Tumor Biology

, Volume 35, Issue 8, pp 7369–7382 | Cite as

Tumor protein D52 (TPD52) and cancer—oncogene understudy or understudied oncogene?

  • Jennifer A. ByrneEmail author
  • Sarah Frost
  • Yuyan Chen
  • Robert K. Bright


The Tumor protein D52 (TPD52) gene was identified nearly 20 years ago through its overexpression in human cancer, and a substantial body of data now strongly supports TPD52 representing a gene amplification target at chromosome 8q21.13. This review updates progress toward understanding the significance of TPD52 overexpression and targeting, both in tumors known to be characterized by TPD52 overexpression/amplification, and those where TPD52 overexpression/amplification has been recently or variably reported. We highlight recent findings supporting microRNA regulation of TPD52 expression in experimental systems and describe progress toward deciphering TPD52’s cellular functions, particularly in cancer cells. Finally, we provide an overview of TPD52’s potential as a cancer biomarker and immunotherapeutic target. These combined studies highlight the potential value of genes such as TPD52, which are overexpressed in many cancer types, but have been relatively understudied.


TPD52 PrLZ CRHSP-28 Gene amplification Tumor antigen 



We would like to thank Drs Rameen Beroukhim [Dana-Faber Cancer Institute, USA], Susan Clark [Garvan Institute of Medical Research, Australia], Joaquin Espinosa [University of Colorado Boulder, USA], Charles Perou [University of North Carolina Chapel Hill, USA], Erdahl Teber [Children’s Medical Research Institute, Australia], and Kai Wang [Pfizer Inc, San Diego, USA] for advice, and Drs Karen Anderson [Arizona State University, USA], Sebastian Fussek and Uwe Zimmermann [University of Greifswald, Germany], and Rolf Renne [University of Florida, USA] for discussions. We also thank past and present group members and external collaborators for their support.

Conflicts of interest



  1. 1.
    Khleif SN, Doroshow JH, Hait WN, AACR-FDA-NCI Cancer Biomarkers Collaborative. AACR-FDA-NCI Cancer Biomarkers Collaborative consensus report: advancing the use of biomarkers in cancer drug development. Clin Cancer Res. 2010;16:3299–318. doi: 10.1158/1078-0432.CCR-10-0880.CrossRefGoogle Scholar
  2. 2.
    Kern SE. Why your new cancer biomarker may never work: recurrent patterns and remarkable diversity in biomarker failures. Cancer Res. 2012;72:6097–101. doi: 10.1158/0008-5472.CAN-12-3232.PubMedCentralCrossRefGoogle Scholar
  3. 3.
    Edwards AM, Isserlin R, Bader GD, Frye SV, Willson TM, Yu FH. Too many roads not taken. Nature. 2011;470:163–5. doi: 10.1038/470163a.CrossRefGoogle Scholar
  4. 4.
    Cheever MA, Allison JP, Ferris AS, Finn OJ, Hastings BM, Hecht TT, et al. The prioritization of cancer antigens: a national cancer institute pilot project for the acceleration of translational research. Clin Cancer Res. 2009;15:5323–37. doi: 10.1158/1078-0432.CrossRefGoogle Scholar
  5. 5.
    Wood LD, Parsons DW, Jones S, Lin J, Sjöblom T, Leary RJ, et al. The genomic landscapes of human breast and colorectal cancers. Science. 2007;318:1108–13.CrossRefGoogle Scholar
  6. 6.
    Lawrence MS, Stojanov P, Mermel CH, Robinson JT, Garraway LA, Golub TR, et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature. 2014;505:495–501. doi: 10.1038/nature12912.PubMedCentralCrossRefGoogle Scholar
  7. 7.
    Iyer G, Hanrahan AJ, Milowsky MI, Al-Ahmadie H, Scott SN, Janakiraman M, et al. Genome sequencing identifies a basis for everolimus sensitivity. Science. 2012;338:221. doi: 10.1126/science.1226344.PubMedCentralCrossRefGoogle Scholar
  8. 8.
