In this study we investigate computationally tumour-oncolytic virus (OV) interactions that take place within a heterogeneous extracellular matrix (ECM). The ECM is viewed as a mixture of two constitutive phases, namely a fibre phase and a non-fibre phase. The multiscale mathematical model presented here focuses on the nonlocal cell-cell and cell-ECM interactions, and how these interactions might be impacted by the infection of cancer cells with the OV. At macroscale we track the kinetics of cancer cells, virus particles and the ECM. At microscale we track (i) the degradation of ECM by matrix degrading enzymes (MDEs) produced by cancer cells, which further influences the movement of tumour boundary; (ii) the re-arrangement of the microfibres that influences the re-arrangement of macrofibres (i.e., fibres at macroscale). With the help of this new multiscale model, we investigate two questions: (i) whether the infected cancer cell fluxes are the result of local or non-local advection in response to ECM density; and (ii) what is the effect of ECM fibres on the the spatial spread of oncolytic viruses and the outcome of oncolytic virotherapy.
Citation: Abdulhamed Alsisi, Raluca Eftimie, Dumitru Trucu. Nonlocal multiscale modelling of tumour-oncolytic viruses interactions within a heterogeneous fibrous/non-fibrous extracellular matrix[J]. Mathematical Biosciences and Engineering, 2022, 19(6): 6157-6185. doi: 10.3934/mbe.2022288
[1] | Zhongzi Zhao, Meng Yan . Positive radial solutions for the problem with Minkowski-curvature operator on an exterior domain. AIMS Mathematics, 2023, 8(9): 20654-20664. doi: 10.3934/math.20231052 |
[2] | Wenjia Li, Guanglan Wang, Guoliang Li . The local boundary estimate of weak solutions to fractional p-Laplace equations. AIMS Mathematics, 2025, 10(4): 8002-8021. doi: 10.3934/math.2025367 |
[3] | Sobajima Motohiro, Wakasugi Yuta . Remarks on an elliptic problem arising in weighted energy estimates for wave equations with space-dependent damping term in an exterior domain. AIMS Mathematics, 2017, 2(1): 1-15. doi: 10.3934/Math.2017.1.1 |
[4] | Limin Guo, Jiafa Xu, Donal O'Regan . Positive radial solutions for a boundary value problem associated to a system of elliptic equations with semipositone nonlinearities. AIMS Mathematics, 2023, 8(1): 1072-1089. doi: 10.3934/math.2023053 |
[5] | Keqiang Li, Shangjiu Wang . Symmetry of positive solutions of a p-Laplace equation with convex nonlinearites. AIMS Mathematics, 2023, 8(6): 13425-13431. doi: 10.3934/math.2023680 |
[6] | Zhanbing Bai, Wen Lian, Yongfang Wei, Sujing Sun . Solvability for some fourth order two-point boundary value problems. AIMS Mathematics, 2020, 5(5): 4983-4994. doi: 10.3934/math.2020319 |
[7] | Lin Zhao . Monotonicity and symmetry of positive solution for 1-Laplace equation. AIMS Mathematics, 2021, 6(6): 6255-6277. doi: 10.3934/math.2021367 |
[8] | Manal Alfulaij, Mohamed Jleli, Bessem Samet . A hyperbolic polyharmonic system in an exterior domain. AIMS Mathematics, 2025, 10(2): 2634-2651. doi: 10.3934/math.2025123 |
[9] | Maria Alessandra Ragusa, Abdolrahman Razani, Farzaneh Safari . Existence of positive radial solutions for a problem involving the weighted Heisenberg p(⋅)-Laplacian operator. AIMS Mathematics, 2023, 8(1): 404-422. doi: 10.3934/math.2023019 |
[10] | Zhiqian He, Liangying Miao . Multiplicity of positive radial solutions for systems with mean curvature operator in Minkowski space. AIMS Mathematics, 2021, 6(6): 6171-6179. doi: 10.3934/math.2021362 |
In this study we investigate computationally tumour-oncolytic virus (OV) interactions that take place within a heterogeneous extracellular matrix (ECM). The ECM is viewed as a mixture of two constitutive phases, namely a fibre phase and a non-fibre phase. The multiscale mathematical model presented here focuses on the nonlocal cell-cell and cell-ECM interactions, and how these interactions might be impacted by the infection of cancer cells with the OV. At macroscale we track the kinetics of cancer cells, virus particles and the ECM. At microscale we track (i) the degradation of ECM by matrix degrading enzymes (MDEs) produced by cancer cells, which further influences the movement of tumour boundary; (ii) the re-arrangement of the microfibres that influences the re-arrangement of macrofibres (i.e., fibres at macroscale). With the help of this new multiscale model, we investigate two questions: (i) whether the infected cancer cell fluxes are the result of local or non-local advection in response to ECM density; and (ii) what is the effect of ECM fibres on the the spatial spread of oncolytic viruses and the outcome of oncolytic virotherapy.
