Erratum: Glycosaminoglycan profiling in patients’ plasma and urine predicts the occurrence of metastatic clear cell renal cell carcinoma (Cell Reports (2016) 15(8) (1822–1836), (S2211124716305009), (10.1016/j.celrep.2016.04.056));Glycosaminoglycan Profiling in Patients' Plasma and Urine Predicts the Occurrence of Metastatic Clear Cell Renal Cell Carcinoma

Cell Reports

Volumn 15, Issue 8, 2016, Pages 1822-1836

  Gatto, Francesco ^a   Volpi, Nicola ^b   Nilsson, Helén ^c   Nookaew, Intawat ^a,g   Maruzzo, Marco ^d   Roma, Anna ^d   Johansson, Martin E ^c   Stierner, Ulrika ^e   Lundstam, Sven ^f   Basso, Umberto ^d   Nielsen, Jens ^a  

^a CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

^b UNIVERSITY OF MODENA AND REGGIO EMILIA   (Italy)

^c LUND UNIVERSITY   (Sweden)

^d VENETO INSTITUTE OF ONCOLOGY IOV IRCCS   (Italy)

^e SAHLGRENSKA ACADEMY AT UNIVERSITY OF GOTHENBURG   (Sweden)

^f SAHLGRENSKA UNIVERSITY HOSPITAL   (Sweden)

^g UNIVERSITY OF ARKANSAS FOR MEDICAL SCIENCES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANTINEOPLASTIC AGENT; BIOLOGICAL MARKER; GLYCOSAMINOGLYCAN; SUNITINIB; MESSENGER RNA; TUMOR MARKER;

ADULT; ARTICLE; CLINICAL ARTICLE; COHORT ANALYSIS; CONTROLLED STUDY; EXTRACELLULAR SPACE; FEMALE; GLYCOSAMINOGLYCAN METABOLISM; HUMAN; HUMAN TISSUE; KIDNEY METASTASIS; MALE; MEASUREMENT ACCURACY; NUCLEAR REPROGRAMMING; PREDICTION; PRIORITY JOURNAL; PROTEIN BLOOD LEVEL; PROTEIN URINE LEVEL; SCORING SYSTEM; TRANSCRIPTION REGULATION; AGED; BIOSYNTHESIS; BLOOD; CASE CONTROL STUDY; GENE EXPRESSION REGULATION; GENETICS; KIDNEY TUMOR; METABOLISM; METASTASIS; MIDDLE AGED; PATHOLOGY; RENAL CELL CARCINOMA; REPRODUCIBILITY; URINE;

AGED; BIOMARKERS, TUMOR; BIOSYNTHETIC PATHWAYS; CARCINOMA, RENAL CELL; CASE-CONTROL STUDIES; COHORT STUDIES; FEMALE; GENE EXPRESSION REGULATION, NEOPLASTIC; GLYCOSAMINOGLYCANS; HUMANS; KIDNEY NEOPLASMS; MALE; MIDDLE AGED; NEOPLASM METASTASIS; REPRODUCIBILITY OF RESULTS; RNA, MESSENGER;

EID: 84966671361     PISSN: None     EISSN: 22111247     Source Type: Journal    
DOI: 10.1016/j.celrep.2021.108795     Document Type: Erratum

References (67)

