Glioblastoma is one of the most dangerous tumors for patients in clinical practice at present, and since glioblastoma originates from the brain, it will have a serious impact on patients. Therefore, more effective clinical therapeutic targets are still needed at this stage. Kinesin family member 15 (KIF15) promotes proliferation in several cancers, but its effect on glioblastoma is unclear. In this study, differentially expressed gene analysis and network analysis were performed to identify critical genes affecting glioma progression. The samples were divided into a KIF15 high-expression group and KIF15 low-expression group, and the association between FIK15 expression level and clinical characteristics was summarized and analyzed by performing medical data analysis; the effect of KIF15 on glioblastoma cell proliferation was detected by employing colony formation and MTT assays. The effect of KIF15 on tumor growth in mice was determined. It was found that KIF15 was a potential gene affecting the progression of glioblastoma. In addition, KIF15 was highly expressed in glioblastoma tumor tissues, and KIF15 was correlated with tumor size, clinical stage and other clinical characteristics. After the KIF15 gene was knocked out, the proliferation ability of glioblastoma was significantly inhibited. KIF15 also contributed to the growth of glioblastoma tumors in mice. Therefore, we found KIF15 to be a promising clinical therapeutic target.
Citation: Leibo Wang, Xuebin Zhang, Jun Liu, Qingjun Liu. RETRACTED ARTICLE: Kinesin family member 15 can promote the proliferation of glioblastoma[J]. Mathematical Biosciences and Engineering, 2022, 19(8): 8259-8272. doi: 10.3934/mbe.2022384
[1] | Nuriya М. Mukhamedova, Mazhyn K. Skakov, Wojciech Wieleba . Determination of phase composition and mechanical properties of surface of the material obtained on the basis of silicon and carbon by spark-plasma sintering method. AIMS Materials Science, 2019, 6(1): 1-9. doi: 10.3934/matersci.2019.1.1 |
[2] | Mohamed Lokman Jalaluddin, Umar Al-Amani Azlan, Mohd Warikh Abd Rashid, Norfauzi Tamin . Effect of sintering temperatures on the physical, structural properties and microstructure of mullite-based ceramics. AIMS Materials Science, 2024, 11(2): 243-255. doi: 10.3934/matersci.2024014 |
[3] | Marcin Kargul, Marek Konieczny . Copper matrix composites reinforced with steel particles. AIMS Materials Science, 2021, 8(3): 321-342. doi: 10.3934/matersci.2021021 |
[4] | Mohamed Lokman Jalaluddin, Umar Al-Amani Azlan, Mohd Warikh Abd Rashid . A preliminary study of porous ceramics with carbon black contents. AIMS Materials Science, 2023, 10(5): 741-754. doi: 10.3934/matersci.2023041 |
[5] | Luca Spiridigliozzi, Grazia Accardo, Emilio Audasso, Barbara Bosio, Sung Pil Yoon, Gianfranco Dell’Agli . Synthesis of easily sinterable ceramic electrolytes based on Bi-doped 8YSZ for IT-SOFC applications. AIMS Materials Science, 2019, 6(4): 610-620. doi: 10.3934/matersci.2019.4.610 |
[6] | Mohamed Lokman Jalaluddin, Umar Al-Amani Azlan, Mohd Warikh Abd Rashid, Norfauzi Tamin, Mohamad Najmi Masri . A review of pore-forming agents on the structures, porosities, and mechanical properties of porous ceramics. AIMS Materials Science, 2024, 11(4): 634-665. doi: 10.3934/matersci.2024033 |
[7] | Wisawat Keaswejjareansuk, Xiang Wang, Richard D. Sisson, Jianyu Liang . Electrospinning process control for fiber-structured poly(Bisphenol A-co-Epichlorohydrin) membrane. AIMS Materials Science, 2020, 7(2): 130-143. doi: 10.3934/matersci.2020.2.130 |
[8] | Marek Konieczny . Mechanical properties and wear characterization of Al-Mg composites synthesized at different temperatures. AIMS Materials Science, 2024, 11(2): 309-322. doi: 10.3934/matersci.2024017 |
[9] | Omar Bataineh, Abdullah F. Al-Dwairi, Zaid Ayoub, Mohammad Al-Omosh . DOE-based experimental investigation and optimization of hardness and corrosion rate for Cu-x%Al2O3 as processed by powder metallurgy. AIMS Materials Science, 2021, 8(3): 416-433. doi: 10.3934/matersci.2021026 |
[10] | Sumesh Narayan, Ananthanarayanan Rajeshkannan . Densification behaviour of sintered aluminum composites during hot deformation. AIMS Materials Science, 2018, 5(5): 902-915. doi: 10.3934/matersci.2018.5.902 |
Glioblastoma is one of the most dangerous tumors for patients in clinical practice at present, and since glioblastoma originates from the brain, it will have a serious impact on patients. Therefore, more effective clinical therapeutic targets are still needed at this stage. Kinesin family member 15 (KIF15) promotes proliferation in several cancers, but its effect on glioblastoma is unclear. In this study, differentially expressed gene analysis and network analysis were performed to identify critical genes affecting glioma progression. The samples were divided into a KIF15 high-expression group and KIF15 low-expression group, and the association between FIK15 expression level and clinical characteristics was summarized and analyzed by performing medical data analysis; the effect of KIF15 on glioblastoma cell proliferation was detected by employing colony formation and MTT assays. The effect of KIF15 on tumor growth in mice was determined. It was found that KIF15 was a potential gene affecting the progression of glioblastoma. In addition, KIF15 was highly expressed in glioblastoma tumor tissues, and KIF15 was correlated with tumor size, clinical stage and other clinical characteristics. After the KIF15 gene was knocked out, the proliferation ability of glioblastoma was significantly inhibited. KIF15 also contributed to the growth of glioblastoma tumors in mice. Therefore, we found KIF15 to be a promising clinical therapeutic target.
