Scholarlink

<p>Oral stem cell research encompasses the study of dental pulp stem cells, periodontal ligament stem cells, regeneration of dental pulp and periodontal ligament, and therapeutic approaches for dental caries. Dental pulp stem cells, located in the oral cavity, have been applied to tooth, alveolar bone, and periodontal tissue regeneration and are anticipated to exert systemic therapeutic effects. Global efforts to identify biomarkers of oral disease have employed expression proteome analysis. However, because most proteins function only after undergoing post-translational modifications, methods based solely on expression proteomics remain limited. Consequently, increasing attention has focused on characterizing protein modifications. Advances now enable comprehensive measurement of modifications across the omics hierarchy, including the epitranscriptome, phosphoproteome, and metabolome, to clarify the layered interactions among the genome, epigenome, transcriptome, and metabolome. "Multi-omics" denotes the integration of multiple omics layers for analysis. Moreover, several omics layers can now be assessed at single-cell resolution, enabling a more detailed projection of biological phenomena and a more holistic understanding. Recently, multi-omics strategies have also been applied to oral stem cell research. This review summarizes emerging insights into oral cavity stem cell biology obtained through multi-omics approaches. We recognize the limitation that our search strategy relied exclusively on the MEDLINE database in PubMed and did not incorporate additional sources such as gray literature, conference proceedings, or clinical practice guidelines. Multi-omics analysis enables the elucidation of multilayered causal relationships in biological phenomena that were previously inaccessible using conventional single-omics approaches, by integrating multiple layers such as the genome (DNA), transcriptome (RNA), proteome (proteins), and metabolome (metabolites). Looking forward, the integration of AI and machine learning is expected to facilitate early diagnosis of oral diseases, precise patient stratification, and the advancement of personalized medicine.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Advances in Oral Cavity Stem Cell Research Revealed through Multi-omics Analysis

  • 期刊论文

  • 发表日期：

    2026年4月18日

查看全文
  • Sachio Tsuchida,
  • Hiroshi Umemura,
  • Masaki Nakajima,
  • Kazuhide Iizuka,
  • Isamu Shimazaki,
  • Elisa Shikata,
  • Tomohiro Nakayama

摘要

Oral stem cell research encompasses the study of dental pulp stem cells, periodontal ligament stem cells, regeneration of dental pulp and periodontal ligament, and therapeutic approaches for dental caries. Dental pulp stem cells, located in the oral cavity, have been applied to tooth, alveolar bone, and periodontal tissue regeneration and are anticipated to exert systemic therapeutic effects. Global efforts to identify biomarkers of oral disease have employed expression proteome analysis. However, because most proteins function only after undergoing post-translational modifications, methods based solely on expression proteomics remain limited. Consequently, increasing attention has focused on characterizing protein modifications. Advances now enable comprehensive measurement of modifications across the omics hierarchy, including the epitranscriptome, phosphoproteome, and metabolome, to clarify the layered interactions among the genome, epigenome, transcriptome, and metabolome. "Multi-omics" denotes the integration of multiple omics layers for analysis. Moreover, several omics layers can now be assessed at single-cell resolution, enabling a more detailed projection of biological phenomena and a more holistic understanding. Recently, multi-omics strategies have also been applied to oral stem cell research. This review summarizes emerging insights into oral cavity stem cell biology obtained through multi-omics approaches. We recognize the limitation that our search strategy relied exclusively on the MEDLINE database in PubMed and did not incorporate additional sources such as gray literature, conference proceedings, or clinical practice guidelines. Multi-omics analysis enables the elucidation of multilayered causal relationships in biological phenomena that were previously inaccessible using conventional single-omics approaches, by integrating multiple layers such as the genome (DNA), transcriptome (RNA), proteome (proteins), and metabolome (metabolites). Looking forward, the integration of AI and machine learning is expected to facilitate early diagnosis of oral diseases, precise patient stratification, and the advancement of personalized medicine.