Profiling of the metabolic transcriptome via single molecule molecular inversion probes

Tessa de Bitter1, Carlijn van de Water1, Corina van den Heuvel1

  • 1Dept of Pathology, Radboud University Medical Centre, Nijmegen, The Netherlands.

Scientific Reports
|September 14, 2017
PubMed

Insights

A novel RNA sequencing method using single molecule molecular inversion probes (smMIPs) effectively profiles cancer metabolism. This cost-effective technique aids in identifying therapeutic targets for individual cancers in clinical settings.

Area of Science:

  • Biochemistry
  • Molecular Biology
  • Oncology

Background:

  • Cancer cells exhibit unique metabolic alterations, presenting potential therapeutic targets.
  • Identifying these cancer-specific metabolic pathways requires robust and accessible methods.
  • Current methods like 13C-tracing are costly and complex, limiting their clinical use.

Purpose of the Study:

  • To validate a novel metabolic profiling technique using multiplex targeted next-generation RNA sequencing with single molecule molecular inversion probes (smMIPs).
  • To assess the utility of smMIP-profiling for measuring the activity and mutations of genes encoding metabolic enzymes.
  • To evaluate the potential of this method for routine patient care.

Main Methods:

  • Multiplex targeted next-generation RNA sequencing utilizing single molecule molecular inversion probes (smMIPs).
  • Profiling of an isogenic cell line pair with differing Von Hippel Lindau protein expression.
  • Measurement of gene activity and mutations in genes encoding metabolic enzymes.

Main Results:

  • smMIP-profiling successfully provided relevant information on active metabolic pathways.
  • The technique demonstrated its ability to measure gene activity and mutations in metabolic enzymes.
  • The method is cost-effective and suitable for medium-to-high throughput analysis.

Conclusions:

  • smMIP-based targeted RNA sequencing is a validated, cost-effective method for metabolic profiling.
  • This approach can identify active metabolic pathways and gene alterations in cancer.
  • Its suitability for medium-high throughput analysis makes it promising for routine patient care and cancer metabolism research.