Mitochondrial Lipid Metabolism Genes as Diagnostic and Prognostic Indicators in Hepatocellular Carcinoma

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Abstract

Background: Due to the heterogeneity of Hepatocellular carcinoma (HCC), there is an urgent need for reliable diagnosis and prognosis. Mitochondria-mediated abnormal lipid metabolism affects the occurrence and progression of HCC.

Objective: This study aims to investigate the potential of mitochondrial lipid metabolism (MTLM) genes as diagnostic and independent prognostic biomarkers for HCC.

Methods: MTLM genes were screened from the Gene Expression Omnibus (GEO) and Gene Set Enrichment Analysis (GSEA) databases, followed by an evaluation of their diagnostic values in both The Cancer Genome Atlas Program (TCGA) and the Affiliated Cancer Hospital of Guangxi Medical University (GXMU) cohort. The TCGA dataset was utilized to construct a gene signature and investigate the prognostic significance, immune infiltration, and copy number alterations. The validity of the prognostic signature was confirmed through GEO, International Cancer Genome Consortium (ICGC), and GXMU cohorts.

Results: The diagnostic receiver operating characteristic (ROC) curve revealed that eight MTLM genes have excellent diagnostic of HCC. A prognostic signature comprising 5 MTLM genes with robust predictive value was constructed using the lasso regression algorithm based on TCGA data. The results of the Stepwise regression model showed that the combination of signature and routine clinical parameters had a higher area under the curve (AUC) compared to a single risk score. Further, a nomogram was constructed to predict the survival probability of HCC, and the calibration curves demonstrated a perfect predictive ability. Finally, the risk score also unveiled the different immune and mutation statuses between the two different risk groups.

Conclusion: MTLT-related genes may serve as diagnostic and prognostic biomarkers for HCC as well as novel therapeutic targets, which may be beneficial for facilitating further understanding the molecular pathogenesis and providing potential therapeutic strategies for HCC.

Graphical Abstract

[1]
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(3), 209-249.
[http://dx.doi.org/10.3322/caac.21660] [PMID: 33538338]
[2]
Petrick, J.L.; Florio, A.A.; Znaor, A.; Ruggieri, D.; Laversanne, M.; Alvarez, C.S.; Ferlay, J.; Valery, P.C.; Bray, F.; McGlynn, K.A. International trends in hepatocellular carcinoma incidence, 1978–2012. Int. J. Cancer, 2020, 147(2), 317-330.
[http://dx.doi.org/10.1002/ijc.32723] [PMID: 31597196]
[3]
Craig, A.J.; von Felden, J.; Garcia-Lezana, T.; Sarcognato, S.; Villanueva, A. Tumour evolution in hepatocellular carcinoma. Nat. Rev. Gastroenterol. Hepatol., 2020, 17(3), 139-152.
[http://dx.doi.org/10.1038/s41575-019-0229-4] [PMID: 31792430]
[4]
Zhou, J.; Sun, H.; Wang, Z.; Cong, W.; Wang, J.; Zeng, M.; Zhou, W.; Bie, P.; Liu, L.; Wen, T.; Han, G.; Wang, M.; Liu, R.; Lu, L.; Ren, Z.; Chen, M.; Zeng, Z.; Liang, P.; Liang, C.; Chen, M.; Yan, F.; Wang, W.; Ji, Y.; Yun, J.; Cai, D.; Chen, Y.; Cheng, W.; Cheng, S.; Dai, C.; Guo, W.; Hua, B.; Huang, X.; Jia, W.; Li, Y.; Li, Y.; Liang, J.; Liu, T.; Lv, G.; Mao, Y.; Peng, T.; Ren, W.; Shi, H.; Shi, G.; Tao, K.; Wang, W.; Wang, X.; Wang, Z.; Xiang, B.; Xing, B.; Xu, J.; Yang, J.; Yang, J.; Yang, Y.; Yang, Y.; Ye, S.; Yin, Z.; Zhang, B.; Zhang, B.; Zhang, L.; Zhang, S.; Zhang, T.; Zhao, Y.; Zheng, H.; Zhu, J.; Zhu, K.; Liu, R.; Shi, Y.; Xiao, Y.; Dai, Z.; Teng, G.; Cai, J.; Wang, W.; Cai, X.; Li, Q.; Shen, F.; Qin, S.; Dong, J.; Fan, J. Guidelines for the Diagnosis and Treatment of Hepatocellular Carcinoma (2019 Edition). Liver Cancer, 2020, 9(6), 682-720.
