Identification of Ubiquitin-Related Gene-Pair Signatures for Predicting Tumor Microenvironment Infiltration and Drug Sensitivity of Lung Adenocarcinoma
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Multi-Omics Data Extraction and Patient Information Precondition
2.2. Construction of Differentially Expressed Ubiquitin-Related Gene Pairs (UbRGPs)
2.3. Consensus Clustering
2.4. Immune Infiltration Analysis in the Tumor Microenvironment (TME)
2.5. Analysis of Somatic Mutations in LUAD
2.6. Establishment and Evaluation of UbRGPs-Related Prognostic Signature
2.7. Correlation Analysis and Clinical Stratification Analysis
2.8. Construction of Calibration Curves and Nomogram
2.9. Chemotherapeutic Drug Susceptibility Prediction
2.10. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR)
2.11. Statistical Analysis
3. Results
3.1. Construction of Differentially Expressed UbRGPs and Identification of LUAD Subtypes
3.2. Tumor Microenvironment Characterization in Two Subtypes
3.3. Establishment and Evaluation of Prognostic Signature
3.4. Correlation between the Clinical Features and Risk Score
3.5. Establishment and Evaluation of Clinical Nomogram and Calibration Curves
3.6. TME Cell Infiltration Characteristics and Somatic Mutation
3.7. Relationship between Drug Sensitivity and Prognostic Signature
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
ANKRD13B | Ankyrin repeat domain 13B |
CDF | Cumulative distribution function |
CI | Confidence interval |
DCUN1D5 | Defective in cullin neddylation 1 domain-containing 5 |
FBXL8 | F-box and leucine-rich repeat protein 8 |
FBXW7 | F-box and WD repeat domain-containing 7 |
GAPDH | Glyceraldehyde 3-phosphate dehydrogenase |
GO | Gene Ontology |
GSEA | Gene-Set Enrichment Analysis |
HCK | Hematopoietic cell kinase |
HR | Hazard ratio |
ICI | Immune checkpoint inhibitor |
ISG15 | ISG15 ubiquitin-like modifier |
IPS | Immunophenoscore |
KBTBD12 | Kelch repeat and BTB domain-containing 12 |
KEGG | Kyoto Encyclopedia of Genes and Genomes |
KLHL35 | Kelch-like family member 35 |
LASSO | Least absolute shrinkage and selection operator |
LUAD | Lung adenocarcinoma |
NSCLC | Non-small cell lung cancer |
OS | Overall survival |
TCGA | The Cancer Genome Atlas |
TMB | Tumor mutation burden |
TME | Tumor microenvironment |
TRAIP | Tumor necrosis factor receptor-associated factor-interacting protein |
TRIM6 | Tripartite motif-containing 6 |
UBE2 | Ubiquitin binding enzyme E2 |
UbRGs | Ubiquitin-related genes |
UbRGPs | Ubiquitin-related gene pairs |
UHRF1 | Ubiquitin-like with PHD and ring-finger domains 1 |
References
- Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
- Ettinger, D.S.; Wood, D.E.; Aisner, D.L.; Akerley, W.; Bauman, J.; Chirieac, L.R.; D’Amico, T.A.; DeCamp, M.M.; Dilling, T.J.; Dobelbower, M.; et al. Non-Small Cell Lung Cancer, Version 5.2017, NCCN Clinical Practice Guidelines in Oncology. J. Natl. Compr. Cancer Netw. 2017, 15, 504–535. [Google Scholar] [CrossRef] [PubMed]
- Miller, M.; Hanna, N. Advances in systemic therapy for non-small cell lung cancer. BMJ 2021, 375, n2363. [Google Scholar] [CrossRef] [PubMed]