Let H,K be complex or real separable Hilbert spaces and n a positive integer. As usual, the symbols Pn(H) and IH stand for the set of all rank-n self-adjoint projections on H, and the identity operator on H, respectively. For S,T∈Pn(H), we say S is orthogonal to T iff ST=0 and the quantity Tr(ST) is the transition probability between S,T. Plainly, S⊥T is equivalent to Tr(ST)=0. If u∈H is a unit vector, then the rank-1 projection onto span{u} will be denoted by u⊗u. The transition probability associated with a pair of rank-1 projections (pure states) is the commonly used concept in quantum theory. We call a family {Si}⊆Pn(H) a complete orthogonal system of rank-n projections (briefly, COSPn) iff
● Si⊥Sj whenever i≠j.
● There is no rank-1 projection T orthogonal to each Si.
The celebrated Wigner's theorem [1, pp.251–254] states that if ϕ:P1(H)→P1(H) is a bijection satisfying
Tr(ϕ(S)ϕ(T))=Tr(ST),S,T∈P1(H), | (1.1) |
equivalently, if ϕ preserves the transition probability between S and T, then there exists a unitary or an anti-unitary U:H→H such that ϕ(A)=UAU∗. Recently, there has been considerable interest in improving and reproving this vital result in many ways (referred to in [2,3,4,5,6,7]).
Wigner's theorem also serves as a frequently used tool for investigating the symmetries in some mathematical structures of quantum mechanics. Suppose that ϕ is a bijection on the set of all observables/the state space/the effect algebra, and such a map preserves a certain property/relation/operation relevant in quantum mechanics. The given problem is to characterize the form of such maps (symmetries), and a classical approach to this problem is to first show that ϕ preserves the rank-1 projections and the corresponding transition probability. This is the crucial step of the proof. Applying Wigner's theorem, one may immediately see that the restriction of ϕ to P1(H) has a nice behavior. Then the final step to prove that ϕ takes the desired form on the entire quantum structure is usually considered as an easier part of the proof. The interested readers are referred to [8, Chapter 2] and references therein for more examples of this approach and some background for the so-called preservers problems.
When using the above method, sometimes we may not ensure that ϕ maps P1(H) into itself, and quite often we merely know that it preserves the zero-transition probability. This motivates us to search for a stronger version of the classical Wigner's theorem. The main aim of this paper is to provide the generalizations of Wigner's theorem in which instead of assuming that ϕ maps P1(H) into itself, we assume that ϕ maps P1(H) into Pn(K).
Theorem 1.1. If ϕ:P1(H)→Pn(K) is a map satisfying
Tr(ϕ(S)ϕ(T))=nTr(ST),S,T∈P1(H), | (1.2) |
then there exists a collection {V1,…,Vn} of linear or conjugate linear isometries from H into K with mutually orthogonal ranges, such that
ϕ(A)=n∑i=1ViAV∗i,A∈P1(H). |
Notice that the property (1.2) is equivalent to the following condition:
‖ϕ(S)−ϕ(T)‖HS=√n‖S−T‖HS,S,T∈P1(H), |
where ‖⋅‖HS represents the Hilbert–Schmidt norm. Namely, our result describes the general form of maps from P1(H) into Pn(K) multiplying √n times the distance induced by this special norm. We point out that several papers [9,10] studied the isometries of Pn(H) with respect to the operator norm.