    Boutros R, Fanayan S, Shehata M, Byrne JA. The tumor protein D52 family: many pieces, many puzzles. Biochem Biophys Res Commun. 2004;325:1115–21.CrossRefGoogle Scholar
  9. 9.
    Shehata M, Weidenhofer J, Thamotharampillai K, Hardy JR, Byrne JA. Tumor protein D52 overexpression and gene amplification in cancers from a mosaic of microarrays. Crit Rev Oncog. 2008;14:33–55.CrossRefGoogle Scholar
  10. 10.
    Byrne JA, Tomasetto C, Garnier JM, Rouyer N, Mattei MG, Bellocq JP, et al. A screening method to identify genes commonly overexpressed in carcinomas and the identification of a novel complementary DNA sequence. Cancer Res. 1995;55:2896–903.Google Scholar
  11. 11.
    Chen SL, Maroulakou IG, Green JE, Romano-Spica V, Modi W, Lautenberger J, et al. Isolation and characterization of a novel gene expressed in multiple cancers. Oncogene. 1996;12:741–51.Google Scholar
  12. 12.
    Parente JA, Goldenring JR, Petropoulos AC, Hellman U, Chew CS. Purification, cloning, and expression of a novel, endogenous, calcium-sensitive, 28-kDa phosphoprotein. J Biol Chem. 1996;271:20096–101.CrossRefGoogle Scholar
  13. 13.
    Groblewski GE, Wishart MJ, Yoshida M, Williams JA. Purification and identification of a 28-kDa calcium-regulated heat-stable protein. A novel secretagogue-regulated phosphoprotein in exocrine pancreas. J Biol Chem. 1996;271:31502–7.CrossRefGoogle Scholar
  14. 14.
    Proux V, Provot S, Felder-Schmittbuhl M-P, Laugier D, Calothy G, Marx M. Characterization of a leucine zipper-containing protein identified by retroviral insertion in avian neuroretina cells. J Biol Chem. 1996;271:30790–7.CrossRefGoogle Scholar
  15. 15.
    Shehata M, Bièche I, Boutros R, Weidenhofer J, Fanayan S, Spalding L, et al. Nonredundant functions for tumor protein D52-like proteins support specific targeting of TPD52. Clin Cancer Res. 2008;14:5050–60.CrossRefGoogle Scholar
  16. 16.
    Tennstedt P, Bölch C, Strobel G, Minner S, Burkhardt L, Grob T, et al. Patterns of TPD52 overexpression in multiple human solid tumor types analyzed by quantitative PCR. Int J Oncol. 2014;44:609–15. doi: 10.3892/ijo.2013.2200.Google Scholar
  17. 17.
    Roslan N, Bièche I, Bright RK, Lidereau R, Chen Y, Byrne JA. TPD52 represents a survival factor in ERBB2-amplified breast cancer cells. Mol. Carcinog. 2013.Google Scholar
  18. 18.
    Byrne JA, Chen Y, Martin La Rotta N, Peters GB. Challenges in identifying candidate amplification targets in human cancers: chromosome 8q21 as a case study. Genes Cancer. 2012;3:87–101.PubMedCentralCrossRefGoogle Scholar
  19. 19.
    Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490:61–70.CrossRefGoogle Scholar
  20. 20.
    Aure MR, Steinfeld I, Baumbusch LO, Liestøl K, Lipson D, Nyberg S, et al. Identifying in-trans process associated genes in breast cancer by integrated analysis of copy number and expression data. PLoS ONE. 2013;8:e53014. doi: 10.1371/journal.pone.0053014.PubMedCentralCrossRefGoogle Scholar
  21. 21.
    Guedj M, Marisa L, de Reynies A, Orsetti B, Schiappa R, Bibeau F, et al. A refined molecular taxonomy of breast cancer. Oncogene. 2012;31:1196–206.PubMedCentralCrossRefGoogle Scholar
  22. 22.
    Cornen S, Guille A, Adélaïde J, Addou-Klouche, Finetti P, Saade M-R, et al. Candidate luminal B breast cancer genes identified by genome, gene expression and DNA methylation profiling. PLOS One. 2014. doi: 10.1371/journal.pone.0081843.
  23. 23.
