Analyze Diet
Veterinary sciences2022; 9(2); 94; doi: 10.3390/vetsci9020094

Faecal Proteomics and Functional Analysis of Equine Melanocytic Neoplasm in Grey Horses.

Abstract: Equine melanocytic neoplasm (EMN) is a common disease in older grey horses. The purpose of this study was to examine the potential proteins throughout EMN stages from faecal proteomic outlining using functional analysis. Faecal samples were collected from the rectum of 25 grey horses divided into three groups; normal group without EMN ( = 10), mild EMN ( = 6) and severe EMN ( = 9). Based on the results, 5910 annotated proteins out of 8509 total proteins were assessed from proteomic profiling. We observed differentially expressed proteins (DEPs) between the normal group and the EMN group, and 109 significant proteins were obtained, of which 28 and 81 were involved in metabolic and non-metabolic functions, respectively. We found 10 proteins that play a key role in lipid metabolism, affecting the tumour microenvironment and, consequently, melanoma progression. Interestingly, FOSL1 (FOS like 1, AP-1 transcription factor subunit) was considered as a potential highly expressed protein in a mild EMN group involved in melanocytes cell and related melanoma. Diacylglycerol kinase (DGKB), TGc domain-containing protein (Tgm2), structural maintenance of chromosomes 4 (SMC4) and mastermind-like transcriptional coactivator 2 (MAML2) were related to lipid metabolism, facilitating melanoma development in the severe-EMN group. In conclusion, these potential proteins can be used as candidate biomarkers for the monitoring of early EMN, the development of EMN, further prevention and treatment.
Publication Date: 2022-02-21 PubMed ID: 35202347PubMed Central: PMC8875177DOI: 10.3390/vetsci9020094Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This study examined proteins related to equine melanocytic neoplasm (EMN), a common disease in grey horses, by analyzing faecal samples. Researchers found differentially expressed proteins between the healthy horses and those with EMN, some of which could serve as potential early indicators or treatment targets for the disease.

Methodology

  • The researchers gathered faecal samples from the rectum of 25 grey horses that were divided into three groups: horses without EMN, horses with mild EMN, and horses with severe EMN.
  • They analyzed these samples using proteomic profiling to identify and assess proteins.

Findings

  • The scientists were able to identify and assess 5910 annotated proteins out of a total of 8509.
  • They found that there were differentially expressed proteins (DEPs) between the normal group and the EMN group, with 109 significant proteins identified.
  • It was observed that, of these proteins, 28 were involved in metabolic functions and 81 in non-metabolic functions.
  • The study also revealed that 10 of these proteins play a crucial role in lipid metabolism, which impacts the tumor environment and hence, the progression of melanoma.

Significant Proteins

  • A protein called FOSL1, which is involved in cells that produce melanin and related melanoma, was found to be highly expressed in the group with mild EMN.
  • Few other proteins identified like Diacylglycerol kinase (DGKB), TGc domain-containing protein (Tgm2), structural maintenance of chromosomes 4 (SMC4), and mastermind-like transcriptional coactivator 2 (MAML2) were found to be related to lipid metabolism. They were seen to facilitate the development of melanoma in the group with severe EMN.

Conclusion

  • According to the researchers, these proteins can potentially serve as candidate biomarkers for early detection and monitoring of EMN, as well as for the development of prevention and treatment strategies.

Cite This Article

APA
Tesena P, Kingkaw A, Phaonakrop N, Roytrakul S, Limudomporn P, Vongsangnak W, Kovitvadhi A. (2022). Faecal Proteomics and Functional Analysis of Equine Melanocytic Neoplasm in Grey Horses. Vet Sci, 9(2), 94. https://doi.org/10.3390/vetsci9020094

Publication

ISSN: 2306-7381
NlmUniqueID: 101680127
Country: Switzerland
Language: English
Volume: 9
Issue: 2
PII: 94