For the case of dimH≥3, Uhlhorn [11] significantly generalized Wigner's theorem by replacing the assumption (1.1) with a weaker one: Tr(ST)=0⇔Tr(ϕ(S)ϕ(T))=0. Uhlhorn's result has been further improved in [12,13]: It is proved that the bijectivity assumption can be relaxed when dimH<∞. Unfortunately, when dimH=∞, it is shown in [14] that there exist injective maps preserving orthogonality in both directions, which behave quite wildly. Thus, an additional hypothesis will be needed in the infinite-dimensional case.
Theorem 1.2. Let dimH≥3. If ϕ:P1(H)→Pn(K) is a map that sends each complete orthogonal system of rank-1 projections to some complete orthogonal system of rank-n projections, then there exists a collection {V1,…,Vn} of linear or conjugate linear isometries from H into K, which have mutually orthogonal ranges and satisfy ∑ni=1ViV∗i=I, such that
ϕ(A)=n∑i=1ViAV∗i,A∈P1(H). | (1.3) |
If 3≤dimH<∞ and dimK=ndimH, then a map ϕ:P1(H)→Pn(K) that preserves orthogonality only in one direction automatically sends each COSP1 to some COSPn. Therefore, a generalization (without bijectivity either) of Uhlhorn's theorem in matrix algebra is a direct consequence of Theorem 1.2.
Corollary 1.3. Let 3≤dimH<∞ and dimK=ndimH. If ϕ:P1(H)→Pn(K) is a map that preserves orthogonality in one direction, then ϕ has the form (1.3).
In what follows, we denote by C(H), F(H), and Fs(H) the set of compact operators, finite-rank operators, and finite-rank self-adjoint operators on H. The following lemma will be used to prove Theorem 1.1.
Lemma 2.1. If ϕ:Fs(H)→Fs(K) is a linear map that sends rank-1 projections to rank-n projections and satisfies
Tr(ϕ(S)ϕ(T))=nTr(ST),S,T∈Fs(H), | (2.1) |
then there exists a collection {V1,…,Vn} of linear or conjugate linear isometries from H into K with mutually orthogonal ranges, such that
ϕ(A)=n∑i=1ViAV∗i,A∈Fs(H). |
To prove Lemma 2.1, we need the following lemmas. For S,T∈Fs(H), we write S≤T if T−S is positive.
Lemma 2.2. Let ϕ:Fs(H)→Fs(K) be a linear map that preserves projections. If S,T∈Fs(H) are projections with S≥T, then ϕ(S)≥ϕ(T).
Proof. Since S,T are projections with S≥T, there exists some projection R orthogonal to T, such that S=T+R. Thus, ϕ(S)=ϕ(T)+ϕ(R)≥ϕ(T).
Lemma 2.3. (see [15, Theorem 1.9.1]) Let M be a dense subspace of a normed space V, and W a Banach space. If ϕ:M→W is a continuous linear map, then ϕ has a unique continuous linear extension ϕ′:V→W.
Proof of Lemma 2.1. By Eq (2.1), we see that ϕ sends orthogonal rank-1 projections to orthogonal rank-n projections. Clearly, any finite-rank projection is the sum of mutually orthogonal rank-1 projections. Consequently, ϕ preserves the projections.
Assume that the underlying space H is complex. Extend ϕ to a complex linear map from F(H) into F(K) by setting
˜ϕ(A+iB):=ϕ(A)+iϕ(B),A,B∈Fs(H). |
Let A=∑iαiPi, αi∈R, Pi∈P1(H), denote the spectral decomposition of any operator A∈Fs(H). Then ˜ϕ(Pi)˜ϕ(Pj)=0 for each i≠j, and hence ˜ϕ(A2)=˜ϕ(A)2. Replacing A by A+B, with A,B∈Fs(H), we obtain that ˜ϕ(AB+BA)=˜ϕ(A)˜ϕ(B)+˜ϕ(B)˜ϕ(A). Then it follows that
˜ϕ((A+iB)2)=˜ϕ(A2)−˜ϕ(B2)+i˜ϕ(AB+BA)=˜ϕ(A)2−˜ϕ(B)2+i(˜ϕ(A)˜ϕ(B)+˜ϕ(B)˜ϕ(A))=(˜ϕ(A)+i˜ϕ(B))2=˜ϕ(A+iB)2. |
This implies that ˜ϕ is a Jordan homomorphism. Since ˜ϕ preserves the self-adjoint operators, we infer that ˜ϕ is a (continuous) Jordan ∗ - homomorphism. It is known that F(H) is dense in the C∗ - algebra C(H). By Lemma 2.3, ˜ϕ can be uniquely extended to a Jordan ∗ - homomorphism from C(H) into C(K). According to [8, Theorem A.6], each Jordan ∗ - homomorphism of the C∗ - algebra is a direct sum of a ∗-antihomomorphism and a ∗ - homomorphism. Every ∗ - homomorphism of C(H) is in fact a direct sum of inner homomorphisms (see [16, Theorem 10.4.7]). Then ˜ϕ has the asserted form.
