Image-guided Coring for Large-scale Studies in Molecular Pathology.

Area of Science:

• Molecular Pathology
• Digital Pathology
• Biobanking

Background:

• Formalin-fixed paraffin-embedded (FFPE) tissue block sampling is crucial for molecular pathology.
• Traditional methods can lack precision, impacting downstream analyses.
• Digital pathology offers potential for improved tissue selection and sampling.

Purpose of the Study:

• To evaluate image-guided coring (IGC) for tissue-based and nucleic acid-based molecular pathology projects.
• To assess IGC's utility in constructing tissue microarrays (TMAs).
• To determine the correlation between image-derived nuclear counts and RNA yields from FFPE samples.

Main Methods:

• IGC was used to construct a TMA of 198 normal and breast cancer cores.
• IGC was employed for FFPE block sampling prior to RNA extraction.
• Computational image analysis quantified nuclear density, and regression models estimated RNA yields based on nuclear count, block age, and core diameter.

Main Results:

• IGC demonstrated high accuracy in obtaining both tumor and normal breast tissue for TMA construction.
• Nuclear count and core diameter were identified as the strongest predictors of RNA yield in both normal and tumor tissues.
• Significant associations were found between quantitative nuclear counts from IGC images and RNA yields.

Conclusions:

• IGC is an effective technique for sampling FFPE tissue blocks for TMA construction and nucleic acid extraction.
• Integrating computational image analysis with IGC shows promise for optimizing tumor sampling in large-scale molecular studies.
• This approach enhances precision in tissue selection for molecular analyses.