    Wilson KS, Roberts H, Leek R, Harris AL, Geradts J. Differential gene expression patterns in HER2/neu-positive and -negative breast cancer cell lines and tissues. Am J Pathol. 2002;161:1171–85.PubMedCentralCrossRefGoogle Scholar
  24. 24.
    Landis MD, Seachrist DD, Montanez-Wiscovich ME, Danielpour D, Keri RA. Gene expression profiling of cancer progression reveals intrinsic regulation of transforming growth factor-beta signaling in ErbB2/Neu-induced tumors from transgenic mice. Oncogene. 2005;24:5173–90.PubMedCentralCrossRefGoogle Scholar
  25. 25.
    Landis MD, Seachrist DD, Abdul-Karim FW, Keri RA. Sustained trophism of the mammary gland is sufficient to accelerate and synchronize development of ErbB2/Neu-induced tumors. Oncogene. 2006;25:3325–34.PubMedCentralCrossRefGoogle Scholar
  26. 26.
    Whiteaker JR, Zhang H, Zhao L, et al. Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer. J Proteome Res. 2007;6:3962–75.CrossRefGoogle Scholar
  27. 27.
    Chen H, Pimienta G, Gu Y, et al. Proteomic characterization of Her2/neu-overexpressing breast cancer cells. Proteomics. 2010;10:3800–10.CrossRefGoogle Scholar
  28. 28.
    Kourtidis A, Jain R, Carkner RD, Eifert C, Brosnan MJ, Conklin DS. An RNA interference screen identifies metabolic regulators NR1D1 and PBP as novel survival factors for breast cancer cells with the ERBB2 signature. Cancer Res. 2010;70:1783–92.PubMedCentralCrossRefGoogle Scholar
  29. 29.
    Haaland CM, Heaphy CM, Butler KS, Fischer EG, Griffith JK, Bisoffi M. Differential gene expression in tumor adjacent histologically normal prostatic tissue indicates field cancerization. Int J Oncol. 2009;35:537–46.Google Scholar
  30. 30.
    Ross AE, Marchionni L, Vuica-Ross M, Cheadle C, Fan J, Berman DM, et al. Gene expression pathways of high grade localized prostate cancer. Prostate. 2011;71:1568–77.Google Scholar
  31. 31.
    Nakagawa T, Kollmeyer TM, Morlan BW, Anderson SK, Bergstralh EJ, Davis BJ, et al. A tissue biomarker panel predicting systemic progression after PSA recurrence post-definitive prostate cancer therapy. PLoS ONE. 2008;3:e2318. doi: 10.1371/journal.pone.0002318.PubMedCentralCrossRefGoogle Scholar
  32. 32.
    Liu W, Xie CC, Thomas CY, Kim ST, Lindberg J, Egevad L, et al. Genetic markers associated with early cancer-specific mortality following prostatectomy. Cancer. 2013;119:2405–12. doi: 10.1002/cncr.27954.CrossRefGoogle Scholar
  33. 33.
    Chen SL, Zhang XK, Halverson DO, Byeon MK, Schweinfest CW, Ferris DK, et al. Characterization of human N8 protein. Oncogene. 1997;15:2577–88.CrossRefGoogle Scholar
  34. 34.
    Rohrbeck A, Neukirchen J, Rosskopf M, Pardillos GG, Geddert H, Schwalen A, et al. Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers. J Transl Med. 2008;6:69. doi: 10.1186/1479-5876-6-69.PubMedCentralCrossRefGoogle Scholar
  35. 35.
    Bangur CS, Switzer A, Fan L, Marton MJ, Meyer MR, Wang T. Identification of genes over-expressed in small cell lung carcinoma using suppression subtractive hybridization and cDNA microarray expression analysis. Oncogene. 2002;21:3814–25.CrossRefGoogle Scholar
  36. 36.
    Ziv T, Barnea E, Segal H, Sharon R, Beer I, Admon A. Comparative proteomics of small cell lung carcinoma. Cancer Biomark. 2006;2:219–34.Google Scholar
  37. 37.
