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Combinatorial Chemistry & High Throughput Screening

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ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

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Research Article

Identification and Validation of Co-Expressed Immune-Related Gene Signature Affecting the Pattern of Immune Infiltrating in Esophageal Cancer

Author(s): Rui Cheng, Hao Zeng, Linyan Chen, Lixing Zhou and Birong Dong*

Volume 26, Issue 4, 2023

Published on: 02 September, 2022

Page: [756 - 768] Pages: 13

DOI: 10.2174/1386207325666220705105906

Price: $65

Abstract

Objective: Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive tract, and its molecular mechanisms have not been fully clarified. This study aimed to evaluate the immune infiltration pattern of esophageal cancer through a gene co-expression network, and to provide biomarkers for immunotherapy of esophageal cancer.

Methods: We downloaded RNA-seq data of ESCC samples from GSE53625 and GSE66258 datasets, then assessed the immune score and tumor purity through the ESTIMATE algorithm. Next, a co-expression network was constructed by the weighted gene co-expression network analysis, and the key co-expressed immune- related genes were identified on the basis of existing human immune-related genes. Afterward, we utilized bioinformatics algorithms including GSVA, CIBERSORT, and ssGSEA to clarify the relationship between hub genes and immune infiltration patterns. Finally, these hub genes were used to evaluate the sensitivity to immunotherapy by the subclass mapping algorithm, which were further validated by digital pathology through the Hover- Net algorithm.

Results: Sixteen immune-related genes with robust expression characteristics were identified and used to build gene signatures. The expression of gene signature was significantly related to the immune infiltration pattern and immunotherapy sensitivity prediction in patients with esophageal cancer. Consistent with previous studies, genetic changes at the level of somatic mutations such as NFE2L2 were revealed.

Conclusion: A total of 16 immune-related genes with the total expression gene signature can be used as biomarkers for immunotherapy of esophageal squamous cell carcinoma. Its molecular mechanisms deserve further study to guide clinical treatment in the future.

Keywords: WGCNA, immune microenvironment, immunotherapy, esophageal cancer, pathological verification, immune infiltration