Researcher Affiliations

Tesena, Parichart
  • Graduate Student in Animal Health and Biomedical Science Program, Faculty of Veterinary Medicine, Kasetsart University, Bangkok 10900, Thailand.
  • Department of Clinical Science and Public Health, Faculty of Veterinary Science, Mahidol University, Salaya, Puttamonthon, Nakhon Pathom 73170, Thailand.
Kingkaw, Amornthep
  • Interdisciplinary Graduate Program in Bioscience, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.
Phaonakrop, Narumon
  • Functional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand.
Roytrakul, Sittiruk
  • Functional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani 12120, Thailand.
Limudomporn, Paviga
  • Department of Zoology, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.
Vongsangnak, Wanwipa
  • Department of Zoology, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.
  • Omics Center for Agriculture, Bioresources, Food, and Health, Kasetsart University (OmiKU), Bangkok 10900, Thailand.
Kovitvadhi, Attawit
  • Department of Physiology, Faculty of Veterinary Medicine, Kasetsart University, Bangkok 10900, Thailand.

Grant Funding

  • P1950420 / Functional ingredient and Food innovation program, National Science and Technology Develop-ment Agency
  • 2565 / Faculty of Veterinary Medicine, Kasetsart University, Bangkok, Thailand

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 79 references
  1. Seltenhammer MH, Simhofer H, Scherzer S, Zechner R, Curik I, Sölkner J, Brandt SM, Jansen B, Pehamberger H, Eisenmenger E. Equine melanoma in a population of 296 grey Lipizzaner horses.. Equine Vet J 2003 Mar;35(2):153-7.
    doi: 10.2746/042516403776114234pubmed: 12638791google scholar: lookup
  2. Rieder S, Stricker C, Joerg H, Dummer R, Stranzinger G. A comparative genetic approach for the investigation of ageing grey horse melanoma.. J. Anim. Breed. Genet. 2000;117:73–82.
  3. Fleury C, Bérard F, Balme B, Thomas L. The study of cutaneous melanomas in Camargue-type gray-skinned horses (1): clinical-pathological characterization.. Pigment Cell Res 2000 Feb;13(1):39-46.
  4. MacGillivray KC, Sweeney RW, Del Piero F. Metastatic melanoma in horses.. J Vet Intern Med 2002 Jul-Aug;16(4):452-6.
  5. Gorham S, Robl M. Melanoma in the grey horse: The darker side of equine ageing.. Vet. Med. 1986;81:446–448.
  6. Rosengren Pielberg G, Golovko A, Sundström E, Curik I, Lennartsson J, Seltenhammer MH, Druml T, Binns M, Fitzsimmons C, Lindgren G, Sandberg K, Baumung R, Vetterlein M, Strömberg S, Grabherr M, Wade C, Lindblad-Toh K, Pontén F, Heldin CH, Sölkner J, Andersson L. A cis-acting regulatory mutation causes premature hair graying and susceptibility to melanoma in the horse.. Nat Genet 2008 Aug;40(8):1004-9.
    doi: 10.1038/ng.185pubmed: 18641652google scholar: lookup
  7. Curik I, Druml T, Seltenhammer M, Sundström E, Pielberg GR, Andersson L, Sölkner J. Complex inheritance of melanoma and pigmentation of coat and skin in Grey horses.. PLoS Genet 2013;9(2):e1003248.
  8. Hida T, Wakamatsu K, Sviderskaya EV, Donkin AJ, Montoliu L, Lynn Lamoreux M, Yu B, Millhauser GL, Ito S, Barsh GS, Jimbow K, Bennett DC. Agouti protein, mahogunin, and attractin in pheomelanogenesis and melanoblast-like alteration of melanocytes: a cAMP-independent pathway.. Pigment Cell Melanoma Res 2009 Oct;22(5):623-34.
  9. Metcalfe LV, O'Brien PJ, Papakonstantinou S, Cahalan SD, McAllister H, Duggan VE. Malignant melanoma in a grey horse: case presentation and review of equine melanoma treatment options.. Ir Vet J 2013 Nov 6;66(1):22.
    doi: 10.1186/2046-0481-66-22pmc: PMC4226278pubmed: 24196087google scholar: lookup
