A novel fatty acid metabolism-related signature identifies MUC4 as a novel therapy target for esophageal squamous cell carcinoma.
Humans
Esophageal Squamous Cell Carcinoma
/ genetics
Esophageal Neoplasms
/ genetics
Fatty Acids
/ metabolism
Mucin-4
/ genetics
Prognosis
Gene Expression Regulation, Neoplastic
Cell Line, Tumor
Female
Male
Biomarkers, Tumor
/ genetics
Cell Proliferation
Middle Aged
Gene Expression Profiling
Nomograms
Kaplan-Meier Estimate
Esophageal squamous cell carcinoma
Fatty acid metabolism
Immune microenvironment
Prognosis
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
30 05 2024
30 05 2024
Historique:
received:
04
03
2024
accepted:
22
05
2024
medline:
31
5
2024
pubmed:
31
5
2024
entrez:
30
5
2024
Statut:
epublish
Résumé
Fatty acid metabolism has been identified as an emerging hallmark of cancer, which was closely associated with cancer prognosis. Whether fatty acid metabolism-related genes (FMGs) signature play a more crucial role in biological behavior of esophageal squamous cell carcinoma (ESCC) prognosis remains unknown. Thus, we aimed to identify a reliable FMGs signature for assisting treatment decisions and prognosis evaluation of ESCC. In the present study, we conducted consensus clustering analysis on 259 publicly available ESCC samples. The clinical information was downloaded from The Cancer Genome Atlas (TCGA, 80 ESCC samples) and Gene Expression Omnibus (GEO) database (GSE53625, 179 ESCC samples). A consensus clustering arithmetic was used to determine the FMGs molecular subtypes, and survival outcomes and immune features were evaluated among the different subtypes. Kaplan-Meier analysis and the receiver operating characteristic (ROC) was applied to evaluate the reliability of the risk model in training cohort, validation cohort and all cohorts. A nomogram to predict patients' 1-year, 3-year and 5-year survival rate was also studied. Finally, CCK-8 assay, wound healing assay, and transwell assay were implemented to evaluate the inherent mechanisms of FMGs for tumorigenesis in ESCC. Two subtypes were identified by consensus clustering, of which cluster 2 is preferentially associated with poor prognosis, lower immune cell infiltration. A fatty acid (FA) metabolism-related risk model containing eight genes (FZD10, TACSTD2, MUC4, PDLIM1, PRSS12, BAALC, DNAJA2 and ALOX12B) was established. High-risk group patients displayed worse survival, higher stromal, immune and ESTIMATE scores than in the low-risk group. Moreover, a nomogram revealed good predictive ability of clinical outcomes in ESCC patients. The results of qRT-PCR analysis revealed that the MUC4 and BAALC had high expression level, and FZD10, PDLIM1, TACSTD2, ALOX12B had low expression level in ESCC cells. In vitro, silencing MUC4 remarkably inhibited ESCC cell proliferation, invasion and migration. Our study fills the gap of FMGs signature in predicting the prognosis of ESCC patients. These findings revealed that cluster subtypes and risk model of FMGs had effects on survival prediction, and were expected to be the potential promising targets for ESCC.
Identifiants
pubmed: 38816411
doi: 10.1038/s41598-024-62917-z
pii: 10.1038/s41598-024-62917-z
doi:
Substances chimiques
Fatty Acids
0
Mucin-4
0
MUC4 protein, human
0
Biomarkers, Tumor
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
12476Informations de copyright
© 2024. The Author(s).
Références
Sung, H. et al. 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 (2021).
pubmed: 33538338
doi: 10.3322/caac.21660
He, Z. & Ke, Y. Precision screening for esophageal squamous cell carcinoma in China. Chin. J. Cancer Res. 32(6), 673–682 (2020).
pubmed: 33446991
pmcid: 7797228
doi: 10.21147/j.issn.1000-9604.2020.06.01
Ogawa, R. et al. Expression profiling of micro-RNAs in human esophageal squamous cell carcinoma using RT-PCR. Med. Mol. Morphol. 42(2), 102–109 (2009).
pubmed: 19536617
doi: 10.1007/s00795-009-0443-1
Yang, J. et al. Understanding esophageal cancer: The challenges and opportunities for the next decade. Front. Oncol. 10, 1727 (2020).
pubmed: 33014854
pmcid: 7511760
doi: 10.3389/fonc.2020.01727
Song, J. et al. A novel ferroptosis-related biomarker signature to predict overall survival of esophageal squamous cell carcinoma. Front. Mol. Biosci. 8, 675193 (2021).