The case when H is real demands an other approach (this idea is borrowed from [17, Theorem 2.2] below). Assume that {ui}i∈Ω is an orthonormal basis for H and denote rngϕ(ui⊗ui)=Ki, i∈Ω. For any i,j∈Ω with i≠j, since [(ui+uj)⊗(ui+uj)]/2 is a projection with range lying within that of ui⊗ui+uj⊗uj, it follows by Lemma 2.2 that
12ϕ((ui⊗uj+uj⊗ui)+(ui⊗ui+uj⊗uj))≤IKi⊕Kj⊕0. |
Therefore, we may write
Pij=ϕ(ui⊗uj+uj⊗ui)=[P′iiP′ijP′jiP′jj]⊕0 |
for some linear operator P′ij:Kj→Ki. For any nonzero α∈R, consider
Q1=(α2+1)−1(α2u1⊗u1+α(u1⊗u2+u2⊗u1)+u2⊗u2)∈P1(H),Q2=(α2+1)−1(u1⊗u1−α(u1⊗u2+u2⊗u1)+α2u2⊗u2)∈P1(H). |
By directly computing, Q1Q2=0. It follows that
0=(α2+1α)2ϕ(Q1)ϕ(Q2)=(ϕ(αu1⊗u1+1αu2⊗u2)+P12)( ϕ(1αu1⊗u1+αu2⊗u2)−P12)=([αIK1001αIK2]⊕0+P12)([1αIK100αIK2]⊕0−P12)=[IK100IK2]⊕0−P212−[αP′11αP′121αP′211αP′22]⊕0+[1αP′11αP′121αP′21αP′22]⊕0=[IK100IK2]⊕0−P212−[(α−1α)P′1100(1α−α)P′22]⊕0. |
Because this equation holds true for any nonzero α∈R, we see that P′11 and P′22 are zeroes. Hence, we obtain
P′12P′21=IK1 and P′21P′12=IK2. |
It follows that P′12=P′21−1=P′21∗ and we have similar conclusions for all Pij.
Since all Ki are isomorphic to Rn, there exists an isomorphism from H⊗Rn to ⨁ΩKi, given by ∑iui⊗ηi→(⋯ηi⋯). Write K=(H⊗Rn)⊕Ks and replace ϕ by the mapping
A→(IK1⊕(⨁i∈Ω,i≠1P′1i)⊕IKs)ϕ(A)(IK1⊕(⨁i∈Ω,i≠1P′1i−1)⊕IKs) |
such that
ϕ(u1⊗ui+ui⊗u1)=[(u1⊗ui+ui⊗u1)⊗IRn]⊕0Ks,i∈Ω. |
We are going to prove that
ϕ(ui⊗uj+uj⊗ui)=[(ui⊗uj+ui⊗uj)⊗IRn]⊕0Ks wheneveri,j∈Ωwithi≠j. |
To see this, let Z=[(u1+ui+uj)⊗(u1+ui+uj)]/3. Then Z is a rank-1 projection such that, up to unitary similarity, ϕ(Z) is equal to a direct sum of 0 and
Y=3−1[IRnIRnIRnIRnIRnP′ijIRnP′ij−1IRn]. |
As Y2=Y, it follows that IRn+2P′ij=3P′ij. Thus P′ij=P′ij−1=IRn.
Since spanR{ui⊗uj+uj⊗ui:i,j∈Ω} is dense in Fs(H) when H is a real Hilbert space, we can prove that
ϕ(A)=U[(A⊗IRn)⊕0Ks]U∗,A∈Fs(H), |
where U:K→K is a unitary. We arrive at the conclusion.