  10. Azimi A, Pernemalm M, Frostvik Stolt M, Hansson J, Lehtiö J, Egyházi Brage S, Hertzman Johansson C. Proteomics analysis of melanoma metastases: association between S100A13 expression and chemotherapy resistance.. Br J Cancer 2014 May 13;110(10):2489-95.
    doi: 10.1038/bjc.2014.169pmc: PMC4021518pubmed: 24722184google scholar: lookup
  11. Ploypetch S, Roytrakul S, Jaresitthikunchai J, Phaonakrop N, Krobthong S, Suriyaphol G. Salivary proteomics of canine oral tumors using MALDI-TOF mass spectrometry and LC-tandem mass spectrometry.. PLoS One 2019;14(7):e0219390.
  12. Ploypetch S, Roytrakul S, Phaonakrop N, Kittisenachai S, Leetanasaksakul K, Pisamai S, Kalpravidh C, Rungsipipat A, Suriyaphol G. In-gel digestion coupled with mass spectrometry (GeLC-MS/MS)-based salivary proteomic profiling of canine oral tumors.. BMC Vet Res 2020 Sep 14;16(1):335.
    doi: 10.1186/s12917-020-02550-wpmc: PMC7489029pubmed: 32928212google scholar: lookup
  13. Ploypetch S, Roytrakul S, Jaresitthikunchai J, Phaonakrop N, Teewasutrakul P, Rungsipipat A, Suriyaphol G. Salivary proteomics in monitoring the therapeutic response of canine oral melanoma.. PLoS One 2021;16(8):e0256167.
  14. Tesena P, Kingkaw A, Vongsangnak W, Pitikarn S, Phaonakrop N, Roytrakul S, Kovitvadhi A. Preliminary Study: Proteomic Profiling Uncovers Potential Proteins for Biomonitoring Equine Melanocytic Neoplasm.. Animals (Basel) 2021 Jun 27;11(7).
    doi: 10.3390/ani11071913pmc: PMC8300200pubmed: 34199079google scholar: lookup
  15. Desser H, Niebauer GW, Gebhart W. [Polyamine and histamine contents in the blood of pigmented, depigmented and melanoma bearing Lipizzaner horses].. Zentralbl Veterinarmed A 1980 Feb;27(1):45-53.
  16. Koss H, Bunney TD, Behjati S, Katan M. Dysfunction of phospholipase Cγ in immune disorders and cancer.. Trends Biochem Sci 2014 Dec;39(12):603-11.
    doi: 10.1016/j.tibs.2014.09.004pubmed: 25456276google scholar: lookup
  17. R Development Core Team. A Language and Environment for Statistical Computing.. .
  18. Fox J, Bouchet-Valat M. Rcmdr: R Commander.. R Package Version 2.6-2. 2020.
  19. LOWRY OH, ROSEBROUGH NJ, FARR AL, RANDALL RJ. Protein measurement with the Folin phenol reagent.. J Biol Chem 1951 Nov;193(1):265-75.
    doi: 10.1016/S0021-9258(19)52451-6pubmed: 14907713google scholar: lookup
  20. Johansson C, Samskog J, Sundström L, Wadensten H, Björkesten L, Flensburg J. Differential expression analysis of Escherichia coli proteins using a novel software for relative quantitation of LC-MS/MS data.. Proteomics 2006 Aug;6(16):4475-85.
    doi: 10.1002/pmic.200500921pubmed: 16858737google scholar: lookup
  21. Thorsell A, Portelius E, Blennow K, Westman-Brinkmalm A. Evaluation of sample fractionation using micro-scale liquid-phase isoelectric focusing on mass spectrometric identification and quantitation of proteins in a SILAC experiment.. Rapid Commun Mass Spectrom 2007;21(5):771-8.
    doi: 10.1002/rcm.2898pubmed: 17279600google scholar: lookup
  22. Howe EA, Sinha R, Schlauch D, Quackenbush J. RNA-Seq analysis in MeV.. Bioinformatics 2011 Nov 15;27(22):3209-10.
  23. Bardou P, Mariette J, Escudié F, Djemiel C, Klopp C. jvenn: an interactive Venn diagram viewer.. BMC Bioinformatics 2014 Aug 29;15(1):293.
    doi: 10.1186/1471-2105-15-293pmc: PMC4261873pubmed: 25176396google scholar: lookup
  24. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M. The KEGG resource for deciphering the genome.. Nucleic Acids Res 2004 Jan 1;32(Database issue):D277-80.
    doi: 10.1093/nar/gkh063pmc: PMC308797pubmed: 14681412google scholar: lookup
  25. Moore J, Shaw C, Shaw E, Buechner-Maxwell V, Scarratt W, Crisman M, Furr M, Roberson J. Melanoma in horses: Current perspectives.. Equin. Vet Educ. 2013;25:144–151.
