
To date, few studies have investigated whether the RNA-editing enzymes adenosine deaminases acting on RNA (ADARs) influence RNA functioning in lung adenocarcinoma (LUAD). To investigate the role of ADAR in lung cancer, we leveraged the advantages of The Cancer Genome Atlas (TCGA) database, from which we obtained transcriptome data and clinical information from 539 patients with LUAD. First, we compared ARAR expression levels in LUAD tissues with those in normal lung tissues using paired and unpaired analyses. Next, we evaluated the influence of ADARs on multiple prognostic indicators, including overall survival at 1, 3 and 5 years, as well as disease-specific survival and progression-free interval, in patients with LUAD. We also used Kaplan-Meier survival curves to estimate overall survival and Cox regression analysis to assess covariates associated with prognosis. A nomogram was constructed to validate the impact of the ADARs and clinicopathological factors on patient survival probabilities. The volcano plot and heat map revealed the differentially expressed genes associated with ADARs in LUAD. Finally, we examined ADAR expression versus immune cell infiltration in LUAD using Spearman's analysis. Using the Gene Expression Profiling Interactive Analysis (GEPIA2) database, we identified the top 100 genes most significantly correlated with ADAR expression, constructed a protein-protein interaction network and performed a Gene Ontology/Kyoto Encyclopedia of Genes and Genomes analysis on these genes. Our results demonstrate that ADARs are overexpressed in LUAD and correlated with poor patient prognosis. ADARs markedly increase the infiltration of T central memory, T helper 2 and T helper cells, while reducing the infiltration of immature dendritic, dendritic and mast cells. Most immune response markers, including T cells, tumor-associated macrophages, T cell exhaustion, mast cells, macrophages, monocytes and dendritic cells, are closely correlated with ADAR expression in LUAD.
Citation: Siqi Hu, Fang Wang, Junjun Yang, Xingxiang Xu. Elevated ADAR expression is significantly linked to shorter overall survival and immune infiltration in patients with lung adenocarcinoma[J]. Mathematical Biosciences and Engineering, 2023, 20(10): 18063-18082. doi: 10.3934/mbe.2023802
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To date, few studies have investigated whether the RNA-editing enzymes adenosine deaminases acting on RNA (ADARs) influence RNA functioning in lung adenocarcinoma (LUAD). To investigate the role of ADAR in lung cancer, we leveraged the advantages of The Cancer Genome Atlas (TCGA) database, from which we obtained transcriptome data and clinical information from 539 patients with LUAD. First, we compared ARAR expression levels in LUAD tissues with those in normal lung tissues using paired and unpaired analyses. Next, we evaluated the influence of ADARs on multiple prognostic indicators, including overall survival at 1, 3 and 5 years, as well as disease-specific survival and progression-free interval, in patients with LUAD. We also used Kaplan-Meier survival curves to estimate overall survival and Cox regression analysis to assess covariates associated with prognosis. A nomogram was constructed to validate the impact of the ADARs and clinicopathological factors on patient survival probabilities. The volcano plot and heat map revealed the differentially expressed genes associated with ADARs in LUAD. Finally, we examined ADAR expression versus immune cell infiltration in LUAD using Spearman's analysis. Using the Gene Expression Profiling Interactive Analysis (GEPIA2) database, we identified the top 100 genes most significantly correlated with ADAR expression, constructed a protein-protein interaction network and performed a Gene Ontology/Kyoto Encyclopedia of Genes and Genomes analysis on these genes. Our results demonstrate that ADARs are overexpressed in LUAD and correlated with poor patient prognosis. ADARs markedly increase the infiltration of T central memory, T helper 2 and T helper cells, while reducing the infiltration of immature dendritic, dendritic and mast cells. Most immune response markers, including T cells, tumor-associated macrophages, T cell exhaustion, mast cells, macrophages, monocytes and dendritic cells, are closely correlated with ADAR expression in LUAD.
The general fifth-order KdV equation is dedicated in a variety of scientific fields which is expressed by in the form of
ut+uxxxxx+auuxxx+buxuxx+cu2ux=0, | (1.1) |
where a,b and c are unknown constants. Many researchers have been studied symmetry reductions, consevation laws by using Lie symmetry analysis and exact traveling wave solutions of Eq (1.1) [1,2,3,4,5,6].
Highly motivated by Eq (1.1), we consider the stochastic Wick-type fractional CDGSK equation in the form of
∂⋄αU∂t⋄α+∂⋄5αU∂x⋄5α+A(t)⋄U⋄∂⋄3αU∂x⋄3α+A(t)⋄∂⋄αU∂x⋄α⋄∂⋄2αU∂x⋄2α+C(t)⋄U⋄2⋄∂⋄αU∂x⋄α=0, | (1.2) |
where "⋄" is Wick product and A(t) and C(t) are white noise functionals defined in the Kondratiev distribution space. In particular, by choosing suitable a,b and c with b=a and c=a2/5, Eq (1.1) can be reduced to the SK and CDG equations as follows; when we take a=b=c=5 and apply fractional order in Eq (1.1), the fractional SK equation is expressed by in the form of
∂αU∂tα+∂5αU∂x5α+5U∂3αU∂x3α+5∂αU∂xα∂2αU∂x2α+5U2∂αU∂xα=0, | (1.3) |
and additionally, by taking a=b=30, c=180 in Eq (1.1) and applying fractional order, the fractional CDG equation is given by
∂αU∂tα+∂5αU∂x5α+30U∂3αU∂x3α+30∂αU∂xα∂2αU∂x2α+180U2∂αU∂xα=0. | (1.4) |
Recently, periodic and rational solutions of the SK and CDG equations have been studied by using the conformable dreivative and (G′/G)-expansion method and so on [16,17,18]. M. Arshad et al. have been applied the generalized exp(−Φ(ξ))-expansion method and the improved sub-equation method for exact solutions of the SK equation [9]. M. Safari has been used to variational iteration method and Adomian decomposition method to find numerical solutions of the CDG equation [7] and (G′/G)-expansion method is used to find exact traveling wave solutions of the CDG equation [8]. In addition, several powerful techniques are available in the literature to find exact and numerical solutions of nonlinear partial diffrential equations (NPDEs) such as predictor-corrector method [10], Jacobi elliptic function method [11,12], Kudrayshov method [13,14], homogeneous balance method [15], and so on. Painlevé test is a powerful approach for investigating the integrability properties of many nonlinear evolution equations. It is important to note about the integrability of NPDEs before finding exact solutions of them. So we can determine appropriate conditions when there is the general solution of NPDE or when we can find some exact solutions of NPDE or when we cannot find any exact solution of NPDE [19]. Fractional calculus is utilized to the study of fractional integrals and fractional derivatives for bounded measurable functions [20]. So, the fractional nonlinear evolution models are an interest issue in mathematical physics and engineering [21,22,23,24,25]. It should be mentioned that deriving exact and numerical solutions of the fractional NPDEs (FNPDEs) can describe physical phenomena better than the generalized NPDEs arising in the various fields [26,27,28,29,30,31,32]. In addition, we believe that finding Wick-type versions of exact traveling wave solutions of the stochastic Wick-type FNPDEs plays a significant role in the description of physical phenomena of their equations.
