While the gastrointestinal symptom cluster (GISC) is common in patients receiving chemotherapy, limited information is available on its underlying mechanism(s). Emerging evidence suggests a role for inflammatory processes through the actions of the nuclear factor kappa B (NF-κB) signaling pathway. This study evaluated for associations between a GISC and levels of DNA methylation for genes within this pathway.
Methods
Prior to their second or third cycle of chemotherapy, 1071 outpatients reported symptom occurrence using the Memorial Symptom Assessment Scale. A GISC was identified using exploratory factor analysis. Differential methylation analyses were performed in two independent samples using EPIC (n = 925) and 450K (n = 146) microarrays. Trans expression-associated CpG (eCpG) loci for 56 NF-κB signaling pathway genes were evaluated. Loci significance were assessed using an exploratory false discovery rate (FDR) of 25% for the EPIC sample. For the validation assessment using the 450K sample, significance was assessed at an unadjusted p-value of 0.05.
Results
For the EPIC sample, the GISC was associated with increased expression of lymphotoxin beta (LTB) at one differentially methylated trans eCpG locus (cg03171795; FDR = 0.168). This association was not validated in the 450K sample.
Conclusions
This study is the first to identify an association between a GISC and epigenetic regulation of a gene that is involved in the initiation of gastrointestinal immune responses. Findings suggest that increased LTB expression by hypermethylation of a trans eCpG locus is involved in the occurrence of this cluster in patients receiving chemotherapy. LTB may be a potential therapeutic target for this common cluster.
AgyekumS.ChurchA.SohailM.KrauszT.Van NoordenS.PolakJ.CohenJ. (2003). Expression of lymphotoxin-beta (LT-beta) in chronic inflammatory conditions. The Journal of Pathology, 199(1), 115–121. https://doi.org/10.1002/path.1249
2.
AnderssonR.SandelinA.DankoC. G. (2015). A unified architecture of transcriptional regulatory elements. Trends in Genetics, 31(8), 426–433. https://doi.org/10.1016/j.tig.2015.05.007
3.
AryeeM. J.JaffeA. E.Corrada-BravoH.Ladd-AcostaC.FeinbergA. P.HansenK. D.IrizarryR. A. (2014). Minfi: A flexible and comprehensive bioconductor package for the analysis of infinium DNA methylation microarrays. Bioinformatics, 30(10), 1363–1369. https://doi.org/10.1093/bioinformatics/btu049
4.
BenjaminiY.HochbergY. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
5.
BockC. (2012). Analysing and interpreting DNA methylation data. Nature Reviews Genetics, 13(10), 705–719. https://doi.org/10.1038/nrg3273
6.
BorelliA.IrlaM. (2021). Lymphotoxin: From the physiology to the regeneration of the thymic function. Cell Death & Differentiation, 28(8), 2305–2314. https://doi.org/10.1038/s41418-021-00834-8
7.
BowenJ. M.GibsonR. J.TsykinA.StringerA. M.LoganR. M.KeefeD. M. (2007). Gene expression analysis of multiple gastrointestinal regions reveals activation of common cell regulatory pathways following cytotoxic chemotherapy. International Journal of Cancer, 121(8), 1847–1856. https://doi.org/10.1002/ijc.22895
8.
BrownT. (2015). The common factor model and exploratory factor analysis (2nd ed.). The Guilford Press.
9.
CarlottoA.HogsettV. L.MaioriniE. M.RazulisJ. G.SonisS. T. (2013). The economic burden of toxicities associated with cancer treatment: Review of the literature and analysis of nausea and vomiting, diarrhoea, oral mucositis and fatigue. PharmacoEconomics, 31(9), 753–766. https://doi.org/10.1007/s40273-013-0081-2
ChenY. A.LemireM.ChoufaniS.ButcherD. T.GrafodatskayaD.ZankeB. W.GallingerS.HudsonT. J.WeksbergR. (2013). Discovery of cross-reactive probes and polymorphic CpGs in the illumina infinium humanmethylation450 microarray. Epigenetics, 8(2), 203–209. https://doi.org/10.4161/epi.23470
12.
