Replication Data for: Comparative and integrated analyses of polyomavirus-negative and -positive Merkel cell carcinoma cell lines and their exosomes proteomic studies (doi:10.18710/OGQOQW)

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Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
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Replication Data for: Comparative and integrated analyses of polyomavirus-negative and -positive Merkel cell carcinoma cell lines and their exosomes proteomic studies

doi:10.18710/OGQOQW

DataverseNO

2019-05-06

1

Konstantinell, Aelita Gloria Virginia, 2019, "Replication Data for: Comparative and integrated analyses of polyomavirus-negative and -positive Merkel cell carcinoma cell lines and their exosomes proteomic studies", https://doi.org/10.18710/OGQOQW, DataverseNO, V1, UNF:6:iYIxN6iz0Ry0HX50eUxSPQ== [fileUNF]

Replication Data for: Comparative and integrated analyses of polyomavirus-negative and -positive Merkel cell carcinoma cell lines and their exosomes proteomic studies

doi:10.18710/OGQOQW

Konstantinell, Aelita Gloria Virginia (UiT The Arctic University of Norway)

UiT The Arctic University of Norway

A65256

A65216

A65216

DataverseNO

UiT The Arctic University of Norway

Konstantinell, Aelita Gloria Virginia

Konstantinell, Aelita Gloria Virginia

2019-04-01

https://doi.org/10.18710/OGQOQW

Medicine, Health and Life Sciences, Merkel cell carcinoma, Merkel cell polyomavirus, Merkel cell carcinoma cell lines, exosome, proteomics

This dataset is analyses of identified proteins between MCPyV-negative (MCC13, MCC26, and UISO) and -positive (MKL1, MKL2, MS1, and WaGa) MCC cell line.

</P>Abstract: Proteomics have become an important tool in discovery and understanding pathological processes at the cellular level. Comparing the proteome of normal cells with diseased (malignant and other pathological conditions) or pathogen-infected cells allows identification of proteins and processes involved in the disease and recognition of possible biomarkers and targets for treatment. Merkel cell carcinoma (MCC) is an aggressive type of cutaneous cancer that affects mostly elderly people. Approximately 80% of the tumors are caused by Merkel cell polyomavirus (MCPyV), while the remaining are caused by UV-induced mutations in the DNA of the cell. To understand the underlying mechanisms of virus-independent and virus-dependent MCC, we compared the proteome of MCPyV-negative (MCC13, MCC26, and UISO) and MCPyV-positive (MKL-1, MKL-2, MS-1, and WaGa) MCC cell lines. In total 4898 proteins were identified, of which 3312 were differentially expressed between the virus-negative and virus-positive cell lines. The viral oncoproteins large T- and small t-antigens were detected in the MCPyV-positive cells, but also in exosomes derived from these cells. Our proteomic data may identify unique biomarkers for MCPyV-negative and –positive MCCs and may allow the design of specific therapeutic strategies against the two types of MCC with a different origin. Moreover, our results suggest that exosomal transmission of MCPyV oncoproteins to recipient cells in the tumor microenvironment contributes to tumorigenesis. Data are available via ProteomeXchange with identifier PXD012909.

2018-07-01-2019-01-15

Experimental data

Biomarkers Discovery: The Benefit of the Study Exosomes Originated from Merkel Cell Carcinoma Cell Lines. doi: 10.18710/KCW912.

Konstantinell, Aelita Gloria Virginia. Comparative and intergrated analyses of polyomavirus-negative and -positive Merkel cell carcinoma cell lines and their exosomes proteomic studies (manuscript). In: Konstantinell, Aelita Gloria Virginia, 2019. Biomarkers Discovery: The Benefit of the Study Exosomes Originated from Merkel Cell Carcinoma Cell Lines. Ph.D. thesis, UiT The Arctic University of Norway, 30.08.2019.

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Konstantinell, Aelita Gloria Virginia. Comparative and intergrated analyses of polyomavirus-negative and -positive Merkel cell carcinoma cell lines and their exosomes proteomic studies (manuscript). In: Konstantinell, Aelita Gloria Virginia, 2019. Biomarkers Discovery: The Benefit of the Study Exosomes Originated from Merkel Cell Carcinoma Cell Lines. Ph.D. thesis, UiT The Arctic University of Norway, 30.08.2019.

• Number of cases: 84

• No. of variables per record: 9

• Type of File: text/tab-separated-values

UNF:6:iYIxN6iz0Ry0HX50eUxSPQ==

• Table5.Theclusterwithasizeof1170proteinsdifferentiallyexpressedbetweenMCPyV-negativeand–positiveMCCcelllinesincluded83cellularcompartments(GOCCslimname)andbiologicalpathways(GOBPslimname)upregulatedwithMCPyV-negativeMCCcelllinessuchasMCC13,MCC26,andUISO. - Table5.Theclusterwithasizeof1170proteinsdifferentiallyexpressedbetweenMCPyV-negativeand–positiveMCCcelllinesincluded83cellularcompartments(GOCCslimname)andbiologicalpathways(GOBPslimname)upregulatedwithMCPyV-negativeMCCcelllinessuchasMCC13,MCC26,andUISO.
• B - B
• C - C
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• G - G
• H - H
• I - I

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01_ReadMe.txt

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An overview and short description of the files contained in dataset, which icludes the contact information, what the dataset is about, column headings in tabular data, some abbreviations, and where to find which data = overview of files.

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