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Related Concept Videos

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

8.6K
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...
8.6K
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Identification Of Cellular Senescence-associated Genes As New Biomarkers For Predicting The Prognosis And Immunotherapy Response Of Non-small Cell Lung Cancer And Construction Of A Prognostic Model

Identification of cellular senescence-associated genes as new biomarkers for predicting the prognosis and immunotherapy response of non-small cell lung cancer and construction of a prognostic model

Dandan Xu1,2, Xiao Chen2, Mingyuan Wu3

  • 1Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.

Heliyon
|April 1, 2024

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Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
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Induction and Validation of Cellular Senescence in Primary Human Cells
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Induction and Validation of Cellular Senescence in Primary Human Cells

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View abstract on PubMed

Summary
This summary is machine-generated.

This study identifies 12 cell senescence-related mRNAs that predict prognosis and immunotherapy response in non-small cell lung cancer (NSCLC). These findings offer a new risk framework for NSCLC patients.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Lung carcinoma is a leading cause of cancer death globally, with limited treatment advancements.
  • Cellular senescence, a state of cell cycle arrest, plays a critical role in tumor development and progression.
  • Understanding senescence-related molecular markers is crucial for improving non-small cell lung cancer (NSCLC) outcomes.

Purpose of the Study:

  • To identify and analyze cell senescence-related messenger RNAs (mRNAs) associated with NSCLC prognosis.
  • To develop a predictive risk model and nomogram for NSCLC based on these senescence-related mRNAs.
  • To investigate the relationship between the risk model, immune infiltration, and immunotherapy response in NSCLC.

Main Methods:

  • Acquired NSCLC expression data from The Cancer Genome Atlas (TCGA).
Keywords:
Cellular senescenceNon-small cell lung cancerPrognostic modelRisk score

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Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
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Induction and Validation of Cellular Senescence in Primary Human Cells
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  • Employed univariate and multivariate Cox proportional hazard models to identify prognostic senescence-related mRNAs.
  • Integrated identified mRNAs with clinical-pathological features to construct a prognostic nomogram and assess immune infiltration.

    • Main Results:

    • A risk model comprising 12 senescence-related mRNAs (IGFBP1, TLR3, WT1, ID1, PTTG1, ERRFI1, HEPACAM, MAP2K3, RAD21, NANOG, PRKCD, SOX5) was developed.
    • The risk score derived from these mRNAs was a significant independent predictor of NSCLC prognosis (HR > 1, p < 0.001).
    • The risk model demonstrated significant differences in immune infiltration and predicted immunotherapy response between high- and low-risk groups.

    Conclusions:

    • Cellular senescence-related mRNAs are reliable predictors of prognosis in non-small cell lung cancer (NSCLC).
    • The developed risk model and nomogram can aid in predicting NSCLC patient outcomes.
    • These senescence-related markers are associated with immune infiltration and may predict immunotherapy response in NSCLC.