Systematic analysis of transcriptome signature for improving outcomes in lung adenocarcinoma-Reference-Cited by-同舟云学术

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Systematic analysis of transcriptome signature for improving outcomes in lung adenocarcinoma

Published:2023-05-09 Issue:11 Volume:149 Page:8951-8968
ISSN:0171-5216
Container-title:Journal of Cancer Research and Clinical Oncology
language:en
Short-container-title:J Cancer Res Clin Oncol

Author:

Ge Xiaoyong,Xu Hui,Weng Siyuan,Zhang Yuyuan,Liu Long,Wang Libo,Xing Zhe,Ba Yuhao,Liu Shutong,Li Lifeng,Wang Yuhui,Han Xinwei

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Oncology,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00432-023-04814-y.pdf

Reference46 articles.

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2. Arashi M, Roozbeh M, Hamzah NA, Gasparini M (2021) Ridge regression and its applications in genetic studies. PLoS One 16:e0245376. https://doi.org/10.1371/journal.pone.0245376

3. Bastien P, Bertrand F, Meyer N, Maumy-Bertrand M (2015) Deviance residuals-based sparse PLS and sparse kernel PLS regression for censored data. Bioinformatics (oxford, England) 31:397–404. https://doi.org/10.1093/bioinformatics/btu660

4. Boutsikou E, Domvri K, Hardavella G, Tsiouda D, Zarogoulidis K, Kontakiotis T (2018) Tumour necrosis factor, interferon-gamma and interleukins as predictive markers of antiprogrammed cell-death protein-1 treatment in advanced non-small cell lung cancer: a pragmatic approach in clinical practice. Ther Adv Med Oncol 10:1758835918768238. https://doi.org/10.1177/1758835918768238

5. Cancer Cell Line Encyclopedia Consortium; Genomics of Drug Sensitivity in Cancer Consortium (2015) Pharmacogenomic agreement between two cancer cell line data sets. Nature 528:84–87. https://doi.org/10.1038/nature15736

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