Generic placeholder image

Current Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

Research Article

A Five-gene Signature based on MicroRNA for Predicting Prognosis and Immunotherapy in Stomach Adenocarcinoma

Author(s): Tianwei Wang, Piji Chen, Tingting Li, Jianong Li, Dong Zhao, Fanfei Meng, Yujie Zhao, Zhendong Zheng* and Xuefei Liu*

Volume 31, Issue 17, 2024

Published on: 05 January, 2024

Page: [2378 - 2399] Pages: 22

DOI: 10.2174/0109298673281631231127051017

Price: $65

Open Access Journals Promotions 2
Abstract

Aims: We aimed to classify molecular subtypes and establish a prognostic gene signature based on miRNAs for the prognostic prediction and therapeutic response in Stomach adenocarcinoma (STAD).

Background: STAD is a common diagnosed gastrointestinal malignancy and its heterogeneity is a big challenge that influences prognosis and precision therapies. Present study was designed to classify molecular subtypes and construct a prognostic gene signature based on miRNAs for the prognostic prediction and therapeutic response in STAD.

Objective: The objective of this study is to investigate the molecular subtypes and prognostic model for STAD.

Methods: A STAD specific miRNA-messenger RNA (mRNA) competing endogenous RNA (ceRNA) network was generated using the RNA-Seq and miRNA expression profiles from The Cancer Genome Atlas (TCGA) database, in which miRNA-related mRNAs were screened. Molecular subtypes were then determined using miRNA-related genes. Through univariate Cox analysis and multivariate regression analysis, a prognostic model was established in GSE84437 Train dataset and validated in GSE84437 Test, TCGA, GSE84437 and GSE66229 datasets. Immunotherapy datasets were employed for assessing the performance of the risk model. Finally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was applied to validate the expression of hub genes used for the risk score signature.

Results: We constructed a ceRNA network containing 84 miRNAs and 907 mRNAs and determined two molecular subtypes based on 26 genes from the intersection of TCGASTAD and GSE84437 datasets. Subtype S2 had poor prognosis, lower tumor mutational burden, higher immune score and lower response to immunotherapy. Subtype S1 was more sensitive to Sorafenib, Pyrimethamine, Salubrinal, Gemcitabine, Vinorelbine and AKT inhibitor VIII. Next, a five-gene signature was generated and its robustness was validated in Test and external datasets. This risk model also had a good prediction performance in immunotherapy datasets.

Conclusion: This study promotes the underlying mechanisms of miRNA-based genes in STAD and offers directions for classification. A five-gene signature accurately predicts the prognosis and helps therapeutic options.

Keywords: Stomach adenocarcinoma, competing endogenous RNA, MicroRNA, classification, prognosis, immunotherapy.

