Proteomics as a tool to improve novel insights into skin diseases: what we know and where we should be going

Abstract

BackgroundBiochemical processes involved in complex skin diseases (skin cancers, psoriasis, and wound) can be identified by combining proteomics analysis and bioinformatics tools, which gain a next-level insight into their pathogenesis, diagnosis, and therapeutic targets.MethodsArticles were identified through a search of PubMed, Embase, and MEDLINE references dated to May 2022, to perform system data mining, and a search of the Web of Science (WoS) Core Collection was utilized to conduct a visual bibliometric analysis.ResultsAn increased trend line revealed that the number of publications related to proteomics utilized in skin diseases has sharply increased recent years, reaching a peak in 2021. The hottest fields focused on are skin cancer (melanoma), inflammation skin disorder (psoriasis), and skin wounds. After deduplication and title, abstract, and full-text screening, a total of 486 of the 7,822 outcomes met the inclusion/exclusion criteria for detailed data mining in the field of skin disease tooling with proteomics, with regard to skin cancer. According to the data, cell death, metabolism, skeleton, immune, and inflammation enrichment pathways are likely the major part and hotspots of proteomic analysis found in skin diseases. Also, the focuses of proteomics in skin disease are from superficial presumption to depth mechanism exploration within more comprehensive validation, from basic study to a combination or guideline for clinical applications. Furthermore, we chose skin cancer as a typical example, compared with other skin disorders. In addition to finding key pathogenic proteins and differences between diseases, proteomic analysis is also used for therapeutic evaluation or can further obtain in-depth mechanisms in the field of skin diseases.ConclusionProteomics has been regarded as an irreplaceable technology in the study of pathophysiological mechanism and/or therapeutic targets of skin diseases, which could provide candidate key proteins for the insight into the biological information after gene transcription. However, depth pathogenesis and potential clinical applications need further studies with stronger evidence within a wider range of skin diseases.

Regenerative Cosmetics: Skin Tissue Engineering for Anti-Aging, Repair, and Hair Restoration

“…Proteomics, the comprehensive study of proteins, has emerged as a powerful tool to identify biomarkers in diseased skin [77], which could be potentially useful to develop targeted cosmetic therapies. Other applications in regenerative cosmetics include elucidating cellular processes involved in skin aging, regeneration, and damage [78], and characterizing biocompatible materials used in engineered skin substitutes [79].…”

Unveiling the Role of Endoplasmic Reticulum Stress Pathways in Canine Demodicosis

“…Research into the pathogenesis of canine demodicosis has mainly focused on mRNA expression changes in both blood and tissue, with only a few studies exploring changes at the protein level using immunohistochemistry and flow cytometry [13,14,[17][18][19][20][21][22][23][24][25][26][27]. Protein-level studies have primarily focused on assessing a limited panel of proteins such as cytokines and cell receptors [17-19, 21, 23].…”

“…Protein‐level studies have primarily focused on assessing a limited panel of proteins such as cytokines and cell receptors [17–19, 21, 23]. Proteomics is a crucial technology in human medicine for understanding disease pathogenesis, discovering biomarkers and identifying potential treatment targets [28]. Proteomics offers advantages over conventional genomics and transcriptomics tools as it can detect post‐translational modifications like phosphorylation, glycosylation and acetylation, providing a deeper characterisation of skin diseases' pathogenesis [29].…”

A bibliometric analysis of hotpots and trends for the relationship between skin inflammation and regeneration

“…Two software, CiteSpace and VOSviewer, are commonly used for visual analysis (25). These software provide researchers a comprehensive insight into the field of research (26), which then enables them to assess progress in both qualitative and quantitative research and position their anticipated contributions to specific areas of research (26).…”