ATM is a Prognostic Biomarker of Survival in Head and Neck Squamous Cell Carcinoma Patients
Download PDF
$currentUrl="http://$_SERVER[HTTP_HOST]$_SERVER[REQUEST_URI]"

Keywords

Head and neck squamous cell carcinoma
Diagnosis
Treatment
Biomarker

DOI

10.26689/par.v8i5.7460

Submitted : 2024-08-26
Accepted : 2024-09-10
Published : 2024-09-25

Abstract

This review examines the role of ATM expression in head and neck squamous cell carcinoma (HNSCC). Analysis revealed significant overexpression of ATM in HNSCC cells compared to normal control samples, suggesting its involvement in cancer proliferation. ATM expression was notably upregulated across various clinical parameters, including different stages of cancer, racial groups, genders, and age groups, highlighting its role in cancer progression. Validation using the GEPIA2 tool confirmed strong ATM expression throughout all four stages of HNSCC, with the highest levels in stage II and the lowest in stage I. Promoter methylation analysis of ATM showed distinct patterns across different demographics and cancer stages, reinforcing its significance. The study also explored the relationship between ATM expression and patient outcomes using the KM plotter tool, finding that high ATM expression was associated with better overall survival (OS), while low ATM expression correlated with better disease-free survival (DFS). Genetic mutation analysis via cBioPortal identified minimal ATM mutations in HNSCC, including in-frame, splice, truncating, and missense mutations, suggesting their role in ATM dysregulation. The STRING tool was used to construct a protein-protein interaction (PPI) network, revealing that the ATM gene interacts with ten key genes (NBN, ATR, CHEK2, MDC1, MSH2, MSH6, MRE11, TP53, TP53BP1, BRCA1), indicating its involvement in various biological functions. Functional annotation of differentially expressed genes (DEGs) through the DAVID web server revealed their participation in critical biological processes, including double-strand break repair, cellular response to DNA damage, and DNA damage checkpoints. KEGG pathway analysis further linked DEGs to cellular senescence, platinum drug resistance, homologous recombination, p53 signaling, and the cell cycle, underscoring ATM’s multifaceted role in HNSCC.

References

Mody MD, Rocco JW, Yom SS, et al., 2021, Head and Neck Cancer. Lancet, 398(10318): 2289–2299. https://doi.org/10.1016/S0140-6736(21)01550-6

Antra, Parashar P, Hungyo H, et al., 2022, Unraveling Molecular Mechanisms of Head and Neck Cancer. Crit Rev Oncol Hematol, 178: 103778. https://doi.org/10.1016/j.critrevonc.2022.103778

Pulte D, Brenner H, 2010, Changes in Survival in Head and Neck Cancers in the Late 20th and Early 21st Century: A Period Analysis. Oncologist, 15(9): 994–1001. https://doi.org/10.1634/theoncologist.2009-0289

Barnes JM, Graboyes EM, Adjei Boakye E, et al., 2023, The Affordable Care Act and suicide incidence among adults with cancer. J Cancer Surviv, 17(2): 449–459. https://doi.org/10.1007/s11764-022-01205-z

Sung H, Ferlay J, Siegel RL, et al., 2021, Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin, 71(3): 209–249. https://doi.org/10.3322/caac.21660

Reis Ferreira M, Pasto A, Ng T, et al., 2022, The Microbiota and Radiotherapy for Head and Neck Cancer: What Should Clinical Oncologists Know? Cancer Treat Rev, 109: 102442. https://doi.org/10.1016/j.ctrv.2022.102442

Rothenberg SM, Ellisen LW, 2012, The Molecular Pathogenesis of Head and Neck Squamous Cell Carcinoma. J Clin Invest, 122(6): 1951–1957. https://doi.org/10.1172/jci59889

Yin J, He X, Qin F, et al., 2022, m6A-Related lncRNA Signature for Predicting Prognosis and Immune Response in Head and Neck Squamous Cell Carcinoma. Am J Transl Res, 14(11): 7653–7669.

Moslemi M, Moradi Y, Dehghanbanadaki H, et al., 2021, The Association Between ATM Variants and Risk of Breast Cancer: A Systematic Review and Meta-Analysis. BMC Cancer, 21(1): 27. https://doi.org/10.1186/s12885-020-07749-6

Dork T, Bendix R, Bremer M, et al., 2001, Spectrum of ATM Gene Mutations in a Hospital-Based Series of Unselected Breast Cancer Patients. Cancer Res, 61(20): 7608–7615.