[1]
Chen, L.; Lu, L.; Gong, X.; Xu, Y.; Chu, X.; Huang, G. Gastric cancer with bone marrow invasion and disseminated intravascular coagulation: A case report. Oncologie, 2022, 24(3), 599-604.
[http://dx.doi.org/10.32604/oncologie.2022.023310]
[2]
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]
[3]
Qiu, H.; Cao, S.; Xu, R. Cancer incidence, mortality, and burden in China: A time-trend analysis and comparison with the United States and United Kingdom based on the global epidemiological data released in 2020. Cancer Commun., 2021, 41(10), 1037-1048.
[http://dx.doi.org/10.1002/cac2.12197] [PMID: 34288593]
[4]
Sun, D.; Cao, M.; Li, H.; He, S.; Chen, W. Cancer burden and trends in China: A review and comparison with Japan and South Korea. Chin. J. Cancer Res., 2020, 32(2), 129-139.
[http://dx.doi.org/10.21147/j.issn.1000-9604.2020.02.01] [PMID: 32410791]
[5]
Balakrishnan, M.; George, R.; Sharma, A.; Graham, D.Y. Changing trends in stomach cancer throughout the world. Curr. Gastroenterol. Rep., 2017, 19(8), 36.
[http://dx.doi.org/10.1007/s11894-017-0575-8] [PMID: 28730504]
[6]
Poorolajal, J.; Moradi, L.; Mohammadi, Y.; Cheraghi, Z.; Gohari-Ensaf, F. Risk factors for stomach cancer: A systematic review and meta-analysis. Epidemiol. Health, 2020, 42, e2020004.
[http://dx.doi.org/10.4178/epih.e2020004] [PMID: 32023777]
[7]
Jafari-Sales, A.; Shariat, A.; Bannazadeh Baghi, H.; Baradaran, B.; Jafari, B. The presence of human papillomavirus and epstein-barr virus infection in gastric cancer: A systematic study. Oncologie, 2022, 24(3), 413-426.
[http://dx.doi.org/10.32604/oncologie.2022.024161]
[8]
Wittekind, C. The development of the TNM classification of gastric cancer. Pathol. Int., 2015, 65(8), 399-403.
[http://dx.doi.org/10.1111/pin.12306] [PMID: 26036980]
[9]
Li, M.; Wei, J.; Xu, G.; Liu, Y.; Zhu, J. Surgery combined with molecular targeted therapy successfully treated giant esophageal gastrointestinal stromal tumor. Oncologie, 2022, 24(2), 349-356.
[http://dx.doi.org/10.32604/oncologie.2022.022436]
[10]
Zhang, M.; Hu, S.; Min, M.; Ni, Y.; Lu, Z.; Sun, X.; Wu, J.; Liu, B.; Ying, X.; Liu, Y. Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing. Gut, 2021, 70(3), 464-475.
[http://dx.doi.org/10.1136/gutjnl-2019-320368] [PMID: 32532891]
[11]
Ali Syeda, Z.; Langden, S.S.S.; Munkhzul, C.; Lee, M.; Song, S.J. Regulatory mechanism of MicroRNA expression in cancer. Int. J. Mol. Sci., 2020, 21(5), 1723.
[http://dx.doi.org/10.3390/ijms21051723] [PMID: 32138313]
[12]
Chen, X.; Li, T.H.; Zhao, Y.; Wang, C.C.; Zhu, C.C. Deep-belief network for predicting potential miRNA-disease associations. Brief. Bioinform., 2021, 22(3), bbaa186.
[http://dx.doi.org/10.1093/bib/bbaa186] [PMID: 34020550]
[13]
Ha, J.; Park, C.; Park, C.; Park, S. IMIPMF: Inferring miRNA-disease interactions using probabilistic matrix factorization. J. Biomed. Inform., 2020, 102, 103358.
[http://dx.doi.org/10.1016/j.jbi.2019.103358] [PMID: 31857202]
[14]
Ha, J.; Park, S. NCMD: Node2vec-based neural collaborative filtering for predicting MiRNA-Disease Association. IEEE/ACM Trans. Comput. Biol. Bioinform., 2023, 20(2), 1257-1268.
[http://dx.doi.org/10.1109/TCBB.2022.3191972]
[15]
Ha, J. MDMF: Predicting miRNA–Disease association based on matrix factorization with disease similarity constraint. J. Pers. Med., 2022, 12(6), 885.
[http://dx.doi.org/10.3390/jpm12060885] [PMID: 35743670]