Proof of Theorem 1.1. Since the whole Fs(H) is real linearly generated by P1(H), we may extend ϕ to a real-linear map ˜ϕ:Fs(H)→Fs(K) by setting
˜ϕ(∑iλiSi):=∑iλiϕ(Si), |
where {λi}⊆R and {Si}⊆P1(H) are finite subsets. We claim that ˜ϕ is well-defined. Assume that ∑iλiSi=∑jμjTj, {μj}⊆R, {Tj}⊆P1(H). Then for each A∈P1(H), it follows by Eq (1.2) that
Tr(∑iλiϕ(Si)ϕ(A))=∑iλiTr(ϕ(Si)ϕ(A))=∑iλinTr(SiA)=nTr(∑iλiSiA)=nTr(∑jμjTjA)=∑jμjnTr(TjA)=∑jμjTr(ϕ(Tj)ϕ(A))=Tr(∑jμjϕ(Tj)ϕ(A)). |
This implies that
Tr((∑iλiϕ(Si)−∑jμjϕ(Tj))ϕ(A))=0. |
Based on the linearity of the function Tr, we can replace ϕ(A) by its linear combination. Then we obtain
Tr((∑iλiϕ(Si)−∑jμjϕ(Tj))(∑iλiϕ(Si)−∑jμjϕ(Tj)))=0. |
Since the square of Hermitian operator (∑iλiϕ(Si)−∑jμjϕ(Tj))2 is positive with zero trace, we deduce that
(∑iλiϕ(Si)−∑jμjϕ(Tj))2=0=∑iλiϕ(Si)−∑jμjϕ(Tj). |
It means that ˜ϕ is well-defined. Then the form of this linear map ˜ϕ is given by Lemma 2.1.
Proof of Theorem 1.2. First, let us recall Gleason's theorem [18]. A positive and trace-class operator σ:H→H with Tr(σ)=1 is called a density operator. We restate Gleason's theorem as follows: Suppose that dimH≥3 and f:P1(H)→[0,1] is a function such that for each complete orthogonal system of rank-1 projections {Si}⊆P1(H), one has
∑if(Si)=1. |
Then there is a density operator σ:H→H for which
f(S)=Tr(σS),S∈P1(H). |
To prove Theorem 1.2, we need to choose an arbitrary density operator ϱ:K→K and define the function fϱ:P1(H)→[0,1] by
fϱ(S):=Tr(ϱϕ(S)),S∈P1(H). |
It follows from our assumption that Gleason's theorem can be used. Therefore, for each density operator ϱ:K→K, there exists a density operator σ:H→H such that
fϱ(S)=Tr(σS),S∈P1(H). |
In particular, pick ϱ=ϕ(T)/n for some fixed T∈P1(H). Then we obtain
fϱ(S)=1nTr(ϕ(T)ϕ(S))=Tr(σTS),S∈P1(H), |
where σT is the density operator corresponding to T. Taking S=T, we infer that
Tr(σTT)=1. |
It is easy to verify that if u is a unit vector such that T=u⊗u, then
Tr(σTT)=⟨σTu,u⟩. |
As 0≤σT≤I, it follows by the operator theory that σTu=u. Therefore, 1 is an eigenvalue of σT and u belongs to the corresponding eigenspace. Under the decomposition H=span{u}⊕{u}⊥, the operator σT has the following matrix representation:
σT=[100X], |
where X is the positive operator acting on {u}⊥ with zero trace. Thus, X=0, which means σT=T.
Hence, for each S∈P1(H), we have Tr(ϕ(S)ϕ(T))=nTr(ST). Since T was chosen arbitrarily, we deduce that ϕ multiplies n times the transition probability. Then Theorem 1.1 tells us the form of the map ϕ.
The conclusion in Theorem 1.2 does not hold when dimH=2, as demonstrated in the following example: In fact, we can identify H with C2 and hence F(H)=M2(C), the set of 2×2 complex matrices. All the rank-1 projections in M2(C) are in 1-to-1 correspondence with the unit vectors in the Bloch sphere in R3, i.e.: $
P1(C2)={2−1[1+x1x2+ix3x2−ix31−x1]:x1,x2,x3∈R with x21+x22+x23=1}. |
It is straightforward to compute the orthogonal complement of
A=2−1[1+x1x2+ix3x2−ix31−x1] is I−A=2−1[1−x1−x2−ix3−x2+ix31+x1]. |
Consider the bijective transformation ϕ:P1(C2)→P1(C2), which fix all rank-1 projections, but change the role of [1000] and [0001]. Obviously, the only COSP1 in M2(C) that contains [1000] is {[1000],[0001]} and hence ϕ preserves orthogonality. However, this discontinuous transformation ϕ can not be extended to any linear transformation (in fact, any Jordan ∗ - homomorphism also) on the whole matrix space M2(C).
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
This study was funded by Fundamental Research Funds for the Central Universities of China (Grant No. 2572022DJ07).