Boundary value problems with p-Laplace operator Δpu=div(|∇u|p−2∇u) arise in many different areas of applied mathematics and physics, such as non-Newtonian fluids, reaction-diffusion problems, non-linear elasticity, etc. But little is known about the p-Laplace operator cases (p≠2) compared to the vast amount of knowledge for the Laplace operator (p=2). In this paper, we discuss the existence of positive radial solution for the p-Laplace boundary value problem (BVP)
{−Δpu=K(|x|)f(u),x∈Ω,∂u∂n=0,x∈∂Ω,lim|x|→∞u(x)=0, | (1.1) |
in the exterior domain Ω={x∈RN:|x|>r0}, where N≥2, r0>0, 1<p<N, ∂u∂n is the outward normal derivative of u on ∂Ω, K:[r0,∞)→R+ is a coefficient function, f:R+→R is a nonlinear function. Throughout this paper, we assume that the following conditions hold:
(A1) K∈C([r0,∞),R+) and 0<∫∞r0rN−1K(r)dr<∞;
(A2) f∈C(R+,R+);
For the special case of p=2, namely the Laplace boundary value problem
{−Δu=K(|x|)f(u),x∈Ω,∂u∂n=0,x∈∂Ω,lim|x|→∞u(x)=0, | (1.2) |
the existence of positive radial solutions has been discussed by many authors, see [1,2,3,4,5,6,7]. The authors of references[1,2,3,4,5,6] obtained some existence results by using upper and lower solutions method, priori estimates technique and fixed point index theory. In [7], the present author built an eigenvalue criteria of existing positive radial solutions. The eigenvalue criterion is related to the principle eigenvalue λ1 of the corresponding radially symmetric Laplace eigenvalue problem (EVP)
{−Δu=λK(|x|)u,x∈Ω,∂u∂n=0,x∈∂Ω,u=u(|x|),lim|x|→∞u(|x|)=0. | (1.3) |
Specifically, if f satisfies one of the following eigenvalue conditions:
(H1) f0<λ1, f∞>λ1;
(H2) f∞<λ1, f0>λ1,
the BVP(1.2) has a classical positive radial solution, where
f0=lim infu→0+f(u)u,f0=lim supu→0+f(u)u,f∞=lim infu→∞f(u)u,f∞=lim supu→∞f(u)u. |
See [7,Theorem 1.1]. This criterion first appeared in a boundary value problem of second-order ordinary differential equations, and built by Zhaoli Liu and Fuyi Li in [8]. Then it was extended to general boundary value problems of ordinary differential equations, See [9,10]. In [11,12], the radially symmetric solutions of the more general Hessian equations are discussed.