[16]
Ha, J. SMAP: Similarity-based matrix factorization framework for inferring miRNA-disease association. Knowl. Base. Syst., 2023, 263, 110295.
[http://dx.doi.org/10.1016/j.knosys.2023.110295]
[17]
Qi, X.; Lin, Y.; Chen, J.; Shen, B. Decoding competing endogenous RNA networks for cancer biomarker discovery. Brief. Bioinform., 2020, 21(2), 441-457.
[http://dx.doi.org/10.1093/bib/bbz006] [PMID: 30715152]
[18]
Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res., 2003, 13(11), 2498-2504.
[http://dx.doi.org/10.1101/gr.1239303] [PMID: 14597658]
[19]
Liao, Y.; Wang, J.; Jaehnig, E.J.; Shi, Z.; Zhang, B. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. Nucleic Acids Res., 2019, 47(W1), W199-W205.
[http://dx.doi.org/10.1093/nar/gkz401] [PMID: 31114916]
[20]
Wilkerson, M.; Waltman, P.; Wilkerson, M.M. Package ‘ConsensusClusterPlus’ a class discovery tool with confidence assessments and item tracking. Bioinformatics, 2013, 26(12), 1572-1573.
[21]
Thorsson, V.; Gibbs, D.L.; Brown, S.D.; Wolf, D.; Bortone, D.S.; Ou, Yang T.H.; Porta-Pardo, E.; Gao, G.F.; Plaisier, C.L.; Eddy, J.A.; Ziv, E.; Culhane, A.C.; Paull, E.O.; Sivakumar, I.K.A.; Gentles, A.J.; Malhotra, R.; Farshidfar, F.; Colaprico, A.; Parker, J.S.; Mose, L.E.; Vo, N.S.; Liu, J.; Liu, Y.; Rader, J.; Dhankani, V.; Reynolds, S.M.; Bowlby, R.; Califano, A.; Cherniack, A.D.; Anastassiou, D.; Bedognetti, D.; Mokrab, Y.; Newman, A.M.; Rao, A.; Chen, K.; Krasnitz, A.; Hu, H.; Malta, T.M.; Noushmehr, H.; Pedamallu, C.S.; Bullman, S.; Ojesina, A.I.; Lamb, A.; Zhou, W.; Shen, H.; Choueiri, T.K.; Weinstein, J.N.; Guinney, J.; Saltz, J.; Holt, R.A.; Rabkin, C.S.; Lazar, A.J.; Serody, J.S.; Demicco, E.G.; Disis, M.L.; Vincent, B.G.; Shmulevich, I.; Caesar-Johnson, S.J.; Demchok, J.A.; Felau, I.; Kasapi, M.; Ferguson, M.L.; Hutter, C.M.; Sofia, H.J.; Tarnuzzer, R.; Wang, Z.; Yang, L.; Zenklusen, J.C.; Zhang, J.J.; Chudamani, S.; Liu, J.; Lolla, L.; Naresh, R.; Pihl, T.; Sun, Q.; Wan, Y.; Wu, Y.; Cho, J.; DeFreitas, T.; Frazer, S.; Gehlenborg, N.; Getz, G.; Heiman, D.I.; Kim, J.; Lawrence, M.S.; Lin, P.; Meier, S.; Noble, M.S.; Saksena, G.; Voet, D.; Zhang, H.; Bernard, B.; Chambwe, N.; Dhankani, V.; Knijnenburg, T.; Kramer, R.; Leinonen, K.; Liu, Y.; Miller, M.; Reynolds, S.; Shmulevich, I.; Thorsson, V.; Zhang, W.; Akbani, R.; Broom, B.M.; Hegde, A.M.; Ju, Z.; Kanchi, R.S.; Korkut, A.; Li, J.; Liang, H.; Ling, S.; Liu, W.; Lu, Y.; Mills, G.B.; Ng, K-S.; Rao, A.; Ryan, M.; Wang, J.; Weinstein, J.N.; Zhang, J.; Abeshouse, A.; Armenia, J.; Chakravarty, D.; Chatila, W.K.; de Bruijn, I.; Gao, J.; Gross, B.E.; Heins, Z.J.; Kundra, R.; La, K.; Ladanyi, M.; Luna, A.; Nissan, M.G.; Ochoa, A.; Phillips, S.M.; Reznik, E.; Sanchez-Vega, F.; Sander, C.; Schultz, N.; Sheridan, R.; Sumer, S.O.; Sun, Y.; Taylor, B.S.; Wang, J.; Zhang, H.; Anur, P.; Peto, M.; Spellman, P.; Benz, C.; Stuart, J.M.; Wong, C.K.; Yau, C.; Hayes, D.N.; Parker, J.S.; Wilkerson, M.D.; Ally, A.; Balasundaram, M.; Bowlby, R.; Brooks, D.; Carlsen, R.; Chuah, E.; Dhalla, N.; Holt, R.; Jones, S.J.M.; Kasaian, K.; Lee, D.; Ma, Y.; Marra, M.A.; Mayo, M.; Moore, R.A.; Mungall, A.J.; Mungall, K.; Robertson, A.G.; Sadeghi, S.; Schein, J.E.; Sipahimalani, P.; Tam, A.; Thiessen, N.; Tse, K.; Wong, T.; Berger, A.C.; Beroukhim, R.; Cherniack, A.D.; Cibulskis, C.; Gabriel, S.B.; Gao, G.F.; Ha, G.; Meyerson, M.; Schumacher, S.E.; Shih, J.; Kucherlapati, M.H.; Kucherlapati, R.S.; Baylin, S.; Cope, L.; Danilova, L.; Bootwalla, M.S.; Lai, P.H.; Maglinte, D.T.; Van