The authors declare there is no conflicts of interest.
[1] |
X. X. Ke, Y. Pang, K. Chen, D. Zhang, F. Wang, S. Zhu, et al., Knockdown of arsenic resistance protein 2 inhibits human glioblastoma cell proliferation through the MAPK/ERK pathway, Oncol. Rep., 40 (2018), 3313-3322. https://doi.org/10.3892/or.2018.6777 doi: 10.3892/or.2018.6777
![]() |
[2] |
H. Y. Li, B. B. Lv, Y. H. Bi, FABP4 accelerates glioblastoma cell growth and metastasis through Wnt10b signalling, Eur. Rev. Med. Pharmacol. Sci., 22 (2018), 7807-7818. https://doi.org/10.26355/eurrev_201811_16405 doi: 10.26355/eurrev_201811_16405
![]() |
[3] |
T. Mashimo, K. Pichumani, V. Vemireddy, K. J. Hatanpaa, D. K. Singh, S. Sirasanagandla, et al., Acetate is a bioenergetic substrate for human glioblastoma and brain metastases, Cell, 159 (2014), 1603-1614. https://doi.org/10.1016/j.cell.2014.11.025 doi: 10.1016/j.cell.2014.11.025
![]() |
[4] |
A. Vartanian, S. Agnihotri, M. R. Wilson, K. E. Burrell, P. D. Tonge, A. Alamsahebpour, et al., Targeting hexokinase 2 enhances response to radio-chemotherapy in glioblastoma, Oncotarget, 7 (2016), 69518-69535. https://doi.org/10.18632/oncotarget.11680 doi: 10.18632/oncotarget.11680
![]() |
[5] |
B. Huang, T. A. Dolecek, Q. Chen, C. R. Garcia, T. Pittman, J. L. Villano, Characteristics and survival outcomes associated with the lack of radiation in the treatment of glioblastoma, Med. Oncol., 35 (2018), 74. https://doi.org/10.1007/s12032-018-1134-3 doi: 10.1007/s12032-018-1134-3
![]() |
[6] |
Z. Shboul, L. Vidyaratne, M. Alam, S. M. S. Reza, K. M. Iftekharuddin, Glioblastoma and survival prediction, Lect. Notes Comput. Sci., 10670 (2018), 358-368. https://doi.org/10.1007/978-3-319-75238-9_31 doi: 10.1007/978-3-319-75238-9_31
![]() |
[7] |
J. K. Sa, S. H. Kim, J. K. Lee, H. J. Cho, Y. J. Shin, H. Shin, et al., Identification of genomic and molecular traits that present therapeutic vulnerability to HGF-targeted therapy in glioblastoma, Neuro-oncology, 21 (2019), 222-233. https://doi.org/10.1093/neuonc/noy105 doi: 10.1093/neuonc/noy105
![]() |
[8] |
Z. C. Zhu, J. W. Liu, K. Li, J. Zheng, Z. Q. Xiong, KPNB1 inhibition disrupts proteostasis and triggers unfolded protein response-mediated apoptosis in glioblastoma cells, Oncogene, 37 (2018), 2936-2952. https://doi.org/10.1038/s41388-018-0180-9 doi: 10.1038/s41388-018-0180-9
![]() |
[9] |
M. Westphal, C. L. Maire, K. Lamszus, EGFR as a target for glioblastoma treatment: An unfulfilled promise, CNS Drugs, 31 (2017), 723-735. https://doi.org/10.1007/s40263-017-0456-6 doi: 10.1007/s40263-017-0456-6
![]() |
[10] |
N. Hirokawa, Y, Tanaka, Kinesin superfamily proteins (KIFs): Various functions and their relevance for important phenomena in life and diseases, Exp. Cell Res., 334 (2015), 16-25. https://doi.org/10.1016/j.yexcr.2015.02.016 doi: 10.1016/j.yexcr.2015.02.016
![]() |
[11] | N. Hirokawa, From electron microscopy to molecular cell biology, molecular genetics and structural biology: Intracellular transport and kinesin superfamily proteins, KIFs: Genes, structure, dynamics and functions, J. Electron Microsc., 60 (2011), 63-92. https://doi.org/10.1093/jmicro/dfr051 |
[12] |
S. S. Siddiqui, Metazoan motor models: Kinesin superfamily in C. elegans, Traffic, 3 (2002), 20-28. https://doi.org/10.1034/j.1600-0854.2002.30104.x doi: 10.1034/j.1600-0854.2002.30104.x
![]() |
[13] |
