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Protein Biomarkers in Malignant Melanoma: An Image Analysis-Based Study on Melanoma Markers of Potential Clinical Relevance
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Molekylär och morfologisk patologi. (HPA)
UCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Ireland.
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Molekylär och morfologisk patologi. (HPA)
Lab Surgpath, Mumbai, India. (HPA Uppsala)
Vise andre og tillknytning
(engelsk)Manuskript (preprint) (Annet vitenskapelig)
Abstract [en]

The thickness of a primary malignant melanoma tumor is the most important prognostic indicator for a patient with primary cutaneous malignant melanoma. To optimize the management and treatment of melanoma patients there is an unmet need to identify characteristics that can further stratify melanoma patients into high or low risk for progressive disease. Despite numerous studies no single marker has yet been shown to add significant prognostic information. An algorithmic approach, combining data from several markers provides an attractive model to identify patients of increased risk of dying from malignant melanoma. The primary aim of the present study was to analyze the correlation between clinical outcome and protein expression patterns of multiple proteins in malignant melanoma tumors using immunohistochemistry and tissue microarrays. Candidate proteins were identified based on a selective and differential expression pattern in melanoma tumors and tested in a cohort of 143 melanoma patients. Protein expression was analyzed using both manual scoring and automated image analysis-based algorithms. We found no single marker of prognosis that was independent of tumor thickness. When combining potential prognostic markers we could define a prognostic index, based on RBM3, MITF, SOX10 and Ki-67, that was independent of tumor thickness in multivariate analysis. Our findings suggest that a good prognosis signature can be identified in melanoma patients with tumors showing a low fraction of Ki-67 positive tumor cells and a high fraction of RBM3 positive tumor cells combined with low intensity levels of SOX10 and MITF.

 

Emneord [en]
malignant melanoma, immunohistochemistry, tissue microarray, protein expression, automated analysis, RBM3, SOX10, MITF, Ki-67
HSV kategori
Forskningsprogram
Patologi; Bioinformatik
Identifikatorer
URN: urn:nbn:se:uu:diva-144108OAI: oai:DiVA.org:uu-144108DiVA, id: diva2:398173
Tilgjengelig fra: 2011-02-16 Laget: 2011-01-27 Sist oppdatert: 2018-01-12
Inngår i avhandling
1. Biomarker Discovery in Cutaneous Malignant Melanoma: A Study Based on Tissue Microarrays and Immunohistochemistry
Åpne denne publikasjonen i ny fane eller vindu >>Biomarker Discovery in Cutaneous Malignant Melanoma: A Study Based on Tissue Microarrays and Immunohistochemistry
2011 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

The incidence of cutaneous malignant melanoma has increased dramatically in Caucasians the last few decades, an increase that is partly explained by altered sun exposure habits. For the individual patient, with a localized disease, the tumor thickness of the excised lesion is the most important prognostic factor. However, there is a need to identify characteristics that can place patients in certain risk groups.

In this study, the protein expression of multiple proteins in malignant melanoma tumors was studied, with the aim of identifying potential new candidate biomarkers. Representative samples from melanoma tissues were assembled in a tissue microarray format and protein expression was detected using immunohistochemistry. Multiple cohorts were used and for a subset of proteins the expression was also analyzed in melanocytes in normal skin and in benign nevi. The immunohistochemical staining was evaluated manually and for part of the proteins also with an automated algorithm.

The protein expression of STX7 was described for the first time in tumors of the melanocytic lineage. Stronger expression of STX7 and SOX10 was seen in superficial spreading melanomas compared with nodular malignant melanomas. An inverse relationship between STX7 expression and T-stage was seen and between SOX10 expression and T-stage and Ki-67, respectively. In a population-based cohort the expression of MITF was analyzed and found to be associated with prognosis. Twenty-one potential biomarkers were analyzed using bioinformatics tools and a protein signature was identified which had a prognostic value independent of T-stage. The protein driving this signature was RBM3, a protein not previously described in malignant melanoma. Other markers included in the signature were MITF, SOX10 and Ki-67.

In conclusion, the protein expression of numerous potential biomarkers was extensively studied and a new prognostic protein panel was identified which can be of value for risk stratification.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2011. s. 53
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 644
Emneord
antibody-based proteomics, automated analysis, biomarker, immunohistochemistry, malignant melanoma, survival, tissue microarray
HSV kategori
Forskningsprogram
Medicinsk vetenskap; Patologi
Identifikatorer
urn:nbn:se:uu:diva-146436 (URN)978-91-554-8007-3 (ISBN)
Disputas
2011-04-02, Rudbecksalen, Rudbecklaboratoriet, Dag Hammarskjöldsv 20, Uppsala, 13:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2011-03-11 Laget: 2011-02-16 Sist oppdatert: 2018-01-12bibliografisk kontrollert

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