Den Berg, D.J.; Weisenberger, D.J.; Auman, J.T.; Balu, S.; Bodenheimer, T.; Fan, C.; Hoadley, K.A.; Hoyle, A.P.; Jefferys, S.R.; Jones, C.D.; Meng, S.; Mieczkowski, P.A.; Mose, L.E.; Perou, A.H.; Perou, C.M.; Roach, J.; Shi, Y.; Simons, J.V.; Skelly, T.; Soloway, M.G.; Tan, D.; Veluvolu, U.; Fan, H.; Hinoue, T.; Laird, P.W.; Shen, H.; Zhou, W.; Bellair, M.; Chang, K.; Covington, K.; Creighton, C.J.; Dinh, H.; Doddapaneni, H.V.; Donehower, L.A.; Drummond, J.; Gibbs, R.A.; Glenn, R.; Hale, W.; Han, Y.; Hu, J.; Korchina, V.; Lee, S.; Lewis, L.; Li, W.; Liu, X.; Morgan, M.; Morton, D.; Muzny, D.; Santibanez, J.; Sheth, M.; Shinbrot, E.; Wang, L.; Wang, M.; Wheeler, D.A.; Xi, L.; Zhao, F.; Hess, J.; Appelbaum, E.L.; Bailey, M.; Cordes, M.G.; Ding, L.; Fronick, C.C.; Fulton, L.A.; Fulton, R.S.; Kandoth, C.; Mardis, E.R.; McLellan, M.D.; Miller, C.A.; Schmidt, H.K.; Wilson, R.K.; Crain, D.; Curley, E.; Gardner, J.; Lau, K.; Mallery, D.; Morris, S.; Paulauskis, J.; Penny, R.; Shelton, C.; Shelton, T.; Sherman, M.; Thompson, E.; Yena, P.; Bowen, J.; Gastier-Foster, J.M.; Gerken, M.; Leraas, K.M.; Lichtenberg, T.M.; Ramirez, N.C.; Wise, L.; Zmuda, E.; Corcoran, N.; Costello, T.; Hovens, C.; Carvalho, A.L.; de Carvalho, A.C.; Fregnani, J.H.; Longatto-Filho, A.; Reis, R.M.; Scapulatempo-Neto, C.; Silveira, H.C.S.; Vidal, D.O.; Burnette, A.; Eschbacher, J.; Hermes, B.; Noss, A.; Singh, R.; Anderson, M.L.; Castro, P.D.; Ittmann, M.; Huntsman, D.; Kohl, B.; Le, X.; Thorp, R.; Andry, C.; Duffy, E.R.; Lyadov, V.; Paklina, O.; Setdikova, G.; Shabunin, A.; Tavobilov, M.; McPherson, C.; Warnick, R.; Berkowitz, R.; Cramer, D.; Feltmate, C.; Horowitz, N.; Kibel, A.; Muto, M.; Raut, C.P.; Malykh, A.; Barnholtz-Sloan, J.S.; Barrett, W.; Devine, K.; Fulop, J.; Ostrom, Q.T.; Shimmel, K.; Wolinsky, Y.; Sloan, A.E.; De Rose, A.; Giuliante, F.; Goodman, M.; Karlan, B.Y.; Hagedorn, C.H.; Eckman, J.; Harr, J.; Myers, J.; Tucker, K.; Zach, L.A.; Deyarmin, B.; Hu, H.; Kvecher, L.; Larson, C.; Mural, R.J.; Somiari, S.; Vicha, A.; Zelinka, T.; Bennett, J.; Iacocca, M.; Rabeno, B.; Swanson, P.; Latour, M.; Lacombe, L.; Têtu, B.; Bergeron, A.; McGraw, M.; Staugaitis, S.M.; Chabot, J.; Hibshoosh, H.; Sepulveda, A.; Su, T.; Wang, T.; Potapova, O.; Voronina, O.; Desjardins, L.; Mariani, O.; Roman-Roman, S.; Sastre, X.; Stern, M-H.; Cheng, F.; Signoretti, S.; Berchuck, A.; Bigner, D.; Lipp, E.; Marks, J.; McCall, S.; McLendon, R.; Secord, A.; Sharp, A.; Behera, M.; Brat, D.J.; Chen, A.; Delman, K.; Force, S.; Khuri, F.; Magliocca, K.; Maithel, S.; Olson, J.J.; Owonikoko, T.; Pickens, A.; Ramalingam, S.; Shin, D.M.; Sica, G.; Van Meir, E.G.; Zhang, H.; Eijckenboom, W.; Gillis, A.; Korpershoek, E.; Looijenga, L.; Oosterhuis, W.; Stoop, H.; van Kessel, K.E.; Zwarthoff, E.C.; Calatozzolo, C.; Cuppini, L.; Cuzzubbo, S.; DiMeco, F.; Finocchiaro, G.; Mattei, L.; Perin, A.; Pollo, B.; Chen, C.; Houck, J.; Lohavanichbutr, P.; Hartmann, A.; Stoehr, C.; Stoehr, R.; Taubert, H.; Wach, S.; Wullich, B.; Kycler, W.; Murawa, D.; Wiznerowicz, M.; Chung, K.; Edenfield, W.J.; Martin, J.; Baudin, E.; Bubley, G.; Bueno, R.; De Rienzo, A.; Richards, W.G.; Kalkanis, S.; Mikkelsen, T.; Noushmehr, H.; Scarpace, L.; Girard, N.; Aymerich, M.; Campo, E.; Giné, E.; Guillermo, A.L.; Van