Crosstalk among Alternative Polyadenylation, Genetic Variants and Ubiquitin Modification Contribute to Lung Adenocarcinoma Risk
Abstract
:1. Introduction
2. Results
2.1. Screening for APA-Related E3s in LUAD
2.2. RNF213 Was Positively Correlated with the Poor Prognosis of LUAD
2.3. Mutations in apaQTL-SNPs Regulating RNF213 Are Associated with an Increased Risk of LUAD
2.4. ZBTB20 Is a Potential Substrate for Ubiquitination by RNF213 in LUAD
2.5. RNF213 Mediates ZBTB20 Ubiquitination and Degradation to Suppress LUAD Progression
3. Discussion
4. Materials and Methods
4.1. Acquisition and Processing of Proteomics and Genomics Data
4.2. Prediction of Substrate Proteins
4.3. Protein-Protein Docking Assay
4.4. Cell Culture and Transfection
4.5. Western Blot Assay
4.6. Co-Immunoprecipitation (Co-IP) and Ubiquitination Assay
4.7. Cell Counting Kit-8 (CCK8) Assay
4.8. Statistical Analysis
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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SNPs | Gene | Location (hg37) | Genotypes | Cases, n (100%) | Controls, n (100%) | Adjusted OR (95%CI) a | p |
---|---|---|---|---|---|---|---|
rs41301932 | RNF213 | chr17:78406974 | GG | 3109 (90.04%) | 3413 (92.00%) | 1 (ref) | - |
GA | 333 (9.64%) | 291 (7.84%) | 1.26 (1.07–1.49) | 0.005 | |||
AA | 11 (0.32%) | 6 (0.16%) | 2.05 (0.76–5.57) | 0.157 | |||
Dominant model | 1.28 (1.09–1.51) | 0.003 | |||||
Additive model | 1.28 (1.09–1.50) | 0.002 | |||||
rs4494603 | RNF213 | chr17:78408213 | CC | 3056 (88.50%) | 3373 (90.92%) | 1 (ref) | - |
CG | 385 (11.15%) | 327 (8.81%) | 1.31 (1.12–1.53) | 0.001 | |||
GG | 12 (0.35%) | 10 (0.27%) | 1.32 (0.57–3.07) | 0.516 | |||
Dominant model | 1.31 (1.12–1.52) | 0.001 | |||||
Additive model | 1.29 (1.11–1.49) | 0.001 | |||||
rs9890400 | RNF213 | chr17:78416493 | AA | 1097 (31.77%) | 1267 (34.15%) | 1 (ref) | - |
AG | 1641 (47.52%) | 1732 (46.68%) | 1.09 (0.98–1.21) | 0.106 | |||
GG | 715 (20.71%) | 711 (19.16%) | 1.16 (1.02–1.32) | 0.028 | |||
Dominant model | 1.11 (1.01–1.23) | 0.037 | |||||
Additive model | 1.08 (1.01–1.15) | 0.023 | |||||
rs56066320 | RNF213 | chr17:78418906 | CC | 2942 (85.20%) | 3257 (87.79%) | 1 (ref) | - |
CG | 493 (14.28%) | 437 (11.78%) | 1.25 (1.09–1.44) | 0.002 | |||
GG | 18 (0.52%) | 16 (0.43%) | 1.30 (0.66–2.55) | 0.453 | |||
Dominant model | 1.25 (1.09–1.44) | 0.001 | |||||
Additive model | 1.23 (1.08–1.40) | 0.001 | |||||
rs13341123 | RNF213 | chr17:78427033 | GG | 2987 (86.50%) | 3297 (88.87%) | 1 (ref) | - |
GT | 451 (13.06%) | 400 (10.78%) | 1.24 (1.07–1.43) | 0.003 | |||
TT | 15 (0.44%) | 13 (0.35%) | 1.14 (0.79–1.66) | 0.486 | |||
Dominant model | 1.24 (1.08–1.43) | 0.003 | |||||
