Genome-wide DNA methylation profile analysis identifies an individualized predictive signature for melanoma immune response-Reference-Cited by-同舟云学术

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Genome-wide DNA methylation profile analysis identifies an individualized predictive signature for melanoma immune response

Published:2023-01 Issue:1 Volume:149 Page:343-356
ISSN:0171-5216
Container-title:Journal of Cancer Research and Clinical Oncology
language:en
Short-container-title:J Cancer Res Clin Oncol

Author:

Yan Junya,Wu Xiaowen,Zhu Yanyan,Cang Shundong

Funder

National Natural Science Foundation of China

CSCO-Roche Cancer Research Fund 2019

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Oncology,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00432-022-04566-1.pdf

Reference47 articles.

1. Accomando WP, Wiencke JK, Houseman EA, Nelson HH, Kelsey KT (2014) Quantitative reconstruction of leukocyte subsets using DNA methylation. Genome Biol 15(3):R50. https://doi.org/10.1186/gb-2014-15-3-r50

2. Ayers M, Lunceford J, Nebozhyn M, Murphy E, Loboda A, Kaufman DR et al (2017) IFN-γ-related mRNA profile predicts clinical response to PD-1 blockade. J Clin Invest 127(8):2930–2940. https://doi.org/10.1172/JCI91190

3. Becht E, Giraldo NA, Lacroix L, Buttard B, Elarouci N, Petitprez F et al (2016) Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression. Genome Biol 17(1):218. https://doi.org/10.1186/s13059-016-1070-5

4. Carlino MS, Larkin J, Long GV (2021) Immune checkpoint inhibitors in melanoma. Lancet 398(10304):1002–1014. https://doi.org/10.1016/S0140-6736(21)01206-X

5. Chen B, Khodadoust MS, Liu CL, Newman AM, Alizadeh AA (2018) Profiling tumor infiltrating immune cells with CIBERSORT. Methods Mol Biol 17(11):243–259. https://doi.org/10.1007/978-1-4939-7493-1_12

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