Formalin-Fixed, Paraffin-Embedded Tissues (FFPE) as a Robust Source for the Profiling of Native and Protease-Generated Protein Amino Termini
Bibliographic record
Abstract
Dysregulated proteolysis represents a hallmark of numerous diseases. In recent years, increasing number of studies has begun looking at the protein termini in hope to unveil the physiological and pathological functions of proteases in clinical research. However, the availability of cryopreserved tissue specimens is often limited. Alternatively, formalin-fixed, paraffin-embedded (FFPE) tissues offer an invaluable resource for clinical research. Pathologically relevant tissues are often stored as FFPE, which represent the most abundant resource of archived human specimens. In this study, we established a robust workflow to investigate native and protease-generated protein N termini from FFPE specimens. We demonstrate comparable N-terminomes of cryopreserved and formalin-fixed tissue, thereby showing that formalin fixation/paraffin embedment does not proteolytically damage proteins. Accordingly, FFPE specimens are fully amenable to N-terminal analysis. Moreover, we demonstrate feasibility of FFPE-degradomics in a quantitative N-terminomic study of FFPE liver specimens from cathepsin L deficient or wild-type mice. Using a machine learning approach in combination with the previously determined cathepsin L specificity, we successfully identify a number of potential cathepsin L cleavage sites. Our study establishes FFPE specimens as a valuable alternative to cryopreserved tissues for degradomic studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".