Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
Sign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User GuideGreen Science

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2025 Raw Data Library. All rights reserved.
PrivacyTerms
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Data from UV-Associated Mutations Underlie the Etiology of MCV-Negative Merkel Cell Carcinomas

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Preprint
en
2023

Data from UV-Associated Mutations Underlie the Etiology of MCV-Negative Merkel Cell Carcinomas

0 Datasets

0 Files

en
2023
DOI: 10.1158/0008-5472.c.6507477

Get instant academic access to this publication’s datasets.

Create free accountHow it works
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
Shahneen Sandhu
Shahneen Sandhu

Institution not specified

Verified
Stephen Q. Wong
Kelly Waldeck
Ismael A. Vergara
+27 more

Abstract

Abstract

Merkel cell carcinoma (MCC) is an uncommon, but highly malignant, cutaneous tumor. Merkel cell polyoma virus (MCV) has been implicated in a majority of MCC tumors; however, viral-negative tumors have been reported to be more prevalent in some geographic regions subject to high sun exposure. While the impact of MCV and viral T-antigens on MCC development has been extensively investigated, little is known about the etiology of viral-negative tumors. We performed targeted capture and massively parallel DNA sequencing of 619 cancer genes to compare the gene mutations and copy number alterations in MCV-positive (n = 13) and -negative (n = 21) MCC tumors and cell lines. We found that MCV-positive tumors displayed very low mutation rates, but MCV-negative tumors exhibited a high mutation burden associated with a UV-induced DNA damage signature. All viral-negative tumors harbored mutations in RB1, TP53, and a high frequency of mutations in NOTCH1 and FAT1. Additional mutated or amplified cancer genes of potential clinical importance included PI3K (PIK3CA, AKT1, PIK3CG) and MAPK (HRAS, NF1) pathway members and the receptor tyrosine kinase FGFR2. Furthermore, looking ahead to potential therapeutic strategies encompassing immune checkpoint inhibitors such as anti-PD-L1, we also assessed the status of T-cell–infiltrating lymphocytes (TIL) and PD-L1 in MCC tumors. A subset of viral-negative tumors exhibited high TILs and PD-L1 expression, corresponding with the higher mutation load within these cancers. Taken together, this study provides new insights into the underlying biology of viral-negative MCC and paves the road for further investigation into new treatment opportunities. Cancer Res; 75(24); 5228–34. ©2015 AACR.

How to cite this publication

Stephen Q. Wong, Kelly Waldeck, Ismael A. Vergara, Jan Schröder, Jason Madore, James S. Wilmott, Andrew J. Colebatch, Ricardo De Paoli‐Iseppi, Jason Li, Richard Lupat, Timothy Semple, Gisela Mir Arnau, Andrew Fellowes, J. Helen Leonard, George Hruby, Graham J. Mann, John F. Thompson, Carleen Cullinane, Meredith Johnston, Mark Shackleton, Shahneen Sandhu, David D.L. Bowtell, Ricky W. Johnstone, Stephen B. Fox, Grant A. McArthur, Anthony T. Papenfuss, Richard A. Scolyer, Anthony J. Gill, Rodney J. Hicks, Richard W. Tothill (2023). Data from UV-Associated Mutations Underlie the Etiology of MCV-Negative Merkel Cell Carcinomas. , DOI: https://doi.org/10.1158/0008-5472.c.6507477.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Preprint

Year

2023

Authors

30

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1158/0008-5472.c.6507477

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration