Genetic biomarkers as prognostic and predictive factors in metastatic malignant melanoma
Year: 2010
Type: dissertation
Study design: Observational Study
Abstract: Malignant melanoma is one of the most chemoresistant malignancies in man. Although effort is put into developing new drugs to treat metastatic melanoma, still dacarbazine, an alkylating agent approved in 1975 for therapeutic use in the USA, is considered standard treatment, despite response rates as low as 10%. Today, there is no biomarker predicting response to this drug. Therefore, we have aimed at identifying such biomarkers and also prognostic markers in metastatic melanomas undergoing dacarbazine therapy. In the present papers we have revealed that metastatic melanoma patients can be classified into 4 different groups according to expression of immuneresponse, proliferative, pigmentation, and stromal genes. Most important, these classes have significant different overall survival. Further, we have identified expression of MGMT, a gene coding for an enzyme responsible for repairing DNA damage caused by alkalyting agents like dacarbazine, to predict disease stabilisation on dacarbazine treatment and to independently predict survival. In a gene known to be activated through mutation in melanomas, BRAF, we have identified alternative spliced forms where a part of the gene coding for the catalytic part of the enzyme is not included, and expression of these alternative spliced forms are correlated to response to dacarbazine treatment. In cell culture, knockdown of this gene recovered dacarbazine sensitivity in a melanoma cell line wild type (codon 600V) in BRAF, whereas a mutated cell line (codon 600E) did not respond to this knockdown. Lastly, we have shown alterations in the p53 pathway to be associated with inferior survival. If combined with low p16INK4a expression, the correlation was even stronger.
Author: Christian Busch
Language: English
Topic: Melanoma and MAPK Pathways
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W1419801982