    Boelens MC, van den Berg A, Fehrmann RS, Geerlings M, de Jong WK, te Meerman GJ, et al. Current smoking-specific gene expression signature in normal bronchial epithelium is enhanced in squamous cell lung cancer. J Pathol. 2009;218:182–91. doi: 10.1002/path.2520.CrossRefGoogle Scholar
  38. 38.
    Hanada S, Kakehashi A, Nishiyama N, Wei M, Yamano S, Chung K, et al. Myristoylated alanine-rich C-kinase substrate as a prognostic biomarker in human primary lung squamous cell carcinoma. Cancer Biomark. 2013;13:289–98. doi: 10.3233/CBM-130354.Google Scholar
  39. 39.
    Zhang H, Liu Q, Zimmerman LJ, Ham AJ, Slebos RJ, Rahman J, et al. Methods for peptide and protein quantitation by liquid chromatography-multiple reaction monitoring mass spectrometry. Mol Cell Proteomics. 2011;10:M110.006593. doi: 10.1074/mcp.M110.006593.PubMedCentralCrossRefGoogle Scholar
  40. 40.
    Spira A, Beane JE, Shah V, Steiling K, Liu G, Schembri F, et al. Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer. Nat Med. 2007;13:361–6.CrossRefGoogle Scholar
  41. 41.
    Zhao P, Zhong W, Ying X, Yao B, Yuan Z, Fu J, et al. Comparative proteomic analysis of anti-benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide-transformed and normal human bronchial epithelial G0/G1 cells. Chem Biol Interact. 2010;186:166–73.CrossRefGoogle Scholar
  42. 42.
    Weir BA, Woo MS, Getz G, Perner S, Ding L, Beroukhim R, et al. Characterizing the cancer genome in lung adenocarcinoma. Nature. 2007;450:893–8.PubMedCentralCrossRefGoogle Scholar
  43. 43.
    Marescalco MS, Capizzi C, Condorelli DF, Barresi V. Genome-wide analysis of recurrent copy-number alterations and copy-neutral loss of heterozygosity in head and neck squamous cell carcinoma. J Oral Pathol Med. 2013. doi: 10.1111/jop.12087.Google Scholar
  44. 44.
    Cheng L, Wang P, Yang S, Yang Y, Zhang Q, Zhang W, et al. Identification of genes with a correlation between copy number and expression in gastric cancer. BMC Med Genomics. 2012;5:14. doi: 10.1186/1755-8794-5-14.PubMedCentralCrossRefGoogle Scholar
  45. 45.
    Aquino PF, Fischer JS, Neves-Ferreira AG, Perales J, Domont GB, Araujo GD, et al. Are gastric cancer resection margin proteomic profiles more similar to those from controls or tumors? J Proteome Res. 2012;11:5836–42. doi: 10.1021/pr300612x.Google Scholar
  46. 46.
    Williams TA, Monticone S, Morello F, Liew CC, Mengozzi G, Pilon C, et al. Teratocarcinoma-derived growth factor-1 is upregulated in aldosterone-producing adenomas and increases aldosterone secretion and inhibits apoptosis in vitro. Hypertension. 2010;55:1468–75. doi: 10.1161/HYPERTENSIONAHA.110.150318.CrossRefGoogle Scholar
  47. 47.
    Herbet M, Salomon A, Feige JJ, Thomas M. Acquisition order of Ras and p53 gene alterations defines distinct adrenocortical tumor phenotypes. PLoS Genet. 2012;8:e1002700. doi: 10.1371/journal.pgen.1002700.PubMedCentralCrossRefGoogle Scholar
  48. 48.
    Ozaki T, Paulussen M, Poremba C, Brinkschmidt C, Rerin J, Ahrens S, et al. Genetic imbalances revealed by comparative genomic hybridization in Ewing tumors. Gene Chromosome Cancer. 2001;32:164–71.CrossRefGoogle Scholar
  49. 49.
    Stock C, Kager L, Fink FM, Gadner H, Ambros PF. Chromosomal regions involved in the pathogenesis of osteosarcomas. Genes Chromosomes Cancer. 2000;28:329–36.CrossRefGoogle Scholar
  50. 50.