  26. Seltenhammer MH, Heere-Ress E, Brandt S, Druml T, Jansen B, Pehamberger H, Niebauer GW. Comparative histopathology of grey-horse-melanoma and human malignant melanoma.. Pigment Cell Res 2004 Dec;17(6):674-81.
  27. Smith SH, Goldschmidt MH, McManus PM. A comparative review of melanocytic neoplasms.. Vet Pathol 2002 Nov;39(6):651-78.
    doi: 10.1354/vp.39-6-651pubmed: 12450197google scholar: lookup
  28. Sever A, Abd Elkadir A, Matana Y, Gopas J, Zeiri Y. Biomarkers for Detection and Monitoring of B16 Melanoma in Mouse Urine and Feces.. J Biomark 2015;2015:841245.
    doi: 10.1155/2015/841245pmc: PMC4437384pubmed: 26317038google scholar: lookup
  29. You JS, Lincoln HC, Kim CR, Frey JW, Goodman CA, Zhong XP, Hornberger TA. The role of diacylglycerol kinase ζ and phosphatidic acid in the mechanical activation of mammalian target of rapamycin (mTOR) signaling and skeletal muscle hypertrophy.. J Biol Chem 2014 Jan 17;289(3):1551-63.
    doi: 10.1074/jbc.M113.531392pmc: PMC3894336pubmed: 24302719google scholar: lookup
  30. Dong W, Lv H, Xia G, Wang M. Does diacylglycerol serve as a signaling molecule in plants?. Plant Signal Behav 2012 Apr;7(4):472-5.
    doi: 10.4161/psb.19644pmc: PMC3419036pubmed: 22499171google scholar: lookup
  31. Kadamur G, Ross EM. Mammalian phospholipase C.. Annu Rev Physiol 2013;75:127-54.
  32. Eichmann TO, Lass A. DAG tales: the multiple faces of diacylglycerol--stereochemistry, metabolism, and signaling.. Cell Mol Life Sci 2015 Oct;72(20):3931-52.
    doi: 10.1007/s00018-015-1982-3pmc: PMC4575688pubmed: 26153463google scholar: lookup
  33. Torres-Ayuso P, Daza-Martín M, Martín-Pérez J, Ávila-Flores A, Mérida I. Diacylglycerol kinase α promotes 3D cancer cell growth and limits drug sensitivity through functional interaction with Src.. Oncotarget 2014 Oct 30;5(20):9710-26.
    doi: 10.18632/oncotarget.2344pmc: PMC4259432pubmed: 25339152google scholar: lookup
  34. Takao S, Akiyama R, Sakane F. Combined inhibition/silencing of diacylglycerol kinase α and ζ simultaneously and synergistically enhances interleukin-2 production in T cells and induces cell death of melanoma cells.. J Cell Biochem 2021 May;122(5):494-506.
    doi: 10.1002/jcb.29876pubmed: 33399248google scholar: lookup
  35. Noessner E. DGK-α: A Checkpoint in Cancer-Mediated Immuno-Inhibition and Target for Immunotherapy.. Front Cell Dev Biol 2017;5:16.
    doi: 10.3389/fcell.2017.00016pmc: PMC5335622pubmed: 28316970google scholar: lookup
  36. Gross SR, Balklava Z, Griffin M. Importance of tissue transglutaminase in repair of extracellular matrices and cell death of dermal fibroblasts after exposure to a solarium ultraviolet A source.. J Invest Dermatol 2003 Aug;121(2):412-23.
  37. Agnihotri N, Kumar S, Mehta K. Tissue transglutaminase as a central mediator in inflammation-induced progression of breast cancer.. Breast Cancer Res 2013 Feb 25;15(1):202.
    doi: 10.1186/bcr3371pmc: PMC3745644pubmed: 23673317google scholar: lookup
  38. Xu L, Begum S, Hearn JD, Hynes RO. GPR56, an atypical G protein-coupled receptor, binds tissue transglutaminase, TG2, and inhibits melanoma tumor growth and metastasis.. Proc Natl Acad Sci U S A 2006 Jun 13;103(24):9023-8.
    doi: 10.1073/pnas.0602681103pmc: PMC1474142pubmed: 16757564google scholar: lookup
  39. Huang L, Xu AM, Liu W. Transglutaminase 2 in cancer.. Am J Cancer Res 2015;5(9):2756-76.
    pmc: PMC4633903pubmed: 26609482
  40. Wu L, Sun T, Kobayashi K, Gao P, Griffin JD. Identification of a family of mastermind-like transcriptional coactivators for mammalian notch receptors.. Mol Cell Biol 2002 Nov;22(21):7688-700.
