Table_4_TNF-Alpha Pathway Alternation Predicts Survival of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer.pdf
Translational research on immune checkpoint inhibitors (ICIs) has been underway. However, in the unselected population, only a few patients benefit from ICIs. Therefore, screening predictive markers of ICI efficacy has become the current focus of attention. We collected mutation and clinical data from an ICI-treated non-small cell lung cancer (NSCLC) cohort. Then, a univariate Cox regression model was used to analyze the relationship between tumor necrosis factor α signaling mutated (TNFα-MT) and the prognosis of immunotherapy for NSCLC. We retrospectively collected 36 NSCLC patients (local-cohort) from the Zhujiang Hospital of Southern Medical University and performed whole-exome sequencing (WES). The expression and mutation data of The Cancer Genome Atlas (TCGA)-NSCLC cohort were used to explore the association between TNFα-MT and the immune microenvironment. A local cohort was used to validate the association between TNFα-MT and immunogenicity. TNFα-MT was associated with significantly prolonged overall survival (OS) in NSCLC patients after receiving immunotherapy. Additionally, TNFα-MT is related to high immunogenicity (tumor mutational burden, neoantigen load, and DNA damage response signaling mutations) and enrichment of infiltrating immune cells. These results suggest that TNFα-MT may serve as a potential clinical biomarker for NSCLC patients receiving ICIs.
History
References
- https://doi.org//10.1002/cam4.1768
- https://doi.org//10.1016/j.lungcan.2020.07.007
- https://doi.org//10.1007/978-3-319-24223-1_1
- https://doi.org//10.1056/NEJMoa1616288
- https://doi.org//10.1002/ijc.32097
- https://doi.org//10.3322/caac.21442
- https://doi.org//10.1016/S1470-2045(15)70054-9
- https://doi.org//10.1056/NEJMoa1606774
- https://doi.org//10.1056/NEJMoa1504627
- https://doi.org//10.1016/j.pharmthera.2020.107694
- https://doi.org//10.1056/NEJMoa1501824
- https://doi.org//10.1016/S0140-6736(16)32517-X
- https://doi.org//10.1038/nature14011
- https://doi.org//10.1097/JTO.0000000000000526
- https://doi.org//10.1111/his.13729
- https://doi.org//10.1097/CJI.0000000000000249
- https://doi.org//10.1186/s12943-019-1062-7
- https://doi.org//10.1016/j.phrs.2020.105028
- https://doi.org//10.7554/eLife.49020
- https://doi.org//10.1158/0008-5472.CAN-18-1814
- https://doi.org//10.1200/JCO.2017.75.7740
- https://doi.org//10.1101/gr.219915.116
- https://doi.org//10.1126/science.aaa1348
- https://doi.org//10.1007/s00262-020-02668-8
- https://doi.org//10.1038/s41417-020-0207-6
- https://doi.org//10.1016/j.biopha.2020.110633
- https://doi.org//10.3390/cancers12071757
- https://doi.org//10.1186/s13045-019-0804-8
- https://doi.org//10.1080/2162402X.2016.1249090
- https://doi.org//10.1080/2162402X.2017.1412902
- https://doi.org//10.1016/j.cell.2019.06.014
- https://doi.org//10.1038/nature04444
- https://doi.org//10.1126/scisignal.2004088
- https://doi.org//10.1093/nar/gkv1507
- https://doi.org//10.1101/gr.239244.118
- https://doi.org//10.1016/j.immuni.2018.03.023
- https://doi.org//10.1200/PO.17.00073
- https://doi.org//10.1093/bioinformatics/btr260
- https://doi.org//10.1007/978-1-4939-7493-1_12
- https://doi.org//10.1089/omi.2011.0118
- https://doi.org//10.3389/fphar.2020.01213
- https://doi.org//10.1002/jcb.26005
- https://doi.org//10.4161/cbt.11.7.15060
- https://doi.org//10.3389/fimmu.2020.02039
- https://doi.org//10.2147/DDDT.S205633
- https://doi.org//10.1155/2016/8941260
- https://doi.org//10.3389/fphar.2020.00441
- https://doi.org//10.4049/jimmunol.1301317
- https://doi.org//10.1038/nri3862
- https://doi.org//10.1056/NEJMra1514296
- https://doi.org//10.1001/archsurg.2012.35
- https://doi.org//10.18632/oncotarget.7282
- https://doi.org//10.1200/JCO.2013.51.3002
- https://doi.org//10.1016/j.bbrc.2012.07.001
- https://doi.org//10.1007/s11010-016-2806-y
- https://doi.org//10.1016/j.ejca.2015.11.020
- https://doi.org//10.1007/s12307-015-0174-x
- https://doi.org//10.1084/jem.20190456
- https://doi.org//10.1038/nrclinonc.2017.101
- https://doi.org//10.1200/EDBK_240837
- https://doi.org//10.1016/j.ctrv.2017.11.007
- https://doi.org//10.3389/fonc.2021.670927
- https://doi.org//10.3389/fimmu.2021.634741
- https://doi.org//10.1038/s41591-018-0136-1
- https://doi.org//10.3389/fimmu.2021.630773
- https://doi.org//10.3389/fcell.2020.608969
- https://doi.org//10.1016/j.cell.2017.01.017
- https://doi.org//10.1038/nrc3239
- https://doi.org//10.7150/thno.33680
- https://doi.org//10.1126/science.aan6733
- https://doi.org//10.1056/NEJMc1713444
- https://doi.org//10.1126/science.aad1253
- https://doi.org//10.1038/s41577-019-0218-4
- https://doi.org//10.1016/j.jtho.2019.08.2509
- https://doi.org//10.1158/2159-8290.CD-14-1397
Usage metrics
Read the peer-reviewed publication
Categories
- Transplantation Immunology
- Tumour Immunology
- Immunology not elsewhere classified
- Immunology
- Veterinary Immunology
- Animal Immunology
- Genetic Immunology
- Applied Immunology (incl. Antibody Engineering, Xenotransplantation and T-cell Therapies)
- Autoimmunity
- Cellular Immunology
- Humoural Immunology and Immunochemistry
- Immunogenetics (incl. Genetic Immunology)
- Innate Immunity