    Monzon FA, Lyons-Weiler M, Buturovic LJ, Rigl CT, Henner WD, Sciulli C, et al. Multicenter validation of a 1,550-gene expression profile for identification of tumor tissue of origin. J Clin Oncol. 2009;27:2503–8. doi: 10.1200/JCO.2008.17.9762.CrossRefGoogle Scholar
  51. 51.
    Machado I, López-Guerrero JA, Calabuig-Fariñas S, Hardy JR, Scotlandi K, Picci P, et al. Clinical significance of tumor protein D52 immunostaining in a large series of Ewing’s sarcoma family of tumors. Pediatr Dev Pathol. 2011;14:255–6. doi: 10.2350/11-01-0956-LET.1.CrossRefGoogle Scholar
  52. 52.
    Li G, Cai Z, Zhang Y, Ru M, Ji F. Screening for pathogenesis-related genes of osteosarcoma using gene microarray. Chin J Cancer Biother. 2007;14:428–34.Google Scholar
  53. 53.
    Zou C, Shen J, Tang Q, Yang Z, Yin J, Li Z, et al. Cancer-testis antigens expressed in osteosarcoma identified by gene microarray correlate with a poor patient prognosis. Cancer. 2012;118:1845–55. doi: 10.1002/cncr.26486.CrossRefGoogle Scholar
  54. 54.
    Flores RJ, Li Y, Yu A, Shen J, Rao PH, Lau SS, et al. A systems biology approach reveals common metastatic pathways in osteosarcoma. BMC Syst Biol. 2012;6:50. doi: 10.1186/1752-0509-6-50.PubMedCentralCrossRefGoogle Scholar
  55. 55.
    Mohseny AB, Machado I, Cai Y, Schaefer KL, Serra M, Hogendoorn PC, et al. Functional characterization of osteosarcoma cell lines provides representative models to study the human disease. Lab Investig. 2011;91:1195–205. doi: 10.1038/labinvest.2011.72.CrossRefGoogle Scholar
  56. 56.
    Machado I, Alberghini M, Giner F, Corrigan M, O’Sullivan M, Noguera R, et al. Histopathological characterization of small cell osteosarcoma with immunohistochemistry and molecular genetic support. A study of 10 cases. Histopathology. 2010;57:162–7.CrossRefGoogle Scholar
  57. 57.
    Barbaric D, Byth K, Dalla-Pozza L, Byrne JA. Expression of tumor protein D52-like genes in childhood leukemia at diagnosis: clinical and sample considerations. Leuk Res. 2006;30:1355–63.CrossRefGoogle Scholar
  58. 58.
    Kang H, Wilson CS, Harvey RC, Chen IM, Murphy MH, Atlas SR, et al. Gene expression profiles predictive of outcome and age in infant acute lymphoblastic leukemia: a Children’s Oncology Group study. Blood. 2012;119:1872–81. doi: 10.1182/blood-2011-10-382861.PubMedCentralCrossRefGoogle Scholar
  59. 59.
    Mattison J, Kool J, Uren AG, de Ridder J, Wessels L, Jonkers J, et al. Novel candidate cancer genes identified by a large-scale cross-species comparative oncogenomics approach. Cancer Res. 2010;70:883–95.PubMedCentralCrossRefGoogle Scholar
  60. 60.
    Zack TI, Schumacher SE, Carter SL, Cherniack AD, Saksena G, Tabak B, et al. Pan-cancer patterns of somatic copy number alteration. Nat Genet. 2013;45:1134–40. doi: 10.1038/ng.2760.CrossRefGoogle Scholar
  61. 61.
    Bert SA, Robinson MD, Strbenac D, Statham AL, Song JZ, Hulf T, et al. Regional activation of the cancer genome by long-range epigenetic remodeling. Cancer Cell. 2013;23:9–22. doi: 10.1016/j.ccr.2012.11.006.CrossRefGoogle Scholar
  62. 62.
    Wang K, Lim HY, Shi S, Lee J, Deng S, Xie T, et al. Genomic landscape of copy number aberrations enables the identification of oncogenic drivers in hepatocellular carcinoma. Hepatology. 2013;58:706–17. doi: 10.1002/hep.26402.CrossRefGoogle Scholar
  63. 63.
