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lncRNA - Long Non-coding RNAs02:39

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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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Updated: Sep 11, 2025

Predictive Immune Modeling of Solid Tumors
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Transcriptomic Signatures in TP53 Positive and Negative Tumor Samples in NSCLC.

Miao Xie1, Baoguang Liu2, Ziyi Chen1

  • 1College of Traditional Chinese Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan, China.

Current Gene Therapy
|August 13, 2025
PubMed
Summary
This summary is machine-generated.

A 12-gene signature predicts survival and immune response in non-small cell lung cancer (NSCLC) patients with TP53 mutations. This discovery offers insights into the tumor immune microenvironment and may guide immunotherapy decisions.

Keywords:
NSCLCTP53-associated transcriptomic signaturelung cancersurvival.

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Area of Science:

  • Oncology
  • Genomics
  • Immunology

Background:

  • Non-small cell lung cancer (NSCLC) is a major cause of cancer mortality globally.
  • TP53 gene mutations are common in NSCLC and influence cancer development.
  • Understanding transcriptomic differences based on TP53 status is crucial for targeted therapies.

Purpose of the Study:

  • To identify differentially expressed genes (DEGs) associated with TP53 mutation status in NSCLC.
  • To develop a prognostic gene signature for predicting overall survival.
  • To assess the signature's ability to predict immune response, particularly for immunotherapy.

Main Methods:

  • Analysis of gene expression profiles from NSCLC tumor samples (GEO and TCGA databases).
  • Differential gene expression analysis to identify DEGs between TP53-mutated and TP53-wildtype groups.
  • LASSO regression to develop a 12-gene prognostic signature and validation using qPCR.

Main Results:

  • Identified 535 DEGs, narrowing down to a 12-gene signature with prognostic value.
  • The 12-gene signature effectively stratified NSCLC patients into low- and high-risk groups for overall survival.
  • Significant differences in immune cell infiltration and pathway activity were observed between risk groups, correlating with the gene signature.

Conclusions:

  • The 12-gene signature shows strong predictive capability for survival and immune response in NSCLC.
  • Findings suggest potential clinical utility in precision oncology and guiding immunotherapy strategies.
  • The study provides insights into TP53 mutation-driven alterations in the tumor immune microenvironment.