H. Miki, M. Setou, K. Kaneshiro, N. Hirokawa, All kinesin superfamily protein, KIF, genes in mouse and human, Proc. Natl. Acad. Sci. U.S.A., 98 (2001), 7004-7011. https://doi.org/10.1073/pnas.111145398 doi: 10.1073/pnas.111145398
![]() |
[14] |
Y. M. Lee, W. Kim, Kinesin superfamily protein member 4 (KIF4) is localized to midzone and midbody in dividing cells, Exp. Mol. Med., 36 (2004), 93-97. https://doi.org/10.1038/emm.2004.13 doi: 10.1038/emm.2004.13
![]() |
[15] |
Z. Shen, A. R. Collatos, J. P. Bibeau, F. Furt, L. Vidali, Phylogenetic analysis of the Kinesin superfamily from physcomitrella, Front. Plant Sci., 3 (2012), 230. https://doi.org/10.3389/fpls.2012.00230 doi: 10.3389/fpls.2012.00230
![]() |
[16] |
K. Tang, N. H. Toda, A microtubule polymerase cooperates with the kinesin-6 motor and a microtubule cross-linker to promote bipolar spindle assembly in the absence of kinesin-5 and kinesin-14 in fission yeast, Mol. Biol. Cell, 28 (2017), 3647-3659. https://doi.org/10.1091/mbc.e17-08-0497 doi: 10.1091/mbc.e17-08-0497
![]() |
[17] |
T. McHugh, H. Drechsler, A. D. McAinsh, N. J. Carter, R. A. Cross, Kif15 functions as an active mechanical ratchet, Mol. Biol. Cell, 29 (2018), 1743-1752. https://doi.org/10.1091/mbc.E18-03-0151 doi: 10.1091/mbc.E18-03-0151
![]() |
[18] |
M. Xu, D. Liu, Z. Dong, X. Wang, X. Wang, Y. Liu, et al., Kinesin-12 influences axonal growth during zebrafish neural development, Cytoskeleton, 71 (2014), 555-563. https://doi.org/10.1002/cm.21193 doi: 10.1002/cm.21193
![]() |
[19] |
J. Feng, Z. Hu, H. Chen, J. Hua, R. Wu, Z. Dong, et al., Depletion of kinesin-12, a myosin-ⅡB-interacting protein, promotes migration of cortical astrocytes, J. Cell. Sci., 129 (2016), 2438-2447. https://doi.org/10.1242/jcs.181867 doi: 10.1242/jcs.181867
![]() |
[20] |
H. Miki, M. Setou, K. Kaneshiro, N. Hirokawa, All kinesin superfamily protein, KIF, genes in mouse and human, Proc. Natl. Acad. Sci. U.S.A., 98 (2001), 7004-7011. https://doi.org/10.1073/pnas.111145398 doi: 10.1073/pnas.111145398
![]() |
[21] |
J. Wang, X. Guo, C. Xie, J. Jiang, KIF15 promotes pancreatic cancer proliferation via the MEK-ERK signalling pathway, Br. J. Cancer, 117 (2017), 245-255. https://doi.org/10.1038/bjc.2017.165 doi: 10.1038/bjc.2017.165
![]() |
[22] |
Y. Qiao, J. Chen, C. Ma, Y. Liu, P. Li, Y. Wang, et al., Increased KIF15 expression predicts a poor prognosis in patients with lung adenocarcinoma, Cell Physiol. Biochem., 51 (2018), 1-10. https://doi.org/10.1159/000495155 doi: 10.1159/000495155
![]() |
[23] |
G. Harris, D. Jayamanne, H. Wheeler, C. Gzell, M. Kastelan, G. Schembri, et al., Survival Outcomes of Elderly Patients With glioblastoma multiforme in their 75th year or older treated with adjuvant therapy, Int. J. Radiat. Oncol. Biol. Phys., 98 (2017), 802-810. https://doi.org/10.1016/j.ijrobp.2017.02.028 doi: 10.1016/j.ijrobp.2017.02.028
![]() |
[24] |
K. K. Jain, A critical overview of targeted therapies for glioblastoma, Front. Oncol., 8 (2018), 419. https://doi.org/10.3389/fonc.2018.00419 doi: 10.3389/fonc.2018.00419
![]() |
[25] |
Y. Zheng, N. Gao, Y. L. Fu, B. Y. Zhang, X. L. Li, P. Gupta, et al., Generation of regulable EGFRvⅢ targeted chimeric antigen receptor T cells for adoptive cell therapy of glioblastoma, Biochem. Biophys. Res. Commun., 507 (2018), 59-66. https://doi.org/10.1016/j.bbrc.2018.10.151 doi: 10.1016/j.bbrc.2018.10.151