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[1]
Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin., 2018, 68(6), 394-424.
[http://dx.doi.org/10.3322/caac.21492] [PMID: 30207593]
[2]
Jackie Oh, S.; Han, S.; Lee, W.; Lockhart, A.C. Emerging immunotherapy for the treatment of esophageal cancer. Expert Opin. Investig. Drugs, 2016, 25(6), 667-677.
[http://dx.doi.org/10.1517/13543784.2016.1163336] [PMID: 26950826]
[3]
Davidson, M.; Chau, I. Immunotherapy for oesophagogastric cancer. Expert Opin. Biol. Ther., 2016, 16(10), 1197-1207.
[http://dx.doi.org/10.1080/14712598.2016.1213233] [PMID: 27409159]
[4]
Shafaee, A.; Dastyar, D.Z.; Islamian, J.P.; Hatamian, M. Inhibition of tumor energy pathways for targeted esophagus cancer therapy. Metabolism, 2015, 64(10), 1193-1198.
[http://dx.doi.org/10.1016/j.metabol.2015.07.005] [PMID: 26271140]
[5]
Wu, L.; Qu, X. Cancer biomarker detection: Recent achievements and challenges. Chem. Soc. Rev., 2015, 44(10), 2963-2997.
[http://dx.doi.org/10.1039/C4CS00370E] [PMID: 25739971]
[6]
Zeng, D.; Li, M.; Zhou, R.; Zhang, J.; Sun, H.; Shi, M.; Bin, J.; Liao, Y.; Rao, J.; Liao, W. Tumor microenvironment characterization in gastric cancer identifies prognostic and immunotherapeutically relevant gene signatures. Cancer Immunol. Res., 2019, 7(5), 737-750.
[http://dx.doi.org/10.1158/2326-6066.CIR-18-0436] [PMID: 30842092]
[7]
Quail, D.F.; Joyce, J.A. Microenvironmental regulation of tumor progression and metastasis. Nat. Med., 2013, 19(11), 1423-1437.
[http://dx.doi.org/10.1038/nm.3394] [PMID: 24202395]
[8]
Raufi, A.G.; Klempner, S.J. Immunotherapy for advanced gastric and esophageal cancer: Preclinical rationale and ongoing clinical investigations. J. Gastrointest. Oncol., 2015, 6(5), 561-569.
[PMID: 26487950]
[9]
Zhang, C.; Cheng, W.; Ren, X.; Wang, Z.; Liu, X.; Li, G.; Han, S.; Jiang, T.; Wu, A. Tumor purity as an underlying key factor in glioma. Clin. Cancer Res., 2017, 23(20), 6279-6291.
[http://dx.doi.org/10.1158/1078-0432.CCR-16-2598] [PMID: 28754819]
[10]
Huang, T.X.; Fu, L. The immune landscape of esophageal cancer. Cancer Commun. (Lond.), 2019, 39(1), 79.
[http://dx.doi.org/10.1186/s40880-019-0427-z] [PMID: 31771653]
[11]
Zhao, Q.; Yu, J.; Meng, X. A good start of immunotherapy in esophageal cancer. Cancer Med., 2019, 8(10), 4519-4526.
[http://dx.doi.org/10.1002/cam4.2336] [PMID: 31231980]
[12]
Junttila, M.R.; de Sauvage, F.J. Influence of tumour micro-environment heterogeneity on therapeutic response. Nature, 2013, 501(7467), 346-354.
[http://dx.doi.org/10.1038/nature12626] [PMID: 24048067]
[13]
Li, Y.; Lu, Z.; Che, Y.; Wang, J.; Sun, S.; Huang, J.; Mao, S.; Lei, Y.; Chen, Z.; He, J. Immune signature profiling identified predictive and prognostic factors for esophageal squamous cell carcinoma. OncoImmunology, 2017, 6(11), e1356147.
[http://dx.doi.org/10.1080/2162402X.2017.1356147] [PMID: 29147607]
[14]
Tanaka, T.; Nakamura, J.; Noshiro, H. Promising immunotherapies for esophageal cancer. Expert Opin. Biol. Ther., 2017, 17(6), 723-733.