This paper is organized as follows; in Section 2, we give the definitions of the Wick product, the Hermite transformation and the conformable fractional derivative and steps of finding exact traveling wave solutions of the stochastic Wick-type FNPDEs. In Section 3, we investigate the integrability of Eq (1.2) by using the Painlevé test and we obtain new Wick-type and non-Wick-type versions of exact traveling wave solutions of Eq (1.2). Section 4 consists of exact traveling wave solutions of the FNPDEs such as Eq (1.3) and Eq (1.4). Finally, some conclusions give in the end of this work.
In this section, we introduce the Wick product, the Hermite transform that can convert the FNPDEs into the stochastic Wick-type FNPDEs and the conformable fractional derivative to convert the orinary nonlinear differential equations into FNPDEs [33,34]. And we also introduce the steps of finding exact traveling wave solutions of the stochastic Wick-type FNPDEs. Let's see the basic definitions firstly.
Assume S(Rd) and (S(Rd))∗ are the Hida test function space and the Hida disturbance space on Rd, respectively. Fixed n∈R, (S)n1 consists of elements
x=∑αcαHα(w) |
where cα∈Rn,||x||21,k≡∑αc2α(α!)2(2N)kα<∞ for all k∈N with c2α=|cα|2=∑nk=1(c(k)α)2,cα=(c(1)α,⋯,c(n)α)∈Rn,α!=∏∞k=1αk! and (2N)α=∏j(2j)αj, and Hα(w)=∏∞i=1Hαi(⟨x,ηi⟩),w∈(S(Rd))∗,α=(α1,α2,⋯)∈J.
The space (S)n−1 consisit of all formal expansions
X=∑αaαHα |
where aα∈Rn,||X||−1,−q≡∑αa2α(2N)−qα<∞, for all n,q∈N. The family of seminorms ||x||1,k,k∈N gives rise to a topology on (S)n1, we can regard (S)n−1 as the dual of (S)n1 by the action
⟨X,x⟩=∑α(aα,cα)α!, |
where (aα,cα) is the usual inner product in Rn.
Definition 2.1. Let X=∑αaαHα and Y=∑βbβHβ be two elements of (S)n−1 with aα,bβ∈Rn. The Wick product of X and Y is the element X⋄Y given by
X⋄Y=∑α,β(aα,bβ)Hα+β. |
Definition 2.2. Let X=∑αaαHα∈(S)n−1 and aα∈Rn. The Hermite transform of X, denoted by ˜X(z), is defined by
˜X(z)=∑aαzα∈Cn(whenconvergent), |
where z=(z1,z2,…)∈Cn and zα=zα11zα22⋯ if α=(α1,α2,…)∈J, where z0j=1.
Note that if X,Y∈(S)n−1, then the Hermite transform of X⋄Y is
~X⋄Y(z)=˜X(z)⋅˜Y(z) |
for all z such that ˜X(z) and ˜Y(z) exist, where ˜X(z)⋅˜Y(z) is complex bilinear product between two elements of Cn defined by (ν1,ν2,…,νn)⋅(w1,w2,…wn)=∑ni=1νiwi, where νi,wi∈C.
Let X=∑αaαHα∈(S)n−1. Then the vector c0=˜X(0)∈Rn is called the generalized expectation of X and is denoted by E(X). Suppose that f:V→Cm is an analytic function, where V is a neighborhood of E(X). Assume that the Taylor series of f around E(X) has some coefficients in Rn, then the Wick version f⋄(X)=H−1(f∘˜X)∈(S)n−1.
The Wick exponent of X∈(S)n−1 is defined by exp⋄{X}=∑∞n=0X⋄n/n!. With the Hermite transformation, the Wick exponent shows the same algebra properties as the usual one. For example, exp⋄{X+Y}=exp⋄{X}⋄exp⋄{Y}.
Now we introduce the conformable fractional derivative as below [39].
Definition 2.3. Given a function g:(0,+∞)→R, then the conformable fractional derivative of a function g is defined by
tDαg(t)=limϵ→0g(t+ϵt1−α)−g(t)ϵ, |
where t>0 and α∈(0,1].
We have some important rules of the conformable fractional derivatives for some familiar functions as follows;
tDαtr=rtr−α,r∈R,tDα(f(t)g(t))=f(t)tDαg(t)+g(t)tDαf(t),tDα((f∘g)(t))=t1−αg″(t)f″(g(t)),tDα(f(t)g(t))=g(t)tDαf(t)−f(t)tDαg(t)g2(t). |
We will present steps for finding exact traveling wave solutions of the stochastic Wick-type FNPDEs. Consider the stochastic Wick-type FNPDE with respect to x and t as
Q⋄(U,D⋄αtU,D⋄αxU,D⋄2αttU,D⋄2αtxU,D⋄2αxxU,…)=0, | (2.1) |
where U=U(x,t) is unknown solution. Eq (2.1) is a polynomial in U and its various partial derivatives. We take the Hermite transformation of Eq (2.1). This turns the Wick product into the ordinary products and the equation takes the following form
˜Q(˜U,Dαt˜U,Dαx˜U,D2αtt˜U,D2αtx˜U,D2αxx˜U,…,z)=0, | (2.2) |
where H(U)=˜U=˜U(x,t,z) and z=(z1,z2,…)∈Kq(r), for some q,r, where Kq(r)={z=(z1,z2,…)∈CNand∑α≠0|zα|2(2N)qα<r2}. Then, under certain conditions, we can take the inverse Hermite transformation U=H−1(˜U)∈(S)−1. and thereby obtain the solution U of the original Wick equation (2.1). We have the following theorem [35].
Theorem 2.1. Suppose ˜U(x,t,z) is a solution (in the usual strong pointwise sense) of Eq. (2.4) for (x,t) in some bounded open set G⊂Rd×R, and for each z∈Kq(R), for some q,R. Moreover, suppose that ˜U(x,t,z) and all its partial derivatives involved in (2.4) are (uniformly) bounded for (x,t,z)∈G×Kq(R), continuous with respect to (x,t)∈G for all z∈Kq(R) and analytic with respect to z∈Kq(R), for all (x,t)∈G. Then there exists U(x,t)∈(S)−1 such that ˜U(x,t,z)=(HU(x,t))(z) for all (x,t,z)∈G×Kq(R) and U(x,t) solves (in the strong sense in (S)−1) Eq (2.1 ) in (S)−1 .
Next we introduce some steps to obtain the solution of Eq (2.2) in detail.
Step 1. Traveling wave variable is supposed by
˜ζ(x,t,z)=kX+∫T0˜ω(s,z)ds, | (2.3) |
where X=xαα,T=tαα, k is unknown constant and ˜ω(s,z) is unknown integrable function. By applying the conformable fractional derivative and traveling wave variable (2.3), Eq. (2.2) can be reduced into the following ordinary differential equation with respect to ζ;
˜Q(˜U,k˜Uζ,ω˜Uζ,k2˜Uζζ,ω2˜Uζζ,kω˜Uζζ,…,z)=0, | (2.4) |
where ˜ζ=ζ, ˜ω=ω, ˜U(ζ)=˜U(x,t,z) and ˜Uζ=d˜U/dζ,˜Uζζ=d2˜U/ζ2, and so on.
Step 2. Let's test the integrability of Eq. (2.4) by using Painlevé test. If Eq (2.4) passes Painlevé test by appropriate conditions of the integrability of Eq (2.4), it can move on next step to find exact solutions of Eq (2.4). If not, Eq (2.4) cannot give any exact solution.