1. Afratis N., Gialeli C., Nikitovic D., Tsegenidis T., Karousou E., Theocharis A.D., Pavão M.S., Tzanakakis G.N., Karamanos N.K. Glycosaminoglycans: key players in cancer cell biology and treatment. FEBS J. 2012, 279:1177-1197.
2. Agren R., Mardinoglu A., Asplund A., Kampf C., Uhlen M., Nielsen J. Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling. Mol. Syst. Biol. 2014, 10:721.
3. Albiges L., Oudard S., Negrier S., Caty A., Gravis G., Joly F., Duclos B., Geoffrois L., Rolland F., Guillot A., et al. Complete remission with tyrosine kinase inhibitors in renal cell carcinoma. J. Clin. Oncol. 2012, 30:482-487.
4. Anower-E-Khuda M.F., Matsumoto K., Habuchi H., Morita H., Yokochi T., Shimizu K., Kimata K. Glycosaminoglycans in the blood of hereditary multiple exostoses patients: half reduction of heparan sulfate to chondroitin sulfate ratio and the possible diagnostic application. Glycobiology 2013, 23:865-876.
5. Batista L.T., Matos L.L., Machado L.R., Suarez E.R., Theodoro T.R., Martins J.R., Nader H.B., Pompeo A.C., Pinhal M.A. Heparanase expression and glycosaminoglycans profile in renal cell carcinoma. Int. J. Urol. 2012, 19:1036-1040.
6. Bordbar A., Monk J.M., King Z.A., Palsson B.O. Constraint-based models predict metabolic and associated cellular functions. Nat. Rev. Genet. 2014, 15:107-120.
7. Coppa G.V., Gabrielli O., Buzzega D., Zampini L., Galeazzi T., Maccari F., Bertino E., Volpi N. Composition and structure elucidation of human milk glycosaminoglycans. Glycobiology 2011, 21:295-303.
8. Creighton C.J., Morgan M., Gunaratne P.H., Wheeler D.A., Gibbs R.A., Gordon Robertson A., Chu A., Beroukhim R., Cibulskis K., Signoretti S., et al. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 2013, 499:43-49.
9. Cuperlovic-Culf M., Cormier K., Touaibia M., Reyjal J., Robichaud S., Belbraouet M., Turcotte S. H NMR Metabolomics analysis of renal cell carcinoma cells: effect of VHL inactivation on metabolism. Int. J. Cancer 2016, 138:2439-2449.
10. Dray S., Dufour A.B. The ade4 package: implementing the duality diagram for ecologists. J. Stat. Softw. 2007, 22:1-20.
11. Ferlay J., Shin H.R., Bray F., Forman D., Mathers C., Parkin D.M. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int. J. Cancer 2010, 127:2893-2917.
12. Fernández-Vega I., García O., Crespo A., Castañón S., Menéndez P., Astudillo A., Quirós L.M. Specific genes involved in synthesis and editing of heparan sulfate proteoglycans show altered expression patterns in breast cancer. BMC Cancer 2013, 13:24.
13. Finley D.S., Pantuck A.J., Belldegrun A.S. Tumor biology and prognostic factors in renal cell carcinoma. Oncologist 2011, 16(Suppl 2):4-13.
14. Friedman J., Hastie T., Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 2010, 33:1-22.
15. Gatto F., Nookaew I., Nielsen J. Chromosome 3p loss of heterozygosity is associated with a unique metabolic network in clear cell renal carcinoma. Proc. Natl. Acad. Sci. USA 2014, 111:E866-E875.
16. Gatto F., Miess H., Schulze A., Nielsen J. Flux balance analysis predicts essential genes in clear cell renal cell carcinoma metabolism. Sci. Rep. 2015, 5:10738.
17. Gupta K., Miller J.D., Li J.Z., Russell M.W., Charbonneau C. Epidemiologic and socioeconomic burden of metastatic renal cell carcinoma (mRCC): a literature review. Cancer Treat. Rev. 2008, 34:193-205.
18. Hakimi A.A., Reznik E., Lee C.H., Creighton C.J., Brannon A.R., Luna A., Aksoy B.A., Liu E.M., Shen R., Lee W., et al. An integrated metabolic atlas of clear cell renal cell carcinoma. Cancer Cell 2016, 29:104-116.
19. Jackson R.L., Busch S.J., Cardin A.D. Glycosaminoglycans: molecular properties, protein interactions, and role in physiological processes. Physiol. Rev. 1991, 71:481-539.
20. Jerby L., Ruppin E. Predicting drug targets and biomarkers of cancer via genome-scale metabolic modeling. Clin. Cancer Res. 2012, 18:5572-5584.
21. Jonasch E., Futreal P.A., Davis I.J., Bailey S.T., Kim W.Y., Brugarolas J., Giaccia A.J., Kurban G., Pause A., Frydman J., et al. State of the science: an update on renal cell carcinoma. Mol. Cancer Res. 2012, 10:859-880.