Fernandes N, Sun Y, Chen S, et al., 2005, DNA Damage-Induced Association of ATM with Its Target Proteins Requires a Protein Interaction Domain in the N Terminus of ATM. J Biol Chem, 280(15): 15158–15164. https://doi.org/10.1074/jbc.M412065200

Andrade MA, Petosa C, O'Donoghue SI, et al., 2001, Comparison of ARM and HEAT Protein Repeats. J Mol Biol, 309(1): 1–18. https://doi.org/10.1006/jmbi.2001.4624

Piazza I, Rutkowska A, Ori A, et al., 2014, Association of Condensin with Chromosomes Depends on DNA Binding by Its HEAT-Repeat Subunits. Nat Struct Mol Biol, 21(6): 560–568. https://doi.org/10.1038/nsmb.2831

Rubinson EH, Gowda AS, Spratt TE, et al., 2010, An Unprecedented Nucleic Acid Capture Mechanism for Excision of DNA Damage. Nature, 468(7322): 406–411. https://doi.org/10.1038/nature09428

Lee JH, Paull TT, 2005, ATM Activation by DNA Double-Strand Breaks Through the Mre11-Rad50-Nbs1 Complex. Science, 308(5721): 551–554. https://doi.org/10.1126/science.1108297

Lee JH, Paull TT, 2004, Direct Activation of the ATM Protein Kinase by the Mre11/Rad50/Nbs1 Complex. Science, 304(5667): 93–6. https://doi.org/10.1126/science.1091496

Uziel T, Lerenthal Y, Moyal L, et al., 2003, Requirement of the MRN Complex for ATM Activation by DNA Damage. EMBO J, 22(20): 5612–5621. https://doi.org/10.1093/emboj/cdg541

Shiloh Y, Ziv Y, 2013, The ATM Protein Kinase: Regulating the Cellular Response to Genotoxic Stress, and More. Nat Rev Mol Cell Biol, 14(4): 197–210. https://doi.org/10.1038/nrm3546

Swift M, Morrell D, Cromartie E, et al., 1986, The Incidence and Gene Frequency of Ataxia-Telangiectasia in the United States. Am J Hum Genet, 39(5): 573–583.

Cremona CA, Behrens A, 2014, ATM Signalling and Cancer. Oncogene, 33(26): 3351–3360. https://doi.org/10.1038/onc.2013.275

Song L, Lin C, Wu Z, et al., 2011, miR-18a Impairs DNA Damage Response Through Downregulation of Ataxia Telangiectasia Mutated (ATM) Kinase. PLoS One, 6(9): e25454. https://doi.org/10.1371/journal.pone.0025454

Rezaeian AH, Khanbabaei H, Calin GA, 2020, Therapeutic Potential of the miRNA-ATM Axis in the Management of Tumor Radioresistance. Cancer Res, 80(2): 139–150. https://doi.org/10.1158/0008-5472.CAN-19-1807

Matsuoka S, Ballif BA, Smogorzewska A, et al., 2007, ATM and ATR Substrate Analysis Reveals Extensive Protein Networks Responsive to DNA Damage. Science, 316(5828): 1160–1166. https://doi.org/10.1126/science.1140321

Thompson D, Duedal S, Kirner J, et al., 2005, Cancer Risks and Mortality in Heterozygous ATM Mutation Carriers. J Natl Cancer Inst, 97(11): 813–822. https://doi.org/10.1093/jnci/dji141

Goldgar DE, Healey S, Dowty JG, et al., 2011, Rare Variants in the ATM Gene and Risk of Breast Cancer. Breast Cancer Res, 13(4): R73. https://doi.org/10.1186/bcr2919

Angele S, Hall J, 2000, The ATM Gene and Breast Cancer: Is It Really A Risk Factor? Mutat Res, 462(2–3): 167–178. https://doi.org/10.1016/s1383-5742(00)00034-x

Chandrashekar DS, Bashel B, Balasubramanya SAH, et al., 2017, UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses. Neoplasia, 19(8): 649–658. https://doi.org/10.1016/j.neo.2017.05.002

Tang Z, Kang B, Li C, et al., 2019, GEPIA2: An Enhanced Web Server for Large-Scale Expression Profiling and Interactive Analysis. Nucleic Acids Res, 47(W1): W556–W560. https://doi.org/10.1093/nar/gkz430

Maciejczyk A, Szelachowska J, Czapiga B, et al., 2013, Elevated BUBR1 Expression is Associated with Poor Survival in Early Breast Cancer Patients: 15-Year Follow-Up Analysis. J Histochem Cytochem, 61(5): 330–339. https://doi.org/10.1369/0022155413480148

Cerami E, Gao J, Dogrusoz U, et al., 2012, The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data. Cancer Discov, 2(5): 401–404. https://doi.org/10.1158/2159-8290.CD-12-0095

von Mering C, Huynen M, Jaeggi D, et al., 2003, STRING: A Database of Predicted Functional Associations Between Proteins. Nucleic Acids Res, 31(1): 258–261. https://doi.org/10.1093/nar/gkg034

Szklarczyk D, Morris JH, Cook H, et al., 2017, The STRING Database in 2017: Quality-Controlled Protein-Protein Association Networks, Made Broadly Accessible. Nucleic Acids Res, 45(D1): D362–D368. https://doi.org/10.1093/nar/gkw937