  41. Noda H, Okumura Y, Nakayama T, Miyabe S, Fujiyoshi Y, Hattori H, Shimozato K, Inagaki H. Clinicopathological significance of MAML2 gene split in mucoepidermoid carcinoma.. Cancer Sci 2013 Jan;104(1):85-92.
    doi: 10.1111/cas.12039pmc: PMC7657246pubmed: 23035786google scholar: lookup
  42. Moriyama M, Osawa M, Mak SS, Ohtsuka T, Yamamoto N, Han H, Delmas V, Kageyama R, Beermann F, Larue L, Nishikawa S. Notch signaling via Hes1 transcription factor maintains survival of melanoblasts and melanocyte stem cells.. J Cell Biol 2006 May 8;173(3):333-9.
    doi: 10.1083/jcb.200509084pmc: PMC2063834pubmed: 16651378google scholar: lookup
  43. Zhang W, Liu H, Liu Z, Zhu D, Amos CI, Fang S, Lee JE, Wei Q. Functional Variants in Notch Pathway Genes NCOR2, NCSTN, and MAML2 Predict Survival of Patients with Cutaneous Melanoma.. Cancer Epidemiol Biomarkers Prev 2015 Jul;24(7):1101-10.
  44. Feng XD, Song Q, Li CW, Chen J, Tang HM, Peng ZH, Wang XC. Structural maintenance of chromosomes 4 is a predictor of survival and a novel therapeutic target in colorectal cancer.. Asian Pac J Cancer Prev 2014;15(21):9459-65.
    doi: 10.7314/APJCP.2014.15.21.9459pubmed: 25422241google scholar: lookup
  45. Bidkhori G, Narimani Z, Hosseini Ashtiani S, Moeini A, Nowzari-Dalini A, Masoudi-Nejad A. Reconstruction of an integrated genome-scale co-expression network reveals key modules involved in lung adenocarcinoma.. PLoS One 2013;8(7):e67552.
  46. Kulawiec M, Safina A, Desouki MM, Still I, Matsui S, Bakin A, Singh KK. Tumorigenic transformation of human breast epithelial cells induced by mitochondrial DNA depletion.. Cancer Biol Ther 2008 Nov;7(11):1732-43.
    doi: 10.4161/cbt.7.11.6729pmc: PMC2783327pubmed: 19151587google scholar: lookup
  47. Zhou B, Yuan T, Liu M, Liu H, Xie J, Shen Y, Chen P. Overexpression of the structural maintenance of chromosome 4 protein is associated with tumor de-differentiation, advanced stage and vascular invasion of primary liver cancer.. Oncol Rep 2012 Oct;28(4):1263-8.
    doi: 10.3892/or.2012.1929pubmed: 22842912google scholar: lookup
  48. Zhang C, Kuang M, Li M, Feng L, Zhang K, Cheng S. SMC4, which is essentially involved in lung development, is associated with lung adenocarcinoma progression.. Sci Rep 2016 Sep 30;6:34508.
    doi: 10.1038/srep34508pmc: PMC5043270pubmed: 27687868google scholar: lookup
  49. Wirtenberger M, Frank B, Hemminki K, Klaes R, Schmutzler RK, Wappenschmidt B, Meindl A, Kiechle M, Arnold N, Weber BH, Niederacher D, Bartram CR, Burwinkel B. Interaction of Werner and Bloom syndrome genes with p53 in familial breast cancer.. Carcinogenesis 2006 Aug;27(8):1655-60.
    doi: 10.1093/carcin/bgi374pubmed: 16501249google scholar: lookup
  50. Peng L, Guo JC, Long L, Pan F, Zhao JM, Xu LY, Li EM. A Novel Clinical Six-Flavoprotein-Gene Signature Predicts Prognosis in Esophageal Squamous Cell Carcinoma.. Biomed Res Int 2019;2019:3869825.
    doi: 10.1155/2019/3869825pmc: PMC6878914pubmed: 31815134google scholar: lookup
  51. Dijkman WP, de Gonzalo G, Mattevi A, Fraaije MW. Flavoprotein oxidases: classification and applications.. Appl Microbiol Biotechnol 2013 Jun;97(12):5177-88.
    doi: 10.1007/s00253-013-4925-7pubmed: 23640366google scholar: lookup
  52. Medina M, Ferreira P, Martínez-Júlvez M. Flavoproteins and flavoenzymes with biomedical and therapeutic impact.. Curr Pharm Des 2013;19(14):2497-8.
    doi: 10.2174/1381612811319140001pubmed: 23116404google scholar: lookup
  53. Maurus K, Hufnagel A, Geiger F, Graf S, Berking C, Heinemann A, Paschen A, Kneitz S, Stigloher C, Geissinger E, Otto C, Bosserhoff A, Schartl M, Meierjohann S. The AP-1 transcription factor FOSL1 causes melanocyte reprogramming and transformation.. Oncogene 2017 Sep 7;36(36):5110-5121.
