The DOI matches its Crossref record; 132 of the 132 references it cites were found in a registry or an index.
Tertiary lymphoid structures, drivers of the anti‐tumor responses in human cancers
Abstract
Summary: The characterization of the microenvironment of human tumors led to the description of tertiary lymphoid structures (TLS) characterized by mature dendritic cells in a T‐cell zone adjacent to B‐cell follicle including a germinal center.TLS represent sites of lymphoid neogenesis that develop in most solid cancers. Analysis of the current literature shows that the TLS presence is associated with a favorable clinical outcome for cancer patients, regardless of the approach used to quantify TLS and the stage of the disease. Using several approaches that combine immunohistochemistry, gene expression assays, and flow cytometry on large series of lung tumors, our work demonstrated that TLS are important sites for the initiation and/or maintenance of the local and systemic T‐ and B‐cell responses against tumors. Surrounded by high endothelial venules, they represent a privileged area for the recruitment of lymphocytes into tumors and generation of central‐memory T and B cells that circulate and limit cancer progression.TLS can be considered as a novel biomarker to stratify the overall survival risk of untreated cancer patients and as a marker of efficient immunotherapies. The induction and manipulation of cancer‐associated TLS using drug agonists and/or biotherapies should open new avenues to treat cancer patients.
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Mantovani, A., Allavena, P., Sica, A., & Balkwill, F. (2008) · Nature · doi:10.1038/nature07205 · Cited by 11,399
Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome
Galon, J., Costes, A., Sanchez-Cabo, F., Kirilovsky, A., Mlecnik, B., Lagorce-Pagès, C., Tosolini, M., Camus, M., Berger, A., Wind, P., et al. (2006) · Science · doi:10.1126/science.1129139 · Cited by 6,516
Self-citationInvolvement of chemokine receptors in breast cancer metastasis
Müller, A., Homey, B., Soto, H., Ge, N., Catron, D., Buchanan, M. E., McClanahan, T., Murphy, E., Yuan, W., Wagner, S. N., et al. (2001) · Nature · doi:10.1038/35065016 · Cited by 5,340
The immune contexture in human tumours: impact on clinical outcome
Fridman, W. H., Pagès, F., Sautès-Fridman, C., & Galon, J. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3245 · Cited by 4,981
Self-citationSpatiotemporal Dynamics of Intratumoral Immune Cells Reveal the Immune Landscape in Human Cancer
Bindea, G., Mlecnik, B., Tosolini, M., Kirilovsky, A., Waldner, M., Obenauf, A. C., Angell, H., Fredriksen, T., Lafontaine, L., Berger, A., et al. (2013) · Immunity · doi:10.1016/j.immuni.2013.10.003 · Cited by 4,422
Self-citationCancer immunotherapy comes of age
Mellman, I., Coukos, G., & Dranoff, G. (2011) · Nature · doi:10.1038/nature10673 · Cited by 3,893
Effector Memory T Cells, Early Metastasis, and Survival in Colorectal Cancer
Pagès, F., Berger, A., Camus, M., Sanchez-Cabo, F., Costes, A., Molidor, R., Mlecnik, B., Kirilovsky, A., Nilsson, M., Damotte, D., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa051424 · Cited by 2,135 · cited 1×
“Thus, high densities of CD8 T cells and CD45RO memory T cells correlate with a favorable prognosis, when located at both the IM and CT (2, 3).”
BackgroundSelf-citationCancer immunotherapy via dendritic cells
Palucka, K., & Banchereau, J. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3258 · Cited by 2,049
RANK is essential for osteoclast and lymph node development.
Dougall, W. C., Glaccum, M., Charrier, K., Rohrbach, K., Brasel, K., De Smedt, T., Daro, E., Smith, J., Tometsko, M. E., Maliszewski, C. R., et al. (1999) · Genes & Development · doi:10.1101/gad.13.18.2412 · Cited by 1,478
Dangers of Using "Optimal" Cutpoints in the Evaluation of Prognostic Factors
Altman, D. G., Lausen, B., Sauerbrei, W., & Schumacher, M. (1994) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/86.11.829 · Cited by 1,143
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Elements of cancer immunity and the cancer–immune set point
Chen, D. S., & Mellman, I. (2017) · Nature · doi:10.1038/nature21349 · Cited by 5,352
The immune contexture in cancer prognosis and treatment
Fridman, W. H., Zitvogel, L., Sautès–Fridman, C., & Kroemer, G. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.101 · Cited by 2,263
Self-citationTertiary lymphoid structures in the era of cancer immunotherapy
Sautès-Fridman, C., Petitprez, F., Calderaro, J., & Fridman, W. H. (2019) · Nature reviews. Cancer · doi:10.1038/s41568-019-0144-6 · Cited by 1,884
The clinical role of the TME in solid cancer
Giraldo, N. A., Sanchez-Salas, R., Peske, J. D., Vano, Y., Becht, E., Petitprez, F., Validire, P., Ingels, A., Cathelineau, X., Fridman, W. H., et al. (2019) · British Journal of Cancer · doi:10.1038/s41416-018-0327-z · Cited by 732
Self-citationImproving immunotherapy outcomes with anti-angiogenic treatments and vice versa
Khan, K. A., & Kerbel, R. S. (2018) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2018.9 · Cited by 657
Metadata
- Authors
- Dieu‐Nosjean, M., Giraldo, N. A., Kaplon, H., Germain, C., Fridman, W. H., & Sautès‐Fridman, C.
- Venue
- Immunological Reviews
- Publisher
- Wiley
- Published
- 2016-04-18
- Volume
- 271
- Issue
- 1
- Pages
- 260-275
- ISSN
- 0105-2896 (ISSN-L)
- 1600-065X
- OpenAlex
- W2339442385
- Cited by
- 417
- References
- 132
- FWCI
- 3.63
- Type
- journal article
- Language
- en
- Open access
- closed
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