pubmed: 34291083
pmcid: 8287967
doi: 10.3389/fmolb.2021.675193
Lian, L. et al. Development and verification of a hypoxia- and immune-associated prognosis signature for esophageal squamous cell carcinoma. J. Gastrointest. Oncol. 13(2), 462–477 (2022).
pubmed: 35557566
pmcid: 9086047
doi: 10.21037/jgo-22-69
Cui, H. et al. Autophagy-related three-gene prognostic signature for predicting survival in esophageal squamous cell carcinoma. Front. Oncol. 11, 650891 (2021).
pubmed: 34336650
pmcid: 8321089
doi: 10.3389/fonc.2021.650891
Schiliro, C. & Firestein, B. L. Mechanisms of metabolic reprogramming in cancer cells supporting enhanced growth and proliferation. Cells. 10(5), 1056 (2021).
pubmed: 33946927
pmcid: 8146072
doi: 10.3390/cells10051056
Li, X. et al. Navigating metabolic pathways to enhance antitumour immunity and immunotherapy. Nat. Rev. Clin. Oncol. 16(7), 425–441 (2019).
pubmed: 30914826
doi: 10.1038/s41571-019-0203-7
Martinez-Reyes, I. & Chandel, N. S. Cancer metabolism: looking forward. Nat. Rev. Cancer. 21(10), 669–680 (2021).
pubmed: 34272515
doi: 10.1038/s41568-021-00378-6
Grande, S. et al. Metabolic heterogeneity evidenced by MRS among patient-derived glioblastoma multiforme stem-like cells accounts for cell clustering and different responses to drugs. Stem Cells Int. 2018, 3292704 (2018).
pubmed: 29531533
pmcid: 5835274
doi: 10.1155/2018/3292704
Tasdogan, A. et al. Metabolic heterogeneity confers differences in melanoma metastatic potential. Nature. 577(7788), 115–120 (2020).
pubmed: 31853067
doi: 10.1038/s41586-019-1847-2
Fhu, C. W. & Ali, A. Fatty acid synthase: An emerging target in cancer. Molecules. 25(17), 3935 (2020).
pubmed: 32872164
pmcid: 7504791
doi: 10.3390/molecules25173935
Pakiet, A., Kobiela, J., Stepnowski, P., Sledzinski, T. & Mika, A. Changes in lipids composition and metabolism in colorectal cancer: A review. Lipids Health Dis. 18(1), 29 (2019).
pubmed: 30684960
pmcid: 6347819
doi: 10.1186/s12944-019-0977-8
Cheng, S. C. et al. mTOR- and HIF-1alpha-mediated aerobic glycolysis as metabolic basis for trained immunity. Science. 345(6204), 1250684 (2014).
pubmed: 25258083
pmcid: 4226238
doi: 10.1126/science.1250684
Hopkins, B. D., Goncalves, M. D. & Cantley, L. C. Insulin-PI3K signalling: An evolutionarily insulated metabolic driver of cancer. Nat. Rev. Endocrinol. 16(5), 276–283 (2020).
pubmed: 32127696
pmcid: 7286536
doi: 10.1038/s41574-020-0329-9
Orita, H., Coulter, J., Tully, E., Kuhajda, F. P. & Gabrielson, E. Inhibiting fatty acid synthase for chemoprevention of chemically induced lung tumors. Clin. Cancer Res. 14(8), 2458–2464 (2008).
pubmed: 18413838
doi: 10.1158/1078-0432.CCR-07-4177
Costabile, M. et al. A novel long chain polyunsaturated fatty acid, beta-Oxa 21:3n–3, inhibits T lymphocyte proliferation, cytokine production, delayed-type hypersensitivity, and carrageenan-induced paw reaction and selectively targets intracellular signals. J. Immunol. 167(7), 3980–3987 (2001).
pubmed: 11564817
doi: 10.4049/jimmunol.167.7.3980
Zhang, Y. et al. Enhancing CD8(+) T cell fatty acid catabolism within a metabolically challenging tumor microenvironment increases the efficacy of melanoma immunotherapy. Cancer Cell. 32(3), 377–391 (2017).
pubmed: 28898698
pmcid: 5751418
doi: 10.1016/j.ccell.2017.08.004
Rohrig, F. & Schulze, A. The multifaceted roles of fatty acid synthesis in cancer. Nat. Rev. Cancer. 16(11), 732–749 (2016).
