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Five markers useful for the distinction of canine mammary malignancy.

Pawłowski KM, Maciejewski H, Majchrzak K, Dolka I, Mol JA, Motyl T, Król M - BMC Vet. Res. (2013)

Bottom Line: There are significant differences in survival between cases with different tumor grades.The expression of this gene set (sehrl, zfp37, mipep, relaxin, and magi3) differs significantly in the most malignant tumors at mRNA level as well as at protein level.These genes are also interesting as targets for further investigations and therapy.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Physiological Sciences, Faculty of Veterinary Medicine, Warsaw University of Life Sciences - WULS, Nowoursynowska 159, 02-776, Warsaw, Poland.

ABSTRACT

Background: Spontaneous canine mammary tumors constitute a serious clinical problem. There are significant differences in survival between cases with different tumor grades. Unfortunately, the distinction between various grades is not clear. A major problem in evaluating canine mammary cancer is identifying those, that are "truly" malignant. That is why the aim of our study was to find the new markers of canine malignancy, which could help to diagnose the most malignant tumors.

Results: Analysis of gene expression profiles of canine mammary carcinoma of various grade of malignancy followed by the boosted tree analysis distinguished a `gene set`. The expression of this gene set (sehrl, zfp37, mipep, relaxin, and magi3) differs significantly in the most malignant tumors at mRNA level as well as at protein level. Despite this `gene set` is very interesting as an additional tool to estimate canine mammary malignancy, it should be validated using higher number of samples.

Conclusions: The proposed gene set can constitute a `malignancy marker` that could help to distinguish the most malignant canine mammary carcinomas. These genes are also interesting as targets for further investigations and therapy. So far, only two of them were linked with the cancer development.

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The clustering of tumors taken to the analysis and variation in expression of 20 the mostly significant genes between the most and less malignant canine mammary tumors. A. Differences in expression of genes in 12 examined samples. Data is presented in a matrix format: each row represents a single gene, and each column an experimental sample. In each sample, the ratio of the abundance of transcripts of each gene to the median abundance of the gene's transcript across all tissue samples is represented by the color of the corresponding cell in the matrix. Green squares, transcript levels below the median; red squares, transcript levels greater than the median. Color saturation reflects the magnitude of the ratio relative to the median for each set of samples. B. Boxplots comparing relative signal measured for 20 most significantly changed genes between less malignant (yellow) and the most malignant (green) tumors.
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Figure 1: The clustering of tumors taken to the analysis and variation in expression of 20 the mostly significant genes between the most and less malignant canine mammary tumors. A. Differences in expression of genes in 12 examined samples. Data is presented in a matrix format: each row represents a single gene, and each column an experimental sample. In each sample, the ratio of the abundance of transcripts of each gene to the median abundance of the gene's transcript across all tissue samples is represented by the color of the corresponding cell in the matrix. Green squares, transcript levels below the median; red squares, transcript levels greater than the median. Color saturation reflects the magnitude of the ratio relative to the median for each set of samples. B. Boxplots comparing relative signal measured for 20 most significantly changed genes between less malignant (yellow) and the most malignant (green) tumors.

Mentions: To create the molecular classifier of canine mammary malignancy we used our previous data [1] deposited in NCBI's Gene Expression Omnibus (GEO) with Series accession number GSE 29601. Briefly, the statistical analysis of gene expression was performed using linear methods for microarrays (limma package in Bioconductor software) [7]. The method tests the hypothesis of no differential expression between the groups of samples compared was performed by using the moderated t-statistic [7], which has similar interpretation as the ordinary t-test statistic. The expression of genes with the Benjamini-Hochberg (FDR) multiple-testing corrected p-value below 0.05 was qualified as significantly changed. Each of the microarrays had been examined separately. Our previously conducted unsupervised analysis [1] had classified the examined canine mammary tumor tissues (grade I, grade II and grade III) into three groups. For the purposes of the hereby study we were mainly focused on two of them: the 1st which consisted of 4 grade III and 1 grade II carcinomas (it was the most malignant group) and the second consisted of 4 grade I carcinomas (it was the group consisted of the lowest estimated malignant tumors) (Figure 1A). We were focused only on these two groups to find genes that present exact characteristic for the most malignant tumors. Thus, to build a canine mammary malignancy classifier the following training data were used: the most malignant tumors (n = 8, two hybridizations per patient) and the lowest estimated malignant tumors (n = 10, two hybridizations per patient).