[http://dx.doi.org/10.1159/000509424] [PMID: 33442540]
[5]
Chan, A.W.H.; Zhong, J.; Berhane, S.; Toyoda, H.; Cucchetti, A.; Shi, K.; Tada, T.; Chong, C.C.N.; Xiang, B.D.; Li, L.Q.; Lai, P.B.S.; Mazzaferro, V.; García-Fiñana, M.; Kudo, M.; Kumada, T.; Roayaie, S.; Johnson, P.J. Development of pre and post-operative models to predict early recurrence of hepatocellular carcinoma after surgical resection. J. Hepatol., 2018, 69(6), 1284-1293.
[http://dx.doi.org/10.1016/j.jhep.2018.08.027] [PMID: 30236834]
[6]
Anwanwan, D.; Singh, S.K.; Singh, S.; Saikam, V.; Singh, R. Challenges in liver cancer and possible treatment approaches. Biochim. Biophys. Acta Rev. Cancer, 2020, 1873(1), 188314.
[http://dx.doi.org/10.1016/j.bbcan.2019.188314] [PMID: 31682895]
[7]
Döhla, J.; Kuuluvainen, E.; Gebert, N.; Amaral, A.; Englund, J.I.; Gopalakrishnan, S.; Konovalova, S.; Nieminen, A.I.; Salminen, E.S.; Torregrosa Muñumer, R.; Ahlqvist, K.; Yang, Y.; Bui, H.; Otonkoski, T.; Käkelä, R.; Hietakangas, V.; Tyynismaa, H.; Ori, A.; Katajisto, P. Metabolic determination of cell fate through selective inheritance of mitochondria. Nat. Cell Biol., 2022, 24(2), 148-154.
[http://dx.doi.org/10.1038/s41556-021-00837-0] [PMID: 35165416]
[8]
Raggi, C.; Taddei, M.L.; Rae, C.; Braconi, C.; Marra, F. Metabolic reprogramming in cholangiocarcinoma. J. Hepatol., 2022, 77(3), 849-864.
[http://dx.doi.org/10.1016/j.jhep.2022.04.038] [PMID: 35594992]
[9]
Hernandez, S.; Simoni-Nieves, A.; Gerardo-Ramírez, M.; Torres, S.; Fucho, R.; Gonzalez, J.; Castellanos-Tapia, L.; Hernández-Pando, R.; Tejero-Barrera, E.; Bucio, L.; Souza, V.; Miranda-Labra, R.; Fernández-Checa, J.C.; Marquardt, J.U.; Gomez-Quiroz, L.E.; García-Ruiz, C.; Gutiérrez-Ruiz, M.C. GDF11 restricts aberrant lipogenesis and changes in mitochondrial structure and function in human hepatocellular carcinoma cells. J. Cell. Physiol., 2021, 236(5), 4076-4090.
[http://dx.doi.org/10.1002/jcp.30151] [PMID: 33174245]
[10]
Lu, Q.; Gao, J.; Tang, S.; Li, Z.; Wang, X.; Deng, C.; Hu, J.; Tao, Y.; Wang, Q. Integrated RNA sequencing and single-cell mass cytometry reveal a novel role of LncRNA HOXA-AS2 in tumorigenesis and stemness of hepatocellular carcinoma. OncoTargets Ther., 2020, 13, 10901-10916.
[http://dx.doi.org/10.2147/OTT.S272717] [PMID: 33149607]
[11]
Ritchie, M.E.; Phipson, B.; Wu, D.; Hu, Y.; Law, C.W.; Shi, W.; Smyth, G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res., 2015, 43(7), e47.
[http://dx.doi.org/10.1093/nar/gkv007] [PMID: 25605792]
[12]
Wu, T.; Hu, E.; Xu, S.; Chen, M.; Guo, P.; Dai, Z.; Feng, T.; Zhou, L.; Tang, W.; Zhan, L.; Fu, X.; Liu, S.; Bo, X.; Yu, G. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation, 2021, 2(3), 100141.
[http://dx.doi.org/10.1016/j.xinn.2021.100141] [PMID: 34557778]
[13]
Tibshirani, R. The lasso method for variable selection in the Cox model. Stat. Med., 1997, 16(4), 385-395.