Step 3. By homogeneous balance method, we take exact solution of Eq. (2.4) in the form of
˜U(ζ)=N∑j=0˜Aj(t,z){Ψ(ζ)Φ(ζ)}j, | (2.5) |
where
Ψ(ζ)Φ(ζ)=˜p(t,z)−˜q(t,z)˜p(t,z)−˜q(t,z)exp{−(˜p(t,z)−˜q(t,z))ζ},if˜p(t,z)≠˜q(t,z), | (2.6) |
that is satisfied the sub-equations
Ψ′(ζ)=˜p(t,z)Ψ(ζ), | (2.7) |
Φ′(ζ)=˜p(t,z)Ψ(ζ)+˜q(t,z)Φ(ζ), | (2.8) |
where ˜p(t,z) and ˜q(t,z) are integrable functions on R and {˜Aj(t,z)}Nj=0 are unknown coefficients to be computed later, with ˜AN(t,z)≠0. The pole-order N of exact solution (2.5) can be determined from the highest order linear term and the highest order nonlinear term in Eq (2.4) by homogeneous balance method [15].
Step 4. Equating each coefficient of the same order of {Ψ(ζ)/Φ(ζ)} to zero by substituting exact solution (2.5) into Eq (2.4) and then the required relations of cofficients and physical parameters are found by solving the algebraic equations in terms of {˜Aj(t,z)}Nj=0,˜p(t,z), ˜q(t,z),k,˜ω(t,z) with the aid of computer package programs. Replacing exact solution (2.5) by the traveling wave variable (2.3) and {˜Aj(t,z)}Nj=0, we can construct the Wick-type exact traveling wave solutions of Eq (2.1) by using the inverse Hermite transform in Theorem 2.1.
In this section, we will obtain the conditions of integrability of Eq (1.2) by employing the Painlevé test. And then we can find the Wick-type and non-Wick-type versions of exact traveling wave solutions of Eq (1.2) by the sub-equations method if it passes the Painlevé test.
Now, by the definitions of the Wick product and the Hermite transformation, first of all, we change the non-Wick-type version of Eq (1.2) that is rewritten by in the form of
∂α˜U∂tα+∂5α˜U∂x5α+˜A(t,z)˜U∂3α˜U∂x3α+˜A(t,z)∂α˜U∂xα∂2α˜U∂x2α+˜C(t,z)˜U2∂α˜U∂xα=0, | (3.1) |
where z=(z1,z2,…)∈CN is a vector parameter. Let ˜U=˜U(x,t,z)=u(ζ(x,t,z)) be the solution of Eq (3.1). With the use of traveling wave variable
ζ=˜ζ(x,t,z)=kX+∫T0˜ω(s,z)ds, | (3.2) |
where X=xαα and T=tαα, and by the properties of the conformable fractional derivative, Eq (3.1) is rewritten by in the form of
˜ω(T,z)uζ+k5uζζζζζ+a(t,z)k3uuζζζ+a(t,z)k3uζuζζ+c(t,z)ku2uζ=0, | (3.3) |
where uζ=du/dζ,uζζ=d2udζ2,… and a(t,z)=˜A(t,z),c(t,z)=˜C(t,z).
Let us test the integrability of Eq (3.3) on the Painlevé test [36,37,38]. First, to determine the pole order of the solution expansion of Eq (3.3), the equation with the leading members corresponding to Eq (3.3) is
k5uζζζζζ+a(t,z)k3uζuζζ=0. | (3.4) |
Substituting u(ζ)=B−r(t,z)ζr into Eq (3.4), we get
r=2,B−r(t,z)=−60k2a(t,z). | (3.5) |
So, we have the first member of the solution expansion in Laurent series as follows;
u≃−60k2a(t,z)ζ2+⋯. | (3.6) |
Now we have to find Fuchs indices [37,38]. For this idea we substitute
u=−60k2a(t,z)ζ2+Bj(t,z)ζj−2, | (3.7) |
into Eq (3.4) and equate the equation at Bj(t,z) to zero, we have the equation for Fuchs indices in the following form of
j5−20j4+155j3−460j2+84j+720=0. | (3.8) |
In order to Eq (3.3) passes the Painlevé test, we have to obtain the integer values for Fuchs indices as follows;
j1=−1,j2=2,j3=6. | (3.9) |
Now, to find the conditions of the integrability of Eq (3.3), we consider Laurent series for general solution expansion of Eq (3.3) in the form of
u(ζ)≃−60k2a(t,z)ζ2+B1(t,z)ζ+B2(t,z)+B3(t,z)ζ+B4(t,z)ζ2+B5(t,z)ζ3+B6(t,z)ζ4, | (3.10) |
where B2(t,z) and B6(t,z) are arbitrary functions corresponding to j2=2,j3=6, respectively.
We substitute Laurent series (3.10) into Eq (3.3) and equate coefficients at different powers of ζ to zero, we have special relations on coefficients and parameters of Eq (3.3) corresponding to Fuchs indices j2=2,j3=6 as follows;
B1(t,z)=±k√(5a2−50c)B2(t,z)a3−30ac, | (3.11) |
2280a3k5−18000ack5=0, | (3.12) |
B3(t,z)=a(a4−60a2c+1500c2)B2(t,z)30k(a4−40a2c+300c2)√(5a2−50c)B2(t,z)a3−30ac, | (3.13) |
B4(t,z)=ka(a6−60a4c+3300a2c2−90000c3)B22(t,z)120k3(2a6−135a4c+2700a2c2−13500c3)−a(t,z)(30a4−1800a2c−27000c2)ω)120k3(2a6−135a4c+2700a2c2−13500c3), | (3.14) |
B5(t,z)=±a2B51(t,z)3600k4B52(t,z)√(5a2−50c)B2(t,z)a3−30ac, | (3.15) |
a4ck(a6−60a4c+3300a2c2−90000c3)B22(t,z)B26(t,z)12k2(2a6−135a4c+2700a2c2−13500c3)−a4c(30a4+1800a2c−27000c2)ωB26(t,z)12k2(2a6−135a4c+2700a2c2−13500c3)−a7c(−5a2+50c)(kB61(t,z)B22(t,z)+B62(t,z)ω)2B6(t,z)1296000k7(a3−30ac)B262(t,z)=0, | (3.16) |
where B51(t,z)=k(a10−20a8c+600a6c2−12×104a4c3+432×104a2c4−297×105c5)B22(t,z)+(30a8−1650a6c+135×102a4c2+405×103a2c3-405×104c4)ω,B52(t,z)=2a10−165a8c+4825a6c2−60750a4c3+3.375×105a2c4−675×103c5,B61(t,z) = a10−20a8c+600a6c2−12×104a4c3+432×104a2c4−297×105c5,B62(t,z)=30a8−1650a6c+135×102a4c2+405×103a2c3−405×104c4,B63(t,z)=2a10−165a8c+4825a6c2−60750a4c3+3.375×105a2c4−675×103c5, letting a=a(t,z),c=c(t,z), ω=˜ω(T,z) and T=tα/Γ(1+α).
Equation (3.3) would passes the Painlevé test if Eqs (3.12) and (3.16) were identically equal to zero. As the consequence of this expansion, there is the solution expansion of Eq (3.3) in Laurent series with two arbitrary functions B2(t,z) and B6(t,z). Then we can obtain exact solutions of Eq (3.3).