    March HN, Rust AG, Wright NA, ten Hoeve J, de Ridder J, Eldridge M, et al. Insertional mutagenesis identifies multiple networks of cooperating genes driving intestinal tumorigenesis. Nat Genet. 2011;43:1202–9. doi: 10.1038/ng.990.PubMedCentralCrossRefGoogle Scholar
  64. 64.
    Gottwein E, Corcoran DL, Mukherjee N, Skalsky RL, Hafner M, Nusbaum JD, et al. Viral microRNA targetome of KSHV-infected primary effusion lymphoma cell lines. Cell Host Microbe. 2011;10:515–26. doi: 10.1016/j.chom.2011.09.012.PubMedCentralCrossRefGoogle Scholar
  65. 65.
    Haecker I, Gay LA, Yang Y, Hu J, Morse AM, McIntyre LM, et al. Ago HITS-CLIP expands understanding of Kaposi’s sarcoma-associated herpesvirus miRNA function in primary effusion lymphomas. PLoS Pathog. 2012;8:e1002884. doi: 10.1371/journal.ppat.1002884.PubMedCentralCrossRefGoogle Scholar
  66. 66.
    Takahashi Y, Forrest AR, Maeno E, Hashimoto T, Daub CO, Yasuda J. MiR-107 and MiR-185 can induce cell cycle arrest in human non-small cell lung cancer cell lines. PLoS ONE. 2009;4:e6677. doi: 10.1371/journal.pone.0006677.PubMedCentralCrossRefGoogle Scholar
  67. 67.
    Kaller M, Liffers ST, Oeljeklaus S, Kuhlmann K, Röh S, Hoffmann R, et al. Genome-wide characterization of miR-34a induced changes in protein and mRNA expression by a combined pulsed SILAC and microarray analysis. Mol Cell Proteomics. 2011;10:M111.010462. doi: 10.1074/mcp.M111.010462.PubMedCentralCrossRefGoogle Scholar
  68. 68.
    Bader AG. miR-34—a microRNA replacement therapy is headed to the clinic. Front Genet. 2012;3:120. doi: 10.3389/fgene.2012.00120.PubMedCentralCrossRefGoogle Scholar
  69. 69.
    Templin T, Paul S, Amundson SA, Young EF, Barker CA, Wolden SL, et al. Radiation-induced micro-RNA expression changes in peripheral blood cells of radiotherapy patients. Int J Radiat Oncol Biol Phys. 2011;80:549–57. doi: 10.1016/j.ijrobp.2010.12.061.PubMedCentralCrossRefGoogle Scholar
  70. 70.
    Ummanni R, Teller S, Junker H, Zimmermann U, Venz S, Scharf C, et al. Altered expression of tumor protein D52 regulates apoptosis and migration of prostate cancer cells. FEBS J. 2008;275:5703–13.CrossRefGoogle Scholar
  71. 71.
    Zhang H, Wang J, Pang B, Liang RX, Li S, Huang PT, et al. PC-1/PrLZ contributes to malignant progression in prostate cancer. Cancer Res. 2007;67:8906–13.CrossRefGoogle Scholar
  72. 72.
    Zhang D, He D, Xue Y, Wang R, Wu K, Xie H, et al. PrLZ protects prostate cancer cells from apoptosis induced by androgen deprivation via the activation of Stat3/Bcl-2 pathway. Cancer Res. 2011;71:2193–202.PubMedCentralCrossRefGoogle Scholar
  73. 73.
    Li L, Zhang D, Zhang L, Zhu G, Sun Y, Wu K, et al. PrLZ expression is associated with the progression of prostate cancer LnCaP cells. Mol Carcinog. 2009;48:432–40.CrossRefGoogle Scholar
  74. 74.
    Li L, Xie H, Liang L, Gao Y, Zhang D, Fang L, et al. Increased PrLZ-mediated androgen receptor transactivation promotes prostate cancer growth at castration-resistant stage. Carcinogenesis. 2013;34:257–67. doi: 10.1093/carcin/bgs337.PubMedCentralCrossRefGoogle Scholar
  75. 75.