[http://dx.doi.org/10.1002/(SICI)1097-0258(19970228)16:4<385:AID-SIM380>3.0.CO;2-3] [PMID: 9044528]
[14]
Li, W.; Nyholt, D.R. Marker selection by Akaike information criterion and Bayesian information criterion. Genet. Epidemiol., 2001, 21(S1), S272-S277.
[http://dx.doi.org/10.1002/gepi.2001.21.s1.s272] [PMID: 11793681]
[15]
Alba, A.C.; Agoritsas, T.; Walsh, M.; Hanna, S.; Iorio, A.; Devereaux, P.J.; McGinn, T.; Guyatt, G. Discrimination and calibration of clinical prediction models. JAMA, 2017, 318(14), 1377-1384.
[http://dx.doi.org/10.1001/jama.2017.12126] [PMID: 29049590]
[16]
Hänzelmann, S.; Castelo, R.; Guinney, J. GSVA: Gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics, 2013, 14(1), 7.
[http://dx.doi.org/10.1186/1471-2105-14-7] [PMID: 23323831]
[17]
Bindea, G.; Mlecnik, B.; Tosolini, M.; Kirilovsky, A.; Waldner, M.; Obenauf, A.C.; Angell, H.; Fredriksen, T.; Lafontaine, L.; Berger, A.; Bruneval, P.; Fridman, W.H.; Becker, C.; Pagès, F.; Speicher, M.R.; Trajanoski, Z.; Galon, J. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity, 2013, 39(4), 782-795.
[http://dx.doi.org/10.1016/j.immuni.2013.10.003] [PMID: 24138885]
[18]
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(11), 1747-1756.
[http://dx.doi.org/10.1101/gr.239244.118] [PMID: 30341162]
[19]
Martin, J.D.; Fukumura, D.; Duda, D.G.; Boucher, Y.; Jain, R.K. Reengineering the tumor microenvironment to alleviate hypoxia and overcome cancer heterogeneity. Cold Spring Harb. Perspect. Med., 2016, 6(12), a027094.
[http://dx.doi.org/10.1101/cshperspect.a027094] [PMID: 27663981]
[20]
Broadfield, L.A.; Pane, A.A.; Talebi, A.; Swinnen, J.V.; Fendt, S.M. Lipid metabolism in cancer: New perspectives and emerging mechanisms. Dev. Cell, 2021, 56(10), 1363-1393.
[http://dx.doi.org/10.1016/j.devcel.2021.04.013] [PMID: 33945792]
[21]
Broadfield, L.A.; Duarte, J.A.G.; Schmieder, R.; Broekaert, D.; Veys, K.; Planque, M.; Vriens, K.; Karasawa, Y.; Napolitano, F.; Fujita, S.; Fujii, M.; Eto, M.; Holvoet, B.; Vangoitsenhoven, R.; Fernandez-Garcia, J.; Van Elsen, J.; Dehairs, J.; Zeng, J.; Dooley, J.; Rubio, R.A.; van Pelt, J.; Grünewald, T.G.P.; Liston, A.; Mathieu, C.; Deroose, C.M.; Swinnen, J.V.; Lambrechts, D.; di Bernardo, D.; Kuroda, S.; De Bock, K.; Fendt, S.M. Fat induces glucose metabolism in nontransformed liver cells and promotes liver tumorigenesis. Cancer Res., 2021, 81(8), 1988-2001.
[http://dx.doi.org/10.1158/0008-5472.CAN-20-1954] [PMID: 33687947]
[22]
Tai, L.H.; de Souza, C.T.; Bélanger, S.; Ly, L.; Alkayyal, A.A.; Zhang, J.; Rintoul, J.L.; Ananth, A.A.; Lam, T.; Breitbach, C.J.; Falls, T.J.; Kirn, D.H.; Bell, J.C.; Makrigiannis, A.P.; Auer, R.A. Preventing postoperative metastatic disease by inhibiting surgery-induced dysfunction in natural killer cells. Cancer Res., 2013, 73(1), 97-107.
[http://dx.doi.org/10.1158/0008-5472.CAN-12-1993] [PMID: 23090117]
[23]
Niavarani, S.R.; Lawson, C.; Bakos, O.; Boudaud, M.; Batenchuk, C.; Rouleau, S.; Tai, L.H. Lipid accumulation impairs natural killer cell cytotoxicity and tumor control in the postoperative period. BMC Cancer, 2019, 19(1), 823.