    doi: 10.1038/onc.2017.135pubmed: 28481878google scholar: lookup
  54. Teutschbein J, Haydn JM, Samans B, Krause M, Eilers M, Schartl M, Meierjohann S. Gene expression analysis after receptor tyrosine kinase activation reveals new potential melanoma proteins.. BMC Cancer 2010 Jul 21;10:386.
    doi: 10.1186/1471-2407-10-386pmc: PMC2912872pubmed: 20663135google scholar: lookup
  55. Brown J, Bothma H, Veale R, Willem P. Genomic imbalances in esophageal carcinoma cell lines involve Wnt pathway genes.. World J Gastroenterol 2011 Jun 28;17(24):2909-23.
    doi: 10.3748/wjg.v17.i24.2909pmc: PMC3129505pubmed: 21734802google scholar: lookup
  56. Bareiss S, Kim K, Lu Q. Delta-catenin/NPRAP: A new member of the glycogen synthase kinase-3beta signaling complex that promotes beta-catenin turnover in neurons.. J Neurosci Res 2010 Aug 15;88(11):2350-63.
    pmc: PMC3813950pubmed: 20623542doi: 10.1002/jnr.22414google scholar: lookup
  57. Lu Q, Aguilar BJ, Li M, Jiang Y, Chen YH. Genetic alterations of δ-catenin/NPRAP/Neurojungin (CTNND2): functional implications in complex human diseases.. Hum Genet 2016 Oct;135(10):1107-16.
    doi: 10.1007/s00439-016-1705-3pmc: PMC5021578pubmed: 27380241google scholar: lookup
  58. van Oers JM, Roa S, Werling U, Liu Y, Genschel J, Hou H Jr, Sellers RS, Modrich P, Scharff MD, Edelmann W. PMS2 endonuclease activity has distinct biological functions and is essential for genome maintenance.. Proc Natl Acad Sci U S A 2010 Jul 27;107(30):13384-9.
    doi: 10.1073/pnas.1008589107pmc: PMC2922181pubmed: 20624957google scholar: lookup
  59. Chalmers ZR, Connelly CF, Fabrizio D, Gay L, Ali SM, Ennis R, Schrock A, Campbell B, Shlien A, Chmielecki J, Huang F, He Y, Sun J, Tabori U, Kennedy M, Lieber DS, Roels S, White J, Otto GA, Ross JS, Garraway L, Miller VA, Stephens PJ, Frampton GM. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden.. Genome Med 2017 Apr 19;9(1):34.
    doi: 10.1186/s13073-017-0424-2pmc: PMC5395719pubmed: 28420421google scholar: lookup
  60. Kim HD, Choe J, Seo YS. The sen1(+) gene of Schizosaccharomyces pombe, a homologue of budding yeast SEN1, encodes an RNA and DNA helicase.. Biochemistry 1999 Nov 2;38(44):14697-710.
    doi: 10.1021/bi991470cpubmed: 10545196google scholar: lookup
  61. Richard P, Feng S, Tsai YL, Li W, Rinchetti P, Muhith U, Irizarry-Cole J, Stolz K, Sanz LA, Hartono S, Hoque M, Tadesse S, Seitz H, Lotti F, Hirano M, Chédin F, Tian B, Manley JL. SETX (senataxin), the helicase mutated in AOA2 and ALS4, functions in autophagy regulation.. Autophagy 2021 Aug;17(8):1889-1906.
  62. Moreira MC, Klur S, Watanabe M, Németh AH, Le Ber I, Moniz JC, Tranchant C, Aubourg P, Tazir M, Schöls L, Pandolfo M, Schulz JB, Pouget J, Calvas P, Shizuka-Ikeda M, Shoji M, Tanaka M, Izatt L, Shaw CE, M'Zahem A, Dunne E, Bomont P, Benhassine T, Bouslam N, Stevanin G, Brice A, Guimarães J, Mendonça P, Barbot C, Coutinho P, Sequeiros J, Dürr A, Warter JM, Koenig M. Senataxin, the ortholog of a yeast RNA helicase, is mutant in ataxia-ocular apraxia 2.. Nat Genet 2004 Mar;36(3):225-7.
    doi: 10.1038/ng1303pubmed: 14770181google scholar: lookup
  63. Chen YZ, Bennett CL, Huynh HM, Blair IP, Puls I, Irobi J, Dierick I, Abel A, Kennerson ML, Rabin BA, Nicholson GA, Auer-Grumbach M, Wagner K, De Jonghe P, Griffin JW, Fischbeck KH, Timmerman V, Cornblath DR, Chance PF. DNA/RNA helicase gene mutations in a form of juvenile amyotrophic lateral sclerosis (ALS4).. Am J Hum Genet 2004 Jun;74(6):1128-35.
    doi: 10.1086/421054pmc: PMC1182077pubmed: 15106121google scholar: lookup
  64. Chook YM, Süel KE. Nuclear import by karyopherin-βs: recognition and inhibition.. Biochim Biophys Acta 2011 Sep;1813(9):1593-606.