Bang, N.; Hanh, P.T.; Phu, B.D.; Tang, Y.; Colman, H.; Evason, K.; Dottino, P.R.; Martignetti, J.A.; Gabra, H.; Juhl, H.; Akeredolu, T.; Stepa, S.; Hoon, D.; Ahn, K.; Kang, K.J.; Beuschlein, F.; Breggia, A.; Birrer, M.; Bell, D.; Borad, M.; Bryce, A.H.; Castle, E.; Chandan, V.; Cheville, J.; Copland, J.A.; Farnell, M.; Flotte, T.; Giama, N.; Ho, T.; Kendrick, M.; Kocher, J-P.; Kopp, K.; Moser, C.; Nagorney, D.; O’Brien, D.; O’Neill, B.P.; Patel, T.; Petersen, G.; Que, F.; Rivera, M.; Roberts, L.; Smallridge, R.; Smyrk, T.; Stanton, M.; Thompson, R.H.; Torbenson, M.; Yang, J.D.; Zhang, L.; Brimo, F.; Ajani, J.A.; Gonzalez, A.M.A.; Behrens, C.; Bondaruk, J.; Broaddus, R.; Czerniak, B.; Esmaeli, B.; Fujimoto, J.; Gershenwald, J.; Guo, C.; Lazar, A.J.; Logothetis, C.; Meric-Bernstam, F.; Moran, C.; Ramondetta, L.; Rice, D.; Sood, A.; Tamboli, P.; Thompson, T.; Troncoso, P.; Tsao, A.; Wistuba, I.; Carter, C.; Haydu, L.; Hersey, P.; Jakrot, V.; Kakavand, H.; Kefford, R.; Lee, K.; Long, G.; Mann, G.; Quinn, M.; Saw, R.; Scolyer, R.; Shannon, K.; Spillane, A.; Stretch; Synott, M.; Thompson, J.; Wilmott, J.; Al-Ahmadie, H.; Chan, T.A.; Ghossein, R.; Gopalan, A.; Levine, D.A.; Reuter, V.; Singer, S.; Singh, B.; Tien, N.V.; Broudy, T.; Mirsaidi, C.; Nair, P.; Drwiega, P.; Miller, J.; Smith, J.; Zaren, H.; Park, J-W.; Hung, N.P.; Kebebew, E.; Linehan, W.M.; Metwalli, A.R.; Pacak, K.; Pinto, P.A.; Schiffman, M.; Schmidt, L.S.; Vocke, C.D.; Wentzensen, N.; Worrell, R.; Yang, H.; Moncrieff, M.; Goparaju, C.; Melamed, J.; Pass, H.; Botnariuc, N.; Caraman, I.; Cernat, M.; Chemencedji, I.; Clipca, A.; Doruc, S.; Gorincioi, G.; Mura, S.; Pirtac, M.; Stancul, I.; Tcaciuc, D.; Albert, M.; Alexopoulou, I.; Arnaout, A.; Bartlett, J.; Engel, J.; Gilbert, S.; Parfitt, J.; Sekhon, H.; Thomas, G.; Rassl, D.M.; Rintoul, R.C.; Bifulco, C.; Tamakawa, R.; Urba, W.; Hayward, N.; Timmers, H.; Antenucci, A.; Facciolo, F.; Grazi, G.; Marino, M.; Merola, R.; de Krijger, R.; Gimenez-Roqueplo, A-P.; Piché, A.; Chevalier, S.; McKercher, G.; Birsoy, K.; Barnett, G.; Brewer, C.; Farver, C.; Naska, T.; Pennell, N.A.; Raymond, D.; Schilero, C.; Smolenski, K.; Williams, F.; Morrison, C.; Borgia, J.A.; Liptay, M.J.; Pool, M.; Seder, C.W.; Junker, K.; Omberg, L.; Dinkin, M.; Manikhas, G.; Alvaro, D.; Bragazzi, M.C.; Cardinale, V.; Carpino, G.; Gaudio, E.; Chesla, D.; Cottingham, S.; Dubina, M.; Moiseenko, F.; Dhanasekaran, R.; Becker, K-F.; Janssen, K-P.; Slotta-Huspenina, J.; Abdel-Rahman, M.H.; Aziz, D.; Bell, S.; Cebulla, C.M.; Davis, A.; Duell, R.; Elder, J.B.; Hilty, J.; Kumar, B.; Lang, J.; Lehman, N.L.; Mandt, R.; Nguyen, P.; Pilarski, R.; Rai, K.; Schoenfield, L.; Senecal, K.; Wakely, P.; Hansen, P.; Lechan, R.; Powers, J.; Tischler, A.; Grizzle, W.E.; Sexton, K.C.; Kastl, A.; Henderson, J.; Porten, S.; Waldmann, J.; Fassnacht, M.; Asa, S.L.; Schadendorf, D.; Couce, M.; Graefen, M.; Huland, H.; Sauter, G.; Schlomm, T.; Simon, R.; Tennstedt, P.; Olabode, O.; Nelson, M.; Bathe, O.; Carroll, P.R.; Chan, J.M.; Disaia, P.; Glenn, P.; Kelley, R.K.; Landen, C.N.; Phillips, J.; Prados, M.; Simko, J.; Smith-McCune, K.; VandenBerg, S.; Roggin, K.; Fehrenbach, A.; Kendler, A.; Sifri, S.; Steele, R.; Jimeno, A.; Carey, F.; Forgie, I.; Mannelli, M.; Carney, M.; Hernandez, B.; Campos, B.; Herold-Mende, C.; Jungk, C.; Unterberg, A.; von