[http://dx.doi.org/10.1186/s12885-019-6045-y] [PMID: 31429730]
[24]
Braicu, E.I.; Darb-Esfahani, S.; Schmitt, W.D.; Koistinen, K.M.; Heiskanen, L.; Pöhö, P.; Budczies, J.; Kuhberg, M.; Dietel, M.; Frezza, C.; Denkert, C.; Sehouli, J.; Hilvo, M. High-grade ovarian serous carcinoma patients exhibit profound alterations in lipid metabolism. Oncotarget, 2017, 8(61), 102912-102922.
[http://dx.doi.org/10.18632/oncotarget.22076] [PMID: 29262533]
[25]
Praharaj, P.P.; Naik, P.P.; Panigrahi, D.P.; Bhol, C.S.; Mahapatra, K.K.; Patra, S.; Sethi, G.; Bhutia, S.K. Intricate role of mitochondrial lipid in mitophagy and mitochondrial apoptosis: Its implication in cancer therapeutics. Cell. Mol. Life Sci., 2019, 76(9), 1641-1652.
[http://dx.doi.org/10.1007/s00018-018-2990-x] [PMID: 30539200]
[26]
Belikova, N.A.; Vladimirov, Y.A.; Osipov, A.N.; Kapralov, A.A.; Tyurin, V.A.; Potapovich, M.V.; Basova, L.V.; Peterson, J.; Kurnikov, I.V.; Kagan, V.E. Peroxidase activity and structural transitions of cytochrome c bound to cardiolipin-containing membranes. Biochemistry, 2006, 45(15), 4998-5009.
[http://dx.doi.org/10.1021/bi0525573] [PMID: 16605268]
[27]
Chu, C.T.; Ji, J.; Dagda, R.K.; Jiang, J.F.; Tyurina, Y.Y.; Kapralov, A.A.; Tyurin, V.A.; Yanamala, N.; Shrivastava, I.H.; Mohammadyani, D.; Wang, K.Z.Q.; Zhu, J.H.; Klein-Seetharaman, J.; Balasubramanian, K.; Amoscato, A.A.; Borisenko, G.; Huang, Z.T.; Gusdon, A.M.; Cheikhi, A.; Steer, E.K.; Wang, R.; Baty, C.; Watkins, S.; Bahar, I.; Bayir, H.; Kagan, V.E. Cardiolipin externalization to the outer mitochondrial membrane acts as an elimination signal for mitophagy in neuronal cells. NatCell Biol, 2013, 15(10), 1197-u168.
[http://dx.doi.org/10.1038/ncb2837] [PMID: 24036476]
[28]
Hernández-Corbacho, M.J.; Canals, D.; Adada, M.M.; Liu, M.; Senkal, C.E.; Yi, J.K.; Mao, C.; Luberto, C.; Hannun, Y.A.; Obeid, L.M. Tumor necrosis factor-α (TNFα)-induced ceramide generation via ceramide synthases regulates loss of focal adhesion kinase (FAK) and programmed cell death. J. Biol. Chem., 2015, 290(42), 25356-25373.
[http://dx.doi.org/10.1074/jbc.M115.658658] [PMID: 26318452]
[29]
Hoye, A.T.; Davoren, J.E.; Wipf, P.; Fink, M.P.; Kagan, V.E. Targeting mitochondria. Acc. Chem. Res., 2008, 41(1), 87-97.
[http://dx.doi.org/10.1021/ar700135m] [PMID: 18193822]
[30]
Montero, J.; Morales, A.; Llacuna, L.; Lluis, J.M.; Terrones, O.; Basañez, G.; Antonsson, B.; Prieto, J.; García-Ruiz, C.; Colell, A.; Fernández-Checa, J.C. Mitochondrial cholesterol contributes to chemotherapy resistance in hepatocellular carcinoma. Cancer Res., 2008, 68(13), 5246-5256.
[http://dx.doi.org/10.1158/0008-5472.CAN-07-6161] [PMID: 18593925]
[31]
Ma, C.; Kesarwala, A.H.; Eggert, T.; Medina-Echeverz, J.; Kleiner, D.E.; Jin, P.; Stroncek, D.F.; Terabe, M.; Kapoor, V.; ElGindi, M.; Han, M.; Thornton, A.M.; Zhang, H.; Egger, M.; Luo, J.; Felsher, D.W.; McVicar, D.W.; Weber, A.; Heikenwalder, M.; Greten, T.F. NAFLD causes selective CD4+ T lymphocyte loss and promotes hepatocarcinogenesis. Nature, 2016, 531(7593), 253-257.