    Lewis JD, Payton LA, Whitford JG, Byrne JA, Smith DI, Yang L, et al. Induction of tumorigenesis and metastasis by the murine orthologue of tumor protein D52. Mol Cancer Res. 2007;5:133–44.CrossRefGoogle Scholar
  76. 76.
    Sullivan KD, Padilla-Just N, Henry RE, Porter CC, Kim J, Tentler JJ, et al. ATM and MET kinases are synthetic lethal with nongenotoxic activation of p53. Nat Chem Biol. 2012;8:646–54. doi: 10.1038/nchembio.965.PubMedCentralCrossRefGoogle Scholar
  77. 77.
    Sims AH, Finnon P, Miller CJ, Bouffler SD, Howell A, Scott D, et al. TPD52 and NFKB1 gene expression levels correlate with G2 chromosomal radiosensitivity in lymphocytes of women with and at risk of hereditary breast cancer. Int J Radiat Biol. 2007;83(6):409–20.CrossRefGoogle Scholar
  78. 78.
    Niu N, Qin Y, Fridley BL, Hou J, Kalari KR, Zhu M, et al. Radiation pharmacogenomics: a genome-wide association approach to identify radiation response biomarkers using human lymphoblastoid cell lines. Genome Res. 2010;20:1482–92. doi: 10.1101/gr.107672.110.PubMedCentralCrossRefGoogle Scholar
  79. 79.
    Adamson B, Smogorzewska A, Sigoillot FD, King RW, Elledge SJ. A genome-wide homologous recombination screen identifies the RNA-binding protein RBMX as a component of the DNA-damage response. Nat Cell Biol. 2012;14:318–28. doi: 10.1038/ncb2426.PubMedCentralCrossRefGoogle Scholar
  80. 80.
    Chen Y, Kamili A, Hardy JR, Groblewski GE, Khanna KK, Byrne JA. Tumor protein D52 represents a negative regulator of ATM protein levels. Cell Cycle. 2013;12:3083–97. doi: 10.4161/cc.26146.CrossRefGoogle Scholar
  81. 81.
    Kaspar KM, Thomas DD, Taft WB, Takeshita E, Weng N, Groblewski GE. CaM kinase II regulation of CRHSP-28 phosphorylation in cultured mucosal T84 cells. Am J Physiol Gastrointest Liver Physiol. 2003;285:G1300–9.Google Scholar
  82. 82.
    Chew CS, Chen X, Zhang H, Berg EA, Zhang H. Calcium/calmodulin-dependent phosphorylation of tumor protein D52 on serine residue 136 may be mediated by CAMK2delta6. Am J Physiol Gastrointest Liver Physiol. 2008;295:G1159–72.PubMedCentralCrossRefGoogle Scholar
  83. 83.
    Thomas DD, Martin CL, Weng N, Byrne JA, Groblewski GE. Tumor protein D52 expression and Ca2+-dependent phosphorylation modulates lysosomal membrane protein trafficking to the plasma membrane. Am J Physiol Cell Physiol. 2010;298:C725–39.PubMedCentralCrossRefGoogle Scholar
  84. 84.
    Messenger SW, Thomas DD, Falkowski MA, Byrne JA, Gorelick FS, Groblewski GE. Tumor protein D52 controls trafficking of an apical endolysosomal secretory pathway in pancreatic acinar cells. Am J Physiol Gastrointest Liver Physiol. 2013;305:G439–52.CrossRefGoogle Scholar
  85. 85.
    Polanski M, Anderson NL. A list of candidate cancer biomarkers for targeted proteomics. Biomark Insights. 2007;1:1–48.PubMedCentralGoogle Scholar
  86. 86.
    Whiteaker JR, Zhao L, Anderson L, Paulovich AG. An automated and multiplexed method for high throughput peptide immunoaffinity enrichment and multiple reaction monitoring mass spectrometry-based quantification of protein biomarkers. Mol Cell Proteomics. 2010;9:184–96.PubMedCentralCrossRefGoogle Scholar
  87. 87.
    Hüttenhain R, Soste M, Selevsek N, Röst H, Sethi A, Carapito C, et al. Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics. Sci Transl Med. 2012;4:142ra94. doi: 10.1126/scitranslmed.3003989.PubMedCentralCrossRefGoogle Scholar
  88. 88.
