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Related Concept Videos

Tumor Progression02:07

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The mammalian target of rapamycin or mTOR protein was discovered in 1994 due to its direct interaction with rapamycin. The protein gets its name from a yeast homolog called TOR. The mTOR protein complex in mammalian cells plays a major role in balancing anabolic processes such as the synthesis of proteins, lipids, and nucleotides and catabolic processes, such as autophagy in response to environmental cues, such as availability of nutrients and growth factors.
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Related Experiment Video

Updated: Dec 10, 2025

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
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muTarget: A platform linking gene expression changes and mutation status in solid tumors.

Ádám Nagy1,2, Balázs Győrffy1,2,3

  • 1Department of Bioinformatics, Semmelweis University, Budapest, Hungary.

International Journal of Cancer
|September 3, 2020
PubMed
Summary

This study links cancer mutations to gene expression changes using The Cancer Genome Atlas data. A new portal (mutarget.com) aids in identifying biomarkers and therapeutic targets for personalized cancer therapies.

Keywords:
gene expressionnext-generation sequencingsolid tumorssomatic mutationtargeted therapy

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Area of Science:

  • Genomics
  • Transcriptomics
  • Cancer Research

Background:

  • Large oncology repositories offer paired genomic and transcriptomic data.
  • Understanding the relationship between gene mutations and expression is crucial for cancer research.

Purpose of the Study:

  • To identify gene expression changes associated with specific gene mutations.
  • To identify mutations that alter the expression of selected genes.
  • To develop a platform for rapid identification of mutational targets.

Main Methods:

  • Utilized The Cancer Genome Atlas (TCGA) for RNA-sequencing and mutation data.
  • Employed R statistical environment with tools like DESeq2, AnnotationDbi, and MAFtools.
  • Performed differential expression analysis using the Mann-Whitney U test.

Main Results:

  • Developed a database of 7876 solid tumors across 18 types with mutation and RNA-seq data.
  • Validated the pipeline through independent analyses in breast cancer, showing highly significant result overlap.
  • Established a portal (mutarget.com) for identifying novel mutational targets.

Conclusions:

  • Linking somatic mutations and gene expression facilitates biomarker and therapeutic target identification in solid tumors.
  • The online platform accelerates the development of personalized cancer therapies.
  • The approach aids in reducing development costs for novel targeted treatments.