- Zhou, J.; Xu, Y.; Lin, S.; Guo, Y.; Deng, W.; Zhang, Y.; Guo, A.; Xue, Y. iUUCD 2.0: An update with rich annotations for ubiquitin and ubiquitin-like conjugations. Nucleic Acids Res. 2018, 46, D447–D453. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhou, X.; Sun, S.C. Targeting ubiquitin signaling for cancer immunotherapy. Signal Transduct. Target. Ther. 2021, 6, 16. [Google Scholar] [CrossRef]
- Ge, Z.; Leighton, J.S.; Wang, Y.; Peng, X.; Chen, Z.; Chen, H.; Sun, Y.; Yao, F.; Li, J.; Zhang, H.; et al. Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types. Cell Rep. 2018, 23, 213–226.e213. [Google Scholar] [CrossRef] [Green Version]
- Yang, S.; Yao, B.; Wu, L.; Liu, Y.; Liu, K.; Xu, P.; Zheng, Y.; Deng, Y.; Zhai, Z.; Wu, Y.; et al. Ubiquitin-related molecular classification and risk stratification of hepatocellular carcinoma. Mol. Ther.-Oncolytics 2021, 21, 207–219. [Google Scholar] [CrossRef]
- Huang, X.; Dixit, V.M. Drugging the undruggables: Exploring the ubiquitin system for drug development. Cell Res. 2016, 26, 484–498. [Google Scholar] [CrossRef]
- Swisher, E.M.; Lin, K.K.; Oza, A.M.; Scott, C.L.; Giordano, H.; Sun, J.; Konecny, G.E.; Coleman, R.L.; Tinker, A.V.; O’Malley, D.M.; et al. Rucaparib in relapsed, platinum-sensitive high-grade ovarian carcinoma (ARIEL2 Part 1): An international, multicentre, open-label, phase 2 trial. Lancet. Oncol. 2017, 18, 75–87. [Google Scholar] [CrossRef] [Green Version]
- Fan, Q.; Wang, Q.; Cai, R.; Yuan, H.; Xu, M. The ubiquitin system: Orchestrating cellular signals in non-small-cell lung cancer. Cell. Mol. Biol. Lett. 2020, 25, 1. [Google Scholar] [CrossRef] [Green Version]
- Huang, Y.; Yang, X.; Lu, Y.; Zhao, Y.; Meng, R.; Zhang, S.; Dong, X.; Xu, S.; Wu, G. UBE2O targets Mxi1 for ubiquitination and degradation to promote lung cancer progression and radioresistance. Cell Death Differ. 2021, 28, 671–684. [Google Scholar] [CrossRef]
- Yang, F.; Xu, J.; Li, H.; Tan, M.; Xiong, X.; Sun, Y. FBXW2 suppresses migration and invasion of lung cancer cells via promoting β-catenin ubiquitylation and degradation. Nat. Commun. 2019, 10, 1382. [Google Scholar] [CrossRef] [Green Version]
- Yen, M.A.-O.; Wu, K.A.-O.; Liu, Y.A.-O.; Chang, Y.Y.; Chang, C.Y.; Hung, J.A.-O.; Tsai, Y.M.; Hsu, Y.L. Ubiquitin Conjugating Enzyme E2 H (UBE2H) Is Linked to Poor Outcomes and Metastasis in Lung Adenocarcinoma. Biology 2021, 10, 378. [Google Scholar] [CrossRef]
- Liu, Z.; Xu, L. UBE2S promotes the proliferation and survival of human lung adenocarcinoma cells. BMB Rep. 2018, 51, 642–647. [Google Scholar] [CrossRef]
- Tang, X.K.; Wang, K.J.; Tang, Y.K.; Chen, L. Effects of ubiquitin-conjugating enzyme 2C on invasion, proliferation and cell cycling of lung cancer cells. Asian Pac. J. Cancer Prev. 2014, 15, 3005–3009. [Google Scholar] [CrossRef]
- Yu, B.; Li, T.; Chen, J.; Wang, F.Q.; Fu, J.H.; Liu, S.M.; Wang, Y.; Zhang, X.; Yang, H.T. Identification of activated pathways in lung adenocarcinoma based on network strategy. J. Cancer Res. Ther. 2020, 16, 793–799. [Google Scholar] [CrossRef]