Remark 3.1. From the compatibilty conditions (3.12) and (3.16) at Fuchs indices j2=2 and j3=6, we have a relation of c(t,z)=19150a2(t,z),a(t,z)≠0 and
B6(t,z)=(17996a2(t,z)kB22(t,z)+35525˜ω(T,z))2B2(t,z)15563625k5(569a2(t,z)kB22(t,z)+980ω(T,z)), |
respectively. By the traveling wave variable (3.2) and Laurent series (3.10), the solution expansion u(ζ) is expressed by in the form of
u(ζ)≈−60k2aζ2±2√2107√B2(t,z)akζ+B2(t,z)±1313528√210√B2(t,z)aaB2(t,z)kζ−252352(3414aB22(t,z)25k2+1176ω5ak3)ζ2±125√210724416√B2(t,z)a(287936a2B22(t,z)3125k3+22736ω125)ζ3+(17996a2kB22(t,z)+35525˜ω(T,z))2B2(t,z)15563625k5(569a2kB22(t,z)+980ω(T,z))ζ4, | (3.17) |
where ζ=kX+∫T0˜ω(τ,z)ds, X=xαα,T=tαα,τ=[αs]1/α,a=a(t,z).
If we take c(t,z)=15a2(t,z) and B2(t,z)=0, the solution expansion u(ζ) is expressed by in the form of
u(ζ)≈−60k2a(t,z)ζ2−5ω(T,z)2a(t,z)k3ζ2 | (3.18) |
where ζ=kX+∫T0˜ω(τ,z)ds, X=xαα,T=tαα,τ=[αs]1/α.
Now, let us find Wick-type and non-Wick-type versions of exact traveling wave solutions of Eq (1.2). First, to determine the pole-order N of exact solution of Eq (3.3), we take the highest order linear term uζζζζζ and the highest order nonlinear term uζuζζ in Eq (3.3) and so we obtain N+5=2N+3 which gives N=2 by the homogeneous balance method [15]. Now, we take exact solution of Eq (3.3) in the form of
˜U(ζ)=˜A0(t,z)+˜A1(t,z){Ψ(ζ)Φ(ζ)}+˜A2(t,z){Ψ(ζ)Φ(ζ)}2, | (3.19) |
where {Ψ(ζ)/Φ(ζ)} is given in Section 2. We substitute exact solution (3.19) and {Ψ(ζ)/Φ(ζ)} into Eq (3.3) and then we can yield the algebraic equations by equating to zero the expressions with the same degree of {Ψ(ζ)/Φ(ζ)}. Solving the algebraic equations with respect to the unknowns ˜A2(t,z),˜A1(t,z),˜A0(t,z) and ˜ω(T,z) by the help of computer package programs, we obtain three nontrivial solution sets as follows;
˜ω(T,z)=−5k5q4(t)(M1(t,z)M2(t,z)+M3(t,z))4˜C(t,z)M4(t,z),˜p(t,z)=−˜q(t,z),˜A(t,z)=˜A(t,z),˜C(t,z)=˜C(t,z),˜A0(t,z)=−5k2˜q2(t,z)((3˜A2(t,z)−8˜C(t,z))M1(t,z)+20˜A(t,z))2˜C(t,z)(˜A(t,z)M1(t,z)+10˜C(t,z)),˜A1(t,z)=±6k2˜q2(t,z)M1(t,z)˜C(t,z),˜A2(t,z)=±3k2˜q2(t,z)M1(t,z)˜C(t,z),M1(t,z)=√9˜A2(t,z)−40˜C(t,z)±3˜A(t,z),M2(t,z)=27˜A5(t,z)−144˜A3(t,z)˜C(t,z)+320˜A(t,z)˜C2(t,z),M3(t,z)=1600˜C3(t,z)−760˜A2(t,z)˜C2(t,z),M4(t,z)=(3˜A3(t,z)−10˜A(t,z)˜C(t,z))M1(t,z)+20˜A2(t,z)˜C(t,z)−50˜C2(t,z), | (3.20) |
˜ω(T,z)=4731.19k2˜q4(t,z),˜p(t,z)=−11.4244˜q(t,z),˜A(t,z)=˜A(t,z),˜C(t,z)=0.0530465˜A2(t,z),˜A0(t,z)=−104.44k2˜q2(t,z)˜A(t,z),˜A1(t,z)=0,˜A2(t,z)=−2785.54k2˜q2(t,z)˜A(t,z), | (3.21) |
˜ω(T,z)=−159.179k5˜q4(t,z),˜p(t,z)=(2±√3)˜q(t,z),˜A(t,z)=˜A(t,z),˜C(t,z)=−0.175˜A2(t,z),˜A0(t,z)=25.5092k2˜q2(t,z)˜A(t,z),˜A1(t,z)=−127.956k2˜q2(t,z)˜A(t,z),˜A2(t,z)=−238.769k2˜q2(t,z)˜A(t,z). | (3.22) |
In order to obtain the Wick-type versions of exact traveling wave solutions of Eq (1.2), we replace exact solution (3.19) by nontrivial solution sets (3.20)–(3.22) and Eq (2.6), and by using the inverse Hermite transformation U=H−1(˜U), we have the Wick-type exact traveling wave solutions of Eq (1.2) in the followings. Based on (3.20), we get the first Wick-type exact traveling wave solution of Eq. (1.2) in the following form
U1(x,t)=±3k2q⋄2(t)⋄M1(t)C(t)⋄[21+exp⋄{2q(t)⋄ζ1(x,t)}]⋄2±6k2q⋄2(t)⋄M1(t)C(t)⋄[21+exp⋄{2q(t)⋄ζ1(x,t)}]−5k2q⋄2(t)⋄((3A⋄2(t)−8C(t))⋄M1(t)+20A(t))2C(t)⋄(A(t)⋄M1(t)+10C(t)), | (3.23) |
where
ζ1(x,t)=kxαα−∫T05k5q⋄4(τ)⋄(M1(τ)⋄M2(τ)+M3(τ))4C(τ)⋄M4(τ)ds, |
τ=[αs]1/α, T=tα/α, and with a relation of p(t)=−q(t),
M1(t)=√9A⋄2(t)−40C(t)±3A(t),M2(t)= 27A⋄5(t)−144A⋄3(t)⋄C(t)+320A(t)⋄C⋄2(t),M3(t)=−760A⋄2(t)⋄C⋄2(t)+1600C⋄3(t),M4(t)=(3A⋄3(t)−10A(t)⋄C(t))⋄M1(t)+20A⋄2(t)⋄C(t)−50C⋄2(t).