Franceschini A, Szklarczyk D, Frankild S, et al., 2013, STRING v9.1: Protein-Protein Interaction Networks, With Increased Coverage and Integration. Nucleic Acids Res, 41(Database issue): D808–815. https://doi.org/10.1093/nar/gks1094

von Mering C, Jensen LJ, Snel B, et al., 2005, STRING: Known and Predicted Protein-Protein Associations, Integrated and Transferred Across Organisms. Nucleic Acids Res, 33(Database issue): D433–D437. https://doi.org/10.1093/nar/gki005

Huang DW, Sherman BT, Lempicki RA, 2009, Systematic and Integrative Analysis of Large Gene Lists Using DAVID Bioinformatics Resources. Nat Protoc, 4(1): 44–57. https://doi.org/10.1038/nprot.2008.211

Denny JC, Collins FS, 2021, Precision Medicine in 2030 – Seven Ways to Transform Healthcare. Cell, 184(6): 1415–1419. https://doi.org/10.1016/j.cell.2021.01.015

Krzyszczyk P, Acevedo A, Davidoff EJ, et al., 2018, The Growing Role of Precision and Personalized Medicine for Cancer Treatment. Technology (Singap World Sci), 6(3–4): 79–100. https://doi.org/10.1142/S2339547818300020

Chi H, Xie X, Yan Y, et al., 2022, Natural Killer Cell-Related Prognosis Signature Characterizes Immune Landscape and Predicts Prognosis of HNSCC. Front Immunol, 13: 1018685. https://doi.org/10.3389/fimmu.2022.1018685

Li Z, Zheng C, Liu H, et al., 2023, A Novel Oxidative Stress-Related Gene Signature as An Indicator of Prognosis and Immunotherapy Responses in HNSCC. Aging (Albany NY), 15(24): 14957–14984. https://doi.org/10.18632/aging.205323

Nan Z, Dou Y, Chen A, et al., 2023, Identification and Validation of A Prognostic Signature of Autophagy, Apoptosis and Pyroptosis-Related Genes for Head and Neck Squamous Cell Carcinoma: To Imply Therapeutic Choices of HPV Negative Patients. Front Immunol, 13: 1100417. https://doi.org/10.3389/fimmu.2022.1100417

Lugano R, Ramachandran M, Dimberg A, 2020, Tumor Angiogenesis: Causes, Consequences, Challenges and Opportunities. Cell Mol Life Sci, 77(9): 1745–1770. https://doi.org/10.1007/s00018-019-03351-7

Stine ZE, Schug ZT, Salvino JM, et al., 2022, Targeting Cancer Metabolism in the Era of Precision Oncology. Nat Rev Drug Discov, 21(2): 141–162. https://doi.org/10.1038/s41573-021-00339-6

Onkar SS, Carleton NM, Lucas PC, et al., 2023, The Great Immune Escape: Understanding the Divergent Immune Response in Breast Cancer Subtypes. Cancer Discov, 13(1): 23–40. https://doi.org/10.1158/2159-8290.CD-22-0475

Rotman G, Shiloh Y, 1998, ATM: From Gene To Function. Hum Mol Genet, 7(10): 1555–1563. https://doi.org/10.1093/hmg/7.10.1555. PMID: 9735376.

Broeks A, Urbanus JH, Floore AN, et al., 2000, ATM-Heterozygous Germline Mutations Contribute to Breast Cancer-Susceptibility. Am J Hum Genet, 66(2): 494–500. https://doi.org/10.1086/302746

Fletcher O, Johnson N, dos Santos Silva I, et al., 2010, Missense Variants in ATM in 26,101 Breast Cancer Cases and 29,842 Controls. Cancer Epidemiol Biomarkers Prev, 19(9): 2143–2151. https://doi.org/10.1158/1055-9965.EPI-10-0374

Thorstenson YR, Roxas A, Kroiss R, et al., 2003, Contributions of ATM Mutations to Familial Breast and Ovarian Cancer. Cancer Res, 63(12): 3325–3333.

Abraham RT, 2004, PI 3-Kinase Related Kinases: ‘Big’ Players in Stress-Induced Signaling Pathways. DNA Repair (Amst), 3(8–9): 883–887. https://doi.org/10.1016/j.dnarep.2004.04.002

Hall MJ, Bernhisel R, Hughes E, et al., 2021, Germline Pathogenic Variants in the Ataxia Telangiectasia Mutated (ATM) Gene are Associated with High and Moderate Risks for Multiple Cancers. Cancer Prev Res (Phila), 14(4): 433–440. https://doi.org/10.1158/1940-6207.CAPR-20-0448

Breast Cancer Association Consortium, Dorling L, Carvalho S, et al., 2021, Breast Cancer Risk Genes – Association Analysis in More than 113,000 Women. N Engl J Med, 384(5): 428–439. https://doi.org/10.1056/NEJMoa1913948

Meng ZH, Ben Y, Li Z, et al., 2004, Aberrations of Breast Cancer Susceptibility Genes Occur Early in Sporadic Breast Tumors and In Acquisition of Breast Epithelial Immortalization. Genes Chromosomes Cancer, 41(3): 214–222. https://doi.org/10.1002/gcc.20089