Niraparib treatment of metastatic melanoma in vivo
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA686436 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13274523_1.fastq.gz | Fastqsanger.gz | |||
| SRR13274523_2.fastq.gz | Fastqsanger.gz | |||
| SRR13274524_1.fastq.gz | Fastqsanger.gz | |||
| SRR13274524_2.fastq.gz | Fastqsanger.gz | |||
| SRR13274525_1.fastq.gz | Fastqsanger.gz |
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Project description:Malignant melanoma has currently the highest increase of incidence of malignancies in the western world. In early stages, front line therapy is surgical excision of the primary tumor. Metastatic disease has previously has very limited possibilities to be cured. Recently, several protein kinase inhibitors and immune modifiers have shown promising results but drug resistance in metastasized melanoma remains a major problem. The need for clinical biomarkers to follow disease progression and treatment effects is high. The aim of the present study was to build a protein sequence database in metastatic melanoma, searching for novel, relevant biomarkers. Ten lymph node metastases (South-Swedish Malignant Melanoma Biobank) were subjected to global protein expression analysis using two proteomics approaches (with/without orthogonal fractionation). Fractionation produced higher numbers of protein identifications (4284). Combining both methods, 5326 unique proteins were identified (2641 proteins overlapping). Deep mining proteomics may contribute to the discovery of novel biomarkers for metastatic melanoma, for example dividing the samples into two metastatic melanoma "genomic subtypes", ("pigmentation" and "high immune") revealed several proteins showing differential levels of expression. In conclusion, the present study provides an initial version of a metastatic melanoma protein sequence database producing a total of more than 5000 unique protein identifications. This dataset consists of data for four samples, analysed by applying strong cation exchange chromatography (SCX) step before the MS step. A sister dataset, consisting of ten samples (that included the current four), was analysed without the (SCX) step.
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