pubmed: 27658529
doi: 10.1038/nrc.2016.89
Kanehisa, M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 28(11), 1947–1951 (2019).
pubmed: 31441146
pmcid: 6798127
doi: 10.1002/pro.3715
Kanehisa, M., Furumichi, M., Sato, Y., Kawashima, M. & Ishiguro-Watanabe, M. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res. 51(D1), D587–D592 (2023).
pubmed: 36300620
doi: 10.1093/nar/gkac963
Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28(1), 27–30 (2000).
pubmed: 10592173
pmcid: 102409
doi: 10.1093/nar/28.1.27
Li, J., Xie, L., Xie, Y. & Wang, F. Bregmannian consensus clustering for cancer subtypes analysis. Comput. Methods Programs Biomed. 189, 105337 (2020).
pubmed: 31962279
doi: 10.1016/j.cmpb.2020.105337
Shi, Y. et al. A novel epithelial-mesenchymal transition gene signature for the immune status and prognosis of hepatocellular carcinoma. Hepatol. Int. 16(4), 906–917 (2022).
pubmed: 35699863
doi: 10.1007/s12072-022-10354-3
Dai, J. J. et al. Identification of senescence-related subtypes, the development of a prognosis model, and characterization of immune infiltration and gut microbiota in colorectal cancer. Front. Med. 9, 916565 (2022).
doi: 10.3389/fmed.2022.916565
Li, Q. et al. The DDR-related gene signature with cell cycle checkpoint function predicts prognosis, immune activity, and chemoradiotherapy response in lung adenocarcinoma. Respir. Res. 23(1), 190 (2022).
pubmed: 35840978
pmcid: 9288070
doi: 10.1186/s12931-022-02110-w
Moretton, A. & Loizou, J. I. Interplay between cellular metabolism and the DNA damage response in cancer. Cancers 12(8), 2051 (2020).
pubmed: 32722390
pmcid: 7463900
doi: 10.3390/cancers12082051
Zhao, Y., Butler, E. B. & Tan, M. Targeting cellular metabolism to improve cancer therapeutics. Cell Death Dis. 4, e532 (2013).
pubmed: 23470539
pmcid: 3613838
doi: 10.1038/cddis.2013.60
Zhou, L. et al. Alterations in cellular iron metabolism provide more therapeutic opportunities for cancer. Int. J. Mol. Sci. 19(5), 1545 (2018).
pubmed: 29789480
pmcid: 5983609
doi: 10.3390/ijms19051545
Kery, M. & Papandreou, I. Emerging strategies to target cancer metabolism and improve radiation therapy outcomes. Br. J. Radiol. 93(1115), 20200067 (2020).
pubmed: 32462882
pmcid: 8519637
doi: 10.1259/bjr.20200067
Luby, A. & Alves-Guerra, M. C. Targeting metabolism to control immune responses in cancer and improve checkpoint blockade immunotherapy. Cancers 13(23), 5912 (2021).
pubmed: 34885023
pmcid: 8656934
doi: 10.3390/cancers13235912
Pavlova, N. N. & Thompson, C. B. the emerging hallmarks of cancer metabolism. Cell Metab. 23(1), 27–47 (2016).
pubmed: 26771115
pmcid: 4715268
doi: 10.1016/j.cmet.2015.12.006
An, Q., Lin, R., Wang, D. & Wang, C. Emerging roles of fatty acid metabolism in cancer and their targeted drug development. Eur. J. Med. Chem. 240, 114613 (2022).
pubmed: 35853429
doi: 10.1016/j.ejmech.2022.114613
Koundouros, N. & Poulogiannis, G. Reprogramming of fatty acid metabolism in cancer. Br. J. Cancer. 122(1), 4–22 (2020).
pubmed: 31819192
doi: 10.1038/s41416-019-0650-z
Huang, D., Tang, E., Zhang, T. & Xu, G. Characteristics of fatty acid metabolism in lung adenocarcinoma to guide clinical treatment. Front. Immunol. 13, 916284 (2022).
pubmed: 35860256
pmcid: 9289740
doi: 10.3389/fimmu.2022.916284
Jiang, F. et al. Characterization of fatty acid metabolism-related genes landscape for predicting prognosis and aiding immunotherapy in glioma patients. Front. Immunol. 13, 902143 (2022).