CinauseroM.AprileG.ErmacoraP.BasileD.VitaleM. G.FanottoV.ParisiG.CalvettiL.SonisS. T. (2017). New frontiers in the pathobiology and treatment of cancer regimen-related mucosal injury. Frontiers in Pharmacology, 8, 354. https://doi.org/10.3389/fphar.2017.00354
13.
DonovanH. S.HaganT. L.CampbellG. B.BoisenM. M.RosenblumL. M.EdwardsR. P.BovbjergD. H.HornC. C. (2016). Nausea as a sentinel symptom for cytotoxic chemotherapy effects on the gut-brain axis among women receiving treatment for recurrent ovarian cancer: An exploratory analysis. Supportive Care in Cancer, 24(6), 2635–2642. https://doi.org/10.1007/s00520-015-3071-4
DuP.ZhangX.HuangC.JafariN.KibbeW. A.HouL.LinS. M. (2010). Comparison of beta-value and M-value methods for quantifying methylation levels by microarray analysis. Bioinformatics, 1(587), 1–9. https://doi.org/10.1186/1471-2105-11-587
16.
ENCODE Project Consortium (2012). An integrated encyclopedia of DNA elements in the human genome. Nature, 489(7414), 57–74. https://doi.org/10.1038/nature11247
17.
ErnstJ.KheradpourP.MikkelsenT. S.ShoreshN.WardL. D.EpsteinC. B.ZhangX.WangL.IssnerR.CoyneM.KuM.DurhamT.KellisM.BernsteinB. E. (2011). Mapping and analysis of chromatin state dynamics in nine human cell types. Nature, 473(7345), 43–49. https://doi.org/10.1038/nature09906
18.
ExtermannM.BonettiM.SledgeG. W.O’DwyerP. J.BonomiP.BensonA. B.3rd (2004). MAX2 – A convenient index to estimate the average per patient risk for chemotherapy toxicity; validation in ECOG trials. European Journal of Cancer, 40(8), 1193–1198. https://doi.org/10.1016/j.ejca.2004.01.028
19.
GibsonR. J.KeefeD. M. (2006). Cancer chemotherapy-induced diarrhoea and constipation: Mechanisms of damage and prevention strategies. Supportive Care in Cancer, 14(9), 890–900. https://doi.org/10.1007/s00520-006-0040-y
20.
GubernatorovaE. O.TumanovA. V. (2016). Tumor necrosis factor and lymphotoxin in regulation of intestinal inflammation. Biochemistry (Mosc), 81(11), 1309–1325. https://doi.org/10.1134/S0006297916110092
21.
HarrisC. S.MiaskowskiC. A.DhruvaA. A.CataldoJ.KoberK. M. (2021). Multi-staged data-integrated multi-omics analysis for symptom science research. Biological Research for Nursing, 23(4), 596–607. https://doi.org/10.1177/10998004211003980
22.
HarrisC. S.KoberK. M.ConleyY. P.DhruvaA. A.HammerM.MiaskowskiC. A. (2022). Symptom clusters in patients receiving chemotherapy: A systematic review. BMJ Supportive & Palliative Care, 12(1), 10–21. https://doi.org/10.1136/bmjspcare-2021-003325
23.
HarrisC. S.KoberK. M.CooperB.ConleyY. P.DhruvaA. A.HammerM. J.PaulS.LevineJ. D.MiaskowskiC. A. (2022). Symptom clusters in outpatients with cancer using different dimensions of the symptom experience. Supportive Care in Cancer, 30(8), 6889–6899. https://doi.org/10.1007/s00520-022-07125-z
24.
JonesM. J.GoodmanS. J.KoborM. S. (2015). DNA methylation and healthy human aging. Aging Cell, 14(6), 924–932. https://doi.org/10.1111/acel.12349
25.
