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Protein biomarkers distinguish between high- and low-risk pediatric acute lymphoblastic leukemia in a tissue specific manner.

Braoudaki M, Lambrou GI, Vougas K, Karamolegou K, Tsangaris GT, Tzortzatou-Stathopoulou F - J Hematol Oncol (2013)

Bottom Line: Cytogenetic analysis was carried out by G- banding and interphase fluorescent in situ hybridization.Differential proteomic analysis was performed using two-dimensional gel electrophoresis and protein identification by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.The differential expression of certain proteins was confirmed by Western blot analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: First Department of Pediatrics, University of Athens Medical School, Choremeio Research Laboratory, Thivon & Levadias 11527 Goudi-Athens, Greece.

ABSTRACT
The current study evaluated the differential expression detected in the proteomic profiles of low risk- and high risk- ALL pediatric patients to characterize candidate biomarkers related to diagnosis, prognosis and patient targeted therapy. Bone marrow and peripheral blood plasma and cell lysates samples were obtained from pediatric patients with low- (LR) and high-risk (HR) ALL at diagnosis. As controls, non-leukemic pediatric patients were studied. Cytogenetic analysis was carried out by G- banding and interphase fluorescent in situ hybridization. Differential proteomic analysis was performed using two-dimensional gel electrophoresis and protein identification by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The differential expression of certain proteins was confirmed by Western blot analysis. The obtained data revealed that CLUS, CERU, APOE, APOA4, APOA1, GELS, S10A9, AMBP, ACTB, CATA and AFAM proteins play a significant role in leukemia prognosis, potentially serving as distinctive biomarkers for leukemia aggressiveness, or as suppressor proteins in HR-ALL cases. In addition, vitronectin and plasminogen probably contributed to leukemogenesis, whilst bicaudal D-related protein 1 could afford a significant biomarker for pediatric ALL therapeutics.

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Kaplan-Meier survival analysis. A: Overall survival curves of patients according to APOA1, CERU, FIBB, FIBG, IGHG1, IGHG2, S10A9, SAA, TTHY, A2MG, APOA1, ACTB, CATA, CERU, FIBB, FIBG, HPT, HEMO, IGHG1, S10A9 (p<0.01); Survival rates between: B: males and females; C: low- and high-risk cases; D:TEL/AML1 positive and negative patients; E:BCR/ABL positive and negative patients; F:MLL positive and negative patients; G: MRD positive and negative patients; H: CNS positive and negative patients; I: Indicatevely, a survival curve for the ACTB protein, which did not manifest significant differences in survival rates. The same was true for all proteins under study.
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Figure 8: Kaplan-Meier survival analysis. A: Overall survival curves of patients according to APOA1, CERU, FIBB, FIBG, IGHG1, IGHG2, S10A9, SAA, TTHY, A2MG, APOA1, ACTB, CATA, CERU, FIBB, FIBG, HPT, HEMO, IGHG1, S10A9 (p<0.01); Survival rates between: B: males and females; C: low- and high-risk cases; D:TEL/AML1 positive and negative patients; E:BCR/ABL positive and negative patients; F:MLL positive and negative patients; G: MRD positive and negative patients; H: CNS positive and negative patients; I: Indicatevely, a survival curve for the ACTB protein, which did not manifest significant differences in survival rates. The same was true for all proteins under study.

Mentions: The OS was estimated at 88.8%. A two-tailed t-test was used to determine the significance in protein expression levels between alive and deceased patients (Figure 8A). OS was found significant regarding APOA1, CERU, FIBB, FIBG, IGHG1, IGHG2, S10A9, SAA, TTHY, A2MG, APOA1, ACTB, CATA, CERU, FIBB, FIBG, HPT, HEMO, IGHG1, and S10A9 molecules (p < 0.01). Therefore, these proteins might play a significant role in leukemia progression and outcome. Additionally, BCR/ABL proved to manifest significant difference with respect to survival (Figure 8E). The rest of the clinical factors did not present significant differences with respect to OS. However, individual proteins did not manifest significant results concerning the survival of leukemic patients, which supports the hypothesis that it is not the effect of an isolated protein, but rather the coordinated regulatory network of proteins. Although OS did not appear to be dependent on individual protein levels, the fact that several proteins are differentially expressed between alive and deceased patients points towards this very fact: it is the result of a network and combination of functions as to leukemia outcome. This raises the possibility that oncogenesis is multifactorial. OS rates have been calculated as the percentage of alive or deceased patients from the day of diagnosis to the present day. In addition, LFS showed more significant confidence levels than OS, yet none of the clinicopathological factors appeared to influence significantly (p < 0.05) the LFS rates (data not shown).