Five markers useful for the distinction of canine mammary malignancy.

Pawłowski KM, Maciejewski H, Majchrzak K, Dolka I, Mol JA, Motyl T, Król M - BMC Vet. Res. (2013)

The clustering of tumors taken to the analysis and variation in expression of 20 the mostly significant genes between the most and less malignant canine mammary tumors. A. Differences in expression of genes in 12 examined samples. Data is presented in a matrix format: each row represents a single gene, and each column an experimental sample. In each sample, the ratio of the abundance of transcripts of each gene to the median abundance of the gene's transcript across all tissue samples is represented by the color of the corresponding cell in the matrix. Green squares, transcript levels below the median; red squares, transcript levels greater than the median. Color saturation reflects the magnitude of the ratio relative to the median for each set of samples. B. Boxplots comparing relative signal measured for 20 most significantly changed genes between less malignant (yellow) and the most malignant (green) tumors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3750412&req=5

Figure 1: The clustering of tumors taken to the analysis and variation in expression of 20 the mostly significant genes between the most and less malignant canine mammary tumors. A. Differences in expression of genes in 12 examined samples. Data is presented in a matrix format: each row represents a single gene, and each column an experimental sample. In each sample, the ratio of the abundance of transcripts of each gene to the median abundance of the gene's transcript across all tissue samples is represented by the color of the corresponding cell in the matrix. Green squares, transcript levels below the median; red squares, transcript levels greater than the median. Color saturation reflects the magnitude of the ratio relative to the median for each set of samples. B. Boxplots comparing relative signal measured for 20 most significantly changed genes between less malignant (yellow) and the most malignant (green) tumors.
Mentions: To create the molecular classifier of canine mammary malignancy we used our previous data [1] deposited in NCBI's Gene Expression Omnibus (GEO) with Series accession number GSE 29601. Briefly, the statistical analysis of gene expression was performed using linear methods for microarrays (limma package in Bioconductor software) [7]. The method tests the hypothesis of no differential expression between the groups of samples compared was performed by using the moderated t-statistic [7], which has similar interpretation as the ordinary t-test statistic. The expression of genes with the Benjamini-Hochberg (FDR) multiple-testing corrected p-value below 0.05 was qualified as significantly changed. Each of the microarrays had been examined separately. Our previously conducted unsupervised analysis [1] had classified the examined canine mammary tumor tissues (grade I, grade II and grade III) into three groups. For the purposes of the hereby study we were mainly focused on two of them: the 1st which consisted of 4 grade III and 1 grade II carcinomas (it was the most malignant group) and the second consisted of 4 grade I carcinomas (it was the group consisted of the lowest estimated malignant tumors) (Figure 1A). We were focused only on these two groups to find genes that present exact characteristic for the most malignant tumors. Thus, to build a canine mammary malignancy classifier the following training data were used: the most malignant tumors (n = 8, two hybridizations per patient) and the lowest estimated malignant tumors (n = 10, two hybridizations per patient).

Bottom Line: There are significant differences in survival between cases with different tumor grades.The expression of this gene set (sehrl, zfp37, mipep, relaxin, and magi3) differs significantly in the most malignant tumors at mRNA level as well as at protein level.These genes are also interesting as targets for further investigations and therapy.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Physiological Sciences, Faculty of Veterinary Medicine, Warsaw University of Life Sciences - WULS, Nowoursynowska 159, 02-776, Warsaw, Poland.

ABSTRACT

Background: Spontaneous canine mammary tumors constitute a serious clinical problem. There are significant differences in survival between cases with different tumor grades. Unfortunately, the distinction between various grades is not clear. A major problem in evaluating canine mammary cancer is identifying those, that are "truly" malignant. That is why the aim of our study was to find the new markers of canine malignancy, which could help to diagnose the most malignant tumors.

Results: Analysis of gene expression profiles of canine mammary carcinoma of various grade of malignancy followed by the boosted tree analysis distinguished a `gene set`. The expression of this gene set (sehrl, zfp37, mipep, relaxin, and magi3) differs significantly in the most malignant tumors at mRNA level as well as at protein level. Despite this `gene set` is very interesting as an additional tool to estimate canine mammary malignancy, it should be validated using higher number of samples.

Conclusions: The proposed gene set can constitute a `malignancy marker` that could help to distinguish the most malignant canine mammary carcinomas. These genes are also interesting as targets for further investigations and therapy. So far, only two of them were linked with the cancer development.

Show MeSH
Related in: MedlinePlus