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Cancer is the leading cause of morbidity and mortality worldwide, characterized by irregular cell growth. Cytotoxicity or killing tumor cells that divide rapidly is the basic function of chemotherapeutic drugs. However, these agents can damage normal dividing cells, leading to adverse effects in the body. In view of great advances in cancer therapy, which are increasingly reported each year, we quantitatively and qualitatively evaluated the papers published between 1981 and December 2015, with a closer look at the highly cited papers (HCPs), for a better understanding of literature related to cytotoxicity in cancer therapy. Online documents in the Web of Science (WOS) database were analyzed based on the publication year, the number of times they were cited, research area, source, language, document type, countries, organizationenhanced and funding agencies. A total of 3,473 publications relevant to the target key words were found in the WOS database over 35 years and 86% of them (n=2,993) were published between 20002015. These papers had been cited 54,330 times without self citation from 1981 to 2015. Of the 3,473 publications, 17 (3,557citations) were the most frequently cited ones between 2005 and 2015. The topmost HCP was about generating a comprehensive preclinical database (CCLE) with 825 (23.2%) citations. One third of the remaining HCPs had focused on drug discovery through improving conventional therapeutic agents such as metformin and ginseng. Another 33% of the HCPs concerned engineered nanoparticles (NPs) such as polyamidoamine (PAMAM) dendritic polymers, PTX/SPIOloaded PLGAs and cell derived NPs to increase drug effectiveness and decrease drug toxicity in cancer therapy. The remaining HCPs reported novel factors such as miR205, Nrf2 and p27 suggesting their interference with development of cancer in targeted cancer therapy. In conclusion, analysis of 35year publications and HCPs on cytotoxicity in cancer in the present report provides opportunities for a better understanding the extent of topics published and may help future research in this area.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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