Deimling, A.; Bossler, A.; Galbraith, J.; Jacobus, L.; Knudson, M.; Knutson, T.; Ma, D.; Milhem, M.; Sigmund, R.; Godwin, A.K.; Madan, R.; Rosenthal, H.G.; Adebamowo, C.; Adebamowo, S.N.; Boussioutas, A.; Beer, D.; Giordano, T.; Mes-Masson, A-M.; Saad, F.; Bocklage, T.; Landrum, L.; Mannel, R.; Moore, K.; Moxley, K.; Postier, R.; Walker, J.; Zuna, R.; Feldman, M.; Valdivieso, F.; Dhir, R.; Luketich, J.; Pinero, E.M.M.; Quintero-Aguilo, M.; Carlotti, C.G., Jr; Dos Santos, J.S.; Kemp, R.; Sankarankuty, A.; Tirapelli, D.; Catto, J.; Agnew, K.; Swisher, E.; Creaney, J.; Robinson, B.; Shelley, C.S.; Godwin, E.M.; Kendall, S.; Shipman, C.; Bradford, C.; Carey, T.; Haddad, A.; Moyer, J.; Peterson, L.; Prince, M.; Rozek, L.; Wolf, G.; Bowman, R.; Fong, K.M.; Yang, I.; Korst, R.; Rathmell, W.K.; Fantacone-Campbell, J.L.; Hooke, J.A.; Kovatich, A.J.; Shriver, C.D.; DiPersio, J.; Drake, B.; Govindan, R.; Heath, S.; Ley, T.; Van Tine, B.; Westervelt, P.; Rubin, M.A.; Lee, J.I.; Aredes, N.D.; Mariamidze, A. The immune landscape of cancer. Immunity, 2019, 51(2), 411-412.
[http://dx.doi.org/10.1016/j.immuni.2019.08.004] [PMID: 31433971]
[22]
Kamarudin, A.N.; Cox, T. Kolamunnage-Dona, R. Time-dependent ROC curve analysis in medical research: Current methods and applications. BMC Med. Res. Methodol., 2017, 17(1), 53.
[http://dx.doi.org/10.1186/s12874-017-0332-6] [PMID: 28388943]
[23]
Yu, G.; Wang, L.G.; Han, Y.; He, Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS, 2012, 16(5), 284-287.
[http://dx.doi.org/10.1089/omi.2011.0118] [PMID: 22455463]
[24]
Mariathasan, S. Turley, S.J.; Nickles, D.; Castiglioni, A.; Yuen, K.; Wang, Y.; Kadel, E.E., III; Koeppen, H.; Astarita, J.L.; Cubas, R.; Jhunjhunwala, S.; Banchereau, R.; Yang, Y.; Guan, Y.; Chalouni, C.; Ziai, J.; Şenbabaoğlu, Y.; Santoro, S.; Sheinson, D.; Hung, J.; Giltnane, J.M.; Pierce, A.A.; Mesh, K.; Lianoglou, S.; Riegler, J.; Carano, R.A.D.; Eriksson, P.; Höglund, M.; Somarriba, L.; Halligan, D.L.; van der Heijden, M.S.; Loriot, Y.; Rosenberg, J.E.; Fong, L.; Mellman, I.; Chen, D.S.; Green, M.; Derleth, C.; Fine, G.D.; Hegde, P.S.; Bourgon, R.; Powles, T. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature, 2018, 554(7693), 544-548.
[http://dx.doi.org/10.1038/nature25501] [PMID: 29443960]
[25]
Balar, A.V.; Galsky, M.D.; Rosenberg, J.E.; Powles, T.; Petrylak, D.P.; Bellmunt, J.; Loriot, Y.; Necchi, A.; Hoffman-Censits, J.; Perez-Gracia, J.L.; Dawson, N.A.; van der Heijden, M.S.; Dreicer, R.; Srinivas, S.; Retz, M.M.; Joseph, R.W.; Drakaki, A.; Vaishampayan, U.N.; Sridhar, S.S.; Quinn, D.I.; Durán, I.; Shaffer, D.R.; Eigl, B.J.; Grivas, P.D.; Yu, E.Y.; Li, S.; Kadel, E.E., III; Boyd, Z.; Bourgon, R.; Hegde, P.S.; Mariathasan, S.; Thåström, A.; Abidoye, O.O.; Fine, G.D.; Bajorin, D.F. Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: A single-arm, multicentre, phase 2 trial. Lancet, 2017, 389(10064), 67-76.
[http://dx.doi.org/10.1016/S0140-6736(16)32455-2] [PMID: 27939400]
[26]
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(9), e107468.
[http://dx.doi.org/10.1371/journal.pone.0107468] [PMID: 25229481]
[27]
Kim, J.Y.; Choi, J.K.; Jung, H. Genome-wide methylation patterns predict clinical benefit of immunotherapy in lung cancer. Clin. Epigenetics, 2020, 12(1), 119.
[http://dx.doi.org/10.1186/s13148-020-00907-4] [PMID: 32762727]
[28]