JonesP. A. (2012). Functions of DNA methylation: Islands, start sites, gene bodies and beyond. Nature Reviews Genetics, 13(7), 484–492. https://doi.org/10.1038/nrg3230
26.
JungbeckM.StopferP.BatailleF.NedospasovS. A.MannelD. N.HehlgansT. (2008). Blocking lymphotoxin beta receptor signalling exacerbates acute DSS-induced intestinal inflammation—opposite functions for surface lymphotoxin expressed by T and B lymphocytes. Molecular Immunology, 45(1), 34–41. https://doi.org/10.1016/j.molimm.2007.05.007
27.
KanehisaM.GotoS. (2000). KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28(1), 27–30. https://doi.org/10.1093/nar/28.1.27
28.
KarnofskyD. (1977). Performance scale. In KennealeyG.MitchellM. (Eds.), Factors that influence the therapeutic response in cancer: A comprehensive treatise. Plenum Press.
29.
KarnutaJ. M.ScacheriP. C. (2018). Enhancers: Bridging the gap between gene control and human disease. Human Molecular Genetics, 27(R2), R219–R227. https://doi.org/10.1093/hmg/ddy167
30.
KennedyE. M.GoehringG. N.NicholsM. H.RobinsC.MehtaD.KlengelT.EskinE.SmithA. K.ConneelyK. N. (2018). An integrated -omics analysis of the epigenetic landscape of gene expression in human blood cells. BMC Genomics, 19(1), 476. https://doi.org/10.1186/s12864-018-4842-3
31.
KentW. J.SugnetC. W.FureyT. S.RoskinK. M.PringleT. H.ZahlerA. M.HausslerD. (2002). The human genome browser at UCSC. Genome Research, 12(6), 996–1006. https://doi.org/10.1101/gr.229102
32.
KoberK.LeeM.-C.OlshenA.ConleyY.SirotaM.KeiserM.HammerM.AbramsG.SchumacherM.LevineJ.MiaskowskiC. (2020). Differential methylation and expression of genes in the hypoxia inducible factor 1 (HIF-1) signaling pathway are associated with paclitaxel-induced peripheral neuropathy in breast cancer survivors and with preclinical models of chemotherapy-induced neuropathic pain. Molecular Pain, 16(1744806920936502), 174480692093650. https://doi.org/10.1177/1744806920936502
33.
LeekJ. T.StoreyJ. D. (2007). Capturing heterogeneity in gene expression studies by surrogate variable analysis. Plos Genetics, 3(9), 1724–1735. https://doi.org/10.1371/journal.pgen.0030161
34.
MatzkaM.Köck-HódiS.JahnP.MayerH. (2018). Relationship among symptom clusters, quality of life, and treatment-specific optimism in patients with cancer. Supportive Care in Cancer, 26(8), 2685–2693. https://doi.org/10.1007/s00520-018-4102-8
35.
McGregorK.BernatskyS.ColmegnaI.HudsonM.PastinenT.LabbeA.GreenwoodC. M. (2016). An evaluation of methods correcting for cell-type heterogeneity in DNA methylation studies. Genome Biology, 17(1), 84. https://doi.org/10.1186/s13059-016-0935-y
36.
MolassiotisA.WengstromY.KearneyN. (2010). Symptom cluster patterns during the first year after diagnosis with cancer. Journal of Pain & Symptom Management, 39(5), 847–858. https://doi.org/10.1016/j.jpainsymman.2009.09.012
OeckinghausA.GhoshS. (2009). The NF-kappaB family of transcription factors and its regulation. Cold Spring Harbor Perspectives in Biology, 1(4), a000034. https://doi.org/10.1101/cshperspect.a000034
39.
PapachristouN.BarnaghiP.CooperB.KoberK. M.MaguireR.PaulS. M.HammerM.WrightF.ArmesJ.FurlongE. P.McCannL.ConleyY. P.PatirakiE.KatsaragakisS.LevineJ. D.MiaskowskiC. (2019). Network analysis of the multidimensional symptom experience of oncology. Scientific Reports, 9(1), 1–11. https://doi.org/10.1038/s41598-018-36973-1
40.
