Myelofibrosis progression grading based on type I and type III collagen and fibrillin 1 expression boosted by whole slide image analysis

• Published in: Histopathology 2023-03, Vol.82 (4), p.622-632
• Main Authors: Szekely, Tamas, Wichmann, Barna, Maros, Mate E, Csizmadia, Annamaria, Bodor, Csaba, Timar, Botond, Krenacs, Tibor
• Format: Article
• Language: English
• Subjects: Automation; Bone marrow; Collagen; Collagen Type I; Collagen Type III; Cytology; Extracellular matrix; Extracellular Matrix Proteins; Fibrillin; Fibrillin-1; Fibrillogenesis; Fibrosis; Humans; Image processing; Immunohistochemistry; Microfibrils; Myelofibrosis; Original; Osteoclastogenesis; Osteosclerosis; Primary Myelofibrosis - diagnosis; primary myelofibrosis progression; Silver; Stromal cells; Transforming Growth Factor beta; Transforming growth factor-b; type I collagen; type III collagen; whole slide digital image analysis
• ISSN: 0309-0167; 1365-2559
• DOI: 10.1111/his.14846

Aims: The progression of primary myelofibrosis is characterised by ongoing extracellular matrix deposition graded based on ‘reticulin’ and ‘collagen’ fibrosis, as revealed by Gomori's silver impregnation. Here we studied the expression of the major extracellular matrix proteins of fibrosis in relation to diagnostic silver grading supported by image analysis. Methods and results: By using automated immunohistochemistry, in this study we demonstrate that the expression of both types I and III collagens and fibrillin 1 by bone marrow stromal cells can reveal the extracellular matrix scaffolding in line with myelofibrosis progression as classified by silver grading. ‘Reticulin’ fibrosis indicated by type III collagen expression and ‘collagen’ fibrosis featured by type I collagen expression were parallel, rather than sequential, events. This is line with the proposed role of type III collagen in regulating type I collagen fibrillogenesis. The uniformly strong fibrillin 1 immune signals offered the best inter‐rater agreements and the highest statistical correlations with silver grading of the three markers, which was robustly confirmed by automated whole slide digital image analysis using a machine learning‐based algorithm. The progressive up‐regulation of fibrillin 1 during myelofibrosis may result from a negative feedback loop as fibrillin microfibrils sequester TGF‐β, the major promoter of fibrosis. This can also reduce TGF‐β‐induced RANKL levels, which would stimulate osteoclastogenesis and thus can support osteosclerosis in advanced myelofibrosis. Conclusions: Through the in‐situ detection of these extracellular matrix proteins, our results verify the molecular pathobiology of fibrosis during myelofibrosis progression. In particular, fibrillin 1 immunohistochemistry, with or without image analysis, can complement diagnostic silver grading at decent cell morphology. In situ detection of type‐I and type‐III collagens and fibrillin‐1 extracellular matrix molecules using immunohistochemistry can verify the molecular pathobiology of fibrosis during myelofibrosis progression in parallel with Gomori’s silver impregnation. While the ongoing collagen deposition represent a pro‐fibrotic response, the expression of fibrillin‐1 protein may result from a negative feedback loop response to the elevated pro‐fibrotic TGF‐β levels. Machine learning based digital image analysis of fibrillin‐1 immunosignals showed high correlations both with the eye control scoring of the imm