  65. Çağatay T, Chook YM. Karyopherins in cancer.. Curr Opin Cell Biol 2018 Jun;52:30-42.
    doi: 10.1016/j.ceb.2018.01.006pmc: PMC5988925pubmed: 29414591google scholar: lookup
  66. Stelma T, Chi A, van der Watt PJ, Verrico A, Lavia P, Leaner VD. Targeting nuclear transporters in cancer: Diagnostic, prognostic and therapeutic potential.. IUBMB Life 2016 Apr;68(4):268-80.
    doi: 10.1002/iub.1484pubmed: 26970212google scholar: lookup
  67. Fischer GM, Vashisht Gopal YN, McQuade JL, Peng W, DeBerardinis RJ, Davies MA. Metabolic strategies of melanoma cells: Mechanisms, interactions with the tumor microenvironment, and therapeutic implications.. Pigment Cell Melanoma Res 2018 Jan;31(1):11-30.
    doi: 10.1111/pcmr.12661pmc: PMC5742019pubmed: 29049843google scholar: lookup
  68. Koundouros N, Poulogiannis G. Reprogramming of fatty acid metabolism in cancer.. Br J Cancer 2020 Jan;122(1):4-22.
    doi: 10.1038/s41416-019-0650-zpmc: PMC6964678pubmed: 31819192google scholar: lookup
  69. Carracedo A, Cantley LC, Pandolfi PP. Cancer metabolism: fatty acid oxidation in the limelight.. Nat Rev Cancer 2013 Apr;13(4):227-32.
    doi: 10.1038/nrc3483pmc: PMC3766957pubmed: 23446547google scholar: lookup
  70. Dumas SJ, García-Caballero M, Carmeliet P. Metabolic Signatures of Distinct Endothelial Phenotypes.. Trends Endocrinol Metab 2020 Aug;31(8):580-595.
    doi: 10.1016/j.tem.2020.05.009pubmed: 32622584google scholar: lookup
  71. Messias MCF, Mecatti GC, Priolli DG, de Oliveira Carvalho P. Plasmalogen lipids: functional mechanism and their involvement in gastrointestinal cancer.. Lipids Health Dis 2018 Mar 7;17(1):41.
    doi: 10.1186/s12944-018-0685-9pmc: PMC5842581pubmed: 29514688google scholar: lookup
  72. Athenstaedt K, Daum G. Phosphatidic acid, a key intermediate in lipid metabolism.. Eur J Biochem 1999 Nov;266(1):1-16.
  73. Wood WG, Li L, Müller WE, Eckert GP. Cholesterol as a causative factor in Alzheimer's disease: a debatable hypothesis.. J Neurochem 2014 May;129(4):559-72.
    doi: 10.1111/jnc.12637pmc: PMC3999290pubmed: 24329875google scholar: lookup
  74. Kim IS, Heilmann S, Kansler ER, Zhang Y, Zimmer M, Ratnakumar K, Bowman RL, Simon-Vermot T, Fennell M, Garippa R, Lu L, Lee W, Hollmann T, Xavier JB, White RM. Microenvironment-derived factors driving metastatic plasticity in melanoma.. Nat Commun 2017 Feb 9;8:14343.
    doi: 10.1038/ncomms14343pmc: PMC5309794pubmed: 28181494google scholar: lookup
  75. Zhang M, Di Martino JS, Bowman RL, Campbell NR, Baksh SC, Simon-Vermot T, Kim IS, Haldeman P, Mondal C, Yong-Gonzales V, Abu-Akeel M, Merghoub T, Jones DR, Zhu XG, Arora A, Ariyan CE, Birsoy K, Wolchok JD, Panageas KS, Hollmann T, Bravo-Cordero JJ, White RM. Adipocyte-Derived Lipids Mediate Melanoma Progression via FATP Proteins.. Cancer Discov 2018 Aug;8(8):1006-1025.
  76. Pellerin L, Carrié L, Dufau C, Nieto L, Ségui B, Levade T, Riond J, Andrieu-Abadie N. Lipid metabolic Reprogramming: Role in Melanoma Progression and Therapeutic Perspectives.. Cancers (Basel) 2020 Oct 27;12(11).
    doi: 10.3390/cancers12113147pmc: PMC7692067pubmed: 33121001google scholar: lookup
  77. McKenzie HC 3rd. Equine hyperlipidemias.. Vet Clin North Am Equine Pract 2011 Apr;27(1):59-72.
    doi: 10.1016/j.cveq.2010.12.008pubmed: 21392654google scholar: lookup
  78. Alves-Bezerra M, Cohen DE. Triglyceride Metabolism in the Liver.. Compr Physiol 2017 Dec 12;8(1):1-8.
    doi: 10.1002/cphy.c170012pmc: PMC6376873pubmed: 29357123google scholar: lookup
  79. Breidenbach A, Fuhrmann H, Deegen E, Lindholm A, Sallmann HP. Studies on equine lipid metabolism. 2. Lipolytic activities of plasma and tissue lipases in large horses and ponies.. Zentralbl Veterinarmed A 1999 Feb;46(1):39-48.