pubmed: 35903107
pmcid: 9315048
doi: 10.3389/fimmu.2022.902143
Ding, C. et al. Characterization of the fatty acid metabolism in colorectal cancer to guide clinical therapy. Mol. Ther. Oncolytics. 20, 532–544 (2021).
pubmed: 33738339
pmcid: 7941088
doi: 10.1016/j.omto.2021.02.010
Tang, Y. et al. Prognosis and dissection of immunosuppressive microenvironment in breast cancer based on fatty acid metabolism-related signature. Front. Immunol. 13, 843515 (2022).
pubmed: 35432381
pmcid: 9009264
doi: 10.3389/fimmu.2022.843515
Nagayama, S. et al. Inverse correlation of the up-regulation of FZD10 expression and the activation of beta-catenin in synchronous colorectal tumors. Cancer Sci. 100(3), 405–412 (2009).
pubmed: 19134005
doi: 10.1111/j.1349-7006.2008.01052.x
Kirikoshi, H., Sekihara, H. & Katoh, M. Expression profiles of 10 members of Frizzled gene family in human gastric cancer. Int. J. Oncol. 19(4), 767–771 (2001).
pubmed: 11562753
Gong, C. et al. BRMS1L suppresses breast cancer metastasis by inducing epigenetic silence of FZD10. Nat. Commun.. 5, 5406 (2014).
pubmed: 25406648
doi: 10.1038/ncomms6406
Shvartsur, A. & Bonavida, B. Trop2 and its overexpression in cancers: Regulation and clinical/therapeutic implications. Genes Cancer. 6(3–4), 84–105 (2015).
pubmed: 26000093
pmcid: 4426947
Ambrogi, F. et al. Trop-2 is a determinant of breast cancer survival. PLoS ONE. 9(5), e96993 (2014).
pubmed: 24824621
pmcid: 4019539
doi: 10.1371/journal.pone.0096993
Urey, C. et al. Low MUC4 expression is associated with survival benefit in patients with resectable pancreatic cancer receiving adjuvant gemcitabine. Scand. J. Gastroenterol. 52(5), 595–600 (2017).
pubmed: 28270046
doi: 10.1080/00365521.2017.1290134
Bafna, S., Kaur, S., Momi, N. & Batra, S. K. Pancreatic cancer cells resistance to gemcitabine: The role of MUC4 mucin. Br. J. Cancer. 101(7), 1155–1161 (2009).
pubmed: 19738614
pmcid: 2768097
doi: 10.1038/sj.bjc.6605285
Chen, H. N. et al. PDLIM1 stabilizes the E-cadherin/beta-catenin complex to prevent epithelial-mesenchymal transition and metastatic potential of colorectal cancer cells. Cancer Res. 76(5), 1122–1134 (2016).
pubmed: 26701804
doi: 10.1158/0008-5472.CAN-15-1962
Birgersson, M. et al. A novel role for brain and acute leukemia cytoplasmic (BAALC) in human breast cancer metastasis. Front. Oncol. 11, 656120 (2021).
pubmed: 33968759
pmcid: 8101327
doi: 10.3389/fonc.2021.656120
Jiang, T. et al. ALOX12B promotes carcinogenesis in cervical cancer by regulating the PI3K/ERK1 signaling pathway. Oncol. Lett. 20(2), 1360–1368 (2020).
pubmed: 32724378
pmcid: 7377187
doi: 10.3892/ol.2020.11641
Shen, M. et al. Polymorphisms in innate immunity genes and lung cancer risk in Xuanwei, China. Environ. Mol. Mutagen. 50(4), 285–290 (2009).
pubmed: 19170196
pmcid: 2666781
doi: 10.1002/em.20452
Siddiqui, S. & Glauben, R. Fatty acid metabolism in myeloid-derived suppressor cells and tumor-associated macrophages: Key factor in cancer immune evasion. Cancers 14(1), 250 (2022).
pubmed: 35008414
pmcid: 8750448
doi: 10.3390/cancers14010250
Endo, Y., Kanno, T. & Nakajima, T. Fatty acid metabolism in T-cell function and differentiation. Int. Immunol. 34, 579 (2022).
pubmed: 35700102
doi: 10.1093/intimm/dxac025
Zhou, X., Zhu, X. & Zeng, H. Fatty acid metabolism in adaptive immunity. FEBS J. 290, 584–599 (2021).
pubmed: 34822226
pmcid: 9130345
doi: 10.1111/febs.16296