Dataset Information

Quantitative Analysis of Immunohistochemistry in Melanoma Tumors.

ABSTRACT: Identification of positive staining is often qualitative and subjective. This is particularly troublesome in pigmented melanoma lesions, because melanin is difficult to distinguish from the brown stain resulting from immunohistochemistry (IHC) using horse radish peroxidase developed with 3,3'-Diaminobenzidine (HRP-DAB). We sought to identify and quantify positive staining, particularly in melanoma lesions. We visualized G-protein coupled estrogen receptor (GPER) expression developed with HRP-DAB and counterstained with Azure B (stains melanin) in melanoma tissue sections (n?=?3). Matched sections (n?=?3), along with 22 unmatched sections, were stained only with Azure B as a control. Breast tissue (n?=?1) was used as a positive HRP-DAB control. Images of the stained tissues were generated using a Nuance Spectral Imaging Camera. Analysis of the images was performed using the Nuance Spectral Imaging software and SlideBook. Data was analyzed using a Kruskal-Wallis one way analysis of variance (ANOVA). We showed that a pigmented melanoma tissue doubly stained with anti-GPER HRP-DAB and Azure B can be unmixed using spectra derived from a matched, Azure B-only section, and an anti-GPER HRP-DAB control. We unmixed each of the melanoma lesions using each of the Azure B spectra, evaluated the mean intensity of positive staining, and examined the distribution of the mean intensities (P?=?.73; Kruskal-Wallis). These results suggest that this method does not require a matched Azure B-only stained control tissue for every melanoma lesion, allowing precious tissues to be conserved for other studies. Importantly, this quantification method reduces the subjectivity of protein expression analysis, and provides a valuable tool for accurate evaluation, particularly for pigmented tissues.

SUBMITTER: Lilyquist J

PROVIDER: S-EPMC5403070 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Quantitative Analysis of Immunohistochemistry in Melanoma Tumors.

Lilyquist Jenna J White Kirsten Anne Meyer KAM Lee Rebecca J RJ Philips Genevieve K GK Hughes Christopher R CR Torres Salina M SM

Medicine 20170401 15

Identification of positive staining is often qualitative and subjective. This is particularly troublesome in pigmented melanoma lesions, because melanin is difficult to distinguish from the brown stain resulting from immunohistochemistry (IHC) using horse radish peroxidase developed with 3,3'-Diaminobenzidine (HRP-DAB). We sought to identify and quantify positive staining, particularly in melanoma lesions. We visualized G-protein coupled estrogen receptor (GPER) expression developed with HRP-DAB ...[more]

PMID: 28403073

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Project description:Uveal melanoma is the most common malignancy of the adult eye. The overall mortality rate is high because this aggressive cancer often metastasizes before ophthalmic diagnosis. Quantitative proteomic analysis of primary metastasizing and non-metastasizing tumors was pursued for insights into mechanisms and biomarkers of uveal melanoma metastasis.Eight metastatic and 7 non-metastatic human primary uveal melanoma tumors were analyzed by LC MS/MS iTRAQ technology with Bruch's membrane/choroid complex from normal postmortem eyes as control tissue. Tryptic peptides from tumor and control proteins were labeled with iTRAQ tags, fractionated by cation exchange chromatography, and analyzed by LC MS/MS. Protein identification utilized the Mascot search engine and the human Uni-Prot/Swiss-Protein database with false discovery ? 1%; protein quantitation utilized the Mascot weighted average method. Proteins designated differentially expressed exhibited quantitative differences (p ? 0.05, t-test) in a training set of five metastatic and five non-metastatic tumors. Logistic regression models developed from the training set were used to classify the metastatic status of five independent tumors.Of 1644 proteins identified and quantified in 5 metastatic and 5 non-metastatic tumors, 12 proteins were found uniquely in ? 3 metastatic tumors, 28 were found significantly elevated and 30 significantly decreased only in metastatic tumors, and 31 were designated differentially expressed between metastatic and non-metastatic tumors. Logistic regression modeling of differentially expressed collagen alpha-3(VI) and heat shock protein beta-1 allowed correct prediction of metastasis status for each of five independent tumor specimens.The present data provide new clues to molecular differences in metastatic and non-metastatic uveal melanoma tumors. While sample size is limited and validation required, the results support collagen alpha-3(VI) and heat shock protein beta-1 as candidate biomarkers of uveal melanoma metastasis and establish a quantitative proteomic database for uveal melanoma primary tumors.

Dataset Information

Quantitative Analysis of Immunohistochemistry in Melanoma Tumors.

Publications

Quantitative Analysis of Immunohistochemistry in Melanoma Tumors.

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