- Xiao, G.; Li, Y.; Wang, M.; Li, X.; Qin, S.; Sun, X.; Liang, R.; Zhang, B.; Du, N.; Xu, C.; et al. FBXW7 suppresses epithelial-mesenchymal transition and chemo-resistance of non-small-cell lung cancer cells by targeting snai1 for ubiquitin-dependent degradation. Cell Prolif. 2018, 51, e12473. [Google Scholar] [CrossRef] [Green Version]
- Xiao, Y.; Yin, C.; Wang, Y.; Lv, H.; Wang, W.; Huang, Y.; Perez-Losada, J.; Snijders, A.M.; Mao, J.H.; Zhang, P. FBXW7 deletion contributes to lung tumor development and confers resistance to gefitinib therapy. Mol. Oncol. 2018, 12, 883–895. [Google Scholar] [CrossRef] [Green Version]
- Yokobori, T.; Yokoyama, Y.; Mogi, A.; Endoh, H.; Altan, B.; Kosaka, T.; Yamaki, E.; Yajima, T.; Tomizawa, K.; Azuma, Y.; et al. FBXW7 mediates chemotherapeutic sensitivity and prognosis in NSCLCs. Mol. Cancer Res. 2014, 12, 32–37. [Google Scholar] [CrossRef] [Green Version]
- Jin, J.O.; Puranik, N.; Bui, Q.T.; Yadav, D.; Lee, P.C. The Ubiquitin System: An Emerging Therapeutic Target for Lung Cancer. Int. J. Mol. Sci. 2021, 22, 9629. [Google Scholar] [CrossRef]
- Li, B.; Cui, Y.; Diehn, M.; Li, R. Development and Validation of an Individualized Immune Prognostic Signature in Early-Stage Nonsquamous Non-Small Cell Lung Cancer. JAMA Oncol. 2017, 3, 1529–1537. [Google Scholar] [CrossRef]
- Kim, S.; Lin, C.W.; Tseng, G.C. MetaKTSP: A meta-analytic top scoring pair method for robust cross-study validation of omics prediction analysis. Bioinformatics 2016, 32, 1966–1973. [Google Scholar] [CrossRef] [Green Version]
- Monti, S.; Tamayo, P.; Mesirov, J.; Golub, T. Consensus clustering: A resampling-based method for class discovery and visualization of gene expression microarray data. Mach. Learn. 2003, 52, 91–118. [Google Scholar] [CrossRef]
- Wilkerson, M.D.; Hayes, D.N. ConsensusClusterPlus: A class discovery tool with confidence assessments and item tracking. Bioinformatics 2010, 26, 1572–1573. [Google Scholar] [CrossRef] [Green Version]
- Li, W.; Wang, H.; Ma, Z.; Zhang, J.; Ou-Yang, W.; Qi, Y.; Liu, J. Multi-omics Analysis of Microenvironment Characteristics and Immune Escape Mechanisms of Hepatocellular Carcinoma. Front. Oncol. 2019, 9, 1019. [Google Scholar] [CrossRef] [Green Version]
- Yu, G.; Wang, L.G.; Han, Y.; He, Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. Omics 2012, 16, 284–287. [Google Scholar] [CrossRef]
- Yoshihara, K.; Shahmoradgoli, M.; Martínez, E.; Vegesna, R.; Kim, H.; Torres-Garcia, W.; Treviño, V.; Shen, H.; Laird, P.W.; Levine, D.A.; et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat. Commun. 2013, 4, 2612. [Google Scholar] [CrossRef]
- Tamminga, M.; Hiltermann, T.J.N.; Schuuring, E.; Timens, W.; Fehrmann, R.S.; Groen, H.J. Immune microenvironment composition in non-small cell lung cancer and its association with survival. Clin. Transl. Immunol. 2020, 9, e1142. [Google Scholar] [CrossRef]
- Chen, B.; Khodadoust, M.S.; Liu, C.L.; Newman, A.M.; Alizadeh, A.A. Profiling Tumor Infiltrating Immune Cells with CIBERSORT. Methods Mol. Biol. 2018, 1711, 243–259. [Google Scholar] [CrossRef]
- Racle, J.; Gfeller, D. EPIC: A Tool to Estimate the Proportions of Different Cell Types from Bulk Gene Expression Data. Methods Mol. Biol. 2020, 2120, 233–248. [Google Scholar] [CrossRef]