[http://dx.doi.org/10.1080/14712598.2017.1315404] [PMID: 28366014]
[15]
Alsina, M.; Moehler, M.; Lorenzen, S. Immunotherapy of esophageal cancer: Current status, many trials and innovative strategies. Oncol. Res. Treat., 2018, 41(5), 266-271.
[http://dx.doi.org/10.1159/000488120] [PMID: 29705786]
[16]
Thompson, E.D.; Zahurak, M.; Murphy, A.; Cornish, T.; Cuka, N.; Abdelfatah, E.; Yang, S.; Duncan, M.; Ahuja, N.; Taube, J.M.; Anders, R.A.; Kelly, R.J. Patterns of PD-L1 expression and CD8 T cell infiltration in gastric adenocarcinomas and associated immune stroma. Gut, 2017, 66(5), 794-801.
[http://dx.doi.org/10.1136/gutjnl-2015-310839] [PMID: 26801886]
[17]
Miao, D.; Margolis, C.A.; Gao, W.; Voss, M.H.; Li, W.; Martini, D.J.; Norton, C.; Bossé, D.; Wankowicz, S.M.; Cullen, D.; Horak, C.; Wind-Rotolo, M.; Tracy, A.; Giannakis, M.; Hodi, F.S.; Drake, C.G.; Ball, M.W.; Allaf, M.E.; Snyder, A.; Hellmann, M.D.; Ho, T.; Motzer, R.J.; Signoretti, S.; Kaelin, W.G., Jr; Choueiri, T.K.; Van Allen, E.M. Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma. Science, 2018, 359(6377), 801-806.
[http://dx.doi.org/10.1126/science.aan5951] [PMID: 29301960]
[18]
Solomon, B.; Young, R.J.; Rischin, D. Head and neck squamous cell carcinoma: Genomics and emerging biomarkers for immunomodulatory cancer treatments. Semin. Cancer Biol., 2018, 52(Pt 2), 228-240.
[http://dx.doi.org/10.1016/j.semcancer.2018.01.008] [PMID: 29355614]
[19]
Doroshow, D.B.; Sanmamed, M.F.; Hastings, K.; Politi, K.; Rimm, D.L.; Chen, L.; Melero, I.; Schalper, K.A.; Herbst, R.S. Immunotherapy in non-small cell lung cancer: Facts and hopes. Clin. Cancer Res., 2019, 25(15), 4592-4602.
[http://dx.doi.org/10.1158/1078-0432.CCR-18-1538] [PMID: 30824587]
[20]
Niazi, M.K.K.; Parwani, A.V.; Gurcan, M.N. Digital pathology and artificial intelligence. Lancet Oncol., 2019, 20(5), e253-e261.
[http://dx.doi.org/10.1016/S1470-2045(19)30154-8] [PMID: 31044723]
[21]
Graham, S.; Vu, Q.D.; Raza, S.E.A.; Azam, A.; Tsang, Y.W.; Kwak, J.T.; Rajpoot, N. Hover-net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images. Med. Image Anal., 2019, 58, 101563.
[http://dx.doi.org/10.1016/j.media.2019.101563] [PMID: 31561183]
[22]
Singh, A.V.; Rosenkranz, D.; Ansari, M.H.D.; Singh, R.; Kanase, A.; Singh, S.P.; Johnston, B.; Tentschert, J.; Laux, P.; Luch, A. Artificial intelligence and machine learning empower advanced biomedical material design to toxicity prediction. Adv. Intell. Syst., 2020, 2(12), 2000084.
[http://dx.doi.org/10.1002/aisy.202000084]
[23]
Singh, A.V.; Jahnke, T.; Kishore, V.; Park, B.W.; Batuwangala, M.; Bill, J.; Sitti, M. Cancer cells biomineralize ionic gold into nanoparticles-microplates via secreting defense proteins with specific gold-binding peptides. Acta Biomater., 2018, 71, 61-71.
[http://dx.doi.org/10.1016/j.actbio.2018.02.022] [PMID: 29499399]
[24]
Newman, A.M.; Liu, C.L.; Green, M.R.; Gentles, A.J.; Feng, W.; Xu, Y.; Hoang, C.D.; Diehn, M.; Alizadeh, A.A. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods, 2015, 12(5), 453-457.
