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Occurrence of differing metabolic dysregulations, a glucose driven and another fatty acid centric in gastric cancer subtypes

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Abstract

Gastric cancer is one of the most common cancers and ranks third in cancer-related deaths across globe. Cancer cells are known to take advantage of the altered metabolic processes to sustain their survival, proliferation, and cancer progression. In this investigation, we explored the available genome-wide expression profiles of few hundreds of gastric tumors and non-cancerous gastric tissues and analyzed in the context of metabolic pathways. Gastric tumors were investigated for the metabolic processes related to glucose metabolism, glucose transport, glutamine metabolism, and fatty acid metabolism, by metabolic pathway-focused gene set enrichment analysis. Notably, all glucose metabolism and glutamine metabolism-related gene sets were found enriched in intestinal subtype gastric tumors. On the other hand, the gene sets related to glucose transport and glucan (glycan) metabolisms are enriched in diffuse subtype gastric tumors. Strikingly, fatty acid metabolisms, fatty acid transport, and fat differentiation-related signatures are also highly activated in diffuse subtype gastric tumors. Exploration of the recently established metabolome profile of the massive panel of cell lines also revealed the metabolites of glucose and fatty acid metabolic pathways to show the differing abundance across gastric cancer subtypes. The subtype-specific metabolic rewiring and the existence of two distinct metabolic dysregulations involving glucose and fatty acid metabolism in gastric cancer subtypes have been identified. The identified differing metabolic dysregulations would pave way for the development of targeted therapeutic strategies for the gastric cancer subtypes.

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References

  • Alò PL, Visca P, Botti C, Galati GM, Sebastiani V, Andreano T, di Tondo U, Pizer ES (2001) Immunohistochemical expression of human erythrocyte glucose transporter and fatty acid synthase in infiltrating breast carcinomas and adjacent typical/atypical hyperplastic or normal breast tissue. Am J Clin Pathol 116:129–134

    PubMed  Google Scholar 

  • Anderson NM, Mucka P, Kern JG, Feng H (2018) The emerging role and targetability of the TCA cycle in cancer metabolism. Protein Cell 9:216–237

    PubMed  CAS  Google Scholar 

  • Baenke F, Peck B, Miess H, Schulze A (2013) Hooked on fat: the role of lipid synthesis in cancer metabolism and tumour development. Dis Model Mech 6:1353–1363

    PubMed  PubMed Central  CAS  Google Scholar 

  • Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M, Yefanov A, Lee H, Zhang N, Robertson CL, Serova N, Davis S, Soboleva A (2013) NCBI GEO: archive for functional genomics data sets - update. Nucleic Acids Res 41:D991–D995

    PubMed  CAS  Google Scholar 

  • Biswas S, Lunec J, Bartlett K (2012) Non-glucose metabolism in cancer cells-is it all in the fat? Cancer Metastasis Rev 31:689–698

    PubMed  CAS  Google Scholar 

  • Cheadle C, Vawter MP, Freed WJ, Becker KG (2003) Analysis of microarray data using Z score transformation. J Mol Diagn 5:73–81

    PubMed  PubMed Central  CAS  Google Scholar 

  • Choi YK, Park KG (2018) Targeting glutamine metabolism for cancer treatment. Biomol Ther 26:19–28

    CAS  Google Scholar 

  • Currie E, Schulze A, Zechner R, Walther TC, Farese RV (2013) Cellular fatty acid metabolism and cancer. Cell Metab 18:153–161

    PubMed  PubMed Central  CAS  Google Scholar 

  • Daniëls VW, Smans K, Royaux I, Chypre M, Swinnen JV, Zaidi N (2014) Cancer cells differentially activate and thrive on de novo lipid synthesis pathways in a low-lipid environment. PLoS One 9:e106913

    PubMed  PubMed Central  Google Scholar 

  • Epstein T, Gatenby RA, Brown JS (2017) The Warburg effect as an adaptation of cancer cells to rapid fluctuations in energy demand. PLoS One 12:e0185085

