Meme Kanserinde Gen Ekspresyonunun Küresel Araştırma Eğilimleri: 2020-2024 Yayınlarının Bibliyometrik İncelenmesi

Öz

Amaç: Bu çalışmada, 2020-2024 yılları arasında yayınlanmış “meme kanseri” ve “gen ekspresyonu” konularını ele alan makalelerin yayın eğilimleri, atıf kalıpları, önde gelen dergiler, katkıda bulunan ülkeler ve alandaki gelişen araştırma konularını inceleyerek belirlenmesi ve analiz edilmesi amaçlanmıştır. Yöntem: 2020-2024 yılları arasında yayımlanan ve Web of Science (WoS) Core Collection veri tabanında indekslenen “meme kanseri” ve “gen ekspresyonu” ile ilgili makaleler üzerinde bibliyometrik analiz yapıldı. Analizde en çok atıf alan makaleler, atıf sıklığı, zaman içindeki yayın eğilimleri, en çok yayın ve atıf alan ülkeler, önde gelen yazarlar, anahtar kelimeleri birlikte kullanımı ve en sık atıf alan kaynaklar gibi özelliklere göre analiz edildi. Bulgular: Toplam 5.095 makale tespit edildi. En yüksek yayın sayısı 2020 yılında kaydedilirken, 2024 yılına doğru kademeli bir düşüş yaşandığı görüldü. Yayınların önemli bir kısmı Çin ve Amerika Birleşik Devletleri kaynaklıdır. Makalelerin çoğu yüksek etkili dergilerde yayınlanmış ve çok sayıda atıf almıştır. Araştırma ağırlıklı olarak meme kanserinde tedavi stratejileri ve patojenik mekanizmalar bağlamında gen ekspresyonuna odaklanmıştır. Sonuç: Bu bibliyometrik analiz, 2020-2024 yılları arasında meme kanseri ve gen ifadesi alanında aktif ve gelişen bir araştırma ortamının varlığını ortaya koymuştur. Bulgular, patofizyolojik mekanizmaların aydınlatılmasına ve tedavi yaklaşımlarının araştırılmasına vurgu yapıldığını göstermektedir. Bu sonuçlar gelecekteki araştırma yönlerine rehberlik edecek değerli bilgiler sunmaktadır.

Anahtar Kelimeler

• Meme kanseri
• Gen ifadesi
• Web of Science
• Bibliyometrik analiz

Global Research Trends in Breast Cancer Gene Expression: A Bibliometric Study of 2020–2024 Publications

Öz

Purpose: This study aimed to identify and analyze articles published between 2020 and 2024 that addressed “breast cancer” and “gene expression” by examining publication trends, citation patterns, prominent journals, contributing countries, and evolving research topics within the field. Methods: A bibliometric analysis was conducted on articles related to “breast cancer” and “gene expression” that were published between 2020 and 2024 and indexed in the Web of Science (WoS) Core Collection database. The analysis included metrics such as the most cited articles, citation frequency, publication trends over time, countries with the highest publications and citations, leading authors, co-occurrence of author keywords, and the most frequently cited sources. Results: A total of 5,095 articles were identified. The highest number of publications was recorded in 2020, followed by a gradual decline toward 2024. A substantial portion of the publications originated from China and the United States of America. Most articles were published in high-impact journals and received a high number of citations. The research predominantly focused on gene expression in the context of treatment strategies and pathogenic mechanisms in breast cancer. Conclusion: This bibliometric analysis demonstrated an active and evolving research landscape in the field of breast cancer and gene expression from 2020 to 2024. The findings underscore the emphasis on elucidating pathophysiological mechanisms and investigating therapeutic approaches. These results offer valuable insights for guiding future research directions.

Anahtar Kelimeler

• Breast cancer
• Gene expression
• Web of Science
• Bibliometric analysis

Kaynakça

1. 1. Bray, F., et al., Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians, 2024. 74(3): p. 229-263.
2. 2. Yang, T., et al., Genetic Testing Enhances the Precision Diagnosis and Treatment of Breast Cancer. International Journal of Molecular Sciences, 2023. 24(23): p. 16607.
3. 3. Ayan, D., et al., Bioinformatic Investigation of Genetic Changes in Paraoxonase Genes in Breast Cancer and Breast Cancer Subtypes. Eur J Breast Health, 2024. 20(3): p. 178-184.
4. 4. Hassan, A.N. and M.S. Al-Attar, Level of Awareness, Screening Practices, and Self-Detection Among Breast Cancer Patients. Eur J Breast Health, 2025. 21(1): p. 52-56.
5. 5. Latha, N.R., et al., Gene expression signatures: a tool for analysis of breast cancer prognosis and therapy. Critical Reviews in Oncology/Hematology, 2020. 151: p. 102964.
6. 6. Bao, T. and N.E. Davidson, Gene expression profiling of breast cancer. Adv Surg, 2008. 42: p. 249-60.
7. 7. Wang, X., et al., Global biomarker trends in triple-negative breast cancer research: a bibliometric analysis. International Journal of Surgery, 2024. 110(12): p. 7962-7983.
8. 8. Yuan, J., et al., Traditional Chinese medicine for breast cancer treatment: a bibliometric and visualization analysis. Pharmaceutical Biology, 2024. 62(1): p. 499-512.