[http://dx.doi.org/10.1038/nmeth.3337] [PMID: 25822800]
[25]
Yoshihara, K.; Shahmoradgoli, M.; Martínez, E.; Vegesna, R.; Kim, H.; Torres-Garcia, W.; Treviño, V.; Shen, H.; Laird, P.W.; Levine, D.A.; Carter, S.L.; Getz, G.; Stemke-Hale, K.; Mills, G.B.; Verhaak, R.G. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat. Commun., 2013, 4, 2612.
[http://dx.doi.org/10.1038/ncomms3612] [PMID: 24113773]
[26]
Barbie, D.A.; Tamayo, P.; Boehm, J.S.; Kim, S.Y.; Moody, S.E.; Dunn, I.F.; Schinzel, A.C.; Sandy, P.; Meylan, E.; Scholl, C.; Fröhling, S.; Chan, E.M.; Sos, M.L.; Michel, K.; Mermel, C.; Silver, S.J.; Weir, B.A.; Reiling, J.H.; Sheng, Q.; Gupta, P.B.; Wadlow, R.C.; Le, H.; Hoersch, S.; Wittner, B.S.; Ramaswamy, S.; Livingston, D.M.; Sabatini, D.M.; Meyerson, M.; Thomas, R.K.; Lander, E.S.; Mesirov, J.P.; Root, D.E.; Gilliland, D.G.; Jacks, T.; Hahn, W.C. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature, 2009, 462(7269), 108-112.
[http://dx.doi.org/10.1038/nature08460] [PMID: 19847166]
[27]
Jiang, P.; Gu, S.; Pan, D.; Fu, J.; Sahu, A.; Hu, X.; Li, Z.; Traugh, N.; Bu, X.; Li, B.; Liu, J.; Freeman, G.J.; Brown, M.A.; Wucherpfennig, K.W.; Liu, X.S. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat. Med., 2018, 24(10), 1550-1558.
[http://dx.doi.org/10.1038/s41591-018-0136-1] [PMID: 30127393]
[28]
Barrett, T.; Wilhite, S.E.; Ledoux, P.; Evangelista, C.; Kim, I.F.; Tomashevsky, M.; Marshall, K.A.; Phillippy, K.H.; Sherman, P.M.; Holko, M.; Yefanov, A.; Lee, H.; Zhang, N.; Robertson, C.L.; Serova, N.; Davis, S.; Soboleva, A. NCBI GEO: Archive for functional genomics data sets--update. Nucleic Acids Res., 2013, 41(Database issue), D991-D995.
[PMID: 23193258]
[29]
Weinstein, J.N.; Collisson, E.A.; Mills, G.B.; Shaw, K.R.; Ozenberger, B.A.; Ellrott, K.; Shmulevich, I.; Sander, C.; Stuart, J.M. The cancer genome atlas pan-cancer analysis project. Nat. Genet., 2013, 45(10), 1113-1120.
[http://dx.doi.org/10.1038/ng.2764] [PMID: 24071849]
[30]
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]
[31]
Langfelder, P.; Horvath, S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics, 2008, 9, 559.
[http://dx.doi.org/10.1186/1471-2105-9-559] [PMID: 19114008]
[32]
Singh, A.V.; Maharjan, R.S.; Jungnickel, H.; Romanowski, H.; Hachenberger, Y.U.; Reichardt, P.; Bierkandt, F.; Siewert, K.; Gadicherla, A.; Laux, P.; Luch, A. Evaluating particle emissions and toxicity of 3D pen printed filaments with metal nanoparticles as additives: In vitro and in silico discriminant function analysis. ACS Sustain. Chem.& Eng., 2021, 9(35), 11724-11737.
[http://dx.doi.org/10.1021/acssuschemeng.1c02589]
[33]
Singh, A.V.; Maharjan, R.S.; Kanase, A.; Siewert, K.; Rosenkranz, D.; Singh, R.; Laux, P.; Luch, A. Machine-learning-based approach to decode the influence of nanomaterial properties on their interaction with cells. ACS Appl. Mater. Interfaces, 2021, 13(1), 1943-1955.
[http://dx.doi.org/10.1021/acsami.0c18470] [PMID: 33373205]
[34]