- Dienstmann, R.; Villacampa, G.; Sveen, A.; Mason, M.J.; Niedzwiecki, D.; Nesbakken, A.; Moreno, V.; Warren, R.S.; Lothe, R.A.; Guinney, J. Relative contribution of clinicopathological variables, genomic markers, transcriptomic subtyping and microenvironment features for outcome prediction in stage II/III colorectal cancer. Ann. Oncol. 2019, 30, 1622–1629. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Finotello, F.; Mayer, C.; Plattner, C.; Laschober, G.; Rieder, D.; Hackl, H.; Krogsdam, A.; Loncova, Z.; Posch, W.; Wilflingseder, D.; et al. Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data. Genome Med. 2019, 11, 34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Li, T.; Fu, J.; Zeng, Z.; Cohen, D.; Li, J.; Chen, Q.; Li, B.; Liu, X.S. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020, 48, W509–W514. [Google Scholar] [CrossRef] [PubMed]
- Aran, D. Cell-Type Enrichment Analysis of Bulk Transcriptomes Using xCell. Methods Mol. Biol. 2020, 2120, 263–276. [Google Scholar] [CrossRef] [PubMed]
- Charoentong, P.; Finotello, F.; Angelova, M.; Mayer, C.; Efremova, M.; Rieder, D.; Hackl, H.; Trajanoski, Z. Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade. Cell Rep. 2017, 18, 248–262. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chalmers, Z.R.; Connelly, C.F.; Fabrizio, D.; Gay, L.; Ali, S.M.; Ennis, R.; Schrock, A.; Campbell, B.; Shlien, A.; Chmielecki, J.; et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017, 9, 34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mayakonda, A.; Lin, D.C.; Assenov, Y.; Plass, C.; Koeffler, H.P. Maftools: Efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 2018, 28, 1747–1756. [Google Scholar] [CrossRef] [Green Version]
- Xiang, G.; Dong, X.; Xu, T.; Feng, Y.; He, Z.; Ke, C.; Xiao, J.; Weng, Y.M. A Nomogram for Prediction of Postoperative Pneumonia Risk in Elderly Hip Fracture Patients. Risk Manag. Healthc. Policy 2020, 13, 1603–1611. [Google Scholar] [CrossRef]
- Geeleher, P.; Cox, N.; Huang, R.S. pRRophetic: An R package for prediction of clinical chemotherapeutic response from tumor gene expression levels. PLoS ONE 2014, 9, e107468. [Google Scholar] [CrossRef]
- Jurmeister, P.; Vollbrecht, C.; Behnke, A.; Frost, N.; Arnold, A.; Treue, D.; Rückert, J.C.; Neudecker, J.; Schweizer, L.; Klauschen, F.; et al. Next generation sequencing of lung adenocarcinoma subtypes with intestinal differentiation reveals distinct molecular signatures associated with histomorphology and therapeutic options. Lung Cancer 2019, 138, 43–51. [Google Scholar] [CrossRef]
- Frost, N.; Kollmeier, J.; Vollbrecht, C.; Grah, C.; Matthes, B.; Pultermann, D.; von Laffert, M.; Lüders, H.; Olive, E.; Raspe, M.; et al. KRAS(G12C)/TP53 co-mutations identify long-term responders to first line palliative treatment with pembrolizumab monotherapy in PD-L1 high (≥50%) lung adenocarcinoma. Transl. Lung Cancer Res. 2021, 10, 737–752. [Google Scholar] [CrossRef]
