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Gene expression profiling leads to discovery of correlation of matrix metalloproteinase 11 and heparanase 2 in breast cancer progression.

Fu J, Khaybullin R, Zhang Y, Xia A, Qi X - BMC Cancer (2015)

Bottom Line: A group of 28 promising genes were identified with ≥ 10-fold changes of expression level and p-values < 0.05.In particular, MMP11 and HPSE2 were closely examined due to the important roles they play in cancer cell growth and migration.Real-time RT-qPCR analyses of both training and testing sets validated the gene expression profiles of MMP11 and HPSE2.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicinal Chemistry, College of Pharmacy, University of Florida, 1600 SW Archer Rd, Health Science Center P5-31, Gainesville, FL, 32610, USA. jfu@ufl.edu.

ABSTRACT

Background: In order to identify biomarkers involved in breast cancer, gene expression profiling was conducted using human breast cancer tissues.

Methods: Total RNAs were extracted from 150 clinical patient tissues covering three breast cancer subtypes (Luminal A, Luminal B, and Triple negative) as well as normal tissues. The expression profiles of a total of 50,739 genes were established from a training set of 32 samples using the Agilent Sure Print G3 Human Gene Expression Microarray technology. Data were analyzed using Agilent Gene Spring GX 12.6 software. The expression of several genes was validated using real-time RT-qPCR.

Results: Data analysis with Agilent GeneSpring GX 12.6 software showed distinct expression patterns between cancer and normal tissue samples. A group of 28 promising genes were identified with ≥ 10-fold changes of expression level and p-values < 0.05. In particular, MMP11 and HPSE2 were closely examined due to the important roles they play in cancer cell growth and migration. Real-time RT-qPCR analyses of both training and testing sets validated the gene expression profiles of MMP11 and HPSE2.

Conclusions: Our findings identified these 2 genes as a novel breast cancer biomarker gene set, which may facilitate the diagnosis and treatment in breast cancer clinical therapies.

No MeSH data available.


Related in: MedlinePlus

Validation of expression of HPSE2 and MMP11 using RT-qPCR. Four samples (C282, C421, C734, and N114) were picked from the training set, representing Luminal A, Luminal B, Triple negative, and normal tissue respectively. Fold changes of gene expression were calculated with the 2-ΔΔCT method, using β-actin as the house keeping gene. Results were shown as mean ± SEM from triplicates (n = 3). *p < 0.05 compared with N114, **p < 0.001 compared with N114
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Fig4: Validation of expression of HPSE2 and MMP11 using RT-qPCR. Four samples (C282, C421, C734, and N114) were picked from the training set, representing Luminal A, Luminal B, Triple negative, and normal tissue respectively. Fold changes of gene expression were calculated with the 2-ΔΔCT method, using β-actin as the house keeping gene. Results were shown as mean ± SEM from triplicates (n = 3). *p < 0.05 compared with N114, **p < 0.001 compared with N114

Mentions: Four tissue samples were first picked from the training set, C282, C421, C734, and N114, representing Luminal A, Luminal B, Triple negative, and normal tissue respectively. As shown in Fig. 4, the expression of HPSE2 in all the three cancer tissues were down-regulated compared with the expression in normal tissue. On the other hand, the levels of MMP11 in all the 3 cancer tissues were elevated compared with that in normal tissue. The RT-qPCR results for these samples were consistent with our gene expression microarray data (Table 2).Fig. 4


Gene expression profiling leads to discovery of correlation of matrix metalloproteinase 11 and heparanase 2 in breast cancer progression.

Fu J, Khaybullin R, Zhang Y, Xia A, Qi X - BMC Cancer (2015)

Validation of expression of HPSE2 and MMP11 using RT-qPCR. Four samples (C282, C421, C734, and N114) were picked from the training set, representing Luminal A, Luminal B, Triple negative, and normal tissue respectively. Fold changes of gene expression were calculated with the 2-ΔΔCT method, using β-actin as the house keeping gene. Results were shown as mean ± SEM from triplicates (n = 3). *p < 0.05 compared with N114, **p < 0.001 compared with N114
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4477316&req=5

Fig4: Validation of expression of HPSE2 and MMP11 using RT-qPCR. Four samples (C282, C421, C734, and N114) were picked from the training set, representing Luminal A, Luminal B, Triple negative, and normal tissue respectively. Fold changes of gene expression were calculated with the 2-ΔΔCT method, using β-actin as the house keeping gene. Results were shown as mean ± SEM from triplicates (n = 3). *p < 0.05 compared with N114, **p < 0.001 compared with N114
Mentions: Four tissue samples were first picked from the training set, C282, C421, C734, and N114, representing Luminal A, Luminal B, Triple negative, and normal tissue respectively. As shown in Fig. 4, the expression of HPSE2 in all the three cancer tissues were down-regulated compared with the expression in normal tissue. On the other hand, the levels of MMP11 in all the 3 cancer tissues were elevated compared with that in normal tissue. The RT-qPCR results for these samples were consistent with our gene expression microarray data (Table 2).Fig. 4

Bottom Line: A group of 28 promising genes were identified with ≥ 10-fold changes of expression level and p-values < 0.05.In particular, MMP11 and HPSE2 were closely examined due to the important roles they play in cancer cell growth and migration.Real-time RT-qPCR analyses of both training and testing sets validated the gene expression profiles of MMP11 and HPSE2.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicinal Chemistry, College of Pharmacy, University of Florida, 1600 SW Archer Rd, Health Science Center P5-31, Gainesville, FL, 32610, USA. jfu@ufl.edu.

ABSTRACT

Background: In order to identify biomarkers involved in breast cancer, gene expression profiling was conducted using human breast cancer tissues.

Methods: Total RNAs were extracted from 150 clinical patient tissues covering three breast cancer subtypes (Luminal A, Luminal B, and Triple negative) as well as normal tissues. The expression profiles of a total of 50,739 genes were established from a training set of 32 samples using the Agilent Sure Print G3 Human Gene Expression Microarray technology. Data were analyzed using Agilent Gene Spring GX 12.6 software. The expression of several genes was validated using real-time RT-qPCR.

Results: Data analysis with Agilent GeneSpring GX 12.6 software showed distinct expression patterns between cancer and normal tissue samples. A group of 28 promising genes were identified with ≥ 10-fold changes of expression level and p-values < 0.05. In particular, MMP11 and HPSE2 were closely examined due to the important roles they play in cancer cell growth and migration. Real-time RT-qPCR analyses of both training and testing sets validated the gene expression profiles of MMP11 and HPSE2.

Conclusions: Our findings identified these 2 genes as a novel breast cancer biomarker gene set, which may facilitate the diagnosis and treatment in breast cancer clinical therapies.

No MeSH data available.


Related in: MedlinePlus