[http://dx.doi.org/10.1038/nature16969] [PMID: 26934227]
[32]
Oh, D.Y.; Kwek, S.S.; Raju, S.S.; Li, T.; McCarthy, E.; Chow, E.; Aran, D.; Ilano, A.; Pai, C.C.S.; Rancan, C.; Allaire, K.; Burra, A.; Sun, Y.; Spitzer, M.H.; Mangul, S.; Porten, S.; Meng, M.V.; Friedlander, T.W.; Ye, C.J.; Fong, L. Intratumoral CD4+ T cells mediate anti-tumor cytotoxicity in human bladder cancer. Cell, 2020, 181(7), 1612-1625.e13.
[http://dx.doi.org/10.1016/j.cell.2020.05.017] [PMID: 32497499]
[33]
Wang, H.; Zhang, H.; Wang, Y.; Brown, Z.J.; Xia, Y.; Huang, Z.; Shen, C.; Hu, Z.; Beane, J.; Ansa-Addo, E.A.; Huang, H.; Tian, D.; Tsung, A. Regulatory T-cell and neutrophil extracellular trap interaction contributes to carcinogenesis in non-alcoholic steatohepatitis. J. Hepatol., 2021, 75(6), 1271-1283.
[http://dx.doi.org/10.1016/j.jhep.2021.07.032] [PMID: 34363921]
[34]
Calderaro, J.; Couchy, G.; Imbeaud, S.; Amaddeo, G.; Letouzé, E.; Blanc, J.F.; Laurent, C.; Hajji, Y.; Azoulay, D.; Bioulac-Sage, P.; Nault, J.C.; Zucman-Rossi, J. Histological subtypes of hepatocellular carcinoma are related to gene mutations and molecular tumour classification. J. Hepatol., 2017, 67(4), 727-738.
[http://dx.doi.org/10.1016/j.jhep.2017.05.014] [PMID: 28532995]
[35]
Lehwald, N. Tao, G.Z.; Jang, K.Y.; Papandreou, I.; Liu, B.; Liu, B.; Pysz, M.A.; Willmann, J.K.; Knoefel, W.T.; Denko, N.C.; Sylvester, K.G. β-Catenin regulates hepatic mitochondrial function and energy balance in mice. Gastroenterology, 2012, 143(3), 754-764.
[http://dx.doi.org/10.1053/j.gastro.2012.05.048] [PMID: 22684045]
[36]
Zender, L.; Villanueva, A.; Tovar, V.; Sia, D.; Chiang, D.Y.; Llovet, J.M. Cancer gene discovery in hepatocellular carcinoma. J. Hepatol., 2010, 52(6), 921-929.
[http://dx.doi.org/10.1016/j.jhep.2009.12.034] [PMID: 20385424]
[37]
Luo, Y.D.; Fang, L.; Yu, H.Q.; Zhang, J.; Lin, X.T.; Liu, X.Y.; Wu, D.; Li, G.X.; Huang, D.; Zhang, Y.J.; Chen, S.; Jiang, Y.; Shuai, L.; He, Y.; Zhang, L.D.; Bie, P.; Xie, C.M. p53 haploinsufficiency and increased mTOR signalling define a subset of aggressive hepatocellular carcinoma. J. Hepatol., 2021, 74(1), 96-108.
[http://dx.doi.org/10.1016/j.jhep.2020.07.036] [PMID: 32738450]
[38]
Khemlina, G.; Ikeda, S.; Kurzrock, R. The biology of Hepatocellular carcinoma: Implications for genomic and immune therapies. Mol. Cancer, 2017, 16(1), 149.
[http://dx.doi.org/10.1186/s12943-017-0712-x] [PMID: 28854942]
[39]
Uhlig, J.; Stein, S.; Kim, H.S. PD-1 targeted immunotherapy for advanced hepatocellular carcinoma: Current utilization and outcomes in the USA. Future Oncol., 2022, 18(14), 1691-1703.
[http://dx.doi.org/10.2217/fon-2021-1487] [PMID: 35172633]
[40]
Sangro, B.; Sarobe, P.; Hervás-Stubbs, S.; Melero, I. Advances in immunotherapy for hepatocellular carcinoma. Nat. Rev. Gastroenterol. Hepatol., 2021, 18(8), 525-543.