PirriC.BaylissE.TrotterJ.OlverI. N.KatrisP.DrummondP.BennettR. (2013). Nausea still the poor relation in antiemetic therapy? The impact on cancer patients’ quality of life and psychological adjustment of nausea, vomiting and appetite loss, individually and concurrently as part of a symptom cluster. Supportive Care in Cancer, 21(3), 735–748. https://doi.org/10.1007/s00520-012-1574-9
41.
PisaniL. F.TontiniG.VecchiM.CrociG. A.PastorelliL. (2022). NF-kB pathway is involved in microscopic colitis pathogenesis. The Journal of International Medical Research, 50(3), 3000605221080104. https://doi.org/10.1177/03000605221080104
42.
PortelaA.EstellerM. (2010). Epigenetic modifications and human disease. Nature Biotechnology, 28(10), 1057–1068. https://doi.org/10.1038/nbt.1685
43.
PortenoyR. K.ThalerH. T.KornblithA. B.LeporeJ. M.Friedlander-KlarH.KiyasuE.SobelK.CoyleN.KemenyN.NortonL.ScherH. (1994). The memorial symptom assessment scale: An instrument for the evaluation of symptom prevalence, characteristics and distress. European Journal of Cancer, 30A(9), 1326–1336. https://doi.org/10.1016/0959-8049(94)90182-1
44.
RakyanV. K.DownT. A.BaldingD. J.BeckS. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews Genetics, 12(8), 529–541. https://doi.org/10.1038/nrg3000
45.
RenH.TangP.ZhaoQ.RenG. (2017). Symptom clusters and related factors in bladder cancer patients three months after radical cystectomy. BMC Urology, 17(1), 65. https://doi.org/10.1186/s12894-017-0255-x
46.
RitchieM. E.PhipsonB.WuD.HuY.LawC. W.ShiW.SmythG. K. (2015). Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research, 43(7), e47. https://doi.org/10.1093/nar/gkv007
47.
RosenbloomK. R.SloanC. A.MalladiV. S.DreszerT. R.LearnedK.KirkupV. M.WongM. C.MaddrenM.FangR.HeitnerS. G.LeeB. T.BarberG. P.HarteR. A.DiekhansM.LongJ. C.WilderS. P.ZweigA. S.KarolchikD.KuhnR. M.HausslerD.KentW. J. (2013). ENCODE data in the UCSC genome browser: Year 5 update. Nucleic Acids Research, 41(D1), D56–D63. https://doi.org/10.1093/nar/gks1172
SalasL. A.KoestlerD. C.ButlerR. A.HansenH. M.WienckeJ. K.KelseyK. T.ChristensenB. C. (2018). An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray. Genome Biology, 19(1), 64. https://doi.org/10.1186/s13059-018-1448-7
50.
SanghaO.StuckiG.LiangM. H.FosselA. H.KatzJ. N. (2003). The self-administered comorbidity questionnaire: A new method to assess comorbidity for clinical and health services research. Arthritis & Rheumatism, 49(2), 156–163. https://doi.org/10.1002/art.10993
51.
SedyJ.BekiarisV.WareC. F. (2014). Tumor necrosis factor superfamily in innate immunity and inflammation. Cold Spring Harbor Perspectives in Biology, 7(4), a016279. https://doi.org/10.1101/cshperspect.a016279
52.
ShiJ. H.SunS. C. (2018). Tumor necrosis factor receptor-associated factor regulation of nuclear factor kappaB and mitogen-activated protein kinase pathways. Frontiers in Immunology, 9(■), 1849. https://doi.org/10.3389/fimmu.2018.01849
53.
SinghK. P.DhruvaA.FlowersE.PaulS. M.HammerM. J.WrightF.CartwrightF.ConleyY. P.MeliskoM.LevineJ. D.MiaskowskiC.KoberK. M. (2020). Alterations in patterns of gene expression and perturbed pathways in the gut-brain axis are associated with chemotherapy-induced nausea. Journal of Pain & Symptom Management, 59(6), 1248–1259. https://doi.org/10.1016/j.jpainsymman.2019.12.352
54.
