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Differentially Expressed Proteins in Malignant and Benign Adrenocortical Tumors

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  • Hanna Kjellin
  • Henrik Johansson
  • Anders Höög
  • Janne Lehtiö
  • Per-Johan Jakobsson
  • Magnus Kjellman

Abstract

We have compared the microsomal protein composition of eight malignant and six benign adrenocortical tumors with proteomic methods. IGF2 had increased level in the malignant tumors, confirming previous microarray studies on the same material. Aldolase A, a glycolytic enzyme, also showed increased levels in the malignant tissue compared to the benign. Additionally, several proteins belonging to complex I in the mitochondrial respiration chain showed decreased levels in the malignant tissue. Taken together, this may indicate a shift in energy metabolism where glycolysis may be favored over tight coupling of glycolysis and mitochondrial respiration, a phenomenon known as the Warburg effect. One of the complex I proteins that showed decreased levels in the malignant tissue was GRIM-19. This protein has been suggested as a tumor suppressive protein by being a negative regulator of STAT3. In summary, an analysis of the microsomal proteome in adrenocortical tumors identifies groups of proteins as well as specific proteins differentially expressed in the benign and malignant forms. These proteins shed light on the biology behind malignancy and could delineate future drug targets.

Suggested Citation

  • Hanna Kjellin & Henrik Johansson & Anders Höög & Janne Lehtiö & Per-Johan Jakobsson & Magnus Kjellman, 2014. "Differentially Expressed Proteins in Malignant and Benign Adrenocortical Tumors," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-10, February.
    • Handle: RePEc:plo:pone00:0087951
    DOI: 10.1371/journal.pone.0087951
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    1. Heather R. Christofk & Matthew G. Vander Heiden & Ning Wu & John M. Asara & Lewis C. Cantley, 2008. "Pyruvate kinase M2 is a phosphotyrosine-binding protein," Nature, Nature, vol. 452(7184), pages 181-186, March.
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    1. Toğaçar, Mesut & Özkurt, Kutsal Baran & Ergen, Burhan & Cömert, Zafer, 2020. "BreastNet: A novel convolutional neural network model through histopathological images for the diagnosis of breast cancer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

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