22. Kreuger J., Kjellén L. Heparan sulfate biosynthesis: regulation and variability. J. Histochem. Cytochem. 2012, 60:898-907.
23. Kruschke J.K. Bayesian estimation supersedes the t test. J. Exp. Psychol. Gen. 2013, 142:573-603.
24. Law C.W., Chen Y., Shi W., Smyth G.K. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 2014, 15:R29.
25. Li B., Qiu B., Lee D.S., Walton Z.E., Ochocki J.D., Mathew L.K., Mancuso A., Gade T.P., Keith B., Nissim I., et al. Fructose-1,6-bisphosphatase opposes renal carcinoma progression. Nature 2014, 513:251-255.
26. Lopez-Raton M., Cadarso-Suarez C., Rodriguez-Alvarez M.X., Gude-Sampedro F. OptimalCutpoints: an R package for selecting optimal cutpoints in diagnostic tests. J. Stat. Softw. 2014, 61:1-36.
27. Mannello F., Maccari F., Ligi D., Canale M., Galeotti F., Volpi N. Characterization of oversulfated chondroitin sulfate rich in 4,6-O-disulfated disaccharides in breast cyst fluids collected from human breast gross cysts. Cell Biochem. Funct. 2014, 32:344-350.
28. Mannello F., Maccari F., Ligi D., Santi M., Gatto F., Linhardt R.J., Galeotti F., Volpi N. Breast cyst fluid heparan sulphate is distinctively N-sulphated depending on apocrine or flattened type. Cell Biochem. Funct. 2015, 33:128-133.
29. Mardinoglu A., Nielsen J. New paradigms for metabolic modeling of human cells. Curr. Opin. Biotechnol. 2015, 34:91-97.
30. Mardinoglu A., Gatto F., Nielsen J. Genome-scale modeling of human metabolism - a systems biology approach. Biotechnol. J. 2013, 8:985-996.
31. McCarthy K.J., Wassenhove-McCarthy D.J. The glomerular basement membrane as a model system to study the bioactivity of heparan sulfate glycosaminoglycans. Microsc. Microanal. 2012, 18:3-21.
32. Mikami T., Kitagawa H. Biosynthesis and function of chondroitin sulfate. Biochim. Biophys. Acta 2013, 1830:4719-4733.
33. Miner J.H., Towler D., Chen F., Kopan R., Hruska K. Organogenesis of the kidney glomerulus: focus on the glomerular basement membrane. Organogenesis 2011, 7:75-82.
34. Mizumoto S., Takahashi J., Sugahara K. Receptor for advanced glycation end products (RAGE) functions as receptor for specific sulfated glycosaminoglycans, and anti-RAGE antibody or sulfated glycosaminoglycans delivered in vivo inhibit pulmonary metastasis of tumor cells. J. Biol. Chem. 2012, 287:18985-18994.
35. Moch H., Srigley J., Delahunt B., Montironi R., Egevad L., Tan P.H. Biomarkers in renal cancer. Virchows Arch. 2014, 464:359-365.
36. Nilsson H., Lindgren D., Mandahl Forsberg A., Mulder H., Axelson H., Johansson M.E. Primary clear cell renal carcinoma cells display minimal mitochondrial respiratory capacity resulting in pronounced sensitivity to glycolytic inhibition by 3-Bromopyruvate. Cell Death Dis. 2015, 6:e1585.
37. Nuzzo R. Scientific method: statistical errors. Nature 2014, 506:150-152.
38. Patil K.R., Nielsen J. Uncovering transcriptional regulation of metabolism by using metabolic network topology. Proc. Natl. Acad. Sci. USA 2005, 102:2685-2689.
39. Peña-Llopis S., Vega-Rubín-de-Celis S., Liao A., Leng N., Pavía-Jiménez A., Wang S., Yamasaki T., Zhrebker L., Sivanand S., Spence P., et al. BAP1 loss defines a new class of renal cell carcinoma. Nat. Genet. 2012, 44:751-759.
40. Rini B.I., Campbell S.C., Escudier B. Renal cell carcinoma. Lancet 2009, 373:1119-1132.
41. Robin X., Turck N., Hainard A., Tiberti N., Lisacek F., Sanchez J.C., Müller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 2011, 12:77.
42. Salanti A., Clausen T.M., Agerbæk M.Ø., Al Nakouzi N., Dahlbäck M., Oo H.Z., Lee S., Gustavsson T., Rich J.R., Hedberg B.J., et al. Targeting human cancer by a glycosaminoglycan binding malaria protein. Cancer Cell 2015, 28:500-514.
43. Sawyers C.L. The cancer biomarker problem. Nature 2008, 452:548-552.
44. Schmidt E.P., Li G., Li L., Fu L., Yang Y., Overdier K.H., Douglas I.S., Linhardt R.J. The circulating glycosaminoglycan signature of respiratory failure in critically ill adults. J. Biol. Chem. 2014, 289:8194-8202.
