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Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
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Related Experiment Video

Updated: Oct 7, 2025

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing
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FPIA: A database for gene fusion profiling and interactive analyses.

Lu Huang1, Huimin Zhu1, Zhenhua Luo2

  • 1Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China.

International Journal of Cancer
|January 5, 2022
PubMed
Summary

Fusion profiling interactive analysis (FPIA) is a new web server for exploring gene fusions in 33 cancer types. This tool aids researchers in discovering potential therapeutic targets and generating hypotheses from multi-omics data.

Keywords:
TCGAgene fusioninteractive analysismultiomicsnovel peptide

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Area of Science:

  • Oncology
  • Bioinformatics
  • Genomics

Background:

  • Gene fusions are key drivers in cancer development and serve as important biomarkers and therapeutic targets.
  • Existing gene fusion databases lack interactive analytical capabilities for comprehensive data exploration.

Purpose of the Study:

  • To introduce Fusion Profiling Interactive Analysis (FPIA), a web server designed for interactive and customizable analysis of fusion genes.
  • To provide researchers with a tool for exploring multi-omics data associated with gene fusions across various cancer types.

Main Methods:

  • Development of a web server, FPIA, integrating data from The Cancer Genome Atlas (TCGA).
  • Inclusion of 31,633 fusion events from 6,910 patients across 33 cancer types.
  • Implementation of multi-omics analysis capabilities including gene expression, mutations, and immune cell infiltration.

Main Results:

  • FPIA enables exploration of fusion-associated biological and molecular differences.
  • The platform facilitates analysis of gene expression, tumor purity, ploidy, mutations, copy number variations, protein expression, immune cell infiltration, stemness, telomere length, microsatellite instability, survival, and novel peptides.
  • The server currently hosts data for 33 cancer types from TCGA.

Conclusions:

  • FPIA complements existing gene fusion databases by offering multi-omics analysis, integrated features, and a user-friendly interface.
  • The comprehensive analyses provided by FPIA are expected to facilitate data mining, hypothesis generation, and the discovery of novel therapeutic targets in cancer research.