Prognostic implications of ERLncRNAs in ccRCC: a novel risk score model and its association with tumor mutation burden and immune microenvironment

  • 0Shandong University of Traditional Chinese Medicine, Jinan, 250013, Shandong, China.

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Summary

This summary is machine-generated.

This study identifies a seven-gene signature of efferocytosis-related long noncoding RNAs (ERLncRNAs) for predicting outcomes and guiding immunotherapy in clear cell renal cell carcinoma (ccRCC). The signature aids in assessing prognosis and treatment response in ccRCC patients.

Area Of Science

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background

  • The role of efferocytosis-related long noncoding RNAs (ERLncRNAs) in clear cell renal cell carcinoma (ccRCC) remains underexplored.
  • Understanding these ERLncRNAs is crucial for developing novel prognostic and therapeutic strategies for ccRCC.

Purpose Of The Study

  • To identify and validate a prognostic signature of ERLncRNAs in ccRCC.
  • To characterize the immune landscape and predict immunotherapeutic response based on the ERLncRNA signature.

Main Methods

  • Utilized The Cancer Genome Atlas (TCGA) data for ccRCC samples.
  • Employed bioinformatics analyses including Pearson correlation, LASSO, and Cox regression for signature development.
  • Assessed immune cell infiltration, tumor mutational burden (TMB), tumor microenvironment (TME), and drug sensitivity.

Main Results

  • A novel seven-ERLncRNA signature (LINC01615, RUNX3-AS1, FOXD2-AS1, AC002070.1, LINC02747, LINC00944, AC092296.1) was identified.
  • The signature demonstrated strong prognostic prediction capabilities, validated by Kaplan-Meier, ROC curves, nomogram, and C-index.
  • Significant differences in immune landscape and TME characteristics were associated with the signature.

Conclusions

  • The developed seven-ERLncRNA signature holds significant potential for prognostic prediction in ccRCC.
  • This signature may serve as a valuable tool for assessing immunotherapeutic response in ccRCC patients.

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