Home > Publications database > Cuproptosis-related lncRNAs emerge as a novel signature for predicting prognosis in prostate carcinoma and functional experimental validation. > print

001     294570
005     20241119182558.0
024 7 _ |a 10.3389/fimmu.2024.1471198
|2 doi
024 7 _ |a pmid:39530098
|2 pmid
024 7 _ |a pmc:PMC11550951
|2 pmc
037 _ _ |a DKFZ-2024-02345
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Lu, Yangbai-
|b 0
245 _ _ |a Cuproptosis-related lncRNAs emerge as a novel signature for predicting prognosis in prostate carcinoma and functional experimental validation.
260 _ _ |a Lausanne
|c 2024
|b Frontiers Media
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1732012964_4248
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a #EA:C070#
520 _ _ |a Prostate cancer (PCa) is one of the most common malignancies of the urinary system. Cuproptosis, a newly discovered form of cell death. The relationship between cuproptosis-related long non-coding RNAs (ClncRNAs) related to PCa and prognosis remains unclear. This study aimed to explore the clinical significance of novel ClncRNAs in the prognostic assessment of PCa.ClncRNAs and differentially expressed mRNAs linked to these ClncRNAs were identified using Pearson's correlation and differential expression analyses. A prognostic signature (risk score) comprising three ClncRNAs was established based on multivariable Cox regression analysis. The predictive performance of this ClncRNAs signature was validated using receiver operating characteristic curves and nomograms. Finally, further in vitro cell experiments were conducted for validation, including quantitative polymerase chain reaction (qPCR), western blot (WB), cell proliferation assays, cell migration assays, cell invasion assays, apoptosis, and cell cycle analysis.We constructed a prognostic signature of ClncRNAs for PCa comprising three key differentially expressed ClncRNAs(AC010896-1, AC016394-2, and SNHG9). Multivariable Cox regression analysis indicated that clinical staging and risk scores of the ClncRNAs signature were independent prognostic factors for PCa. Compared to other clinical features, the ClncRNAs signature exhibited higher diagnostic efficiency and performed well in predicting the 1-, 3-, and 5-year progression-free intervals (PFIs) for PCa. Notably, in terms of immune activity, PCa patients with high-risk scores exhibited higher tumor mutational burden (TMB) levels, while their Tumor Immune Dysfunction and Exclusion (TIDE) scores were lower than those of PCa patients with low-risk scores. Additionally, in vitro cellular functional experiments, we knocked down SNHG9 that is the most significantly differentially expressed ClncRNA among the three key ClncRNAs. SNHG9 knockdown resulted in a significant increase in G1 phase cells and a decrease in S and G2 phases, indicating inhibition of DNA synthesis and cell cycle progression. Colony formation assays showed reduced clonogenic ability, with fewer and smaller colonies. Western blot analysis revealed the upregulation of the key cuproptosis-related mRNAs FDX1 and DLST. These findings suggested that SNHG9 promotes PCa cell proliferation, migration, and invasion.Building on the three ClncRNAs, we identified a novel prognostic signature of PCa. The ClncRNA SNHG9 can promote PCa cell proliferation, migration, and invasion.
536 _ _ |a 313 - Krebsrisikofaktoren und Prävention (POF4-313)
|0 G:(DE-HGF)POF4-313
|c POF4-313
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
650 _ 7 |a SNHG9
|2 Other
650 _ 7 |a cuproptosis
|2 Other
650 _ 7 |a lncRNAs
|2 Other
650 _ 7 |a prognosis signature
|2 Other
650 _ 7 |a prostate carcinoma
|2 Other
650 _ 7 |a RNA, Long Noncoding
|2 NLM Chemicals
650 _ 7 |a Biomarkers, Tumor
|2 NLM Chemicals
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a RNA, Long Noncoding: genetics
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Prostatic Neoplasms: genetics
|2 MeSH
650 _ 2 |a Prostatic Neoplasms: pathology
|2 MeSH
650 _ 2 |a Prognosis
|2 MeSH
650 _ 2 |a Biomarkers, Tumor: genetics
|2 MeSH
650 _ 2 |a Gene Expression Regulation, Neoplastic
|2 MeSH
650 _ 2 |a Cell Line, Tumor
|2 MeSH
650 _ 2 |a Cell Proliferation: genetics
|2 MeSH
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a Gene Expression Profiling
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Cell Movement: genetics
|2 MeSH
650 _ 2 |a Transcriptome
|2 MeSH
650 _ 2 |a Nomograms
|2 MeSH
650 _ 2 |a Apoptosis: genetics
|2 MeSH
700 1 _ |a Wu, Jinfeng-
|b 1
700 1 _ |a Li, Xianzhe
|0 P:(DE-He78)a92f91afa83da73641a4f3abec1d3c6d
|b 2
|e First author
|u dkfz
700 1 _ |a Leng, Qu-
|b 3
700 1 _ |a Tan, Jian-
|b 4
700 1 _ |a Huang, Hongxing-
|b 5
700 1 _ |a Zhong, Rui-
|b 6
700 1 _ |a Chen, Zhenjie-
|b 7
700 1 _ |a Zhang, Yongxin-
|b 8
773 _ _ |a 10.3389/fimmu.2024.1471198
|g Vol. 15, p. 1471198
|0 PERI:(DE-600)2606827-8
|p 1471198
|t Frontiers in immunology
|v 15
|y 2024
|x 1664-3224
909 C O |o oai:inrepo02.dkfz.de:294570
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 2
|6 P:(DE-He78)a92f91afa83da73641a4f3abec1d3c6d
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-313
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Krebsrisikofaktoren und Prävention
|x 0
914 1 _ |y 2024
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b FRONT IMMUNOL : 2022
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2021-05-11T10:28:02Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2021-05-11T10:28:02Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Anonymous peer review
|d 2021-05-11T10:28:02Z
915 _ _ |a Creative Commons Attribution CC BY (No Version)
|0 LIC:(DE-HGF)CCBYNV
|2 V:(DE-HGF)
|b DOAJ
|d 2021-05-11T10:28:02Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-10-26
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-10-26
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2023-10-26
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b FRONT IMMUNOL : 2022
|d 2023-10-26
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2023-10-26
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2023-10-26
920 1 _ |0 I:(DE-He78)C070-20160331
|k C070
|l C070 Klinische Epidemiologie und Alternf.
|x 0
920 0 _ |0 I:(DE-He78)C070-20160331
|k C070
|l C070 Klinische Epidemiologie und Alternf.
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C070-20160331
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21