    PubMed  PubMed Central  Google Scholar 

  • Favaro E, Bensaad K, Chong MG, Tennant DA, Ferguson DJP, Snell C, Steers G, Turley H, Li JL, Günther UL, Buffa FM, McIntyre A, Harris AL (2012) Glucose utilization via glycogen phosphorylase sustains proliferation and prevents premature senescence in cancer cells. Cell Metab 16:751–764

    PubMed  CAS  Google Scholar 

  • Fischer GM, Vashisht Gopal YN, McQuade JL, Peng W, DeBerardinis RJ, Davies MA (2018) Metabolic strategies of melanoma cells: mechanisms, interactions with the tumor microenvironment, and therapeutic implications. Pigment Cell Melanoma Res 31:11–30

    PubMed  Google Scholar 

  • Fouad YA, Aanei C (2017) Revisiting the hallmarks of cancer. Am J Cancer Res 7:1016–1036

    PubMed  PubMed Central  CAS  Google Scholar 

  • Freedman JA, Tyler DS, Nevins JR, Augustine CK (2011) Use of gene expression and pathway signatures to characterize the complexity of human melanoma. Am J Pathol 178:2513–2522

    PubMed  PubMed Central  CAS  Google Scholar 

  • Furuta E, Pai SK, Zhan R, Bandyopadhyay S, Watabe M, Mo YY, Hirota S, Hosobe S, Tsukada T, Miura K, Kamada S, Saito K, Iiizumi M, Liu W, Ericsson J, Watabe K (2008) Fatty acid synthase gene is up-regulated by hypoxia via activation of Akt and sterol regulatory element binding protein-1. Cancer Res 68:1003–1011

    PubMed  CAS  Google Scholar 

  • Hochachka PW, Rupert JL, Goldenberg L, Gleave M, Kozlowski P (2002) Going malignant: the hypoxia-cancer connection in the prostate. BioEssays. 24:749–757

    PubMed  CAS  Google Scholar 

  • Hur H, Paik MJ, Xuan Y, Nguyen D-T, Ham I-H, Yun J, Cho YK, Lee G, Han SU (2014) Quantitative measurement of organic acids in tissues from gastric cancer patients indicates increased glucose metabolism in gastric cancer. PLoS One 9:e98581

    PubMed  PubMed Central  Google Scholar 

  • Lauren P (1965) The two histological main types of gastric carcinoma: diffuse and so-called intestinal-type carcinoma. An attempt at a histo-clinical classification. Acta Pathol Microbiol Scand 64:31–49

    PubMed  CAS  Google Scholar 

  • Lee WNP, Guo P, Lim S, Bassilian S, Lee ST, Boren J, Cascante M, Go VLW, Boros LG (2004) Metabolic sensitivity of pancreatic tumour cell apoptosis to glycogen phosphorylase inhibitor treatment. Br J Cancer 91:2094–2100

    PubMed  PubMed Central  CAS  Google Scholar 

  • Lee SS, Bae SK, Park YS, Park JS, Kim TH, Yoon HK, Ahn HJ, Lee SM (2017) Correlation of molecular subtypes of invasive ductal carcinoma of breast with glucose metabolism in FDG PET/CT: based on the recommendations of the St. Gallen consensus meeting 2013. Nucl Med Mol Imaging 51:79–85

    PubMed  CAS  Google Scholar 

  • Levine AJ, Puzio-Kuter AM (2010) The control of the metabolic switch in cancers by oncogenes and tumor suppressor genes. Science 330(6009):1340–1344

    PubMed  CAS  Google Scholar 

  • Li C, Wong WH (2003) In: Parmigiani G, Garrett ES, Irizarry R, Zeger SL (eds) DNA-Chip analyzer (dChip). In the analysis of gene expression data: methods and software. Springer, New York, pp 120–141

