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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

Box-and-Whisker plots. The gene expression levels of HPSE2 (a) and MMP11 (b) from the 32 samples in the training set covering Luminal A (n = 19), Luminal B (n = 3), Triple negative (n = 3) and normal control (n = 7) were shown in the box-and-whisker plots. The plots were generated using GeneSpring 12.6 software. The correlation of fold changes (FC) and normalized intensity (NI) values were calculated using the formula FC (Xn) = 2 ^ [averaged NI (Xn)-averaged NI (XControl)]. X: individual genes; n: breast cancer subtypes; NI (Xn): Normalized intensity of gene X in subtype n; NI (Control): normalized intensity of gene X in normal samples
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Fig7: Box-and-Whisker plots. The gene expression levels of HPSE2 (a) and MMP11 (b) from the 32 samples in the training set covering Luminal A (n = 19), Luminal B (n = 3), Triple negative (n = 3) and normal control (n = 7) were shown in the box-and-whisker plots. The plots were generated using GeneSpring 12.6 software. The correlation of fold changes (FC) and normalized intensity (NI) values were calculated using the formula FC (Xn) = 2 ^ [averaged NI (Xn)-averaged NI (XControl)]. X: individual genes; n: breast cancer subtypes; NI (Xn): Normalized intensity of gene X in subtype n; NI (Control): normalized intensity of gene X in normal samples

Mentions: Gene selection in real-time RT-qPCR validation is based on the selection criteria of corrected p-value < 0.05 and fold changes ≥ 10 and the relevance of genes to breast cancer progression. It is interesting to notice that both MMP11 and HPSE2 appear in the 28 top genes list in Table 2. As illustrated in Fig. 6, MMPs, HPSE, HPSE2 are closely involved in cancer cells’ invasion and metastasis. It has been previously documented that MMPs and HPSE play essential roles in breast cancer [32, 33]. However, the close relationship between MMP11 and HPSE2 has not been reported, which brings new insight into the breast cancer field. From our gene microarray data, MMP11 was found to be up-regulated while HPSE2 was down-regulated in breast cancer compared with normal control (Fig. 7). Therefore, MMP11 and HPSE2 were selected for real-time RT-qPCR validation to investigate their potential roles as a gene set in breast cancer progression.


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)

Box-and-Whisker plots. The gene expression levels of HPSE2 (a) and MMP11 (b) from the 32 samples in the training set covering Luminal A (n = 19), Luminal B (n = 3), Triple negative (n = 3) and normal control (n = 7) were shown in the box-and-whisker plots. The plots were generated using GeneSpring 12.6 software. The correlation of fold changes (FC) and normalized intensity (NI) values were calculated using the formula FC (Xn) = 2 ^ [averaged NI (Xn)-averaged NI (XControl)]. X: individual genes; n: breast cancer subtypes; NI (Xn): Normalized intensity of gene X in subtype n; NI (Control): normalized intensity of gene X in normal samples
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig7: Box-and-Whisker plots. The gene expression levels of HPSE2 (a) and MMP11 (b) from the 32 samples in the training set covering Luminal A (n = 19), Luminal B (n = 3), Triple negative (n = 3) and normal control (n = 7) were shown in the box-and-whisker plots. The plots were generated using GeneSpring 12.6 software. The correlation of fold changes (FC) and normalized intensity (NI) values were calculated using the formula FC (Xn) = 2 ^ [averaged NI (Xn)-averaged NI (XControl)]. X: individual genes; n: breast cancer subtypes; NI (Xn): Normalized intensity of gene X in subtype n; NI (Control): normalized intensity of gene X in normal samples
Mentions: Gene selection in real-time RT-qPCR validation is based on the selection criteria of corrected p-value < 0.05 and fold changes ≥ 10 and the relevance of genes to breast cancer progression. It is interesting to notice that both MMP11 and HPSE2 appear in the 28 top genes list in Table 2. As illustrated in Fig. 6, MMPs, HPSE, HPSE2 are closely involved in cancer cells’ invasion and metastasis. It has been previously documented that MMPs and HPSE play essential roles in breast cancer [32, 33]. However, the close relationship between MMP11 and HPSE2 has not been reported, which brings new insight into the breast cancer field. From our gene microarray data, MMP11 was found to be up-regulated while HPSE2 was down-regulated in breast cancer compared with normal control (Fig. 7). Therefore, MMP11 and HPSE2 were selected for real-time RT-qPCR validation to investigate their potential roles as a gene set in breast cancer progression.

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