PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 30, 2026Journal of Cancer Research and Clinical Oncology0 citationsOpen Access

Knowledge mapping and bibliometric insights of scientific research on targeted protein degradation in oncology

MSMoutaz W. Sweileh

Key Points

  • To systematically map the scientific landscape of targeted protein degradation in oncology through bibliometric analysis.
  • Conducted bibliometric analysis using the Scopus database for publications from January 2000 to December 2025.
  • Analyzed indicators such as publication trends, citations, H-index, and co-authorship patterns.
  • Utilized VOSviewer for network visualization of keyword co-occurrence and international collaboration.
  • Identified 1334 publications with a compound annual growth rate of 51.9% from 2016 to 2025.
  • Field growth was characterized by high interdisciplinary collaboration with significant contributions from China and the USA.
  • Found that PROTAC technology is a primary focus, linked to oncogenic targets and characterized by an impressive H-index of 111.

Abstract

Disruption of cellular proteostasis leads to the accumulation and persistence of pathogenic proteins that drive oncogenesis. Key oncogenic and tumor suppressor proteins are frequently dysregulated in cancer, yet remain challenging to target by conventional small-molecule inhibitors. Targeted protein degradation (TPD), particularly through Proteolysis Targeting Chimeras (PROTACs) and molecular glues, has emerged as a transformative strategy that enables catalytic and selective elimination of disease-driving proteins. This study aimed to systematically map the global scientific landscape of TPD research in oncology using bibliometric methods. A comprehensive bibliometric analysis was conducted using the Scopus database covering articles published between January 2000 and December 2025. Bibliometric indicators including publication trends, compound annual growth rate (CAGR), citations, H-index, authorship pattern, and institutional contributions were analyzed. Network visualization of keyword co-occurrence, chronological evolution, and international collaboration were performed using VOSviewer. A total of 1334 publications were identified, demonstrating exponential growth, particularly after 2018, with a CAGR of 51.9% (2016–2025). The field is highly interdisciplinary, dominated by biochemistry, pharmacology, and chemistry. The dataset exhibited a high H-index (111), reflecting rapid intellectual maturation. Authorship analysis revealed a median of 10 authors per article, underscoring extensive collaboration. China and the United States emerged as dominant contributors, forming central hubs in the global research network. PROTAC technology represented the primary research focus, with strong association to ubiquitin–proteasome mechanisms and oncogenic targets such as BRD4, MYC, androgen receptor, and estrogen receptor. Highly cited articles were predominantly methodological, highlighting foundational advances in degrader design and mechanism. TPD research is rapidly evolving toward clinically driven innovations with emerging focus on advanced delivery systems, lysosome-targeting strategies, next-generation degrader design strategies, and combination therapies to overcome pharmacokinetic and therapeutic limitations. TPD research in oncology is undergoing rapid expansion and transitioning from conceptual innovation to translational application. PROTACs dominate the field due to their modularity and catalytic efficiency, although challenges remain, including pharmacokinetic limitations, restricted E3 ligase diversity, and potential resistance mechanisms. Overall, TPD represents a paradigm shift toward event-driven pharmacology with significant potential to transform precision oncology by enabling the therapeutic elimination of previously intractable targets.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Moutaz W. Sweileh (2026) studied this question.

synapsesocial.com/papers/69f2f0e31e5f7920c6386f0dhttps://doi.org/10.1007/s00432-026-06482-0
Ask AI
Helpful
Bookmark
Share
View Full Paper