    Google Scholar 

  • Li H, Ning S, Ghandi M, Kryukov GV, Gopal S, Deik A, Souza A, Pierce K, Keskula P, Hernandez D, Ann J, Shkoza D, Apfel V, Zou Y, Vazquez F, Barretina J, Pagliarini RA, Galli GG, Root DE, Hahn WC, Tsherniak A, Giannakis M, Schreiber SL, Clish CB, Garraway LA, Sellers WR (2019) The landscape of cancer cell line metabolism. Nat Med 25:850–860

    PubMed  PubMed Central  CAS  Google Scholar 

  • Martin JD, Fukumura D, Duda DG, Boucher Y, Jain RK (2016) Reengineering the tumor microenvironment to alleviate hypoxia and overcome cancer heterogeneity. Cold Spring Harb Perspect Med 6(12):a031195

    PubMed  PubMed Central  Google Scholar 

  • Mashima T, Seimiya H, Tsuruo T (2009) De novo fatty-acid synthesis and related pathways as molecular targets for cancer therapy. Br J Cancer 100:1369–1372

    PubMed  PubMed Central  CAS  Google Scholar 

  • Menendez JA, Lupu R (2007) Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis. Nat Rev Cancer 7:763–777

    PubMed  CAS  Google Scholar 

  • Migita T, Narita T, Nomura K, Miyagi E, Inazuka F, Matsuura M, Ushijima M, Mashima T, Seimiya H, Satoh Y, Okumura S, Nakagawa K, Ishikawa Y (2008) ATP citrate lyase: activation and therapeutic implications in non-small cell lung cancer. Cancer Res 68:8547–8554

    PubMed  CAS  Google Scholar 

  • Nayak AP, Kapur A, Barroilhet L, Patankar MS (2018) Oxidative phosphorylation: a target for novel therapeutic strategies against ovarian cancer. Cancers 10(9):1–15

    CAS  Google Scholar 

  • Nelson DL, Cox MM (2017) Lehninger principles of biochemistry book, Seventh edn. WH Freeman, New York

    Google Scholar 

  • Ngo DC, Ververis K, Tortorella SM, Karagiannis TC (2015) Introduction to the molecular basis of cancer metabolism and the Warburg effect. Mol Biol Rep 42:819–823

    PubMed  CAS  Google Scholar 

  • Nomura DK, Long JZ, Niessen S, Hoover HS, Ng SW, Cravatt BF (2010) Monoacylglycerol lipase regulates a fatty acid network that promotes Cancer pathogenesis. Cell. 140:49–61

    PubMed  PubMed Central  CAS  Google Scholar 

  • Ooi CH, Ivanova T, Wu J, Lee M, Tan IB, Tao J, Ward L, Koo JH, Gopalakrishnan V, Zhu Y, Cheng LL, Lee J, Rha SY, Chung HC, Ganesan K, So J, Soo KC, Lim D, Chan WH, Wong WK, Bowtell D, Yeoh KG, Grabsch H, Boussioutas A, Tan P (2009) Oncogenic pathway combinations predict clinical prognosis in gastric cancer. PLoS Genet 5:e1000676

    PubMed  PubMed Central  Google Scholar 

  • Pike LS, Smift AL, Croteau NJ, Ferrick DA, Wu M (2011) Inhibition of fatty acid oxidation by etomoxir impairs NADPH production and increases reactive oxygen species resulting in ATP depletion and cell death in human glioblastoma cells. Biochim Biophys Acta Bioenerg 1807:726–734

    CAS  Google Scholar 

  • Rawla P, Barsouk A (2019) Epidemiology of gastric cancer: global trends, risk factors and prevention. Prz Gastroenterol 14:26–38

    PubMed  CAS  Google Scholar 

  • Romero-Garcia S, Lopez-Gonzalez JS, Báez-Viveros JL, Aguilar-Cazares D, Prado-Garcia H (2011) Tumor cell metabolism: an integral view. Cancer Biol Ther 12:939–948

    PubMed  PubMed Central  CAS  Google Scholar 

  • Rousset M, Fogh J, Zweibaum A (1981) Presence of glycogen and growth–related variations in 58 cultured human tumor cell lines of various tissue origins. Cancer Res 41:1165–1170