Hugo, W.; Zaretsky, J.M.; Sun, L.; Song, C.; Moreno, B.H.; Hu-Lieskovan, S.; Berent-Maoz, B.; Pang, J.; Chmielowski, B.; Cherry, G.; Seja, E.; Lomeli, S.; Kong, X.; Kelley, M.C.; Sosman, J.A.; Johnson, D.B.; Ribas, A.; Lo, R.S. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell, 2016, 165(1), 35-44.
[http://dx.doi.org/10.1016/j.cell.2016.02.065] [PMID: 26997480]
[29]
Ostrand-Rosenberg, S. Cross-talk between myeloid-derived suppressor cells (MDSC), macrophages, and dendritic cells enhances tumor-induced immune suppression. In: Seminars in cancer biology; Elsevier, 2012.
[30]
Mullen, J.; Kato, S.; Sicklick, J.K.; Kurzrock, R. Targeting ARID1A mutations in cancer. Cancer Treat. Rev., 2021, 100, 102287.
[http://dx.doi.org/10.1016/j.ctrv.2021.102287] [PMID: 34619527]
[31]
Kim, Y.B.; Ahn, J.M.; Bae, W.J.; Sung, C.O.; Lee, D. Functional loss of ARID1A is tightly associated with high PD-L1 expression in gastric cancer. Int. J. Cancer, 2019, 145(4), 916-926.
[http://dx.doi.org/10.1002/ijc.32140] [PMID: 30664822]
[32]
Gu, Y. Somatic ARID1A mutation stratifies patients with gastric cancer to PD-1 blockade and adjuvant chemotherapy. Cancer Immunol. Immunother., 2022, 1-10.
[PMID: 36369379]
[33]
Kim, J.W.; Lee, H.S.; Nam, K.H.; Ahn, S.; Kim, J.W.; Ahn, S.H.; Park, D.J.; Kim, H.H.; Lee, K.W. PIK3CA mutations are associated with increased tumor aggressiveness and Akt activation in gastric cancer. Oncotarget, 2017, 8(53), 90948-90958.
[http://dx.doi.org/10.18632/oncotarget.18770] [PMID: 29207615]
[34]
Yao, J.; You, Q.; Zhang, X.; Zhang, Y.; Xu, J.; Zhao, X.; Li, J.; Wang, X.; Gong, Z.; Zhang, D.; Wang, W. PIK3CA somatic mutations as potential biomarker for immunotherapy in elder orTP53 mutated gastric cancer patients. Clin. Genet., 2023, 103(2), 200-208.
[http://dx.doi.org/10.1111/cge.14260] [PMID: 36346122]
[35]
Sobierajska, K. Endothelial cells in the tumor microenvironment. Tumor Microenvironment: Non-Hematopoietic Cells, , 2020, 71-86.
[http://dx.doi.org/10.1007/978-3-030-37184-5_6]
[36]
Nagl, L.; Horvath, L.; Pircher, A.; Wolf, D. Tumor endothelial cells (TECs) as potential immune directors of the tumor microenvironment–new findings and future perspectives. Front. Cell Dev. Biol., 2020, 8, 766.
[http://dx.doi.org/10.3389/fcell.2020.00766] [PMID: 32974337]
[37]
Xue, X.; Huang, J.; Yu, K.; Chen, X.; He, Y.; Qi, D.; Wu, Y. YB-1 transferred by gastric cancer exosomes promotes angiogenesis via enhancing the expression of angiogenic factors in vascular endothelial cells. BMC Cancer, 2020, 20(1), 996.
[http://dx.doi.org/10.1186/s12885-020-07509-6] [PMID: 33054752]
[38]
Sahai, E.; Astsaturov, I.; Cukierman, E.; DeNardo, D.G.; Egeblad, M.; Evans, R.M.; Fearon, D.; Greten, F.R.; Hingorani, S.R.; Hunter, T.; Hynes, R.O.; Jain, R.K.; Janowitz, T.; Jorgensen, C.; Kimmelman, A.C.; Kolonin, M.G.; Maki, R.G.; Powers, R.S.; Puré, E.; Ramirez, D.C.; Scherz-Shouval, R.; Sherman, M.H.; Stewart, S.; Tlsty, T.D.; Tuveson, D.A.; Watt, F.M.; Weaver, V.; Weeraratna, A.T.; Werb, Z. A framework for advancing our understanding of cancer-associated fibroblasts. Nat. Rev. Cancer, 2020, 20(3), 174-186.
[http://dx.doi.org/10.1038/s41568-019-0238-1] [PMID: 31980749]
[39]
