A systematic review of proteomic biomarkers associated with risk stratification in pediatric acute lymphoblastic leukemia
Archives of Advances in Biosciences,
Vol. 9 No. 1 (2018),
25 December 2017
,
Page 50-55
https://doi.org/10.22037/jps.v9i1.13763
Abstract
Risk-based therapy protocols have dramatically improved survival rates in more than 80% of childhood acute lymphoblastic leukemia (chALL). Prognostic biomarkers could be valuable for predicting the relapsed ALL patients and may therefore contribute to improving ALL outcome. Presently, there are little data on the role of prognostic biomarkers in the risk stratification of ALL. The aim of the present systematic review is to survey the identified prognostic biomarkers of chALL. In this study, protein-protein interaction of identified biomarkers was evaluated to reveal the biological pathways related to high risk chALL. To pursue this goal, firstly all relevant studies were collected through the PubMed and Google Scholar databases with no restrictions. Then, the biomarkers of high risk patients were recorded and finally protein-protein interaction of biomarkers was analyzed through using the STRING database. After screening 82 abstracts, three studies were included with 36 high risk and 33 low risk B-ALL participants. Totally, 142 biomarkers were investigated in this study. Protein interaction network analysis of biomarkers revealed two main pathways, namely ribosome and spliceosome. Dysregulation of two key pathways, ribosome and spliceosome can be associated with the high risk phenotype of childhood acute lymphoblastic leukemia.
- Acute lymphoblastic leukemia
- Prognostic biomarker
- Ribosome pathway
- Spliceosome pathway
How to Cite
References
Kaspers GJ, Pieters R, Klumper E, de Waal FC, Veerman AJ. The treatment of recurrence in children with acute lymphatic leukemia. Current results and various developments. Tijdschr Kindergeneeskd. 1993: 6: 1-7
Dobson S, Waanders E, Grandal I, Gan O, McLeod J, Minden M, et al. Evolving heterogeneity in acute lymphoblastic leukemia. Exp. Hematol. 2014; 42: S31.
Pui CH, Carroll WL, Meshinchi S, Arceci RJ. Biology, risk stratification, and therapy of pediatric acute leukemias: an update. J Clin Oncol. 2011; 29: 551–565.
Geng H, Brennan S, Milne TA, Chen WY, Li Y, Hurtz C, et al. Integrative epigenomic analysis identifies biomarkers and therapeutic targets in adult B-acute lymphoblastic leukemia. Cancer Discov. 2012; 2: 1004–1023.
Felip E, Martinez P. Can sensitivity to cytotoxic chemotherapy be predicted by biomarkers? Annals of oncology. 2012; 23: 189-92.
Campana D. Minimal residual disease in acute lymphoblastic leukemia. Hematology Am Soc Hematol Educ Program. 2010; 2010: 7-12.
Coustan-Smith E, Song G, Clark C, Key L, Liu P, Mehrpooya M, et al. New markers for minimal residual disease detection in acute lymphoblastic leukemia. Blood. 2011; 117: 6267–6276.
Neale GAM, Coustan-Smith E, Stow P, Pan Q, Chen X. Pui CH, Campana D. Comparative analysis of flow cytometry and polymerase chain reaction for the detection of minimal residual disease in childhood acute lymphoblastic leukemia. Leukemia. 2004; 18: 934–938
López V, Elena W, Duojiao C, William C, Madero L, Wang X. Proteomics-based discovery of biomarkers for paediatric acute lymphoblastic leukaemia: challenges and opportunities. J Cell Mol Med. 2014; 18: 1239–1246.
Huang CJ, Yang SH, Lee CL, Cheng YC, Tai SY, Chien CC. Ribosomal proteinS27-like in colorectal cancer: a candidate for predicting prognoses. PLoS One. 2013; 24: e67043.
Goudarzi KM, Lindström MS. Role of ribosomal protein mutations in tumor development (Review). Int J Oncol. 2016; 48: 1313-24.
De Keersmaecker K, Atak ZK, Li N, Vicente C, Patchett S, Girardi T, et al. Exome sequencing identifies mutation in CNOT3 and ribosomal genes RPL5 and RPL10 in T-cell acute lymphoblastic leukemia. Nat Genet. 2013; 45: 186-90.
Chen J, Wei Y, Feng Q, Ren L, He G, Chang W, et al. Ribosomal protein S15A promotes malignant transformation and predicts poor outcome in colorectal cancer through misregulation of p53 signaling pathway. Int J Oncol. 2016; 48: 1628-38.
Yong WH, Shabihkhani M, Telesca D, Yang S, Tso JL, Menjivar JC, et al. Ribosomal Proteins RPS11 and RPS20, Two Stress-Response Markers of Glioblastoma Stem Cells, Are Novel Predictors of Poor Prognosis in Glioblastoma Patients. PLoS One. 2015; 27: e0141334.
Yan TT, Fu XL, Li J, Bian YN, Liu DJ, Hua R, et al. Downregulation of RPL15 may predict poor survival and associate with tumor progression in pancreatic ductal adenocarcinoma. Oncotarget. 2015; 10: 37028-42.
Tsofack SP, Meunier L, Sanchez L, Madore J, Provencher D, Mes-Masson AM, Lebel M. Low expression of the X-linked ribosomal protein S4 in human serous epithelial ovarian cancer is associated with a poor prognosis. BMC Cancer. 2013; 22: 303.
Yoshida S, Matsumoto K, Arao T, Taniguchi H, Goto I, Hanafusa T, Nishio K, Yamada Y. Gene amplification of ribosomal protein S6 kinase-1 and -2 in gastric cancer. Anticancer Res. 2013; 33: 469-75.
Adamia S, Haibe-Kains B, Pilarski PM, Bar-Natan M, Pevzner S, Avet-Loiseau H, et al. A genome-wide aberrant RNA splicing in patients with acute myeloid leukemia identifies novel potential disease markers and therapeutic targets. Clin Cancer Res. 2014; 1: 1135-45.
Hou HA, Liu CY, Kuo YY, Chou WC, Tsai CH, Lin CC, et al. Splicing factor mutations predict poor prognosis in patients with de novo acute myeloid leukemia. Oncotarget. 2016; 23: 9084-101.
Kashyap MK, Kumar D, Villa R, La Clair JJ, Benner C, Sasik R, et al. Targeting the spliceosome in chronic lymphocytic leukemia with the macrolides FD-895 and pladienolide-B. Haematologica. 2015;100: 945-54.
Larrayoz M, Blakemore SJ, Dobson RC, Blunt MD, Rose-Zerilli MJ, Walewska R, et al. The SF3B1 inhibitor spliceostatin A (SSA) elicitsapoptosis in chronic lymphocytic leukaemia cells through downregulation of Mcl-1. Leukemia. 2016; 30: 351-60.
Lo TC, Barnhill LM, Kim Y, Nakae EA, Yu AL, Diccianni MB. Inactivation of SHIP1 in T-cell acute lymphoblastic leukemia due to mutation and extensive alternative splicing. Leuk Res. 2009; 33: 1562-6.
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