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Related Concept Videos

Ribosome Profiling02:24

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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RNA Splicing01:32

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Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...
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Related Experiment Video

Updated: Nov 18, 2025

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy
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Transcriptome analysis and prognostic model construction based on splicing profiling in glioblastoma.

Jiting Qiu1, Chunhui Wang2, Hongkang Hu2

  • 1Department of Neurosurgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 201803, P.R. China.

Oncology Letters
|February 8, 2021
PubMed
Summary

This study reveals alternative splicing (AS) profiling as a key prognostic indicator for glioblastoma (GBM). Novel genomic models based on AS events can improve risk stratification and treatment strategies for aggressive brain tumors.

Keywords:
alternative splicingalternative splicing signatureglioblastomaprognostic modelsplicing factors

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Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • Glioblastoma (GBM) is an aggressive brain tumor with poor prognosis.
  • Current prognostic models for GBM lack comprehensive analysis of alternative splicing (AS) profiling.

Purpose of the Study:

  • To systematically analyze the prognostic significance of AS profiling in GBM.
  • To develop novel prognostic models for GBM based on AS events and splicing factors.

Main Methods:

  • Utilized RNA-sequencing and clinical data from The Cancer Genome Atlas and SpliceAid2 database.
  • Employed least absolute shrinkage and selection operator (LASSO) Cox regression for prognostic model assessment.
  • Constructed a correlation network between survival-associated AS events and splicing factors.

Main Results:

  • Developed robust prognostic models for GBM risk stratification based on AS event types.
  • Identified a final prognostic signature as an independent predictor of GBM patient outcomes (HR=4.61).
  • Highlighted heat shock protein b-1, protein arginine N-methyltransferase 5, protein FAM50B, and BiP as independent prognostic factors.

Conclusions:

  • Alternative splicing profiling offers a valuable tool for GBM prognosis.
  • The developed genomic models can enhance risk stratification and inform treatment strategies.
  • Findings support the development of novel therapeutic approaches for glioblastoma.