Subsequently, from (3.21) and (3.22), we obtain the following Wick-type exact traveling wave solutions of Eq (1.2):
U2(x,t)=−238.769k2q⋄2(t)A(t)⋄[12.424411.4244+exp⋄{12.4244q(t)⋄ζ2(x,t)}]⋄2−104.44k2q⋄2(t)A(t), | (3.24) |
where
ζ2(x,t)=kxαα+∫T04731.19k2q⋄4(τ)ds, |
τ=[αs]1/α, T=tα/α and with the relations of p(t)=−11.4244q(t) and C(t)=0.053A⋄2(t), and
U3(x,t)=−238.769k2q⋄2(t)A(t)⋄[2.73213.7321−exp⋄{−2.7321q(t)⋄ζ3(x,t)}]⋄2−127.956k2q⋄2(t)A(t)⋄[2.73213.7321−exp⋄{−2.7321q(t)⋄ζ3(x,t)}]+25.5092k2q⋄2(t)A(t), | (3.25) |
where
ζ3(x,t)=kxαα−∫T0159.179k5q⋄4(τ)ds, |
τ=[αs]1/α, T=tα/α and with the relations of p(t)=3.7321q(t) and C(t)=−0.175A⋄2(t), and
U4(x,t)=−238.769k2q⋄2(t)A(t)⋄[0.73210.2679−exp⋄{0.732q(t)⋄ζ4(x,t)}]⋄2+127.956k2q⋄2(t)A(t)⋄[0.73210.2679−exp⋄{0.732q(t)⋄ζ4(x,t)}]+25.5092k2q⋄2(t)A(t), | (3.26) |
where
ζ4(x,t)=kxαα−∫T0159.179k5q⋄4(τ)ds, |
τ=[αs]1/α, T=tα/α and with the relations of p(t)=0.2679q(t) and C(t)=−0.175A⋄2(t).
In white noise analysis, a version of Brownian motion B(t) expresses informally B(t)=∫t0W(τ)dτ and in a generalized sense, W(t)=dB(t)/dt, which is white noise defined in R. Let's take A(t)=f1(t)+W(t) and C(t)=f2(t)+W(t) where f1(t) and f2(t) be integrable functions on R. Based on the Wick-type exact traveling wave solutions (3.23)–(3.26), the non-Wick-type exact traveling wave solutions can be expressed by in the forms of
U12(x,t)=±3k2q2(t)M1(t)f2(t)+W(t)[21+exp{2q(t)ζ12(x,t)}]2±6k2q2(t)M1(t)f2(t)+W(t)[21+exp{2q(t)ζ12(x,t)}]−5k2q2(t)((3(f1(t)+W(t))2−8(f2(t)+W(t)))M1(t)+20(f1(t)+W(t)))2(f2(t)+W(t))((f1(t)+W(t))M1(t)+10(f2(t)+W(t))), | (3.27) |
where
ζ12(x,t)=kxαα−∫T05k5q4(τ)(M1(τ)M2(τ)+M3(τ))4(f2(τ)+W(τ))M4(τ)ds, |
τ=[αs]1/α, T=tα/α, and with a relation of p(t)=−q(t),
M1(t)=±3(f1(t)+W(t))+√9(f1(t)+W(t))2−40(f2(t)+W(t)),
M2(t)=27(f1(t)+W(t))5−144(f1(t)+W(t))3(f2(t)+W(t))+320(f1(t)+W(t))(f2(t)+W(t))2,
M3(t)=−760(f1(t)+W(t))2(f1(t)+W(t))2+1600(f2(t)+W(t))3,
M4(t)=(3(f1(t)+W(t))3−10(f1(t)+W(t))(f2(t)+W(t)))M1(t)+20(f1(t)+W(t))2(f2(t)+W(t))−50(f2(t)+W(t))2.
U22(x,t)=−238.769k2q2(t)f1(t)+W(t)[12.424411.4244+exp{12.4244q(t)ζ22(x,t)}]2−104.44k2q2(t)f1(t)+W(t), | (3.28) |
where
ζ22(x,t)=kxαα+∫T04731.19k2q4(τ)ds, |
τ=[αs]1/α, T=tα/α and with relations of p(t)=−11.4244q(t) and C(t)=0.053A2(t), and
U32(x,t)=−238.769k2q2(t)f1(t)+W(t)[2.73213.7321−exp{−2.7321q(t)ζ32(x,t)}]2−127.956k2q2(t)f1(t)+W(t)[2.73213.7321−exp{−2.7321q(t)ζ32(x,t)}]+25.5092k2q2(t)f1(t)+W(t), | (3.29) |
where
ζ32(x,t)=kxαα−∫T0159.179k5q4(τ)ds, |
τ=[αs]1/α, T=tα/α and with relations of p(t)=2.7321q(t) and C(t)=−0.175A2(t), and
U42(x,t)=−238.769k2q2(t)f1(t)+W(t)[0.73210.2679−exp{0.732q(t)ζ42(x,t)}]2+127.956k2q2(t)f1(t)+W(t)[0.73210.2679−exp{0.732q(t)ζ42(x,t)}]+25.5092k2q2(t)f1(t)+W(t), | (3.30) |
where
ζ42(x,t)=kxαα−∫T0159.179k5q4(τ)ds, |
τ=[αs]1/α, T=tα/α and with relations of p(t)=0.2679q(t) and C(t)=−0.175A2(t).
Remark 3.2. Wick-type exact traveling wave solution (3.23) of Eq (1.2) is depending on white noise functionals A(t),C(t) and a parameter function q(t) by a relation of p(t)=−q(t). There are some relations between white noise functionals and parameter functions such as {C(t)=0.053A2(t),p(t)=−11.4244q(t)}, {C(t)=−0.175A2(t),p(t)=2.7321q(t)} and {C(t)=−0.175A2(t),p(t)=0.2679q(t)}. So we know that these solutions (3.24)–(3.26) are only depending on white noise functional A(t) and parameter function q(t). Specially, we perform the dynamics of the non-Wick-type exact traveling wave solution (3.28) without white noise (W(t)=0) has different soliton-type behaviours in Figure 1 and we perform the dynamics of (3.28) with white noise W(t)=−cosh(0.1RandomReal[t]) in Figure 2, as the fractional orders α=0.3,0.5 and the integral order α=1, under k=0.5,q(t)=0.1cos(0.1t),f1(t)=−0.1cos(0.1t), respectively. And we represent that the non-Wick-type exact traveling wave solution (3.29) without white noise (W(t)=0) has different soliton-type behaviours in Figure 3 as the fractional orders α=0.1,0.5 and the integral order α=1, under k=0.5,q(t)=0.1cos(0.1t),f1(t)=−0.1cos(0.1t).
In order to solve the fractional SK equation (1.3), substituting the transformation U(t,x)=u(ζ) and traveling wave variable
ζ=ζ(x,t)=kxαα+∫T0ω(s)ds, | (4.1) |
where T=tα/α into Eq (1.3), Eq (1.3) can be converted to the ordinary nonlinear differential equation
ω(T)u′+k5u(5)+5k3uu‴+5k3u′u″+5ku2u′=0, | (4.2) |
where u(n)=dnu/dζn is the nth order derivative of u with respect to ζ and n is the positive integer number.
Equation (1.3) has two exact traveling wave solutions with the use of the part of Section 2 as follows; the first exact traveling wave solution of Eq (1.3) is expressed by
USK1(x,t)=21.3693k2q2(t)[21+exp{2q(t)ζ1(x,t)}]2−42.7386k2q2(t)[21+exp{2q(t)ζ1(x,t)}]+10.075k2q2(t), | (4.3) |
where
ζ1(x,t)=kxαα+∫T085.2814k5q4(τ)ds, |
τ=[αs]1/α, T=tα/α and with a relation of p(t)=−q(t), and the second exact traveling wave solution of Eq (1.3) is given by
USK2(x,t)=−3.36932k2q2(t)[21+exp{2q(t)ζ2(x,t)}]2+6.73863k2q2(t)[21+exp{2q(t)ζ2(x,t)}]−3.32505k2q2(t), | (4.4) |
where
ζ2(x,t)=kxαα+∫T035.0311k5q4(τ)ds, |
τ=[αs]1/α, T=tα/α and with a relation of p(t)=−q(t).
