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Related Concept Videos

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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Clinical Data Analysis Identifies Prognostic Long Non-coding RNA Signatures in Lung Adenocarcinoma.

Madhur Sharma1, Nidhi Chourasia2, Priyanka Priyanka3

  • 1Department of Biochemistry, University of Delhi South Campus, New Delhi, India.

Cancer Genomics & Proteomics
|April 29, 2026
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Summary

This study identified three long non-coding RNAs (lncRNAs) – FAM83A-AS1, CYTOR, and MIR4435-2HG – as key indicators of poor prognosis in lung adenocarcinoma (LUAD). Their expression levels correlate with disease progression and patient survival, offering potential new biomarkers for this cancer.

Keywords:
LUADLncRNALong non-coding RNAcancer transcriptomicsfunctional enrichment analysislong ncRNAprognostic biomarker

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Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Lung adenocarcinoma (LUAD) is a major non-small cell lung cancer (NSCLC) subtype with poor outcomes due to molecular complexity.
  • Limited prognostic biomarkers hinder effective patient stratification and treatment in LUAD.
  • Long non-coding RNAs (lncRNAs) are implicated in cancer, but their role in LUAD progression and prognosis requires further elucidation.

Purpose of the Study:

  • To identify long non-coding RNAs (lncRNAs) that are significantly associated with the progression and prognosis of lung adenocarcinoma (LUAD).
  • To explore the potential of identified lncRNAs as prognostic biomarkers for LUAD patients.

Main Methods:

  • Utilized The Cancer Genome Atlas (TCGA) database for lncRNA expression data from 488 LUAD tumors and 58 normal lung tissues.
  • Performed differential expression analysis and Kaplan-Meier survival analysis to identify prognostic lncRNAs.
  • Assessed monotonic expression trends across tumor stage, lymph-node status, and tumor size using Spearman correlation.

Main Results:

  • Identified 68 lncRNAs consistently overexpressed in LUAD compared to normal lung tissue.
  • Discovered that higher expression of specific lncRNAs, notably FAM83A-AS1, CYTOR, and MIR4435-2HG, correlated with poorer overall survival.
  • Observed significant associations between these three lncRNAs and increased lymph-node involvement and tumor size, indicating a link to tumor burden.

Conclusions:

  • FAM83A-AS1, CYTOR, and MIR4435-2HG are identified as robust lncRNAs associated with poor prognosis in LUAD.
  • These lncRNAs show coordinated expression patterns linked to survival, nodal status, and tumor size.
  • The findings suggest these lncRNAs could serve as valuable prognostic biomarkers for risk stratification in lung adenocarcinoma.