Cooperation of Genomic, Transcriptomics and Proteomic Methods in the Detection of Mutated Proteins

Abstract

Insights

Genomic, transcriptomic, and proteomic analyses aid in characterizing tumors. TransPEM software facilitates neoantigen detection for targeted anti-tumor therapies by converting single nucleotide polymorphism data into peptide libraries.

Area of Science:

  • Bioinformatics
  • Genomics
  • Transcriptomics
  • Proteomics

Background:

  • Tumor heterogeneity poses challenges for non-specific anti-tumor therapies.
  • Advancements in genomic, transcriptomic, and proteomic methods allow detailed individual tumor characterization.
  • These methods, including sequencing, detect genetic variations and mutated proteins.

Purpose of the Study:

  • To describe bioinformatics analysis of genomic, transcriptomic, and proteomic data.
  • To present TransPEM software for converting single nucleotide polymorphism data into peptide libraries for neopeptide detection.
  • To outline proteomics methods and their limitations for anti-tumor therapy.

Main Methods:

  • Genomic, transcriptomic, and proteomic analyses for tumor characterization.
  • Whole-genome, whole-transcriptome, and exome sequencing for single nucleotide polymorphism detection.
  • Development and application of TransPEM software for data conversion.

Main Results:

  • TransPEM software enables the conversion of single nucleotide polymorphism data into peptide libraries.
  • This facilitates the detection of neopeptides using proteomic methods.
  • The study highlights the potential for combined methods to improve neoantigen discovery.

Conclusions:

  • Bioinformatics analysis integrating genomics, transcriptomics, and proteomics is crucial for personalized anti-tumor therapy.
  • TransPEM software offers a valuable tool for neoantigen identification.
  • Further development and application of these integrated approaches can enhance therapeutic strategies.