- Bommeljé, C.C.; Weeda, V.B.; Huang, G.; Shah, K.; Bains, S.; Buss, E.; Shaha, M.; Gönen, M.; Ghossein, R.; Ramanathan, S.Y.; et al. Oncogenic function of SCCRO5/DCUN1D5 requires its Neddylation E3 activity and nuclear localization. Clin. Cancer Res. 2014, 20, 372–381. [Google Scholar] [CrossRef] [Green Version]
- Oh, J.; Pradella, D.; Shao, C.; Li, H.; Choi, N.; Ha, J.; Ruggiero, S.; Fu, X.D.; Zheng, X.; Ghigna, C.; et al. Widespread Alternative Splicing Changes in Metastatic Breast Cancer Cells. Cells 2021, 10, 858. [Google Scholar] [CrossRef]
- Long, W.; Li, Q.; Zhang, J.; Xie, H. Identification of key genes in the tumor microenvironment of lung adenocarcinoma. Med. Oncol. 2021, 38, 83. [Google Scholar] [CrossRef]
- Ziegler, S.F.; Marth, J.D.; Lewis, D.B.; Perlmutter, R.M. Novel protein-tyrosine kinase gene (hck) preferentially expressed in cells of hematopoietic origin. Mol. Cell. Biol. 1987, 7, 2276–2285. [Google Scholar] [CrossRef]
- Poh, A.R.; Love, C.G.; Masson, F.; Preaudet, A.; Tsui, C.; Whitehead, L.; Monard, S.; Khakham, Y.; Burstroem, L.; Lessene, G.; et al. Inhibition of Hematopoietic Cell Kinase Activity Suppresses Myeloid Cell-Mediated Colon Cancer Progression. Cancer Cell 2017, 31, 563–575.e565. [Google Scholar] [CrossRef] [Green Version]
- Yoo, L.; Yoon, A.R.; Yun, C.O.; Chung, K.C. Covalent ISG15 conjugation to CHIP promotes its ubiquitin E3 ligase activity and inhibits lung cancer cell growth in response to type I interferon. Cell Death Dis. 2018, 9, 97. [Google Scholar] [CrossRef] [Green Version]
- Tessema, M.; Yingling, C.M.; Thomas, C.L.; Klinge, D.M.; Bernauer, A.M.; Liu, Y.; Dacic, S.; Siegfried, J.M.; Dahlberg, S.E.; Schiller, J.H.; et al. SULF2 methylation is prognostic for lung cancer survival and increases sensitivity to topoisomerase-I inhibitors via induction of ISG15. Oncogene 2012, 31, 4107–4116. [Google Scholar] [CrossRef] [Green Version]
- Tao, J.; Hua, P.; Wen, J.; Hu, Y.; Yang, H.; Xie, X. Prognostic value of ISG15 mRNA level in drinkers with esophageal squamous cell cancers. Int. J. Clin. Exp. Pathol. 2015, 8, 10975–10984. [Google Scholar]
- Jinawath, N.; Furukawa, Y.; Hasegawa, S.; Li, M.; Tsunoda, T.; Satoh, S.; Yamaguchi, T.; Imamura, H.; Inoue, M.; Shiozaki, H.; et al. Comparison of gene-expression profiles between diffuse- and intestinal-type gastric cancers using a genome-wide cDNA microarray. Oncogene 2004, 23, 6830–6844. [Google Scholar] [CrossRef] [Green Version]
- Fu, J.; Li, Y.; Li, C.; Tong, Y.; Li, M.; Cang, S. A special prognostic indicator: Tumor mutation burden combined with immune infiltrates in lung adenocarcinoma with TP53 mutation. Transl. Cancer Res. 2021, 10, 3963–3978. [Google Scholar] [CrossRef]
- Shitani, M.; Sasaki, S.; Akutsu, N.; Takagi, H.; Suzuki, H.; Nojima, M.; Yamamoto, H.; Tokino, T.; Hirata, K.; Imai, K.; et al. Genome-wide analysis of DNA methylation identifies novel cancer-related genes in hepatocellular carcinoma. Tumour Biol. 2012, 33, 1307–1317. [Google Scholar] [CrossRef]
- Morris, M.R.; Ricketts, C.J.; Gentle, D.; McRonald, F.; Carli, N.; Khalili, H.; Brown, M.; Kishida, T.; Yao, M.; Banks, R.E.; et al. Genome-wide methylation analysis identifies epigenetically inactivated candidate tumour suppressor genes in renal cell carcinoma. Oncogene 2011, 30, 1390–1401. [Google Scholar] [CrossRef] [Green Version]