    PubMed  CAS  Google Scholar 

  • Santos CR, Schulze A (2012) Lipid metabolism in cancer. FEBS J 279:2610–2623

    PubMed  CAS  Google Scholar 

  • Schneider G, Schmidt-Supprian M, Rad R, Saur D (2017) Tissue-specific tumorigenesis – context matters. Nat Rev Cancer 17:239–253

    PubMed  PubMed Central  CAS  Google Scholar 

  • Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102:15545–15550

    PubMed  PubMed Central  CAS  Google Scholar 

  • Tarca AL, Romero R, Draghici S (2006) Analysis of microarray experiments of gene expression profiling. Am J Obstet Gynecol 195:373–388

    PubMed  PubMed Central  CAS  Google Scholar 

  • Tsuji T, Yoshinaga M, Togami S, Douchi T, Nagata Y (2004) Fatty acid synthase expression and clinicopathological findings in endometrial cancer. Acta Obstet Gynecol Scand. Wiley Online Library 83:586–590

    PubMed  Google Scholar 

  • Visca P, Sebastiani V, Pizer ES, Botti C, De Carli P, Filippi S et al (2003) Immunohistochemical expression and prognostic significance of FAS and GLUT1 in bladder carcinoma. Anticancer Res 23:335–339

    PubMed  CAS  Google Scholar 

  • Wang J, Ye C, Chen C, Xiong H, Xie B, Zhou J, Chen Y, Zheng S, Wang L (2017) Glucose transporter GLUT1 expression and clinical outcome in solid tumors: a systematic review and meta-analysis. Oncotarget. 8:16875–16886

    PubMed  PubMed Central  Google Scholar 

  • Warburg O (1956) On the origin of cancer cells. Science 123:309–314

    PubMed  CAS  Google Scholar 

  • Warburg O, Wind F, Negelein E (1927) The metabolism of tumors in the body. J Gen Physiol 8:519–530

    PubMed  PubMed Central  CAS  Google Scholar 

  • Wilson CL, Miller CJ (2005) Simpleaffy: a BioConductor package for Affymetrix quality control and data analysis. Bioinformatics. 21:3683–3685

    PubMed  CAS  Google Scholar 

  • Yang CS, Matsuura K, Huang NJ, Robeson AC, Huang B, Zhang L, Kornbluth S (2015) Fatty acid synthase inhibition engages a novel caspase-2 regulatory mechanism to induce ovarian cancer cell death. Oncogene 34:3264–3272

    PubMed  CAS  Google Scholar 

  • Zheng J (2012) Energy metabolism of cancer: glycolysis versus oxidative phosphorylation (review). Oncol Lett 4:1151–1157

    PubMed  PubMed Central  CAS  Google Scholar 

  • Zois CE, Harris AL (2016) Glycogen metabolism has a key role in the cancer microenvironment and provides new targets for cancer therapy. J Mol Med 94:137–154

    PubMed  CAS  Google Scholar 

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Acknowledgments

We thank Council of Scientific and Industrial Research (CSIR), Govt. of India for NET-SRF fellowship support to Karthik Balakrishnan. UGC-CEGS, UGC-NRCBS, UGC-CAS, DBT-IPLS, DST-FIST, and DST-PURSE program supported central facilities of School of Biological Sciences, Madurai Kamaraj University are acknowledged.

Funding

This work was supported by the Department of Biotechnology (DBT), Government of India, with the Unit of Excellence (UOE) in Cancer Genetics grant, BT/MED/30/SP11290/2015 to Dr. Kumaresan Ganesan, Madurai Kamaraj University.

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KB and KG conceived and designed the experiments and wrote the paper. KB performed the experiments and KB and KG analyzed the data. KG also contributed the materials.

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Correspondence to Kumaresan Ganesan.

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Balakrishnan, K., Ganesan, K. Occurrence of differing metabolic dysregulations, a glucose driven and another fatty acid centric in gastric cancer subtypes. Funct Integr Genomics 20, 813–824 (2020). https://doi.org/10.1007/s10142-020-00753-w

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