Additive model | 1.23 (1.07–1.41) | 0.003 |
Variables | CPTAC Discovery Study | Chinese LUAD Study | TCGA-LUAD | FLCCA GWAS | ||||
---|---|---|---|---|---|---|---|---|
Case (n = 101) | p Value (RNF213) | Case (n = 103) | p Value (RNF213) | Case (n = 515) | p Value (RNF213) | Case (n = 3453) | Control (n = 3710) | |
Age, n (100%) | 0.357 | 0.632 | 0.958 | |||||
≤60 | 41 (40.59%) | 51 (49.51%) | 159 (30.87%) | 1669 (48.33%) | 2013 (54.26%) | |||
>60 | 60 (59.41%) | 52 (50.49%) | 337 (65.44%) | 1784 (51.67%) | 1697 (45.74%) | |||
Unknown | 0 | 0 | 19 (3.69%) | 0 | 0 | |||
Gender | 0.979 | 0.176 | 0.617 | |||||
Female | 37 (36.63%) | 65 (63.11%) | 276 (53.59%) | |||||
Male | 64 (63.37%) | 38 (36.89%) | 239 (46.41%) | |||||
Stage, n (100%) | 0.795 | 0.011 | 0.867 | |||||
I | 54 (53.47%) | 51 (49.51%) | 276 (53.59%) | |||||
II | 29 (28.71%) | 17 (16.51%) | 121 (23.50%) | |||||
III/IV | 18 (17.82%) | 35 (33.98%) | 110 (21.36%) | |||||
Unknown | 0 | 0 | 8 (1.55%) | |||||
Pathologic T, n (100%) | 0.306 | 0.672 | 0.581 | |||||
T1/T2 | 89 (88.12%) | 85 (82.52%) | 446 (86.60%) | |||||
T3/T4 | 12 (11.88%) | 18 (17.48%) | 66 (12.82%) | |||||
Unknown | 0 | 0 | 3 (0.58%) | |||||
Pathologic N, n (100%) | 0.646 | 0.020 | 0.744 | |||||
N0 | 71 (70.30%) | 64 (62.14%) | 332 (64.47%) | |||||
N1 | 14 (13.86%) | 10 (9.71%) | 95 (18.45%) | |||||
N2/N3 | 16 (15.84%) | 29 (28.16%) | 76 (14.76%) | |||||
Unknown | 0 | 0 | 12 (2.30%) | |||||
Pathologic M, n (100%) | 0.230 | 0.282 | 0.757 | |||||
M0 | 83 (82.18) | 101 (98.06%) | 346 (67.18%) | |||||
M1 | 1 (0.99%) | 2 (1.94%) | 25 (4.85%) | |||||
Unknown | 17 (16.83%) | 0 (0%) | 144 (27.77%) |
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Wu, Y.; Yuan, Y.; Xu, H.; Zhang, W.; Ning, A.; Li, S.; Chen, Q.; Tao, X.; Pan, G.; Tian, T.; et al. Crosstalk among Alternative Polyadenylation, Genetic Variants and Ubiquitin Modification Contribute to Lung Adenocarcinoma Risk. Int. J. Mol. Sci. 2024, 25, 8084. https://doi.org/10.3390/ijms25158084
Wu Y, Yuan Y, Xu H, Zhang W, Ning A, Li S, Chen Q, Tao X, Pan G, Tian T, et al. Crosstalk among Alternative Polyadenylation, Genetic Variants and Ubiquitin Modification Contribute to Lung Adenocarcinoma Risk. International Journal of Molecular Sciences. 2024; 25(15):8084. https://doi.org/10.3390/ijms25158084
Chicago/Turabian StyleWu, Yutong, Yanqiong Yuan, Huiwen Xu, Wendi Zhang, Anhui Ning, Siqi Li, Qiong Chen, Xiaobo Tao, Gongbu Pan, Tian Tian, and et al. 2024. "Crosstalk among Alternative Polyadenylation, Genetic Variants and Ubiquitin Modification Contribute to Lung Adenocarcinoma Risk" International Journal of Molecular Sciences 25, no. 15: 8084. https://doi.org/10.3390/ijms25158084