Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data.
Lazaro Hiram BetancourtKrzysztof PawlowskiJonatan ErikssonA Marcell SzaszShamik MitraIndira Pla ParadaCharlotte WelinderHenrik EkedahlPer BrobergRoger AppelqvistMaria YakovlevaYutaka SugiharaKenichi MiharadaChristian IngvarLotta LundgrenBo BaldetorpHåkan OlssonMelinda RezeliElisabet WieslanderPeter L HorvatovichJohan MalmGöran JönssonGyörgy Marko-VargaPublished in: Scientific reports (2019)
Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research.
Keyphrases
- lymph node
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- mass spectrometry
- high resolution mass spectrometry
- electronic health record
- big data
- squamous cell carcinoma
- skin cancer
- machine learning
- radiation therapy
- gene expression
- young adults
- patient reported outcomes
- liquid chromatography
- early stage
- sentinel lymph node
- rectal cancer
- label free
- amino acid
- combination therapy