The purpose of this paper is to establish a similar existence result of positive radial solution of BVP (1.1). Our results are related to the principle eigenvalue λp,1 of the radially symmetric p-Laplce eigenvalue problem (EVP)
{−Δpu=λK(|x|)|u|p−2u,x∈Ω,∂u∂n=0,x∈∂Ω,u=u(|x|),lim|x|→∞u(|x|)=0. | (1.4) |
Different from EVP (1.3), EVP (1.4) is a nonlinear eigenvalue problem, and the spectral theory of linear operators is not applicable to it. In Section 2 we will prove that EVP (1.4) has a minimum positive real eigenvalue λp,1, see Lemma 2.3. For BVP (1.1), we conjecture that eigenvalue criteria is valid if f0, f0, f∞ and f∞ is replaced respectively by
fp0=lim infu→0+f(u)up−1,fp0=lim supu→0+f(u)up−1,fp∞=lim infu→∞f(u)up−1,fp∞=lim supu→∞f(u)up−1. | (1.5) |
But now we can only prove a weaker version of it: In second inequality of (H1) and (H2), λp,1 needs to be replaced by the larger number
B=[∫10Ψ(∫1stp−1a(t)dt)ds]−(p−1), | (1.6) |
where a∈C+(0,1] is given by (2.4) and Ψ∈C(R) is given by (2.7). Our result is as follows:
Theorem 1.1. Suppose that Assumptions (A1) and (A2) hold. If the nonlinear function f satisfies one of the the following conditions:
(H1)∗ fp0<λp,1, fp∞>B;
(H2)∗ fp∞<λp,1, fp0>B,
then BVP (1.1) has at least one classical positive radial solution.
As an example of the application of Theorem 1.1, we consider the following p-Laplace boundary value problem
{−Δpu=K(|x|)|u|γ,x∈Ω,∂u∂n=0,x∈∂Ω,lim|x|→∞u(x)=0. | (1.7) |
Corresponding to BVP (1.1), f(u)=|u|γ. If γ>p−1, by (1.5) fp0=0, fp∞=+∞, and (H1) holds. If 0<γ<p−1, then fp∞=0, fp0=+∞, and (H2) holds. Hence, by Theorem 1.1 we have
Corollary 1. Let K:[r0,∞)→R+ satisfy Assumption (A1), γ>0 and γ≠p−1. Then BVP (1.7) has a positive radial solution.
The proof of Theorem 1.1 is based on the fixed point index theory in cones, which will be given in Section 3. Some preliminaries to discuss BVP (1.1) are presented in Section 2.
For the radially symmetric solution u=u(|x|) of BVP (1.1), setting r=|x|, since
−Δpu=div(|∇u|p−2∇u)=−(|u′(r)|p−2u′(r))′−N−1r|u′(r)|p−2u′(r), |
BVP (1.1) becomes the ordinary differential equation BVP in [r0,∞)
{−(|u′(r)|p−2u′(r))′−N−1r|u′(r)|p−2u′(r)=K(r)f(u(r)),r∈[r0,∞),u′(r0)=0,u(∞)=0, | (2.1) |
where u(∞)=limr→∞u(r).
Let q>1 be the constant satisfying 1p+1q=1. To solve BVP (2.1), make the variable transformations
t=(r0r)(q−1)(N−p),r=r0t−1/(q−1)(N−p),v(t)=u(r(t)), | (2.2) |
Then BVP (2.1) is converted to the ordinary differential equation BVP in (0,1]
{−(|v′(t)|p−2v′(t))′=a(t)f(v(t)),t∈(0,1],v(0)=0,v′(1)=0, | (2.3) |
where
a(t)=rq(N−1)(t)(q−1)p(N−p)pr0q(N−p)K(r(t)),t∈(0,1]. | (2.4) |
BVP (2.3) is a quasilinear ordinary differential equation boundary value problem with singularity at t=0. A solution v of BVP (2.3) means that v∈C1[0,1] such that |v′|p−2v′∈C1(0,1] and it satisfies the Eq (2.3). Clearly, if v is a solution of BVP (2.3), then u(r)=v(t(r)) is a solution of BVP (2.1) and u(|x|) is a classical radial solution of BVP (1.1). We discuss BVP (2.3) to obtain positive radial solutions of BVP (1.1).
Let I=[0,1] and R+=[0,+∞). Let C(I) denote the Banach space of all continuous function v(t) on I with norm ‖v‖C=maxt∈I|v(t)|, C1(I) denote the Banach space of all continuous differentiable function on I. Let C+(I) be the cone of all nonnegative functions in C(I).
