Mapping the rapid growth of multi-omics in tumor immunotherapy: Bibliometric evidence of technology convergence and paradigm shifts DOI Creative Commons
Huijing Dong,

Xinmeng Wang,

Yumin Zheng

et al.

Human Vaccines & Immunotherapeutics, Journal Year: 2025, Volume and Issue: 21(1)

Published: April 24, 2025

This study aims to fill the knowledge gap in systematically mapping evolution of omics-driven tumor immunotherapy research through a bibliometric lens. While omics technologies (genomics, transcriptomics, proteomics, metabolomics)provide multidimensional molecular profiling, their synergistic potential with remains underexplored large-scale trend analyses. A comprehensive search was conducted using Web Science Core Collection for literature related immunotherapy, up August 2024. Bibliometric analyses, R version 4.3.3, VOSviewer 1.6.20, and Citespace 6.2, examined publication trends, country institutional contributions, journal distributions, keyword co-occurrence, citation bursts. analysis 9,494 publications demonstrates rapid growth since 2019, China leading output (63% articles) yet exhibiting limited multinational collaboration (7.9% vs. UK's 61.8%). Keyword co-occurrence burst analyses reveal evolving frontiers: early emphasis on "PD-1/CTLA-4 blockade" has transitioned toward "machine learning," "multi-omics," "lncRNA," reflecting shift predictive modeling biomarker discovery. Multi-omics integration facilitated development immune infiltration-based prognostic models, such as TIME subtypes, which have been validated across multiple types, inform clinical trial design (e.g. NCT06833723). Additionally, proteomic melanoma patients suggests that metabolic biomarkers, particularly oxidative phosphorylation lipid metabolism, may stratify responders PD-1 blockade therapy. Moreover, spatial confirmed ENPP1 novel therapeutic target Ewing sarcoma. Citation trends underscore translation, mutation-guided therapies. Omics are transforming by enhancing discovery improving predictions. Future advancements will necessitate longitudinal monitoring, AI-driven multi-omics integration, international accelerate translation. presents systematic framework exploring emerging frontiers offers insights optimizing precision-driven immunotherapy.

Language: Английский

Therapeutic potential of exosomal lncRNAs derived from stem cells in wound healing: focusing on mesenchymal stem cells DOI Creative Commons

Ali Morabbi,

Mohammad Karimian

Stem Cell Research & Therapy, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 11, 2025

The self-renewal ability and multipotency of stem cells give them great potential for use in wound healing. Stem cell-derived exosomes, owing to their close biological resemblance parent cells, offer a more efficient, safer, economical approach facilitating cellular communication interactions within different environments. This makes particularly valuable the treatment both acute chronic wounds, such as lacerations, burns, diabetic ulcers. Long non-coding RNAs (lncRNAs) enclosed one leading actors these extracellular microvesicles, through interaction with miRNAs regulation various signaling pathways involved inflammation, angiogenesis, cell proliferation, migration, could heal wounds. Exosome-derived lncRNAs from facilitate matrix remodeling between macrophages fibroblasts. Moreover, alongside regulating expression inflammatory cytokines, controlling reactive oxygen species levels, enhancing autophagic activity, they also modulate immune responses support Regulating genes related by increasing blood supply accelerating delivery essential substances environment, is another effect exosomal derived These can enhance skin healing homeostasis, proliferation differentiation wound-healing process, fibroblast viability migration injury site. Ultimately, exosome-derived novel insights into molecular mechanisms underlying improved They pave way therapeutic strategies, fostering further research better future. Meanwhile, exosomes mesenchymal due exceptional regenerative properties, well have emerged innovative tools review article aims narrate roles focus on cells.

Language: Английский

Citations

0

Mapping the rapid growth of multi-omics in tumor immunotherapy: Bibliometric evidence of technology convergence and paradigm shifts DOI Creative Commons
Huijing Dong,

Xinmeng Wang,

Yumin Zheng

et al.

Human Vaccines & Immunotherapeutics, Journal Year: 2025, Volume and Issue: 21(1)

Published: April 24, 2025

This study aims to fill the knowledge gap in systematically mapping evolution of omics-driven tumor immunotherapy research through a bibliometric lens. While omics technologies (genomics, transcriptomics, proteomics, metabolomics)provide multidimensional molecular profiling, their synergistic potential with remains underexplored large-scale trend analyses. A comprehensive search was conducted using Web Science Core Collection for literature related immunotherapy, up August 2024. Bibliometric analyses, R version 4.3.3, VOSviewer 1.6.20, and Citespace 6.2, examined publication trends, country institutional contributions, journal distributions, keyword co-occurrence, citation bursts. analysis 9,494 publications demonstrates rapid growth since 2019, China leading output (63% articles) yet exhibiting limited multinational collaboration (7.9% vs. UK's 61.8%). Keyword co-occurrence burst analyses reveal evolving frontiers: early emphasis on "PD-1/CTLA-4 blockade" has transitioned toward "machine learning," "multi-omics," "lncRNA," reflecting shift predictive modeling biomarker discovery. Multi-omics integration facilitated development immune infiltration-based prognostic models, such as TIME subtypes, which have been validated across multiple types, inform clinical trial design (e.g. NCT06833723). Additionally, proteomic melanoma patients suggests that metabolic biomarkers, particularly oxidative phosphorylation lipid metabolism, may stratify responders PD-1 blockade therapy. Moreover, spatial confirmed ENPP1 novel therapeutic target Ewing sarcoma. Citation trends underscore translation, mutation-guided therapies. Omics are transforming by enhancing discovery improving predictions. Future advancements will necessitate longitudinal monitoring, AI-driven multi-omics integration, international accelerate translation. presents systematic framework exploring emerging frontiers offers insights optimizing precision-driven immunotherapy.

Language: Английский

Citations

0