[http://dx.doi.org/10.1038/s41575-021-00438-0] [PMID: 33850328]
[41]
Ren, Z.; Xu, J.; Bai, Y.; Xu, A.; Cang, S.; Du, C.; Li, Q.; Lu, Y.; Chen, Y.; Guo, Y.; Chen, Z.; Liu, B.; Jia, W.; Wu, J.; Wang, J.; Shao, G.; Zhang, B.; Shan, Y.; Meng, Z.; Wu, J.; Gu, S.; Yang, W.; Liu, C.; Shi, X.; Gao, Z.; Yin, T.; Cui, J.; Huang, M.; Xing, B.; Mao, Y.; Teng, G.; Qin, Y.; Wang, J.; Xia, F.; Yin, G.; Yang, Y.; Chen, M.; Wang, Y.; Zhou, H.; Fan, J.; Grp, O-S. Sintilimab plus a bevacizumab biosimilar (IBI305) versus sorafenib in unresectable hepatocellular carcinoma (ORIENT-32): A randomised, open-label, phase 2–3 study. Lancet Oncol., 2021, 22(7), 977-990.
[http://dx.doi.org/10.1016/S1470-2045(21)00252-7] [PMID: 34143971]
[42]
Sperandio, R.C.; Pestana, R.C.; Miyamura, B.V.; Kaseb, A.O. Hepatocellular carcinoma immunotherapy. Annu. Rev. Med., 2022, 73(1), 267-278.
[http://dx.doi.org/10.1146/annurev-med-042220-021121] [PMID: 34606324]
[43]
Anderson, A.C.; Joller, N.; Kuchroo, V.K. Lag-3, Tim-3, and TIGIT: Co-inhibitory receptors with specialized functions in immune regulation. Immunity, 2016, 44(5), 989-1004.
[http://dx.doi.org/10.1016/j.immuni.2016.05.001] [PMID: 27192565]
[44]
Xu, S.; Wang, Z.; Ye, J.; Mei, S.; Zhang, J. Identification of iron metabolism-related genes as prognostic indicators for lower-grade glioma. Front. Oncol., 2021, 11, 729103.
[http://dx.doi.org/10.3389/fonc.2021.729103] [PMID: 34568059]
[45]
Xia, P.; Zhang, H.; Xu, K.; Jiang, X.; Gao, M.; Wang, G.; Liu, Y.; Yao, Y.; Chen, X.; Ma, W.; Zhang, Z.; Yuan, Y. MYC-targeted WDR4 promotes proliferation, metastasis, and sorafenib resistance by inducing CCNB1 translation in hepatocellular carcinoma. Cell Death Dis., 2021, 12(7), 691.
[http://dx.doi.org/10.1038/s41419-021-03973-5] [PMID: 34244479]
[46]
Lau, H.W.; Ma, H.T.; Yeung, T.K.; Tam, M.Y.; Zheng, D.; Chu, S.K.; Poon, R.Y.C. Quantitative differences between cyclin-dependent kinases underlie the unique functions of CDK1 in human cells. Cell Rep., 2021, 37(2), 109808.
[http://dx.doi.org/10.1016/j.celrep.2021.109808] [PMID: 34644583]
[47]
Cao, S.; Liu, H.; Fan, J.; Yang, K.; Yang, B.; Wang, J.; Li, J.; Meng, L.; Li, H. An oxidative stress-related gene pair (CCNB1/PKD1), competitive endogenous RNAs, and immune-infiltration patterns potentially regulate intervertebral disc degeneration development. Front. Immunol., 2021, 12, 765382.
[http://dx.doi.org/10.3389/fimmu.2021.765382] [PMID: 34858418]
[48]
Chang, J.G.; Tien, N.; Chang, Y.C.; Lin, M.L.; Chen, S.S. Oxidative stress-induced unscheduled CDK1–Cyclin B1 activity impairs ER–mitochondria-mediated bioenergetic metabolism. Cells, 2021, 10(6), 1280.
[http://dx.doi.org/10.3390/cells10061280] [PMID: 34064109]
[49]
Clemm von Hohenberg, K.; Müller, S.; Schleich, S.; Meister, M.; Bohlen, J.; Hofmann, T.G.; Teleman, A.A. Cyclin B/CDK1 and cyclin A/CDK2 phosphorylate DENR to promote mitotic protein translation and faithful cell division. Nat. Commun., 2022, 13(1), 668.