To discuss BVP (2.3), we first consider the corresponding simple boundary value problem
{−(|v′(t)|p−2v′(t))′=a(t)h(t),t∈(0,1],v(0)=0,v′(1)=0, | (2.5) |
where h∈C+(I) is a given function. Let
Φ(v)=|v|p−2v=|v|p−1sgnv,v∈R, | (2.6) |
then w=Φ(v) is a strictly monotone increasing continuous function on R and its inverse function
Φ−1(w):=Ψ(w)=|w|q−1sgnw,w∈R, | (2.7) |
is also a strictly monotone increasing continuous function.
Lemma 2.1. For every h∈C(I), BVP (2.5) has a unique solution v:=Sh∈C1(I). Moreover, the solution operator S:C(I)→C(I) is completely continuous and has the homogeneity
S(νh)=νq−1Sh,h∈C(I),ν≥0. | (2.8) |
Proof. By (2.4) and Assumption (A1), the coefficient a(t)∈C+(0,1] and satisfies
∫10a(t)dt=1[(q−1)(N−p)]p−1r0N−p∫∞r0rN−1K(r)dr<∞. | (2.9) |
Hence a∈L(I).
For every h∈C(I), we verify that
v(t)=∫t0Ψ(∫1sa(τ)h(τ)dτ)ds:=Sh(t),t∈I | (2.10) |
is a unique solution of BVP (2.5). Since the function G(s):=∫1sa(τ)h(τ)dτ∈C(I), from (2.10) it follows that v∈C1(I) and
v′(t)=Ψ(∫1ta(τ)h(τ)dτ),t∈I. | (2.11) |
Hence,
|v′(t)|p−2v′(t)=Φ(v′(t))=∫1ta(τ)h(τ)dτ,t∈I. |
This means that (|v′(t)|p−2v′(t)∈C1(0,1] and
(|v′(t)|p−2v′(t))′=−a(t)h(t),t∈(0,1], |
that is, v is a solution of BVP (2.5).
Conversely, if v is a solution of BVP (2.5), by the definition of the solution of BVP (2.5), it is easy to show that v can be expressed by (2.10). Hence, BVP (2.5) has a unique solution v=Sh.
By (2.10) and the continuity of Ψ, the solution operator S:C(I)→C(I) is continuous. Let D⊂C(I) be bounded. By (2.10) and (2.11) we can show that S(D) and its derivative set {v′|v∈S(D)} are bounded sets in C(I). By the Ascoli-Arzéla theorem, S(D) is a precompact subset of C(I). Thus, S:C(I)→C(I) is completely continuous.
By the uniqueness of solution of BVP (2.5), we easily verify that the solution operator S satisfies (2.8).
Lemma 2.2. If h∈C+(I), then the solution v=Sh of LBVP (2.5) satisfies: ‖v‖c=v(1), v(t)≥t‖v‖C for every t∈I.
Proof. Let h∈C+(I) and v=Sh. By (2.10) and (2.11), for every t∈I v(t)≥0 and v′(t)≥0. Hence, v(t) is a nonnegative monotone increasing function and ‖v‖C=maxt∈Iv(t)=v(1). From (2.11) and the monotonicity of Ψ, we notice that v′(t) is a monotone decreasing function on I. For every t∈(0,1), by Lagrange's mean value theorem, there exist ξ1∈(0,t) and ξ2∈(t,1), such that
(1−t)v(t)=(1−t)(v(t)−v(0))=v′(ξ1)t(1−t)≥v′(t)t(1−t),tv(t)=tv(1)−t(v(1)−v(t))=tv(1)−tv′(ξ2)(1−t)≥tv(1)−v′(t)t(1−t). |
Hence
v(t)=tv(t)+(1−t)v(t)≥tv(1)=t‖v‖C. |
Obviously, when t=0 or 1, this inequality also holds. The proof is completed.
Consider the radially symmetric p-Laplace eigenvalue problem EVP (1.3). We have
Lemma 2.3. EVP (1.4) has a minimum positive real eigenvalue λp,1, and λp,1 has a radially symmetric positive eigenfunction.