Bhattacharya, S.; Dunn, P.; Thomas, C.G.; Smith, B.; Schaefer, H.; Chen, J.; Hu, Z.; Zalocusky, K.A.; Shankar, R.D.; Shen-Orr, S.S.; Thomson, E.; Wiser, J.; Butte, A.J. ImmPort, toward repurposing of open access immunological assay data for translational and clinical research. Sci. Data, 2018, 5, 180015.
[http://dx.doi.org/10.1038/sdata.2018.15] [PMID: 29485622]
[35]
Zhou, Y.; Zhou, B.; Pache, L.; Chang, M.; Khodabakhshi, A.H.; Tanaseichuk, O.; Benner, C.; Chanda, S.K. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun., 2019, 10(1), 1523.
[http://dx.doi.org/10.1038/s41467-019-09234-6] [PMID: 30944313]
[36]
Zhang, Y.; Kurupati, R.; Liu, L.; Zhou, X.Y.; Zhang, G.; Hudaihed, A.; Filisio, F.; Giles-Davis, W.; Xu, X.; Karakousis, G.C.; Schuchter, L.M.; Xu, W.; Amaravadi, R.; Xiao, M.; Sadek, N.; Krepler, C.; Herlyn, M.; Freeman, G.J.; Rabinowitz, J.D.; Ertl, H.C.J. Enhancing CD8+ T cell fatty acid catabolism within a metabolically challenging tumor microenvironment increases the efficacy of melanoma immunotherapy. Cancer Cell, 2017, 32(3), 377-391.e9.
[http://dx.doi.org/10.1016/j.ccell.2017.08.004] [PMID: 28898698]
[37]
Odunsi, K. Immunotherapy in ovarian cancer. Ann. Oncol., 2017, 28(suppl_8), viii1-viii7.
[http://dx.doi.org/10.1093/annonc/mdx444]
[38]
Bremnes, R.M.; Busund, L.T.; Kilvær, T.L.; Andersen, S.; Richardsen, E.; Paulsen, E.E.; Hald, S.; Khanehkenari, M.R.; Cooper, W.A.; Kao, S.C.; Dønnem, T. The role of tumor-infiltrating lymphocytes in development, progression, and prognosis of non-small cell lung cancer. J. Thorac. Oncol., 2016, 11(6), 789-800.
[http://dx.doi.org/10.1016/j.jtho.2016.01.015] [PMID: 26845192]
[39]
Wen, Q.; Yang, Z.; Zhu, J.; Qiu, Q.; Dai, H.; Feng, A.; Xing, L. Pretreatment CT-based radiomics signature as a potential imaging biomarker for predicting the expression of PD-L1 and CD8+TILs in ESCC. OncoTargets Ther., 2020, 13, 12003-12013.
[http://dx.doi.org/10.2147/OTT.S261068] [PMID: 33244242]
[40]
Sudo, T.; Nishida, R.; Kawahara, A.; Saisho, K.; Mimori, K.; Yamada, A.; Mizoguchi, A.; Kadoya, K.; Matono, S.; Mori, N.; Tanaka, T.; Akagi, Y. Clinical impact of tumor-infiltrating lymphocytes in esophageal squamous cell carcinoma. Ann. Surg. Oncol., 2017, 24(12), 3763-3770.
[http://dx.doi.org/10.1245/s10434-017-5796-4] [PMID: 28160141]
[41]
Wang, Z.; Wang, Y.; Peng, M.; Yi, L. UBASH3B is a novel prognostic biomarker and correlated with immune infiltrates in prostate cancer. Front. Oncol., 2020, 9, 1517.
[http://dx.doi.org/10.3389/fonc.2019.01517] [PMID: 32010618]
[42]
Wang, Z.; Peng, M. A novel prognostic biomarker LCP2 correlates with metastatic melanoma-infiltrating CD8+ T cells. Sci. Rep., 2021, 11(1), 9164.
[http://dx.doi.org/10.1038/s41598-021-88676-9] [PMID: 33911146]
[43]
Yang, Y.; Zang, Y.; Zheng, C.; Li, Z.; Gu, X.; Zhou, M.; Wang, Z.; Xiang, J.; Chen, Z.; Zhou, Y. CD3D is associated with immune checkpoints and predicts favorable clinical outcome in colon cancer. Immunotherapy, 2020, 12(1), 25-35.
[http://dx.doi.org/10.2217/imt-2019-0145] [PMID: 31914842]