SinghK.KoberK. M.PaulS. M.HammerM.WrightF.ConleyY. P.LevineJ. D.MiaskowskiC. (2020). Gastrointestinal symptoms are associated with trajectories of chemotherapy-induced nausea. Supportive Care in Cancer, 28(5), 2205–2215. https://doi.org/10.1007/s00520-019-05031-5
55.
SinghK.CaoH.MiaskowskiC.ConleyY. P.HammerM.WrightF.LevineJ. D.KoberK. M. (2021). Perturbations in endocytotic and apoptotic pathways are associated with chemotherapy-induced nausea. Biological Research for Nursing, 23(2), 238–247. https://doi.org/10.1177/1099800420951271
56.
SkermanH. M.YatesP. M.BattistuttaD. (2012). Cancer-related symptom clusters for symptom management in outpatients after commencing adjuvant chemotherapy, at 6 months, and 12 months. Supportive Care in Cancer, 20(1), 95–105. https://doi.org/10.1007/s00520-010-1070-z
57.
SonisS. T.EltingL. S.KeefeD.PetersonD. E.SchubertM.Hauer-JensenM.BekeleB. N.Raber-DurlacherJ.DonnellyJ. P.RubensteinE. B.Mucositis Study Section of the Multinational Association of Supportive Care in Cancer and the International Society for Oral Oncology (2004). Perspectives on cancer therapy-induced mucosal injury: Pathogenesis, measurement, epidemiology, and consequences for patients. Cancer, 100(9 Suppl), 1995–2025. https://doi.org/10.1002/cncr.20162
58.
SonisS.HaddadR.PosnerM.WatkinsB.FeyE.MorganT. V.MookanamparambilL.RamoniM. (2007). Gene expression changes in peripheral blood cells provide insight into the biological mechanisms associated with regimen-related toxicities in patients being treated for head and neck cancers. Oral Oncology, 43(3), 289–300. https://doi.org/10.1016/j.oraloncology.2006.03.014
59.
SonisS. T. (2002). Biologic role for nuclear factor-kappa B in disease and its potential involvement in mucosal injury associated with anti-neoplastic therapy. Critical Reviews in Oral Biology and Medicine, 13(5), 380–389. https://doi.org/10.1177/154411130201300502
SullivanC. W.LeutwylerH.DunnL. B.MiaskowskiC. (2018). A review of the literature on symptom clusters in studies that included oncology patients receiving primary or adjuvant chemotherapy. Journal of Clinical Nursing, 27(3–4), 516–545. https://doi.org/10.1111/jocn.14057
62.
SuwisithN.HanucharururnkulS.DoddM.VorapongsathornT.PongthavorakamolK.AsavamethaN. (2008). Symptom clusters and functional status of women with breast cancer. Thai Journal of Nursing Research, 12(3), 153–165. https://doi.org/10.1016/j.ejon.2009.09.005
63.
SzklarczykD.GableA. L.LyonD.JungeA.WyderS.Huerta-CepasJ.SimonovicM.DonchevaN. T.MorrisJ. H.BorkP.JensenL. J.MeringC. V. (2019). STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47(D1), D607–D613. https://doi.org/10.1093/nar/gky1131
64.
UpadhyayV.FuY. X. (2013). Lymphotoxin signalling in immune homeostasis and the control of microorganisms. Nature Reviews. Immunology, 13(4), 270–279. https://doi.org/10.1038/nri3406
YangG. S.MiX.Jackson-CookC. K.StarkweatherA. R.Lynch KellyD.ArcherK. J.ZouF.LyonD. E. (2020). Differential DNA methylation following chemotherapy for breast cancer is associated with lack of memory improvement at one year. Epigenetics, 15(5), 499–510. https://doi.org/10.1080/15592294.2019.1699695
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