9. 9. Aria, M. and C. Cuccurullo, bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of informetrics, 2017. 11(4): p. 959-975.
10. 10. Yaz, F., et al., A Bibliometric Analysis of Publications on Tinnitus: A Study Based on Web of Science Data From 1980 to 2020. J Int Adv Otol, 2023. 19(2): p. 121-129.
11. 11. Schettini, F., et al., Clinical, pathological, and PAM50 gene expression features of HER2-low breast cancer. npj Breast Cancer, 2021. 7(1): p. 1.
12. 12. Fehrenbacher, L., et al., NSABP B-47/NRG Oncology Phase III Randomized Trial Comparing Adjuvant Chemotherapy With or Without Trastuzumab in High-Risk Invasive Breast Cancer Negative for HER2 by FISH and With IHC 1+ or 2. J Clin Oncol, 2020. 38(5): p. 444-453.
13. 13. Chang, G., et al., YTHDF3 Induces the Translation of m(6)A-Enriched Gene Transcripts to Promote Breast Cancer Brain Metastasis. Cancer Cell, 2020. 38(6): p. 857-871.e7.
14. 14. Xu, X., et al., CircRNA inhibits DNA damage repair by interacting with host gene. Molecular Cancer, 2020. 19(1): p. 128.
15. 15. Wan, W., et al., METTL3/IGF2BP3 axis inhibits tumor immune surveillance by upregulating N(6)-methyladenosine modification of PD-L1 mRNA in breast cancer. Mol Cancer, 2022. 21(1): p. 60.
16. 16. Barroso-Sousa, R., et al., Prevalence and mutational determinants of high tumor mutation burden in breast cancer. Ann Oncol, 2020. 31(3): p. 387-394.
17. 17. Pusztai, L., et al., Durvalumab with olaparib and paclitaxel for high-risk HER2-negative stage II/III breast cancer: Results from the adaptively randomized I-SPY2 trial. Cancer Cell, 2021. 39(7): p. 989-998.e5.
18. 18. Sebastian, A., et al., Single-Cell Transcriptomic Analysis of Tumor-Derived Fibroblasts and Normal Tissue-Resident Fibroblasts Reveals Fibroblast Heterogeneity in Breast Cancer. Cancers, 2020. 12(5): p. 1307.
19. 19. Chen, H., et al., Cross-talk of four types of RNA modification writers defines tumor microenvironment and pharmacogenomic landscape in colorectal cancer. Mol Cancer, 2021. 20(1): p. 29.
20. 20. Wolf, D.M., et al., Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies. Cancer Cell, 2022. 40(6): p. 609-623.e6.
21. 21. Jian, X., et al., Hsa_circ_001680 affects the proliferation and migration of CRC and mediates its chemoresistance by regulating BMI1 through miR-340. Mol Cancer, 2020. 19(1): p. 20.
22. 22. Hurvitz, S.A., et al., Potent Cell-Cycle Inhibition and Upregulation of Immune Response with Abemaciclib and Anastrozole in neoMONARCH, Phase II Neoadjuvant Study in HR(+)/HER2(-) Breast Cancer. Clin Cancer Res, 2020. 26(3): p. 566-580.
23. 23. Karn, T., et al., Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo. Ann Oncol, 2020. 31(9): p. 1216-1222.
24. 24. Flaherty, K.T., et al., The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design. JNCI: Journal of the National Cancer Institute, 2020. 112(10): p. 1021-1029.
25. 25. Hiller, J.G., et al., Preoperative β-Blockade with Propranolol Reduces Biomarkers of Metastasis in Breast Cancer: A Phase II Randomized Trial. Clin Cancer Res, 2020. 26(8): p. 1803-1811.
26. 26. Xu, Y., et al., The FTO/miR-181b-3p/ARL5B signaling pathway regulates cell migration and invasion in breast cancer. Cancer Communications, 2020. 40(10): p. 484-500.
27. 27. Eikesdal, H.P., et al., Olaparib monotherapy as primary treatment in unselected triple negative breast cancer. Ann Oncol, 2021. 32(2): p. 240-249.
28. 28. Bareche, Y., et al., Unraveling Triple-Negative Breast Cancer Tumor Microenvironment Heterogeneity: Towards an Optimized Treatment Approach. JNCI: Journal of the National Cancer Institute, 2019. 112(7): p. 708-719.
29. 29. Bagati, A., et al., Integrin αvβ6-TGFβ-SOX4 Pathway Drives Immune Evasion in Triple-Negative Breast Cancer. Cancer Cell, 2021. 39(1): p. 54-67.e9.
30. 30. Schrörs, B., et al., Multi-Omics Characterization of the 4T1 Murine Mammary Gland Tumor Model. Frontiers in Oncology, 2020. Volume 10 - 2020.
31. 31. Neves Rebello Alves, L., et al., Biomarkers in Breast Cancer: An Old Story with a New End. Genes (Basel), 2023. 14(7).
32. 32. Mehta, D., et al., Exploring the Role of Seven Key Genes in Breast Cancer: Insights from In Silico and In Vitro Analyses. Gene Expression, 2024. 23(4): p. 246-256.
33. 33. Schena, M., et al., Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 1995. 270(5235): p. 467-70.
34. 34. Arpino, G., et al., Gene expression profiling in breast cancer: a clinical perspective. Breast, 2013. 22(2): p. 109-120.
35. 35. Wu, D., et al., A bibliometric and visualization analysis of research trends and hotspots on targeted therapy for breast cancer from 2003 to 2022. Front Oncol, 2024. 14: p. 1366900.
36. 36. Jiang, S., et al., A bibliometric analysis of metastatic breast cancer: two-decade report (2002-2022). Front Oncol, 2023. 13: p. 1229222.
37. 37. Nwosu, I.O. and S.R. Piccolo, A Comprehensive Meta-Analysis of Breast Cancer Gene Expression. bioRxiv, 2024: p. 2024.08.30.610515.
38. 38. Donthu, N., et al., How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 2021. 133: p. 285-296.