Evidence map›Paper›PMID 39788498›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2024

Identification of apoptosis

Zhaoyang Liu, Lingli Luo, Xinyi Wu, Bingqi Wang, Min Wang, Xianping Li

Abstract read
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zhaoyang LiuDepartment of Laboratory Medicine, Second Xiangya Hospital, Central South University, Changsha 410011. liuzhaoyangxyeyy@163.com.
Lingli LuoLaboratory Center, Hunan Children's Hospital, Changsha 410007, China.
Xinyi WuDepartment of Laboratory Medicine, Second Xiangya Hospital, Central South University, Changsha 410011.
Bingqi WangDepartment of Laboratory Medicine, Second Xiangya Hospital, Central South University, Changsha 410011.
Min WangDepartment of Laboratory Medicine, Second Xiangya Hospital, Central South University, Changsha 410011.
Xianping LiDepartment of Laboratory Medicine, Second Xiangya Hospital, Central South University, Changsha 410011. xianpingli2017@csu.edu.cn.

Funding

the Scientific Research Plan Project of Hunan Provincial Health Commission D202311007103
6 · The paper itself

Abstract

objectivesLong non-coding RNAs (lncRNAs) play an essential role in cancer biology. Cervical intraepithelial neoplasia grade 3 (CIN3) is the most severe precancerous lesion of cervical cancer. However, the mechanism of multiple lncRNAs in CIN3 has not been studied in-depth and is worth exploring. This study aims to summarize the lncRNA expression profile in CIN 3 and screen for lncRNAs with potential oncogenic effects.

methodsTo further clarify the role of lncRNAs in the development of CIN3, this study collected cancer tissue and para-cancer tissue specimens from three CIN3 patients. The RNA sequencing (RNA-Seq) analysis was used to construct expression profiles of lncRNAs and confirmed by real-time reverse transcription PCR (real-time RT-PCR) methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed with computational methods. We obtained their possible target genes through the cis- and trans-regulatory analysis of the lncRNAs. In addition, this study predicted new transcripts and lncRNAs by Cufflinks analysis and coding potential identification (Coding Potential Calculator) analysis to discover new tumor regulatory molecules.

resultsThe differential expressions of 1 555 genes, 1 562 mRNAs, 241 ncRNAs, and 6 616 new predicted-lncRNAs were found. The most prominently up-regulated and down-regulated lncRNAs were NR_145433.1 and ENST00000513672.1, respectively. KEGG analysis revealed that lncRNA-targeted genes were closely related to apoptosis, metabolic, p53 signaling pathway, and other cancer-related pathways. The real-time RT-PCR validation results of 5 apoptosis-related lncRNAs (NR_145433.1, ENST00000510610.2, UC001Kfo, ENST00000602964.1, and NR_123733.1) in cervical cancer were consistent with the sequencing results.

conclusionsThis study provides a comprehensive expression profile of lncRNAs in CIN3 patients, particularly the apoptosis-related expression profile of lncRNAs, and provides direction and clues for the study of cervical cancer and the search for potential therapeutic targets.

Indexed as

ApoptosisRNA, Long NoncodingUterine Cervical DysplasiaUterine Cervical NeoplasmsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyHumansSequence Analysis, RNARNA, Long Noncodingapoptosiscervical cancercervical intraepithelial neoplasia grade 3long non-coding RNAsRNA sequencing

Identifiers

PMID39788498
PMCPMC11495978

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.