Cancer Research

Rapid RNA biomarker discovery

RNA Biomarker Discovery

Suitable biomarkers are key to improve cancer screening, diagnosis and monitoring. Which biomarker will prove to be the best?

Ease your path to cancer biomarker discoveries and get results that are relevant with our portfolio of comprehensive Sample to Insight workflows for cancer miRNA, cancer gene expression, transcriptome or functionality studies. From FFPE samples to FFPE RNA-seq and discovering  new cancer pathway, QIAGEN empowers cancer researchers with trusted and innovative solutions to increase your efficiency in  RNA biomarker research.

Cancer RNA biomarkers icon

Recognizing trends in cancer research can help to accelerate our knowledge and push the field forward. Share your opinion on hot topics and see the results with our live polls. Look out for them on our community pages and let us know if you have an idea for a new poll.

FFPE teaser
Successful biomarker profiling from FFPE samples – a series of tips and tricks

QIAGEN scientists share their expertise:

  • miRNAs can serve as invaluable cancer biomarkers – what do you need to consider for primer design, quality control and normalization strategies in miRNA qPCR analysis?
  • RNA-seq and especially rRNA removal from FFPE samples are challenging due to the degraded nature of the RNA – how can you best perform whole transcriptome RNA-seq?

Get answers on these questions and many more in our talk series

Guidelines for Profiling Biofluid miRNAs

These guidelines provide important information and tips to ensure successful miRNA profiling using NGS or PCR-based techniques with a focus on biofluid sample types including blood, serum/plasma, urine and exosomes. The extensive brochure combines the knowledge and expertise from our experts in sample collection and stabilization, isolation of miRNA, NGS and data analysis, PCR-based analysis and quality control. 

Recommended products for cell-free miRNA analysis:
Use Locked Nucleic Acids (LNA)
Learn more about our expanded miRNA qPCR portfolio