    Caron M, Choquet-Kastylevsky G, Joubert-Caron R. Cancer immunomics using autoantibody signatures for biomarker discovery. Mol Cell Proteomics. 2007;6:1115–22.CrossRefGoogle Scholar
  89. 89.
    Pedersen JW, Wandall HH. Autoantibodies as biomarkers in cancer. Lab Med. 2011;42:623–8.CrossRefGoogle Scholar
  90. 90.
    Scanlan MJ, Gout I, Gordon CM, Williamson B, Stockert E, Gure AO, et al. Humoral immunity to human breast cancer: antigen definition and quantitative analysis of mRNA expression. Cancer Immun. 2001;1:4.Google Scholar
  91. 91.
    Anderson KS, Sibani S, Wallstrom G, Qiu J, Mendoza EA, Raphael J, et al. Protein microarray signature of autoantibody biomarkers for the early detection of breast cancer. J Proteome Res. 2011;10:85–96. doi: 10.1021/pr100686b.PubMedCentralCrossRefGoogle Scholar
  92. 92.
    Wang J, Barker K, Steel J, Park J, Saul J, Festa F, et al. A versatile protein microarray platform enabling antibody profiling against denatured proteins. Proteomics Clin Appl. 2013;7:378–83. doi: 10.1002/prca.201200062.PubMedCentralCrossRefGoogle Scholar
  93. 93.
    Mayer-Sonnenfeld T, Har-Noy M, Lillehei KO, Graner MW. Proteomic analyses of different human tumor-derived chaperone-rich cell lysate (CRCL) anti-cancer vaccines reveal antigen content and strong similarities amongst the vaccines along with a basis for CRCL’s unique structure: CRCL vaccine proteome leads to unique structure. Int J Hyperthermia. 2013;29:520–7. doi: 10.3109/02656736.2013.796529.CrossRefGoogle Scholar
  94. 94.
    Payton LA, Lewis JD, Byrne JA, Bright RK. Vaccination with metastasis-related tumor associated antigen TPD52 and CpG/ODN induces protective tumor immunity. Cancer Immunol Immunother. 2008;57:799–811.CrossRefGoogle Scholar
  95. 95.
    Bright JD, Schultz HN, Byrne JA, Bright RK. Injection site and regulatory T cells influence durable vaccine-induced tumor immunity to an over-expressed self tumor associated antigen. Oncoimmunology. 2013;2:e25049.PubMedCentralCrossRefGoogle Scholar
  96. 96.
    Lewis JD, Sullivan LA, Byrne JA, de Riese W, Bright RK. Memory and cellular immunity induced by a DNA vaccine encoding self antigen TPD52 administered with soluble GM-CSF. Cancer Immunol Immunother. 2009;58:1337–49.CrossRefGoogle Scholar
  97. 97.
    Bright JD, Aldrich JF, Byrne JA, Bright RK. Vaccination with the prostate cancer over-expressed tumor self-protein TPD52 elicits protective tumor immunity and a potentially unique subset of CD8+ T cells. Austin J Clin Immunol. 2014, in press.Google Scholar
  98. 98.
    Mirshahidi S, Kramer VG, Whitney JB, Essono S, Lee S, Dranoff G, et al. Overlapping synthetic peptides encoding TPD52 as breast cancer vaccine in mice: prolonged survival. Vaccine. 2009;27:1825–33.CrossRefGoogle Scholar

Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2014

Authors and Affiliations

  • Jennifer A. Byrne
    • 1
    • 2
    Email author
  • Sarah Frost
    • 1
    • 2
  • Yuyan Chen
    • 1
    • 2
  • Robert K. Bright
    • 3
  1. 1.Molecular Oncology Laboratory, Children’s Cancer Research Unit, Kids Research InstituteThe Children’s Hospital at WestmeadWestmeadAustralia
  2. 2.The University of Sydney Discipline of Paediatrics and Child Health, The Children’s Hospital at WestmeadWestmeadAustralia
  3. 3.Department of Immunology and Molecular Microbiology and TTUHSC Cancer CenterTexas Tech University Health Sciences CenterLubbockUSA

Personalised recommendations