Increased attention is paid to the structural components of tissues. These components are mostly collagens and various proteoglycans. Emerging evidence suggests that altered components and noncoded modifications of the matrix may be both initiators and drivers of disease, exemplified by excessive tissue remodeling leading to tissue stiffness, as well as by changes in the signaling potential of both intact matrix and fragments thereof. Although tissue structure until recently was viewed as a simple architecture anchoring cells and proteins, this complex grid may contain essential information enabling the maintenance of the structure and normal functioning of tissue. The aims of this review are to (1) discuss the structural components of the matrix and the relevance of their mutations to the pathology of diseases such as fibrosis and cancer, (2) introduce the possibility that post-translational modifications (PTMs), such as protease cleavage, citrullination, cross-linking, nitrosylation, glycosylation, and isomerization, generated during pathology, may be unique, disease-specific biochemical markers, (3) list and review the range of simple enzyme-linked immunosorbent assays (ELISAs) that have been developed for assessing the extracellular matrix (ECM) and detecting abnormal ECM remodeling, and (4) discuss whether some PTMs are the cause or consequence of disease. New evidence clearly suggests that the ECM at some point in the pathogenesis becomes a driver of disease. These pathological modified ECM proteins may allow insights into complicated pathologies in which the end stage is excessive tissue remodeling, and provide unique and more pathology-specific biochemical markers.

Emerging evidence suggests that altered components and posttranslational modifications of proteins in the extracellular matrix (ECM) may both initiate and drive disease progression. The ECM is a complex grid consisting of multiple proteins, most of which play a vital role in containing the essential information needed for maintenance of a sophisticated structure anchoring the cells and sustaining normal function of tissues. Therefore, the matrix itself may be considered as a paracrine/endocrine entity, with more complex functions than previously appreciated. The aims of this review are to 1) explore key structural and functional components of the ECM as exemplified by monogenetic disorders leading to severe pathologies, 2) discuss selected pathological posttranslational modifications of ECM proteins resulting in altered functional (signaling) properties from the original structural proteins, and 3) discuss how these findings support the novel concept that an increasing number of components of the ECM harbor signaling functions that can modulate fibrotic liver disease. The ECM entails functions in addition to anchoring cells and modulating their migratory behavior. Key ECM components and their posttranslational modifications often harbor multiple domains with different signaling potential, in particular when modified during inflammation or wound healing. This signaling by the ECM should be considered a paracrine/endocrine function, as it affects cell phenotype, function, fate, and finally tissue homeostasis. These properties should be exploited to establish novel biochemical markers and antifibrotic treatment strategies for liver fibrosis as well as other fibrotic diseases.

Recent research in the field of osteoarthritis (OA) has focused on understanding the underlying molecular and clinical phenotypes of the disease. This narrative review article focuses on recent advances in our understanding of the phenotypes of OA and proposes that the disease represents a diversity of clinical phenotypes that are underpinned by a number of molecular mechanisms, which may be shared by several phenotypes and targeted more specifically for therapeutic purposes. The clinical phenotypes of OA supposedly have different underlying etiologies and pathogenic pathways and they progress at different rates. Large OA population cohorts consist of a majority of patients whose disease progresses slowly and a minority of individuals whose disease may progress faster. The ability to identify the people with relatively rapidly progressing OA can transform clinical trials and enhance their efficiency. The identification, characterization, and classification of molecular phenotypes of rapidly progressing OA, which represent patients who may benefit most from intervention, could potentially serve as the basis for precision medicine for this disabling condition. Imaging and biochemical markers (biomarkers) are important diagnostic and research tools that can assist with this challenge.

The success of disease-modifying osteoarthritis drug (DMOAD) development is still elusive. While there have been successes in preclinical and early clinical studies, phase 3 clinical trials have failed so far and there is still no approved, widely available DMOAD on the market. The latest research suggests that, among other causes, poor trial outcomes might be explained by the fact that osteoarthritis (OA) is a heterogeneous disease with distinct phenotypes. OA trials might be more successful if they would address and target a specific phenotype. The increasing availability of advanced techniques to detect particular OA characteristics expands the possibilities to distinguish between such potential OA phenotypes. Magnetic resonance imaging is among the key imaging techniques to stratify and monitor patients with changes in bone, cartilage and inflammation. Biochemical markers have mainly used as secondary parameters and could further delineate phenotypes. Moreover, post-hoc analyses of trial data have suggested the existence of distinct pain phenotypes and their relevance in the design of clinical trials. Although ongoing work in the field supports the concept of OA heterogeneity, this has not yet resulted in more effective treatment options. This paper reviews the current knowledge about potential OA phenotypes and suggests that combining patient clinical data, quantitative imaging, biochemical markers and utilizing data-driven approaches in patient selection and efficacy assessment will allow for more successful development of effective DMOADs.

Different stimulants might induce different extracellular matrix profiles. It is essential to gain an understanding and quantification of these changes to allow for focused anti-fibrotic drug development. This study investigated the expression of extracellular matrix by dermal fibroblast mimicking fibrotic skin diseases as SSc using clinically validated biomarkers. Primary healthy human dermal fibroblasts were grown in media containing FICOLL. The cells were stimulated with PDGF-AB, TGF-β1, or IL-6. Anti-fibrotic compounds (iALK-5, Nintedanib) were added together with growth factors. Biomarkers of collagen formation and degradation together with fibronectin were evaluated by ELISAs in the collected supernatant. Immunohistochemical staining was performed to visualize fibroblasts and proteins, while selected gene expression levels were examined through qPCR. TGF-β and PDGF, and to a lesser extent IL-6, increased the metabolic activity of the fibroblasts. TGF-β primarily increased type I collagen and fibronectin protein and gene expression together with αSMA. PDGF stimulation resulted in increased type III and VI collagen formation and gene expression. IL-6 decreased fibronectin levels. iALK5 could inhibit TGF-β induced fibrosis while nintedanib could halt fibrosis induced by TGF-β or PDGF. Tocilizumab could not inhibit fibrosis induced in this model. The extent and nature of fibrosis are dependent on the stimulant. The model has potential as a pre-clinical model as the fibroblasts fibrotic phenotype could be reversed by an ALK5 inhibitor and Nintedanib.