Example 4.1. For the integral order α=1, substituting constant coefficients f1(t)=5,f2(t)=5 and W(t)=0 into non-wick-type exact traveling wave solution (3.27), and a new version of exact traveling wave solution of Eq (1.2) is given by in the form of
U(x,t)=12k2q2(t)[21+exp{2q(t)ζ(x,t)}]2+24k2q2(t)[21+exp{2q(t)ζ(x,t)}]−83k2q2(t), | (4.5) |
where ζ(x,t)=kx+∫t0552k5q4(s)ds, and with a relation of p(t)=−q(t). We expect that this solution has periodic solitons in the dynamics to be seen in Figure 6.
Remark 4.2. We discuss the dynamical behaviours of the obtained exact traveling wave solutions in order to describe physical interpretation of the fractional SK equation. The fractional SK equation has two nontrivial exact traveling wave solutions with a relation of time-dependent parameters as p(t)=−q(t) as follows; exact traveling wave solution (4.3) gives the dynamics as irregular traveling waves for the fractional orders α=0.1,0.5 and dark-type solitons for the integral order α=1 with suitable parameters k=0.002,q(t)=20cos(0.1t)+15sin(0.2t) in Figure 4. In Figure 5, exact traveling wave solution (4.4) describes solitary waves for the fractional orders α=0.2,0.5 and the integral order α=1 with k=0.002,q(t)=20cos(0.1t). The dynamics of exact traveling wave solution (4.5) represent periodic solitons feature and the density plot by k=0.002,q(t)=20cos(0.1t) in Figure 6.
In order to solve Eq (1.4), substituting the transformation U(t,x)=u(ζ) and traveling wave variable (4.1) into Eq (1.4), Eq (1.4) is expressed by in the form of
ω(T)u′+k5u(5)+30k3uu‴+30k3u′u″+180ku2u′=0. | (4.6) |
Similarly, we use the method in Section 4.1 to find exact traveling wave solutions of Eq. (1.4) and so we obtain the followings; the first exact traveling wave solution of Eq (1.4) is expressed by
UCDG1(x,t)=3.56155k2q2(t)[21+exp{2q(t)ζ1(x,t)}]2−7.12311k2q2(t)[21+exp{2q(t)ζ1(x,t)}]+1.67917k2q2(t), | (4.7) |
where ζ1(x,t)=kxαα+∫T085.2814k5q4(τ)ds,τ=[αs]1/α, T=tα/α and with a relation of p(t)=−q(t), and the second exact traveling wave solution of Eq (1.4) is given by
UCDG2(x,t)=−0.561553k2q2(t)[21+exp{2q(t)ζ2(x,t)}]2+1.12311k2q2(t)[21+exp{2q(t)ζ2(x,t)}]−0.554174k2q2(t), | (4.8) |
where ζ2(x,t)=kxαα+∫T035.0311k5q4(τ)ds,τ=[αs]1/α, T=tα/α and with a relation of p(t)=−q(t).
Example 4.3. For the integral order α=1, substituting f1(t)=30,f2(t)=180 and W(t)=0 into non-Wick-type exact traveling wave solution (3.27) and then we have a new version of exact traveling wave solution of Eq (1.2) expressed by in the form of
U(x,t)=−2k2q2(t)[21+exp{2q(t)ζ(x,t)}]2+4k2q2(t)[21+exp{2q(t)ζ(x,t)}]−253648k2q2(t), | (4.9) |
where ζ(x,t)=kx−∫t0552k5q4(s)ds, and with a relation of p(t)=−q(t).
Remark 4.4. There are some performances of the obtained solutions of the fractional CDG equation. Exact traveling wave solution (4.7) gives different waves for the fractional orders α=0.1,0.5 and the dark-type solitons solution for the integral order α=1, respectively, under k=0.002,q(t)=20cos(0.1t) in Figure 7. In Figure 8, exact traveling wave solution (4.8) performs solitary wave for α=0.1 a soliton-like for α=0.5 and solitons for the integral order α=1, respectively, under k=0.017,q(t)=20cos(0.1t). Figure 9 performs (a) the dynamic of exact traveling wave solution (4.9) with periodic solitons and (b) the density plot, under k=0.003,q(t)=20cos(0.1t).
In this paper, we obtained new Wick-type and non-Wick-type versions of exact traveling wave solutions of the stochastic Wick-type fractional CDGSK equation and new exact traveling wave solutions of the fractional SK and CDG equations by employing the sub-equations method. The considered equations provided us more new exact solutions than the solutions by other existing methods and these solutions might be of great importance in various fields of applied science for interpreting some physical phenomena by performing the dynamics of the obtained solutions under suitable physical parameters. We believe that the sub-equations method is very straightforward and powerful to find exact solutions of the nonlinear evolution equations.
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. NRF-2019R1A6A1A10073079).
The authors declare no conflict of interest.
[1] |
C. Jin, G. K. Lagoudas, C. Zhao, S. Bullman, A. Bhutkar, B. Hu, et al., Commensal microbiota promote lung cancer development via γδ T cells, Cell, 176 (2019), 998–1013. https://doi.org/10.1016/j.cell.2018.12.040 doi: 10.1016/j.cell.2018.12.040
![]() |
[2] |
J. Huo, Y. Xu, T. Sheu, R. J. Volk, Y. T. Shih, Complication rates and downstream medical costs associated with invasive diagnostic procedures for lung abnormalities in the community setting, JAMA Int. Med., 179 (2019), 324–332. https://doi.org/10.1001/jamainternmed.2018.6277 doi: 10.1001/jamainternmed.2018.6277
![]() |
[3] |
R. K. Meleppat, C. R. Fortenbach, Y. Jian, E. S. Martinez, K. Wagner, B. S. Modjtahedi, et al., In vivo imaging of retinal and choroidal morphology and vascular plexuses of vertebrates using swept-source optical coherence tomography, Transl. Vis. Sci. Technol., 11 (2022), 11. https://doi.org/10.1167/tvst.11.8.11 doi: 10.1167/tvst.11.8.11
![]() |
[4] |
R. K. Meleppat, K. E. Ronning, S. J. Karlen, M. E. Burns, E. N. Pugh, R. J. Zawadzki, In vivo multimodal retinal imaging of disease-related pigmentary changes in retinal pigment epithelium, Sci. Rep., 11 (2021), 16252. https://doi.org/10.1038/s41598-021-95320-z doi: 10.1038/s41598-021-95320-z
![]() |
[5] |
K. S. Blandin, P. A. Crosbie, H. Balata, J. Chudziak, T. Hussell, C. Dive, Progress and prospects of early detection in lung cancer, Open Biol., 7 (2017), 170070. https://doi.org/10.1098/rsob.170070 doi: 10.1098/rsob.170070