- Wei, F.; Ma, C.; Zhou, T.; Dong, X.; Luo, Q.; Geng, L.; Ding, L.; Zhang, Y.; Zhang, L.; Li, N.; et al. Exosomes derived from gemcitabine-resistant cells transfer malignant phenotypic traits via delivery of miRNA-222-3p. Mol. Cancer 2017, 16, 132. [Google Scholar] [CrossRef] [Green Version]
- Pastuszak-Lewandoska, D.; Domańska-Senderowska, D.; Antczak, A.; Kordiak, J.; Górski, P.; Czarnecka, K.H.; Migdalska-Sęk, M.; Nawrot, E.; Kiszałkiewicz, J.M.; Brzeziańska-Lasota, E. The Expression Levels of IL-4/IL-13/STAT6 Signaling Pathway Genes and SOCS3 Could Help to Differentiate the Histopathological Subtypes of Non-Small Cell Lung Carcinoma. Mol. Diagn. Ther. 2018, 22, 621–629. [Google Scholar] [CrossRef]
- Dai, L.; Li, Z.; Tao, Y.; Liang, W.; Hu, W.; Zhou, S.; Fu, X.; Wang, X. Emerging roles of suppressor of cytokine signaling 3 in human cancers. Biomed. Pharmacother. 2021, 144, 112262. [Google Scholar] [CrossRef]
- Liu, Y.; Fan, X.; Zhao, Z.; Shan, X. LncRNA SLC7A11-AS1 Contributes to Lung Cancer Progression Through Facilitating TRAIP Expression by Inhibiting miR-4775. OncoTargets Ther. 2020, 13, 6295–6302. [Google Scholar] [CrossRef]
- Han, Y.G.; Yun, M.; Choi, M.; Lee, S.G.; Kim, H. TRAIP regulates Histone H2B monoubiquitination in DNA damage response pathways. Oncol. Rep. 2019, 41, 3305–3312. [Google Scholar] [CrossRef]
- Li, J.; Yu, T.; Yan, M.; Zhang, X.; Liao, L.; Zhu, M.; Lin, H.; Pan, H.; Yao, M. DCUN1D1 facilitates tumor metastasis by activating FAK signaling and up-regulates PD-L1 in non-small-cell lung cancer. Exp. Cell Res. 2019, 374, 304–314. [Google Scholar] [CrossRef]
- Cuella-Martin, R.; Hayward, S.B.; Fan, X.; Chen, X.; Huang, J.W.; Taglialatela, A.; Leuzzi, G.; Zhao, J.; Rabadan, R.; Lu, C.; et al. Functional interrogation of DNA damage response variants with base editing screens. Cell 2021, 184, 1081–1097.e1019. [Google Scholar] [CrossRef]
- Guo, Z.; Zeng, Y.; Chen, Y.; Liu, M.; Chen, S.; Yao, M.; Zhang, P.; Zhong, F.; Jiang, K.; He, S.; et al. TRAIP promotes malignant behaviors and correlates with poor prognosis in liver cancer. Biomed. Pharmacother. 2020, 124, 109857. [Google Scholar] [CrossRef] [PubMed]
- Li, M.; Wu, W.; Deng, S.; Shao, Z.; Jin, X. TRAIP modulates the IGFBP3/AKT pathway to enhance the invasion and proliferation of osteosarcoma by promoting KANK1 degradation. Cell Death Dis. 2021, 12, 767. [Google Scholar] [CrossRef] [PubMed]
- Ding, D.X.; Li, Q.; Shi, K.; Li, H.; Guo, Q.; Zhang, Y.Q. LncRNA NEAT1-miR-101-3p/miR-335-5p/miR-374a-3p/miR-628-5p-TRIM6 axis identified as the prognostic biomarker for lung adenocarcinoma via bioinformatics and meta-analysis. Transl. Cancer Res. 2021, 10, 4870–4883. [Google Scholar] [CrossRef] [PubMed]
- Wei, C.; Wu, J.; Liu, W.; Lu, J.; Li, H.; Hai, B. Tripartite motif-containing protein 6 facilitates growth and migration of breast cancer through degradation of STUB1. Eur. J. Histochem. 2021, 65, 3214. [Google Scholar] [CrossRef]