[44]
Chung, W.C.; Zhou, X.; Atfi, A.; Xu, K. PIK3CG is a potential therapeutic target in androgen receptor-indifferent metastatic prostate cancer. Am. J. Pathol., 2020, 190(11), 2194-2202.
[http://dx.doi.org/10.1016/j.ajpath.2020.07.013] [PMID: 32805234]
[45]
Shi, M.J.; Meng, X.Y.; Wu, Q.J.; Zhou, X.H. High CD3D/CD4 ratio predicts better survival in muscle-invasive bladder cancer. Cancer Manag. Res., 2019, 11, 2987-2995.
[http://dx.doi.org/10.2147/CMAR.S191105] [PMID: 31114346]
[46]
Martincorena, I.; Campbell, P.J. Somatic mutation in cancer and normal cells. Science, 2015, 349(6255), 1483-1489.
[http://dx.doi.org/10.1126/science.aab4082] [PMID: 26404825]
[47]
Song, Y.; Li, L.; Ou, Y.; Gao, Z.; Li, E.; Li, X.; Zhang, W.; Wang, J.; Xu, L.; Zhou, Y.; Ma, X.; Liu, L.; Zhao, Z.; Huang, X.; Fan, J.; Dong, L.; Chen, G.; Ma, L.; Yang, J.; Chen, L.; He, M.; Li, M.; Zhuang, X.; Huang, K.; Qiu, K.; Yin, G.; Guo, G.; Feng, Q.; Chen, P.; Wu, Z.; Wu, J.; Ma, L.; Zhao, J.; Luo, L.; Fu, M.; Xu, B.; Chen, B.; Li, Y.; Tong, T.; Wang, M.; Liu, Z.; Lin, D.; Zhang, X.; Yang, H.; Wang, J.; Zhan, Q. Identification of genomic alterations in oesophageal squamous cell cancer. Nature, 2014, 509(7498), 91-95.
[http://dx.doi.org/10.1038/nature13176] [PMID: 24670651]
[48]
Rojo de la Vega, M.; Chapman, E.; Zhang, D.D. NRF2 and the hallmarks of cancer. Cancer Cell, 2018, 34(1), 21-43.
[http://dx.doi.org/10.1016/j.ccell.2018.03.022] [PMID: 29731393]
[49]
Lignitto, L.; LeBoeuf, S.E.; Homer, H.; Jiang, S.; Askenazi, M.; Karakousi, T.R.; Pass, H.I.; Bhutkar, A.J.; Tsirigos, A.; Ueberheide, B.; Sayin, V.I.; Papagiannakopoulos, T.; Pagano, M. Nrf2 activation promotes lung cancer metastasis by inhibiting the degradation of bach1. Cell, 2019, 178(2), 316-329.e18.
[http://dx.doi.org/10.1016/j.cell.2019.06.003] [PMID: 31257023]
[50]
Ju, Q.; Li, X.; Zhang, H.; Yan, S.; Li, Y.; Zhao, Y. NFE2L2 is a potential prognostic biomarker and is correlated with immune infiltration in brain lower grade glioma: A pan-cancer analysis. Oxid. Med. Cell. Longev., 2020, 2020, 3580719.
[http://dx.doi.org/10.1155/2020/3580719] [PMID: 33101586]
[51]
Jeong, Y.; Hellyer, J.A.; Stehr, H.; Hoang, N.T.; Niu, X.; Das, M.; Padda, S.K.; Ramchandran, K.; Neal, J.W.; Wakelee, H.; Diehn, M. Role of KEAP1/NFE2L2 mutations in the chemotherapeutic response of patients with non-small cell lung cancer. Clin. Cancer Res., 2020, 26(1), 274-281.
[http://dx.doi.org/10.1158/1078-0432.CCR-19-1237] [PMID: 31548347]
[52]
Jean-Quartier, C.; Jeanquartier, F.; Jurisica, I.; Holzinger, A. In silico cancer research towards 3R. BMC Cancer, 2018, 18(1), 408.
[http://dx.doi.org/10.1186/s12885-018-4302-0] [PMID: 29649981]
[53]
Strausberg, R.L.; Greenhut, S.F.; Grouse, L.H.; Schaefer, C.F.; Buetow, K.H. In silico analysis of cancer through the cancer genome anatomy project. Trends Cell Biol., 2001, 11(11), S66-S71.
[http://dx.doi.org/10.1016/S0962-8924(01)02104-3] [PMID: 11684445]

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