Proof. For the radially symmetric eigenvalue problem EVP (1.4), writing r=|x| and making the variable transformations of (2.2), it is converted to the one-dimensional weighted p-Laplace eigenvalue problem (EVP)
{−(|v′(t)|p−2v′(t))′=λa(t)|v(t)|p−2v(t),t∈(0,1],v(0)=0,v′(1)=0, | (2.12) |
where v(t)=u(r(t)). Clearly, λ∈R is an eigenvalue of EVP (1.4) if and only if it is an eigenvalue of EVP (2.12). By (2.4) and (2.9), a∈C+(0,1]∩L(I) and ∫10a(s)ds>0. This guarantees that EVP (2.12) has a minimum positive real eigenvalue λp,1, which given by
λp,1=inf{∫10|w′(t)|pdt∫10a(t)wp(t)dt|w∈C1(I),w(0)=0,w′(1)=0,∫10a(t)wp(t)dt≠0}. | (2.13) |
Moreover, λp,1 is simple and has a positive eigenfunction ϕ∈C+(I)∩C1(I). See [13, Theorem 5], [14, Theorem 1.1] or [15, Theorem 1.2]. Hence, λp,1 is also the minimum positive real eigenvalue of EVP (1.4), and ϕ((r0/|x|)(q−1)(N−p)) is corresponding positive eigenfunction.
Now we consider BVP (2.3). Define a closed convex cone K of C(I) by
K={v∈C(I)|v(t)≥t‖v‖C,t∈I}. | (2.14) |
By Lemma 2.2, S(C+(I))⊂K. Let f∈C(R+,R+), and define a mapping F:K→C+(I) by
F(v)(t):=f(v(t)),t∈I. | (2.15) |
Then F:K→C+(I) is continuous and it maps every bounded subset of K into a bounded subset of C+(I). Define the composite mapping by
A=S∘F. | (2.16) |
Then A:K→K is completely continuous by the complete continuity of the operator S:C+(I)→K. By the definitions of S and K, the positive solution of BVP (2.3) is equivalent to the nonzero fixed point of A.
Let E be a Banach space and K⊂E be a closed convex cone in E. Assume D is a bounded open subset of E with boundary ∂D, and K∩D≠∅. Let A:K∩¯D→K be a completely continuous mapping. If Av≠v for every v∈K∩∂D, then the fixed point index i(A,K∩D,K) is well defined. One important fact is that if i(A,K∩D,K)≠0, then A has a fixed point in K∩D. In next section, we will use the following two lemmas in [16,17] to find the nonzero fixed point of the mapping A defined by (2.16).
Lemma 2.4. Let D be a bounded open subset of E with 0∈D, and A:K∩¯D→K a completely continuous mapping. If μAv≠v for every v∈K∩∂D and 0<μ≤1, then i(A,K∩D,K)=1.
Lemma 2.5. Let D be a bounded open subset of E with 0∈D, and A:K∩¯D→K a completely continuous mapping. If ‖Av‖≥‖v‖ and Av≠v for every v∈K∩∂D, then i(A,K∩D,K)=0.
Proof of Theorem 1.1. We only consider the case that (H1)* holds, and the case that (H2)* holds can be proved by a similar way.
Let K⊂C(I) be the closed convex cone defined by (2.14) and A:K→K be the completely continuous mapping defined by (2.16). If v∈K is a nontrivial fixed point of A, then by the definitions of S and A, v(t) is a positive solution of BVP (2.3) and u=v(r0N−2/|x|N−2) is a classical positive radial solution of BVP (1.1). Let 0<R1<R2<+∞ and set
D1={v∈C(I):‖v‖C<R1},D2={v∈C(I):‖v‖C<R2}. | (3.1) |
We prove that A has a fixed point in K∩(¯D2∖D1) when R1 is small enough and R2 large enough.