- Zhao, H.; Huang, J.; Chen, M.; Li, B.; Chen, X.; Zhou, M. Tripartite Motif Protein 6 Promotes Colorectal Cancer Cell Migration and Metastasis via SOCS2-STAT3 Signaling. Front. Oncol. 2021, 11, 695525. [Google Scholar] [CrossRef]
- Zheng, S.; Zhou, C.; Wang, Y.; Li, H.; Sun, Y.; Shen, Z. TRIM6 promotes colorectal cancer cells proliferation and response to thiostrepton by TIS21/FoxM1. J. Exp. Clin. Cancer Res. 2020, 39, 23. [Google Scholar] [CrossRef]
- Daskalos, A.; Oleksiewicz, U.; Filia, A.; Nikolaidis, G.; Xinarianos, G.; Gosney, J.R.; Malliri, A.; Field, J.K.; Liloglou, T. UHRF1-mediated tumor suppressor gene inactivation in nonsmall cell lung cancer. Cancer 2011, 117, 1027–1037. [Google Scholar] [CrossRef]
- Unoki, M.; Daigo, Y.; Koinuma, J.; Tsuchiya, E.; Hamamoto, R.; Nakamura, Y. UHRF1 is a novel diagnostic marker of lung cancer. Br. J. Cancer 2010, 103, 217–222. [Google Scholar] [CrossRef] [Green Version]
- Tu, Z.; Deng, X.; Hou, S.; Feng, A.; Zhang, Q. UHRF1 predicts poor prognosis by triggering cell cycle in lung adenocarcinoma. J. Cell. Mol. Med. 2020, 24, 8069–8077. [Google Scholar] [CrossRef]
- Tian, D.; Tang, J.; Geng, X.; Li, Q.; Wang, F.; Zhao, H.; Narla, G.; Yao, X.; Zhang, Y. Targeting UHRF1-dependent DNA repair selectively sensitizes KRAS mutant lung cancer to chemotherapy. Cancer Lett. 2020, 493, 80–90. [Google Scholar] [CrossRef]
- Ren, X.B.; Zhao, J.; Liang, X.F.; Guo, X.D.; Jiang, S.B.; Xiang, Y.Z. Identification TRIM46 as a Potential Biomarker and Therapeutic Target for Clear Cell Renal Cell Carcinoma Through Comprehensive Bioinformatics Analyses. Front. Med. 2021, 8, 785331. [Google Scholar] [CrossRef]
- Meng, M.; Lan, T.; Tian, D.; Qin, Z.; Li, Y.; Li, J.; Cao, H. Integrative Bioinformatics Analysis Demonstrates the Prognostic Value of Chromatin Accessibility Biomarkers in Clear Cell Renal Cell Carcinoma. Front. Oncol. 2021, 11, 814396. [Google Scholar] [CrossRef]
- Chang, S.C.; Hsu, W.; Su, E.C.; Hung, C.S.; Ding, J.L. Human FBXL8 Is a Novel E3 Ligase Which Promotes BRCA Metastasis by Stimulating Pro-Tumorigenic Cytokines and Inhibiting Tumor Suppressors. Cancers 2020, 12, 2210. [Google Scholar] [CrossRef]
- Chang, S.C.; Hung, C.S.; Zhang, B.X.; Hsieh, T.H.; Hsu, W.; Ding, J.L. A Novel Signature of CCNF-Associated E3 Ligases Collaborate and Counter Each Other in Breast Cancer. Cancers 2021, 13, 2873. [Google Scholar] [CrossRef]
- Wang, B.; Wang, X.; Tseng, Y.; Huang, M.; Luo, F.; Zhang, J.; Liu, J. Distinguishing colorectal adenoma from hyperplastic polyp by WNT2 expression. J. Clin. Lab. Anal. 2021, 35, e23961. [Google Scholar] [CrossRef]
- Landi, L.; D’Incà, F.; Gelibter, A.; Chiari, R.; Grossi, F.; Delmonte, A.; Passaro, A.; Signorelli, D.; Gelsomino, F.; Galetta, D.; et al. Bone metastases and immunotherapy in patients with advanced non-small-cell lung cancer. J. Immunother. Cancer 2019, 7, 316. [Google Scholar] [CrossRef]
- Bian, C.; Wang, Y.; Lu, Z.; An, Y.; Wang, H.; Kong, L.; Du, Y.; Tian, J. ImmunoAIzer: A Deep Learning-Based Computational Framework to Characterize Cell Distribution and Gene Mutation in Tumor Microenvironment. Cancers 2021, 13, 1659. [Google Scholar] [CrossRef]
