. L., Baas, P., Crinò, L., Eberhardt, W. E. E., Poddubskaya, E., Antonia, S., Pluzanski, A., Vokes, E. E., Holgado, E., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1504627 · Cited by 8,447
Herbst, R. S., Baas, P., Kim, D.-W., Felip, E., Pérez-Gracia, J. L., Han, J.-Y., Molina, J., Kim, J.-H., Arvis, C. D., Ahn, M.-J., et al. (2016) · The Lancet · doi:10.1016/s0140-6736(15)01281-7 · Cited by 6,449
Tumor-associated B7-H1 promotes T-cell apoptosis: A potential mechanism of immune evasion
Dong, H., Strome, S. E., Salomao, D. R., Tamura, H., Hirano, F., Flies, D. B., Roche, P. C., Lu, J., Zhu, G., Tamada, K., et al. (2002) · Nature Medicine · doi:10.1038/nm730 · Cited by 5,025
Self-citationDong, H., Zhu, G., Tamada, K., & Chen, L. (1999) · Nature Medicine · doi:10.1038/70932 · Cited by 2,496
Self-citationTaube, J. M., Anders, R. A., Young, G. D., Xu, H., Sharma, R., McMiller, T. L., Chen, S., Klein, A. P., Pardoll, D. M., Topalian, S. L., et al. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003689 · Cited by 2,157
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Davis, A. A., & Patel, V. G. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0768-9 · Cited by 960
Hendry, S., Salgado, R., Gevaert, T., Russell, P. A., John, T., Thapa, B., Christie, M., van de Vijver, K., Estrada, M. V., Gonzalez-Ericsson, P. I., et al. (2017) · Advances in Anatomic Pathology · doi:10.1097/pap.0000000000000162 · Cited by 709
PD-1 and PD-L1 in cancer immunotherapy: clinical implications and future considerations
Jiang, Y., Chen, M., Nie, H., & Yuan, Y. (2019) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2019.1571892 · Cited by 640
Fu, T., Dai, L.-J., Wu, S.-Y., Xiao, Y., Ma, D., Jiang, Y.-Z., & Shao, Z.-M. (2021) · Journal of Hematology & Oncology · doi:10.1186/s13045-021-01103-4 · Cited by 480
Metadata
- Authors
- Mansfield, A. S., Aubry, M. C., Moser, J. C., Harrington, S. M., Dronca, R. S., Park, S. S., & Dong, H.
- Venue
- Annals of Oncology
- Publisher
- Elsevier BV
- Published
- 2016-10
- Volume
- 27
- Issue
- 10
- Pages
- 1953-1958
- ISSN
- 0923-7534 (ISSN-L)
- OpenAlex
- W2493219106
- Cited by
- 336
- References
- 28
- FWCI
- 17.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Mansfield, A. S., Aubry, M. C., Moser, J. C., Harrington, S. M., Dronca, R. S., Park, S. S., & Dong, H. (2016). Temporal and spatial discordance of programmed cell death-ligand 1 expression and lymphocyte tumor infiltration between paired primary lesions and brain metastases in lung cancer. Annals of Oncology. https://doi.org/10.1093/annonc/mdw289
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
