An optimized workflow for improved gene expression profiling for formalin-fixed, paraffin-embedded tumor samples

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Whole genome microarray gene expression profiling is vital for identifying cancer biomarkers.
• Diagnostic samples are often formalin-fixed, paraffin-embedded tissue (FFPET), posing challenges for gene expression analysis.
• Existing methods are suboptimal for FFPET samples, limiting biomarker discovery.

Purpose of the Study:

• To develop and validate a novel workflow and data analysis method for gene expression profiling of FFPET samples.
• To optimize the detection of prognostic and predictive genetic markers in human cancers using FFPET.
• To overcome limitations associated with RNA extraction and amplification from FFPET.

Main Methods:

• Matched pairs of breast tumor samples were preserved as FFPET and fresh-frozen (FF).
• RNA was extracted from FFPET samples and amplified using three commercial kits.
• In silico optimization of the microarray probe set was performed to improve accuracy.

Main Results:

• The FFPET-optimized workflow demonstrated 80% specificity and 97% sensitivity compared to FF samples.
• In silico probe set redesign enhanced sequence detection sensitivity.
• The workflow successfully detected more genes from FFPET samples than previous methods.

Conclusions:

• The developed FFPET-optimized workflow significantly improves gene detection capabilities.
• This advancement opens new avenues for the discovery and clinical application of mRNA biomarkers.
• The findings facilitate the use of archival FFPET samples for comprehensive cancer research.