Citations

This article has been cited 3 times.
  1. Miglio A, Cremonini V, Leonardi L, Manuali E, Coliolo P, Barbato O, Dall'Aglio C, Antognoni MT. Omics Technologies in Veterinary Medicine: Literature Review and Perspectives in Transfusion Medicine. Transfus Med Hemother 2023 Jun;50(3):198-207.
    doi: 10.1159/000530870pubmed: 37408648google scholar: lookup
  2. Tesena P, Vinijkumthorn R, Kingkaw A, Yanyongsirikarn P, Phasuk K, Ploypetch S, Phaonakrop N, Roytrakul S, Vongsangnak W, Prapaiwan N. Probing Wnt pathway and functional signal in equine melanocytic neoplasms through quantitative proteomics and immunohistochemistry. BMC Vet Res 2025 Aug 7;21(1):509.
    doi: 10.1186/s12917-025-04956-wpubmed: 40775356google scholar: lookup
  3. Vinijkumthorn R, Kingkaw A, Yanyongsirikarn P, Phaonakrop N, Roytrakul S, Vongsangnak W, Tesena P. Phosphorylation of SNW1 protein associated with equine melanocytic neoplasm identified in serum and feces. Sci Rep 2024 Dec 28;14(1):30842.
    doi: 10.1038/s41598-024-81338-6pubmed: 39730520google scholar: lookup