Reducing inter-observer variability: harnessing molecular insights for clinical applications

Pathological assessment of tissue samples is crucial for diagnosis and optimal treatment decisions. However, pathology often suffers from subjectivity, resulting in inter-observer variability, and has limitations in identifying subtle molecular changes. Proteomics offers a promising solution by providing both molecular evidence and unbiased classification, thereby increasing the quality and reliability of tissue assessments. For proteomics to be useful, the molecular information from formalin-fixed paraffin-embedded (FFPE) biopsy tissues must be consistent, quantitatively accurate, and rich in clinically relevant molecular information.

Over the years, we have developed several methods for both fresh frozen (FF) and FFPE tissues, aiming to deliver results quickly (within 24 hours) and in line with current pathology practices.

We will present a range of methods that work with tissues, albeit with varying success rates and identification numbers. Key factors guiding our choice of method include integration with current pathology procedures and the analytical repeatability on tens to hundreds of biopsies. Currently, we have achieved a throughput where, within the scope of 24 hours, the workflow reveals molecular differences and similarities of over 5000 proteins per biopsy, across hundreds of patient samples.

The methods we present are based on data-independent acquisition mass spectrometry (diaMS), generating gigabytes of data per sample per time-point, with exceptionally high quantitative accuracy. The FFPE-based method we conclude with provides a coefficient of variation below 20%, analysing over 5000 proteins per sample in parallel.

We will highlight findings from an ongoing large cohort study consisting of hundreds of transplant biopsies, revealing physical parameters such as the effects of size, time in the autosampler, and their impact on clinical validation.

The findings presented here demonstrate the ease, speed, and robustness of the MS-based method. From minute tissue sections, a wealth of molecular data can assist and enhance pathology, potentially reducing inter-observer variability.