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lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
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  1. Home
  3. Integrated Analysis Identifies Cuproptosis-related Gene Dlat And Its Competing Endogenous Rnas Network To Predict The Prognosis Of Pancreatic Adenocarcinoma Patients.
  1. Home
  3. Integrated Analysis Identifies Cuproptosis-related Gene Dlat And Its Competing Endogenous Rnas Network To Predict The Prognosis Of Pancreatic Adenocarcinoma Patients.

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Integrated analysis identifies cuproptosis-related gene DLAT and its competing endogenous RNAs network to predict the

Congya Zhou1, Long Jin1, Jiao Yu1

  • 1Department of Radiation Oncology, Shaanxi Provincial People's Hospital, Xi'an, China.

Medicine
|March 1, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

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This study identifies a prognostic signature of three cuproptosis-related genes (CRGs) for pancreatic cancer (PAAD). A LINC00857/has-miR-1179/DLAT axis was also found to impact PAAD progression, offering potential therapeutic targets.

Area of Science:

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background:

  • Pancreatic adenocarcinoma (PAAD) presents a significant clinical challenge due to its aggressive nature and poor patient outcomes.
  • The prognostic implications of cuproptosis-related genes (CRGs) and their associated competing endogenous RNA (ceRNA) networks in PAAD remain largely unexplored.

Purpose of the Study:

  • To investigate the role of CRGs and their ceRNA network in predicting the prognosis of PAAD.
  • To identify novel biomarkers and potential therapeutic targets for PAAD.

Main Methods:

  • Differential expression analysis of CRGs in PAAD tissues versus normal tissues.
  • Construction of a prognostic signature using LASSO Cox regression and Kaplan-Meier survival analysis.
  • Bioinformatic screening for CRG-related miRNA and lncRNAs, followed by in vitro validation (RT-qPCR, CCK-8, colony formation, Transwell assays) of the DLAT gene.

Main Results:

  • A 3-gene prognostic signature (DLAT, LIAS, LIPT1) for PAAD was established, with a high-risk score correlating with poor overall survival (OS).
  • The prognostic signature demonstrated predictive accuracy for OS with AUC values of 0.62 (1-year), 0.66 (3-year), and 0.79 (5-year).
  • The ceRNA network analysis identified the LINC00857/has-miR-1179/DLAT axis, and in vitro experiments confirmed that LINC00857 and DLAT knockdown inhibited PAAD cell growth and invasion.

Conclusions:

  • A novel 3-gene cuproptosis-related prognostic signature (DLAT, LIAS, LIPT1) can predict PAAD patient prognosis.
  • The LINC00857/has-miR-1179/DLAT ceRNA axis is implicated in PAAD development and progression.
  • These findings offer valuable insights for developing diagnostic and prognostic biomarkers and therapeutic strategies for PAAD.