45. Schmidt E.P., Overdier K.H., Sun X., Lin L., Liu X., Yang Y., Ammons L.A., Hiller T.D., Suflita M.A., Yu Y., et al. Urinary glycosaminoglycans predict outcomes in septic shock and ARDS. Am. J. Respir. Crit. Care Med. 2016, Published online February 29, 2016.
46. Schulze A., Harris A.L. How cancer metabolism is tuned for proliferation and vulnerable to disruption). Nature 2012, 491:364-373.
47. Shao C., Shi X., White M., Huang Y., Hartshorn K., Zaia J. Comparative glycomics of leukocyte glycosaminoglycans. FEBS J. 2013, 280:2447-2461.
48. Silbert J.E., Sugumaran G. Biosynthesis of chondroitin/dermatan sulfate. IUBMB Life 2002, 54:177-186.
49. Silver D.J., Siebzehnrubl F.A., Schildts M.J., Yachnis A.T., Smith G.M., Smith A.A., Scheffler B., Reynolds B.A., Silver J., Steindler D.A. Chondroitin sulfate proteoglycans potently inhibit invasion and serve as a central organizer of the brain tumor microenvironment. J. Neurosci. 2013, 33:15603-15617.
50. Smetsers T.F., van de Westerlo E.M., ten Dam G.B., Overes I.M., Schalkwijk J., van Muijen G.N., van Kuppevelt T.H. Human single-chain antibodies reactive with native chondroitin sulfate detect chondroitin sulfate alterations in melanoma and psoriasis. J. Invest. Dermatol. 2004, 122:707-716.
51. Smyth G.K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 2004, 3:1-25.
52. Thacker B.E., Xu D., Lawrence R., Esko J.D. Heparan sulfate 3-O-sulfation: a rare modification in search of a function. Matrix Biol. 2014, 35:60-72.
53. Tibshirani R. Regression shrinkage and selection via the Lasso. J. R. Stat. Soc. B 1996, 58:267-288.
54. Ucakturk E., Akman O., Sun X., Baydar D.E., Dolgun A., Zhang F., Linhardt R.J. Changes in composition and sulfation patterns of glycoaminoglycans in renal cell carcinoma. Glycoconj. J. 2016, 33:103-112.
55. Vander Heiden M.G., Cantley L.C., Thompson C.B. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 2009, 324:1029-1033.
56. Väremo L., Nielsen J., Nookaew I. Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods. Nucleic Acids Res. 2013, 41:4378-4391.
57. Väremo L., Gatto F., Nielsen J. Kiwi: a tool for integration and visualization of network topology and gene-set analysis. BMC Bioinformatics 2014, 15:408.
58. Volpi N., Linhardt R.J. High-performance liquid chromatography-mass spectrometry for mapping and sequencing glycosaminoglycan-derived oligosaccharides. Nat. Protoc. 2010, 5:993-1004.
59. Volpi N., Maccari F. Composition of urinary glycosaminoglycans in a patient with pseudoxanthoma elasticum and familial Mediterranean fever. Clin. Chim. Acta 2005, 359:207-209.
60. Volpi N., Maccari F. Microdetermination of chondroitin sulfate in normal human plasma by fluorophore-assisted carbohydrate electrophoresis (FACE). Clin. Chim. Acta 2005, 356:125-133.
61. Volpi N., Galeotti F., Yang B., Linhardt R.J. Analysis of glycosaminoglycan-derived, precolumn, 2-aminoacridone-labeled disaccharides with LC-fluorescence and LC-MS detection. Nat. Protoc. 2014, 9:541-558.
62. Volpi N., Coppa G.V., Zampini L., Maccari F., Galeotti F., Garavelli L., Galeazzi T., Padella L., Santoro L., Gabrielli O. Plasmatic and urinary glycosaminoglycan profile in a patient affected by multiple sulfatase deficiency. Clin. Chem. Lab. Med. 2015, 53:e157-e160.
63. Wade A., Robinson A.E., Engler J.R., Petritsch C., James C.D., Phillips J.J. Proteoglycans and their roles in brain cancer. FEBS J. 2013, 280:2399-2417.
64. Wagenmakers E.-J., Farrell S. AIC model selection using Akaike weights. Psychon. Bull. Rev. 2004, 11:192-196.
65. Wahlgren T., Harmenberg U., Sandström P., Lundstam S., Kowalski J., Jakobsson M., Sandin R., Ljungberg B. Treatment and overall survival in renal cell carcinoma: a Swedish population-based study (2000-2008). Br. J. Cancer 2013, 108:1541-1549.
66. Wang Y., Roche O., Yan M.S., Finak G., Evans A.J., Metcalf J.L., Hast B.E., Hanna S.C., Wondergem B., Furge K.A., et al. Regulation of endocytosis via the oxygen-sensing pathway. Nat. Med. 2009, 15:319-324.
67. Ward P.S., Thompson C.B. Metabolic reprogramming: a cancer hallmark even warburg did not anticipate. Cancer Cell 2012, 21:297-308.