Novel Approach for the Assessment of Meniscus Degeneration Using Imaging Mass Spectrometry (IMS)

Meniscal tears are among the most common knee injuries due to traumatic injury, and degenerative processes which can be strongly associated with osteoarthritis. Since insurance companies compensate only traumatic injuries exact diagnosis is required in the German insurance system. Current histological examination of the meniscus tear cannot sufficiently assess severity of the degeneration, due to high inter-observer variation in the diagnostic procedure, as well as demonstrate whether meniscal injuries are attributable to old age and disease or trauma. In this regard, we use IMS to identify molecular signatures capable to discriminate meniscus tears into traumatic and degenerative types which cannot be distinguished with current histopathological methods. A study design of 14 cases was used in our initial discovery set to determine differential expression of proteins in high and low degree cartilage lesions. Tissue sections (3μm) from formalin-fixed paraffin-embedded specimens of meniscal tear were collected for IMS analysis and for histological staining. Histopathological examination was assessed by two pathologists, and specific areas showing high and low degeneration were digitally marked in each sample. For IMS analysis, sections were deparaffinized, antigen retrieved, and in situ digested with trypsin. 200µl trypsin solution (0.5µg/µl) and α-Cyano-4-hydroxycinnamic acid matrix solution (7 mg/ml in 50/50 acetonitrile /0.5% TFA) were applied onto the sections using an ImagePrep devise (Bruker Daltonik GmbH), and subsequent MALDI analysis was performed at image resolution of 150 µm using an Autoflex Speed TOF/TOF mass spectrometer (Bruker Daltonik GmbH). Mass spectra from the marked areas were exported and loaded into ClinProTools 3.0 software (Bruker Daltonik GmbH) for statistical analysis. Pairwise statistical comparison was performed on the basis of P-values from the Wilcoxon/Kruskal-Wallis test (p<0.05) and with a 99.9% of confidence level. Mass spectra profiles were extracted from tissue samples consisting of two matched pairs of high-degeneration and low-degeneration counterpart areas occurring in the same individual. Two sample groups (high degeneration and low degeneration) were then created in order to produce an average spectrum representative of a group identified through histology. Statistical analysis revealed nearly a 2-fold increase of 14 m/z signals in the high degeneration sample group, including m/z 548.2, 585.3, 603.2, 614.5, 656.3, 1032.6, 1151.6, 1349.7, 1431.8, 1350.7, 1912.9, 1913.9, 1925.9, 1927.1. The overlay of the marked histological section and the image obtained from IMS analysis showed correlation with regard to the distribution of the discriminant peptides. We provided evidence that IMS technology can be used to rapidly and accurately to distinguish high from low grade meniscus degeneration at the peptide level, supporting the diagnosis made by the pathologists. This methodology will be applied to a larger cohort of patient biopsies in order to create a classification model able to distinguish different grades of degeneration, as well as to assess the origin of meniscal tear. Further work will include identification of the peptide features detected in order to rationalize the biological significance.