![]() |
[6] |
P. C. Hoffman, A. M. Mauer, E. E. Vokes, Lung cancer, Lancet, 355 (2000), 479–485. https://doi.org/10.1016/S0140-6736(00)82038-3 doi: 10.1016/S0140-6736(00)82038-3
![]() |
[7] |
S. M. Park, E. Y. Choi, M. Bae, S. Kim, J. B. Park, H. Yoo, et al., Histone variant H3F3A promotes lung cancer cell migration through intronic regulation, Nat. Commun., 7 (2016), 12914. https://doi.org/10.1038/ncomms12914 doi: 10.1038/ncomms12914
![]() |
[8] |
B. L. Bass, RNA editing by adenosine deaminases that act on RNA, Annu. Rev. Biochem., 71 (2002), 817–846. https://doi.org/10.1146/annurev.biochem.71.110601.135501 doi: 10.1146/annurev.biochem.71.110601.135501
![]() |
[9] |
L. Bazak, A. Haviv, M. Barak, J. H. Jacob, P. Deng, R. Zhang, et al., A-to-I RNA editing occurs at over a hundred million genomic sites, located in a majority of human genes, Genome Res., 24 (2014), 365–376. https://doi.org/10.1101/gr.164749.113 doi: 10.1101/gr.164749.113
![]() |
[10] |
K. Licht, U. Kapoor, F. Amman, E. Picardi, D. Martin, P. Bajad, et al., A high resolution A-to-I editing map in the mouse identifies editing events controlled by pre-mRNA splicing, Genome Res., 29 (2019), 1453–1463. https://doi.org/10.1101/gr.242636.118 doi: 10.1101/gr.242636.118
![]() |
[11] |
K. Pestal, C. C. Funk, J. M. Snyder, N. D. Price, P. M. Treuting, D. B. Stetson, Isoforms of RNA-editing enzyme adar1 independently control nucleic acid sensor MDA5-driven autoimmunity and multi-organ development, Immunity, 43 (2015), 933–944. https://doi.org/10.1016/j.immuni.2015.11.001 doi: 10.1016/j.immuni.2015.11.001
![]() |
[12] |
B. J. Liddicoat, A. M. Chalk, C. R. Walkley, ADAR1, inosine and the immune sensing system: distinguishing self from non-self, Wiley. Interdiscip. Rev. RNA., 7 (2016), 157–172. https://doi.org/10.1002/wrna.1322 doi: 10.1002/wrna.1322
![]() |
[13] |
B. J. Liddicoat, R. Piskol, A. M. Chalk, G. Ramaswami, M. Higuchi, J. C. Hartner, et al., RNA editing by ADAR1 prevents MDA5 sensing of endogenous dsRNA as nonself, Science, 349 (2015), 1115–1120. https://doi.org/10.1126/science.aac7049 doi: 10.1126/science.aac7049
![]() |
[14] |
G. I. Rice, P. R. Kasher, G. M. Forte, N. M. Mannion, S. M. Greenwood, M. Szynkiewicz, et al., Mutations in ADAR1 cause Aicardi-Goutières syndrome associated with a type Ⅰ interferon signature, Nat. Genet., 44 (2012), 1243–1248. https://doi.org/10.1038/ng.2414 doi: 10.1038/ng.2414
![]() |
[15] |
Y. Miyamura, T. Suzuki, M. Kono, K. Inagaki, S. Ito, N. Suzuki, et al., Mutations of the RNA-specific adenosine deaminase gene (DSRAD) are involved in dyschromatosis symmetrica hereditaria, Am. J. Hum. Genet., 73 (2003), 693–699. https://doi.org/10.1086/378209 doi: 10.1086/378209
![]() |
[16] |
X. J. Zhang, P. P. He, M. Li, C. D. He, K. L. Yan, Y. Cui, et al., Seven novel mutations of the ADAR gene in Chinese families and sporadic patients with dyschromatosis symmetrica hereditaria (DSH), Hum. Mutat., 23 (2004), 629–630. https://doi.org/10.1002/humu.9246 doi: 10.1002/humu.9246
![]() |
[17] |
T. H. Chan, C. H. Lin, L. Qi, J. Fei, Y. Li, K. J. Yong, et al., A disrupted RNA editing balance mediated by ADARs (Adenosine De Aminases that act on RNA) in human hepatocellular carcinoma, Gut, 63 (2014), 832–843. https://doi.org/10.1136/gutjnl-2012-304037 doi: 10.1136/gutjnl-2012-304037
![]() |
[18] |
L. Han, L. Diao, S. Yu, X. Xu, J. Li, R. Zhang, et al., The genomic landscape and clinical relevance of A-to-I RNA editing in human cancers, Cancer Cell, 28 (2015), 515–528. https://doi.org/10.1016/j.ccell.2015.08.013 doi: 10.1016/j.ccell.2015.08.013
![]() |
[19] |
X. Peng, X. Xu, Y, Wang, D. H. Hawke, S. Yu, L. Han, et al., A-to-I RNA editing contributes to proteomic diversity in cancer, Cancer Cell, 35 (2018), 817–828. https://doi.org/10.1016/j.ccell.2018.03.026 doi: 10.1016/j.ccell.2018.03.026
![]() |
[20] |
H. Liu, J. Golji, L. K. Brodeur, F. S. Chung, J. T. Chen, R. S. deBeaumont, et al., Tumor-derived IFN triggers chronic pathway agonism and sensitivity to ADAR loss, Nat. Med., 25 (2019), 95–102. https://doi.org/10.1038/s41591-018-0302-5 doi: 10.1038/s41591-018-0302-5
![]() |
[21] |
J. J. Ishizuka, R. T. Manguso, C. K. Cheruiyot, K. Bi, A. Panda, A. V. Iracheta, et al., Loss of ADAR1 in tumours overcomes resistance to immune checkpoint blockade, Nature, 565 (2019), 43–48. https://doi.org/10.1038/s41586-018-0768-9 doi: 10.1038/s41586-018-0768-9
![]() |
[22] |
K. Fritzell, L. D. Xu, M. Otrocka, C. Andréasson, M. Öhman, Sensitive ADAR editing reporter in cancer cells enables high-throughput screening of small molecule libraries, Nucleic Acids Res., 47 (2019), 22. https://doi.org/10.1093/nar/gky1228 doi: 10.1093/nar/gky1228
![]() |
[23] |
J. Vivian, A. A. Rao, F. A. Nothaft, C. Ketchum, J. Armstrong, A. Novak, et al., Toil enables reproducible, open source, big biomedical data analyses, Nat. Biotechnol., 35 (2017), 314–316. https://doi.org/10.1038/nbt.3772 doi: 10.1038/nbt.3772
![]() |
[24] |
M. Uhlén, L. Fagerberg, B. M. Hallström, C. Lindskog, P. Oksvold, A. Mardinoglu, et al., Tissue-based map of the human proteome, Science, 347 (2015), 1260419. https://doi.org/10.1126/science.1260419 doi: 10.1126/science.1260419
![]() |
[25] |
S. Hänzelmann, R. Castelo, J. Guinney, GSVA: Gene set variation analysis for microarray and RNA-seq data, BMC. Bioinf., 14 (2013), 7. https://doi.org/10.1186/1471-2105-14-7 doi: 10.1186/1471-2105-14-7
![]() |
[26] |