- Fan, T.; Zhu, M.; Wang, L.; Liu, Y.; Tian, H.; Zheng, Y.; Tan, F.; Sun, N.; Li, C.; He, J. Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma. Aging 2020, 13, 2397–2417. [Google Scholar] [CrossRef]
Covariates | Type | Entire TCGA | Testing | Training | p Value # | GSE13213 |
---|---|---|---|---|---|---|
n = 484 | n = 242 | n = 242 | n = 117 | |||
Age (%) | ≤65 | 233 (48.14%) | 119 (49.17%) | 114 (47.11%) | 0.7159 | 78 (66.67%) |
>65 | 251 (51.86%) | 123 (50.83%) | 128 (52.89%) | 39 (33.33%) | ||
Gender (%) | FEMALE | 263 (54.34%) | 132 (54.55%) | 131 (54.13%) | 1 | 57 (48.72%) |
MALE | 221 (45.66%) | 110 (45.45%) | 111 (45.87%) | 60 (51.28%) | ||
Stage (%) | Stage I–II | 384 (79.34%) | 193 (79.75%) | 191 (78.93%) | 0.9106 | 92 (78.63%) |
Stage III–IV | 100 (20.66%) | 49 (20.25%) | 51 (21.07%) | 25 (21.37%) | ||
T stage (%) | T1-2 | 422 (87.19%) | 218 (90.08%) | 204 (84.3%) | 0.077 | 104 (88.89%) |
T3-4 | 62 (12.81%) | 24 (9.92%) | 38 (15.7%) | 13 (11.11%) | ||
N stage (%) | N0 | 322 (66.53%) | 163 (67.36%) | 159 (65.7%) | 0.7726 | 87 (74.36%) |
N1-3 | 162 (33.47%) | 79 (32.64%) | 83 (34.3%) | 30 (25.64%) | ||
M stage (%) | M0 | 463 (95.66%) | 233 (96.28%) | 230 (95.04%) | 0.6554 | 117 (100%) |
M1 | 21 (4.34%) | 9 (3.72%) | 12 (4.96%) | / |
UbRG 1 | Full Name | UbRG 2 | Full Name | UbRGP | Coefficient |
---|---|---|---|---|---|
DCUN1D5 | Defective in cullin neddylation 1 domain-containing 5 | HCK | Hematopoietic cell kinase | DCUN1D5|HCK | 0.98856 |
UHRF1 | Ubiquitin-like with PHD and ring-finger domains 1 | TRAIP | Tumor necrosis factor receptor-associated factor-interacting protein | UHRF1|TRAIP | 0.920628 |
TRIM6 | Tripartite motif-containing 6 | KLHL35 | Kelch-like family member 35 | TRIM6|KLHL35 | 0.857858 |
TRIM6 | Tripartite motif-containing 6 | FBXL8 | F-box and leucine-rich repeat protein 8 | TRIM6|FBXL8 | 0.521508 |
KBTBD12 | Kelch repeat and BTB domain-containing 12 | ANKRD13B | Ankyrin repeat domain 13B | KBTBD12|ANKRD13B | 0.443928 |
SOCS3 | Suppressor of cytokine signaling 3 | ISG15 | ISG15 ubiquitin-like modifier | SOCS3|ISG15 | −0.42018 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, Y.; An, L.; Jia, Z.; Li, J.; Zhou, E.; Wu, F.; Yin, Z.; Geng, W.; Liao, T.; Xiao, W.; et al. Identification of Ubiquitin-Related Gene-Pair Signatures for Predicting Tumor Microenvironment Infiltration and Drug Sensitivity of Lung Adenocarcinoma. Cancers 2022, 14, 3478. https://doi.org/10.3390/cancers14143478
Li Y, An L, Jia Z, Li J, Zhou E, Wu F, Yin Z, Geng W, Liao T, Xiao W, et al. Identification of Ubiquitin-Related Gene-Pair Signatures for Predicting Tumor Microenvironment Infiltration and Drug Sensitivity of Lung Adenocarcinoma. Cancers. 2022; 14(14):3478. https://doi.org/10.3390/cancers14143478
Chicago/Turabian StyleLi, Yumei, Lanfen An, Zhe Jia, Jingxia Li, E Zhou, Feng Wu, Zhengrong Yin, Wei Geng, Tingting Liao, Wenjing Xiao, and et al. 2022. "Identification of Ubiquitin-Related Gene-Pair Signatures for Predicting Tumor Microenvironment Infiltration and Drug Sensitivity of Lung Adenocarcinoma" Cancers 14, no. 14: 3478. https://doi.org/10.3390/cancers14143478