Grunberg, N.; Pevsner-Fischer, M.; Goshen-Lago, T.; Diment, J.; Stein, Y.; Lavon, H.; Mayer, S.; Levi-Galibov, O.; Friedman, G.; Ofir-Birin, Y.; Syu, L.J.; Migliore, C.; Shimoni, E.; Stemmer, S.M.; Brenner, B.; Dlugosz, A.A.; Lyden, D.; Regev-Rudzki, N.; Ben-Aharon, I.; Scherz-Shouval, R. Cancer-associated fibroblasts promote aggressive gastric cancer phenotypes via heat shock factor 1–mediated secretion of extracellular vesicles. Cancer Res., 2021, 81(7), 1639-1653.
[http://dx.doi.org/10.1158/0008-5472.CAN-20-2756] [PMID: 33547159]
[40]
Tam, S.Y.; Wu, V.W.C.; Law, H.K.W. Hypoxia-induced epithelial-mesenchymal transition in cancers: HIF-1α and beyond. Front. Oncol., 2020, 10, 486.
[http://dx.doi.org/10.3389/fonc.2020.00486] [PMID: 32322559]
[41]
Tandon, V.; de la Vega, L.; Banerjee, S. Emerging roles of DYRK2 in cancer. J. Biol. Chem., 2021, 296, 100233.
[http://dx.doi.org/10.1074/jbc.REV120.015217] [PMID: 33376136]
[42]
Zhang, X.; Xiao, R.; Lu, B.; Wu, H.; Jiang, C.; Li, P.; Huang, J. Kinase DYRK2 acts as a regulator of autophagy and an indicator of favorable prognosis in gastric carcinoma. Colloids Surf. B Biointerfaces, 2022, 209(Pt 1), 112182.
[http://dx.doi.org/10.1016/j.colsurfb.2021.112182] [PMID: 34749023]
[43]
Evangelisti, C.; Rusciano, I.; Mongiorgi, S.; Ramazzotti, G.; Lattanzi, G.; Manzoli, L.; Cocco, L.; Ratti, S. The wide and growing range of lamin B-related diseases: From laminopathies to cancer. Cell. Mol. Life Sci., 2022, 79(2), 126.
[http://dx.doi.org/10.1007/s00018-021-04084-2] [PMID: 35132494]
[44]
Liu, M.; Li, H.; Zhang, H.; Zhou, H.; Jiao, T.; Feng, M.; Na, F.; Sun, M.; Zhao, M.; Xue, L.; Xu, L. RBMS1 promotes gastric cancer metastasis through autocrine IL-6/JAK2/STAT3 signaling. Cell Death Dis., 2022, 13(3), 287.
[http://dx.doi.org/10.1038/s41419-022-04747-3] [PMID: 35361764]
[45]
Yue, T.; Li, J.; Liang, M.; Yang, J.; Ou, Z.; Wang, S.; Ma, W.; Fan, D. Identification of the KCNQ1OT1/miR-378a-3p/RBMS1 axis as a novel prognostic biomarker associated with immune cell infiltration in gastric cancer. Front. Genet., 2022, 13, 928754.
[http://dx.doi.org/10.3389/fgene.2022.928754] [PMID: 35910231]
[46]
Zeng, X.; Wang, H.Y.; Wang, Y.P.; Bai, S.Y.; Pu, K.; Zheng, Y.; Guo, Q.H.; Guan, Q.L.; Ji, R.; Zhou, Y.N. COL4A family: Potential prognostic biomarkers and therapeutic targets for gastric cancer. Transl. Cancer Res., 2020, 9(9), 5218-5232.
[http://dx.doi.org/10.21037/tcr-20-517] [PMID: 35117889]
[47]
Si, W.; Shen, J.; Zheng, H.; Fan, W. The role and mechanisms of action of microRNAs in cancer drug resistance. Clin. Epigenetics, 2019, 11(1), 25.
[http://dx.doi.org/10.1186/s13148-018-0587-8] [PMID: 30744689]
[48]
Huang, R.; Gu, W.; Sun, B.; Gao, L. Identification of COL4A1 as a potential gene conferring trastuzumab resistance in gastric cancer based on bioinformatics analysis. Mol. Med. Rep., 2018, 17(5), 6387-6396.
[http://dx.doi.org/10.3892/mmr.2018.8664] [PMID: 29512712]
[49]
Ding, F.; Gao, F.; Zhang, S.; Lv, X.; Chen, Y.; Liu, Q. A review of the mechanism of DDIT4 serve as a mitochondrial related protein in tumor regulation. Sci. Prog., 2021, 104(1)
[http://dx.doi.org/10.1177/0036850421997273] [PMID: 33729069]
[50]
Li, N.; Ouyang, Y.; Chen, S.; Peng, C.; He, C.; Hong, J.; Yang, X.; Zhu, Y.; Lu, N.H. Integrative analysis of differential lncRNA/mRNA expression profiling in Helicobacter pylori infection-associated gastric carcinogenesis. Front. Microbiol., 2020, 11, 880.
[http://dx.doi.org/10.3389/fmicb.2020.00880] [PMID: 32457731]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy