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Related Concept Videos

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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Tumor suppressor genes are normal genes that can slow down cell division, repair DNA mistakes, or program the cells for apoptosis in case of irreparable damage. Hence, they play an essential role in preventing the proliferation of damaged cells.
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Related Experiment Video

Updated: Jun 14, 2025

The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
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Non-coding transcriptome profiles in clear-cell renal cell carcinoma.

Tereza Tesarova1,2, Ondrej Fiala3,4, Milan Hora5

  • 1Toxicogenomics Unit, National Institute of Public Health, Prague, Czech Republic. tereza.tesarova@szu.cz.

Nature Reviews. Urology
|September 6, 2024
PubMed
Summary
This summary is machine-generated.

Non-coding RNAs (ncRNAs) show promise as biomarkers for clear-cell renal cell carcinoma (ccRCC), aiding in personalized treatment. Further research and clinical trials are needed for their integration into patient care.

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Area of Science:

  • Uro-oncology
  • Molecular pathology
  • Biomarker discovery

Background:

  • Clear-cell renal cell carcinoma (ccRCC) is a prevalent urological cancer with rising incidence.
  • Identifying molecular biomarkers is crucial for predicting treatment response and personalizing therapy in ccRCC.
  • Non-coding RNAs (ncRNAs) are implicated in ccRCC pathogenesis and are being investigated as potential biomarkers.

Purpose of the Study:

  • To identify and evaluate non-coding RNA (ncRNA) biomarkers in clear-cell renal cell carcinoma (ccRCC).
  • To explore the association of ncRNA biomarkers with patient prognosis, pathological characteristics, and treatment outcomes.
  • To assess the potential of ncRNAs for personalized therapy selection in ccRCC.

Main Methods:

  • RNA sequencing analysis of ccRCC tissue samples.
  • Identification of dysregulated ncRNAs.
  • Correlation analysis of ncRNA expression with clinical parameters and treatment response.

Main Results:

  • Several ncRNAs were identified as dysregulated in ccRCC.
  • These ncRNAs demonstrate potential as prognostic and predictive biomarkers.
  • The findings suggest a role for ncRNAs in ccRCC development and progression.

Conclusions:

  • Dysregulated ncRNAs hold significant potential as biomarkers for ccRCC, aiding in prognosis and treatment selection.
  • Clinical implementation of ncRNA biomarkers is currently limited by validation and standardization challenges.
  • Accelerating clinical use requires comprehensive studies and integration into clinical trials.