[http://dx.doi.org/10.1038/s41467-022-28265-0] [PMID: 35115540]
[50]
Zhao, X.; Qin, W.; Jiang, Y.; Yang, Z.; Yuan, B.; Dai, R.; Shen, H.; Chen, Y.; Fu, J.; Wang, H. ACADL plays a tumor-suppressor role by targeting Hippo/YAP signaling in hepatocellular carcinoma. NPJ Precis. Oncol., 2020, 4(1), 7.
[http://dx.doi.org/10.1038/s41698-020-0111-4] [PMID: 32219176]
[51]
Xu, B.; Jiang, M.; Chu, Y.; Wang, W.; Chen, D.; Li, X.; Zhang, Z.; Zhang, D.; Fan, D.; Nie, Y.; Shao, F.; Wu, K.; Liang, J. Gasdermin D plays a key role as a pyroptosis executor of non-alcoholic steatohepatitis in humans and mice. J. Hepatol., 2018, 68(4), 773-782.
[http://dx.doi.org/10.1016/j.jhep.2017.11.040] [PMID: 29273476]
[52]
Softic, S.; Meyer, J.G.; Wang, G.X.; Gupta, M.K.; Batista, T.M.; Lauritzen, H.P.M.M.; Fujisaka, S.; Serra, D.; Herrero, L.; Willoughby, J.; Fitzgerald, K.; Ilkayeva, O.; Newgard, C.B.; Gibson, B.W.; Schilling, B.; Cohen, D.E.; Kahn, C.R. Dietary sugars alter hepatic fatty acid oxidation via transcriptional and post-translational modifications of mitochondrial proteins. Cell Metab., 2019, 30(4), 735-753.e4.
[http://dx.doi.org/10.1016/j.cmet.2019.09.003] [PMID: 31577934]
[53]
Pang, B.; Xu, X.; Lu, Y.; Jin, H.; Yang, R.; Jiang, C.; Shao, D.; Liu, Y.; Shi, J. Prediction of new targets and mechanisms for quercetin in the treatment of pancreatic cancer, colon cancer, and rectal cancer. Food Funct., 2019, 10(9), 5339-5349.
[http://dx.doi.org/10.1039/C9FO01168D] [PMID: 31393490]
[54]
Jardé, T.; Caldefie-Chézet, F.; Goncalves-Mendes, N.; Mishellany, F.; Buechler, C.; Penault-Llorca, F.; Vasson, M.P. Involvement of adiponectin and leptin in breast cancer: Clinical and in vitro studies. Endocr. Relat. Cancer, 2009, 16(4), 1197-1210.
[http://dx.doi.org/10.1677/ERC-09-0043] [PMID: 19661131]
[55]
Shi, Q.; Liu, Y.; Lu, M.; Lei, Q.Y.; Chen, Z.; Wang, L.; He, X. A pathway-guided strategy identifies a metabolic signature for prognosis prediction and precision therapy for hepatocellular carcinoma. Comput. Biol. Med., 2022, 144, 105376.
[http://dx.doi.org/10.1016/j.compbiomed.2022.105376] [PMID: 35286894]
[56]
Schmiesing, J.; Storch, S.; Dörfler, A.C.; Schweizer, M.; Makrypidi-Fraune, G.; Thelen, M.; Sylvester, M.; Gieselmann, V.; Meyer-Schwesinger, C.; Koch-Nolte, F.; Tidow, H.; Mühlhausen, C.; Waheed, A.; Sly, W.S.; Braulke, T. Disease-linked glutarylation impairs function and interactions of mitochondrial proteins and contributes to mitochondrial heterogeneity. Cell Rep., 2018, 24(11), 2946-2956.
[http://dx.doi.org/10.1016/j.celrep.2018.08.014] [PMID: 30208319]
[57]
Guerreiro, G.; Amaral, A.U.; Ribeiro, R.T.; Faverzani, J.; Groehs, A.C.; Sitta, A.; Deon, M.; Wajner, M.; Vargas, C.R. l-Carnitine prevents oxidative stress in striatum of glutaryl-CoA dehydrogenase deficient mice submitted to lysine overload. Biochim. Biophys. Acta Mol. Basis Dis., 2019, 1865(9), 2420-2427.
[http://dx.doi.org/10.1016/j.bbadis.2019.06.007] [PMID: 31181292]