Protein biomarkers distinguish between high- and low-risk pediatric acute lymphoblastic leukemia in a tissue specific manner.

Braoudaki M, Lambrou GI, Vougas K, Karamolegou K, Tsangaris GT, Tzortzatou-Stathopoulou F - J Hematol Oncol (2013)

Kaplan-Meier survival analysis. A: Overall survival curves of patients according to APOA1, CERU, FIBB, FIBG, IGHG1, IGHG2, S10A9, SAA, TTHY, A2MG, APOA1, ACTB, CATA, CERU, FIBB, FIBG, HPT, HEMO, IGHG1, S10A9 (p<0.01); Survival rates between: B: males and females; C: low- and high-risk cases; D:TEL/AML1 positive and negative patients; E:BCR/ABL positive and negative patients; F:MLL positive and negative patients; G: MRD positive and negative patients; H: CNS positive and negative patients; I: Indicatevely, a survival curve for the ACTB protein, which did not manifest significant differences in survival rates. The same was true for all proteins under study.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3717072&req=5

Figure 8: Kaplan-Meier survival analysis. A: Overall survival curves of patients according to APOA1, CERU, FIBB, FIBG, IGHG1, IGHG2, S10A9, SAA, TTHY, A2MG, APOA1, ACTB, CATA, CERU, FIBB, FIBG, HPT, HEMO, IGHG1, S10A9 (p<0.01); Survival rates between: B: males and females; C: low- and high-risk cases; D:TEL/AML1 positive and negative patients; E:BCR/ABL positive and negative patients; F:MLL positive and negative patients; G: MRD positive and negative patients; H: CNS positive and negative patients; I: Indicatevely, a survival curve for the ACTB protein, which did not manifest significant differences in survival rates. The same was true for all proteins under study.
Mentions: The OS was estimated at 88.8%. A two-tailed t-test was used to determine the significance in protein expression levels between alive and deceased patients (Figure 8A). OS was found significant regarding APOA1, CERU, FIBB, FIBG, IGHG1, IGHG2, S10A9, SAA, TTHY, A2MG, APOA1, ACTB, CATA, CERU, FIBB, FIBG, HPT, HEMO, IGHG1, and S10A9 molecules (p < 0.01). Therefore, these proteins might play a significant role in leukemia progression and outcome. Additionally, BCR/ABL proved to manifest significant difference with respect to survival (Figure 8E). The rest of the clinical factors did not present significant differences with respect to OS. However, individual proteins did not manifest significant results concerning the survival of leukemic patients, which supports the hypothesis that it is not the effect of an isolated protein, but rather the coordinated regulatory network of proteins. Although OS did not appear to be dependent on individual protein levels, the fact that several proteins are differentially expressed between alive and deceased patients points towards this very fact: it is the result of a network and combination of functions as to leukemia outcome. This raises the possibility that oncogenesis is multifactorial. OS rates have been calculated as the percentage of alive or deceased patients from the day of diagnosis to the present day. In addition, LFS showed more significant confidence levels than OS, yet none of the clinicopathological factors appeared to influence significantly (p < 0.05) the LFS rates (data not shown).

Bottom Line: Cytogenetic analysis was carried out by G- banding and interphase fluorescent in situ hybridization.Differential proteomic analysis was performed using two-dimensional gel electrophoresis and protein identification by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.The differential expression of certain proteins was confirmed by Western blot analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: First Department of Pediatrics, University of Athens Medical School, Choremeio Research Laboratory, Thivon & Levadias 11527 Goudi-Athens, Greece.

ABSTRACT
The current study evaluated the differential expression detected in the proteomic profiles of low risk- and high risk- ALL pediatric patients to characterize candidate biomarkers related to diagnosis, prognosis and patient targeted therapy. Bone marrow and peripheral blood plasma and cell lysates samples were obtained from pediatric patients with low- (LR) and high-risk (HR) ALL at diagnosis. As controls, non-leukemic pediatric patients were studied. Cytogenetic analysis was carried out by G- banding and interphase fluorescent in situ hybridization. Differential proteomic analysis was performed using two-dimensional gel electrophoresis and protein identification by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The differential expression of certain proteins was confirmed by Western blot analysis. The obtained data revealed that CLUS, CERU, APOE, APOA4, APOA1, GELS, S10A9, AMBP, ACTB, CATA and AFAM proteins play a significant role in leukemia prognosis, potentially serving as distinctive biomarkers for leukemia aggressiveness, or as suppressor proteins in HR-ALL cases. In addition, vitronectin and plasminogen probably contributed to leukemogenesis, whilst bicaudal D-related protein 1 could afford a significant biomarker for pediatric ALL therapeutics.

Show MeSH
Related in: MedlinePlus