![]() |
[26] |
M. Momeny, F. Moghaddaskho, N. K. Gortany, H. Yousefi, Z. Sabourinejad, G. Zarrinrad, et al., Blockade of vascular endothelial growth factor receptors by tivozanib has potential anti-tumour effects on human glioblastoma cells, Sci. Rep., 7 (2017), 44075. https://doi.org/10.1038/srep44075 doi: 10.1038/srep44075
![]() |
[27] |
E. G. Sturgill, S. R. Norris, Y. Guo, R. Ohi, Kinesin-5 inhibitor resistance is driven by kinesin-12, J. Cell. Biol., 213 (2016), 213-227. https://doi.org/10.1083/jcb.201507036 doi: 10.1083/jcb.201507036
![]() |
[28] |
C. Müller, D. Gross, V. Sarli, M. Gartner, A. Giannis, G. Bernhardt, et al., Inhibitors of kinesin Eg5: Antiproliferative activity of monastrol analogues against human glioblastoma cells, Cancer Chemother. Pharmacol., 59 (2007), 157-164. https://doi.org/10.1007/s00280-006-0254-1 doi: 10.1007/s00280-006-0254-1
![]() |
[29] |
A. I. Marcus, U. Peters, S. L. Thomas, S. Garrett, A. Zelnak, T. M. Kapoor, et al., Mitotic kinesin inhibitors induce mitotic arrest and cell death in Taxol-resistant and sensitive cancer cells, J. Biol. Chem., 280 (2005), 11569-11577. https://doi.org/10.1074/jbc.M413471200 doi: 10.1074/jbc.M413471200
![]() |
[30] |
D. W. Buster, D. H. Baird, W. Yu, J. M. Solowska, M. Chauviere, A. Mazurek, Expression of the mitotic kinesin Kif15 in postmitotic neurons: Implications for neuronal migration and development, J. Neurocytol., 32 (2003), 79-96. https://doi.org/10.1023/A:1027332432740 doi: 10.1023/A:1027332432740
![]() |
[31] |
B. Stangeland, A. A. Mughal, Z. Grieg, C. J. Sandberg, M. Joel, S. Nygard, et al., Combined expressional analysis, bioinformatics and targeted proteomics identify new potential therapeutic targets in glioblastoma stem cells, Oncotarget, 6 (2015), 26192-26215. https://doi.org/10.18632/oncotarget.4613 doi: 10.18632/oncotarget.4613
![]() |
[32] |
O. Rath, F. Kozielski, Kinesins and cancer, Nat. Rev. Cancer, 12 (2012), 527-539. https://doi.org/10.1038/nrc3310 doi: 10.1038/nrc3310
![]() |
[33] |
G. Bergnes, K. Brejc, L. Belmont, Mitotic kinesins: Prospects for antimitotic drug discovery, Curr. Top. Med. Chem., 5 (2005), 127-145. https://doi.org/10.2174/1568026053507697 doi: 10.2174/1568026053507697
![]() |
[34] |
Z. Z. Wang, J. Yang, B. H. Jiang, J. B. Di, P. Gao, L. Peng, et al., KIF14 promotes cell proliferation via activation of Akt and is directly targeted by miR-200c in colorectal cancer, Int. J. Oncol., 53 (2018), 1939-1952. https://doi.org/10.3892/ijo.2018.4546 doi: 10.3892/ijo.2018.4546
![]() |
[35] |
X. Zhao, L. L. Zhou, X. Li, J. Ni, P. Chen, R. Ma, Overexpression of KIF20A confers malignant phenotype of lung adenocarcinoma by promoting cell proliferation and inhibiting apoptosis, Cancer Med., 7 (2018), 4678-4689. https://doi.org/10.1002/cam4.1710 doi: 10.1002/cam4.1710
![]() |
[36] |
Y. Teng, B. Guo, X. Mu, S. Liu, KIF26B promotes cell proliferation and migration through the FGF2/ERK signaling pathway in breast cancer, Biomed. Pharmacother., 108 (2018), 766-773. https://doi.org/10.1016/j.biopha.2018.09.036 doi: 10.1016/j.biopha.2018.09.036
![]() |
[37] |
Q. Y. Wang, B. Han, W. Huang, C. J. Qi, F. Liu, Identification of KIF15 as a potential therapeutic target and prognostic factor for glioma, Oncol. Rep., 43 (2020), 1035-1044. https://doi.org/10.3892/or.2020.7510 doi: 10.3892/or.2020.7510
![]() |