Successful in vivo hyperthermal therapy toward breast cancer by Chinese medicine shikonin-loaded thermosensitive micelle
Authors: Nian Huang
Puichi Lo
Yun Sun
Li Zhang
Xia Dong
Di Chen
Kexing Fan
Xiandi Zhu
Wei Li
Fulei Zhang
Yonghua Su
Changquan Ling
Jie Gao
Ying Wang
Journal: International Journal of Nanomedicine (2017)
Discipline: PHARMACOLOGY & TOXICOLOGY
Keywords: breast cancer; critical micelle concentration; hyperthermal therapy; in vivo; intra-tumor accumulation
Affiliations: Department of Integrative Oncology, Changhai Hospital of Traditional Chinese Medicine., International Joint Cancer Institute, The Second Military Medical University, Shanghai., Department of Biomedical Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong, China.

Abstract:  The Chinese traditional medicine Shikonin is an ideal drug due to its multiple targets to tumor cells. But in clinics, improving its aqueous solubility and tumor accumulation is still a challenge. Herein, a copolymer with tunable poly(N-isopropylacrymaide) and polylactic acid block lengths is designed, synthesized, and characterized in nuclear magnetic resonance. The corresponding thermosensitive nanomicelle (TN) with well-defined core-shell structure is then assembled in an aqueous solution. For promoting the therapeutic index, the physical-chemistry properties of TNs including narrow size, low critical micellar concentration, high serum stability, tunable volume phase transition temperature (VPTT), high drug-loading capacity, and temperature-controlled drug release are systematically investigated and regulated through the fine self-assembly. The shikonin is then entrapped in a degradable inner core resulting in a shikonin-loaded thermosensitive nanomicelle (STN) with a VPTT of ~40°C. Compared with small-molecular shikonin, the in vitro cellular internalization and cytotoxicity of STN against breast cancer cells (Michigan Cancer Foundation-7) are obviously enhanced. In addition, the therapeutic effect is further enhanced by the programmed cell death (PCD) specifically evoked by shikonin. Interestingly, both the proliferation inhibition and PCD are synergistically promoted as T &gt; VPTT, namely the temperature-regulated passive targeting. Consequently, as intravenous injection is administered to the BALB/c nude mice bearing breast cancer, the intratumor accumulation of STNs is significantly increased as T &gt; VPTT, which is regulated by the in-house developed heating device. The in vivo antitumor assays against breast cancer further confirm the synergistically enhanced therapeutic efficiency. The findings of this study indicate that STN is a potential effective nanoformulation in clinical cancer therapy. 

Retracted: No

PubPeer comments:
 In this 2018 paper, the authors, H. Wang, **Z. Xu**, X. Zeng, claimed that u201cHFLTSs are a very effective and flexible technique which focuses on a specific type of complex linguistic expressions, i.e., comparative linguistic expressions.u201d ![file] However, in a 2017 paper (DOI: DOI 10.1007 s10700-016-9257-5) authored by **Z. Xu** and W. Zhou, the authors claimed that **u201cHowever, it can be easily found that the occurring probabilities of the possible values in the HFE are equal, which is obviously impracticalu201d** ![file] Moreover, in Definition 1, the authors used the linguistic term set $S={s_0, s_1, ldots, s_{tau} }$. ![file] However, in a paper (doi: 10.1016 j.knosys.2014.12.009) by H. Liao, **Z. Xu**, X. Zeng, and J. Merigo published in 2015, the authors explicitly pointed out that such a set of linguistic terms would lead to undesirable results. It is interesting to note that this issue was not even mentioned throughout this 2018 paper ![file] , 
 #1 Dear Prof Albiventris, Thank you for your interest in our paper. I would like the reply your comments based on my personal understanding. (1) **Regarding the position of hesitant fuzzy linguistic term set** Generally, I agree with the statement in (DOI: DOI 10.1007 s10700-016-9257-5). If the probabilities are available, then we should consider them and model this case by probability-involved models, such as probabilistic linguistic term set. However, if we don t have the probabilistic information, such as the expressions between good and extremely good , we have to model this kind of expressions by means of hesitant fuzzy linguistic term sets. (2) **Regarding the version of linguistic term set** I agree with the statement in (doi: 10.1016 j.knosys.2014.12.009) that the linguistic term set $S_1 = { s_{-g}, ldots, s_0, ldots, s_g }$ has some merits, comparing with $S={s_0, s_1, ldots, s_{tau} }$. But this does not mean $S_1$ is better than $S$ in all sense. - For preference analysis, the results based on $S_1$ is more rational than those based on $S$. I think the author in (doi: 10.1016 j.knosys.2014.12.009) meant this situation. - For information fusion, there is no difference between the two (except for their predefined semantics). In fact, there is a one-one mapping between $S_1$ and $S$ if $tau = 2g$. This is why we did not include the viewpoint in our paper. Best regards, Hai ,