0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free Access<p>This file contains supplemental materials and methods, supplemental tables: ST1 Demographic characteristics of CRC patients recruited for microarray assay, ST2: Distributions of demographic and clinicopathologic characteristics of patients recruited for TMA; ST3: Demographic information of colorectal adenoma (ADE) patients for PCR analysis; ST4:Demographic information of colorectal cancer (CRC) patients for PCR analysis; supplemental figures SF1:Construction of an immunity-associated network involved in CRC progression; SF2:Roles of RELA and MIR17HG in murine AOM-DSS models and CRC cohorts; SF3:miR-17-5p promotes CRC tumorigenesis; SF4: MIR17HG promotes CRC tumorigenesis through suppressing BLNK; SF5: MIR17HG promotes CRC tumorigenesis through binding to miR-17-3p in vitro and in vivo; SF6: Regulation of MALT1, NFKBIE, PPP3R1 and MAP3K7 by miR-17-3p in CRC; SF7: Expression levels of PD-L1 mRNA in cells; SF8: Expression levels of PD-L1 protein in tumor tissues</p>
Jie Xu, Qingtao Meng, Xiaobo Li, Hongbao Yang, Jin Xu, Na Gao, Hao Sun, Shenshen Wu, Giuseppe Familiari, Michela Relucenti, Haitao Zhu, Jiong Wu, Rui Chen (2023). Supplementary Data from Long Noncoding RNA MIR17HG Promotes Colorectal Cancer Progression via miR-17-5p. , DOI: https://doi.org/10.1158/0008-5472.22420728.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Preprint
Year
2023
Authors
13
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1158/0008-5472.22420728
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access