Z. Tang, B. Kang, C. Li, T. Chen, Z. Zhang, GEPIA2: An enhanced web server for large-scale expression profiling and interactive analysis, Nucleic Acids Res., 47 (2019), w556–w560. https://doi.org/10.1093/nar/gkz430 doi: 10.1093/nar/gkz430
![]() |
[27] |
R. S. Herbst, J. V. Heymach, S. M. Lippman, Lung cancer, N. Engl. J. Med., 359 (2008), 1367–1380. https://doi.org/10.1056/NEJMra0802714 doi: 10.1056/NEJMra0802714
![]() |
[28] |
B. J. Booth, S. Nourreddine, D. Katrekar, Y. Savva, D. Bose, T. J. Long, et al., RNA editing: Expanding the potential of RNA therapeutics, Mol. Ther., 31 (2023), 533–549. https://doi.org/10.1016/j.ymthe.2023.01.005 doi: 10.1016/j.ymthe.2023.01.005
![]() |
[29] |
B. Song, Y. Shiromoto, M. Minakuchi, K. Nishikura, The role of RNA editing enzyme ADAR1 in human disease, Wiley. Interdiscip. Rev. RNA, 13 (2022), 1665. https://doi.org/10.1002/wrna.1665 doi: 10.1002/wrna.1665
![]() |
[30] |
J. Quin, J. Sedmík, D. Vukić, A. Khan, L. P. Keegan, M. A. O'Connell, ADAR RNA modifications, the epitranscriptome and innate immunity, Trends. Biochem. Sci., 46 (2021), 758–771. https://doi.org/10.1016/j.tibs.2021.02.002 doi: 10.1016/j.tibs.2021.02.002
![]() |
[31] |
G. Lev-Maor, R. Sorek, E. Y. Levanon, N. Paz, E. Eisenberg, G. Ast, RNA-editing-mediated exon evolution, Genome Biol., 8 (2007), 29. https://doi.org/10.1186/gb-2007-8-2-r29 doi: 10.1186/gb-2007-8-2-r29
![]() |
[32] |
L. Chen, Y. Li, C. H. Lin, T. H. Chan, R. K. Chow, Y. Song, et al., Recoding RNA editing of AZIN1 predisposes to hepatocellular carcinoma, Nat. Med., 19 (2013), 209–216. https://doi.org/10.1038/nm.3043 doi: 10.1038/nm.3043
![]() |
[33] |
S. Takeda, K. Shigeyasu, Y. Okugawa, K. Yoshida, Y. Mori, S. Yano, et al., Activation of AZIN1 RNA editing is a novel mechanism that promotes invasive potential of cancer-associated fibroblasts in colorectal cancer, Cancer Lett., 444 (2019), 127–135. https://doi.org/10.1016/j.canlet.2018.12.009 doi: 10.1016/j.canlet.2018.12.009
![]() |
[34] |
Y. Li, N. X. Wang, C. Yin, S. S. Jiang, J. C. Li, S. Y. Yang, RNA editing enzyme ADAR1 regulates METTL3 in an editing dependent manner to promote breast cancer progression via METTL3/ARHGAP5/YTHDF1 Axis, Int. J. Mol. Sci., 23 (2022), 9656. https://doi.org/10.3390/ijms23179656 doi: 10.3390/ijms23179656
![]() |
[35] |
B. A. Chua, D. W. Van, C. Jamieson, R. A. J. Signer, Post-Transcriptional regulation of homeostatic, stressed, and malignant stem cells, Cell. Stem. Cell., 26 (2020), 138–159. https://doi.org/10.1016/j.stem.2020.01.005 doi: 10.1016/j.stem.2020.01.005
![]() |
[36] |
D. A. Silvestris, C. Scopa, S. Hanchi, F. Locatelli, A. Gallo, De Novo A-to-I RNA editing discovery in lncRNA, Cancers (Basel), 12 (2020), 2959. https://doi.org/10.3390/cancers12102959 doi: 10.3390/cancers12102959
![]() |
[37] |
L. Nair, H. Chung, U. Basu, Regulation of long non-coding RNAs and genome dynamics by the RNA surveillance machinery, Nat. Rev. Mol. Cell. Biol., 21 (2020), 123–136. https://doi.org/10.1038/s41580-019-0209-0 doi: 10.1038/s41580-019-0209-0
![]() |
[38] |
H. Wang, S. Chen, J. Wei, G. Song, Y. Zhao, A-to-I RNA editing in cancer: From evaluating the editing level to exploring the editing effects, Front Oncol., 10 (2020), 632187. https://doi.org/10.3389/fonc.2020.632187 doi: 10.3389/fonc.2020.632187
![]() |
[39] |
J. M. Ramírez, A. R. Baker, F. J. Slack, P. Santisteban, ADAR1-mediated RNA editing is a novel oncogenic process in thyroid cancer and regulates miR-200 activity, Oncogene, 39 (2020), 3738–3753. https://doi.org/10.1038/s41388-020-1248-x doi: 10.1038/s41388-020-1248-x
![]() |
[40] |
P. R. de Santiago, A. Blanco, F. Morales, K. Marcelain, O. Harismendy, M. H. Sjöberg, et al., Immune-related IncRNA LINC00944 responds to variations in ADAR1 levels and it is associated with breast cancer prognosis, Life Sci., 268 (2021), 118956. https://doi.org/10.1016/j.lfs.2020.118956 doi: 10.1016/j.lfs.2020.118956
![]() |
[41] |
C. Ma, X. Wang, F. Yang, Y. Zang, J. Liu, X. Wang, et al., Circular RNA HSA_CIRC_0004872 inhibits gastric cancer progression via the miR-224/Smad4/ADAR1 successive regulatory circuit, Mol. Cancer, 19 (2020), 157. https://doi.org/10.1186/s12943-020-01268-5 doi: 10.1186/s12943-020-01268-5
![]() |
[42] |
T. Zhang, C. Yin, A. Fedorov, L. Qiao, H. Bao, N. Beknazarov, et al., ADAR1 masks the cancer immunotherapeutic promise of ZBP1-driven necroptosis, Nature, 606 (2022), 594–602. https://doi.org/10.1038/s41586-022-04753-7 doi: 10.1038/s41586-022-04753-7
![]() |
[43] |
M. C. Garassino, S. Gadgeel, E. Esteban, E. Felip, G. Speranza, M. Domine, et al., Patient-reported outcomes following pembrolizumab or placebo plus pemetrexed and platinum in patients with previously untreated, metastatic, non-squamous non-small-cell lung cancer (KEYNOTE-189): A multicentre, double-blind, randomised, placebo-controlled, phase 3 trial, Lancet Oncol., 21 (2020), 387–397. https:/doi.org/10.1016/s1470-2045(19)30801-0 doi: 10.1016/S1470-2045(19)30801-0
![]() |
[44] |
D. Fujimoto, S. Miura, K. Yoshimura, K. Wakuda, Y. Oya, T. Yokoyama, et al., Pembrolizumab plus chemotherapy-induced pneumonitis in chemo-naïve patients with non-squamous non-small cell lung cancer: A multicentre, retrospective cohort study, Eur. J. Cancer, 150 (2021), 63–72. https://doi.org/10.1016/j.ejca.2021.03.016 doi: 10.1016/j.ejca.2021.03.016
![]() |
[45] |
Z. Tang, T. Zhang, B. Yang, J. Su, Q. Song, spaCI: deciphering spatial cellular communications through adaptive graph model, Brief Bioinform., 24 (2023), bbac563. https://doi.org/10.1093/bib/bbac563 doi: 10.1093/bib/bbac563
![]() |
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