Since fp0<λp,1, by the definition of fp0, there exist ε∈(0,λp,1) and δ>0, such that
f(u)≤(λp,1−ε)up−1,0≤u≤δ. | (3.2) |
Choosing R1∈(0,δ), we prove that A satisfies the condition of Lemma 2.4 in K∩∂D1, namely
μAv≠v,∀v∈K∩∂D1,0<μ≤1. | (3.3) |
In fact, if (3.3) does not hold, there exist v0∈K∩∂D1 and 0<μ0≤1 such that μ0Av0=v0. By the homogeneity of S, v0=μ0S(F(v0))=S(μ0p−1F(v0)). By the definition of S, v0 is the unique solution of BVP (2.5) for h=μ0p−1F(v0)∈C+(I). Hence, v0∈C1(I) satisfies the differential equation
{−(|v′0(t)|p−2v0′(t))′=μ0p−1a(t)f(v0(t)),t∈(0,1],v0(0)=0,v0′(1)=0. | (3.4) |
Since v0∈K∩∂D1, by the definitions of K and D1,
0≤v0(t)≤‖v0‖C=R1<δ,t∈I. |
Hence by (3.2),
f(v0(t))≤(λp,1−ε)v0p−1(t),t∈I. |
By this inequality and Eq (3.4), we have
−(|v′0(t)|p−2v0′(t))′≤μ0p−1(λp,1−ε)a(t)v0p−1(t),t∈(0,1]. |
Multiplying this inequality by v0(t) and integrating on (0,1], then using integration by parts for the left side, we have
∫10|v′0(t)|pdt≤μ0p−1(λp,1−ε)∫10a(t)v0p(t)dt≤(λp,1−ε)∫10a(t)v0p(t)dt. | (3.5) |
Since v0∈K∩∂D, by the definition of K,
∫10a(t)v0p(t)dt≥‖v0‖Cp∫10tpa(t)dt=R1p∫10tpa(t)dt>0. |
Hence, by (2.13) and (3.5) we obtain that
λp,1≤∫10|v′0(t)|pdt∫10a(t)v0p(t)dt≤λp,1−ε, |
which is a contradiction. This means that (3.3) holds, namely A satisfies the condition of Lemma 2.4 in K∩∂D1. By Lemma 2.4, we have
i(A,K∩D1,K)=1. | (3.6) |
On the other hand, by the definition (1.6) of B, we have
B<[∫1σΨ(∫1stp−1a(t)dt)ds]−(p−1)→B(σ→0+),σ∈(0,1). | (3.7) |
Since fp∞>B, by (3.7) there exists σ0∈(0,1), such that
B0:=[∫1σ0Ψ(∫1stp−1a(t)dt)ds]−(p−1)<fp∞. | (3.8) |
By this inequality and the definition of fp∞, there exists H>0 such that
f(u)>B0up−1,u>H. | (3.9) |
Choosing R2>max{δ,H/σ0}, we show that
‖Av‖C≥‖v‖C,v∈K∩∂D2. | (3.10) |
For ∀v∈K∩∂D2 and t∈[σ0,1], by the definitions of K and D2
v(t)≥t‖v‖C≥σ0R2>H. |
By this inequality and (3.9),
f(v(t))>B0vp−1(t)≥B0‖v‖p−1Ctp−1,t∈[σ0,1]. | (3.11) |
Since Av=S(F(v)), by the expression (2.10) of the solution operator S and (3.11), noticing (p−1)(q−1)=1, we have
‖Av‖C≥Av(1)=∫10Ψ(∫1sa(t)f(v(t))dt)ds≥∫1σ0Ψ(∫1sa(t)f(v(t))dt)ds≥∫1σ0Ψ(∫1sa(t)B0‖v‖p−1Ctp−1dt)ds=Bq−10‖v‖C∫1σ0Ψ(∫1stp−1a(t)dt)ds=‖v‖C. |
Namely, (3.10) holds. Suppose A has no fixed point on ∂D2. Then by (3.10), A satisfies the condition of Lemma 2.5 in K∩∂D2. By Lemma 2.5, we have
i(A,K∩D2,K)=0. | (3.12) |
By the additivity of fixed point index, (3.6) and (3.11), we have
i(A,K∩(D2∖¯D1),K)=i(A,K∩D2,K)−i(A,K∩D1,K)=−1. |
Hence A has a fixed point in K∩(D2∖¯D1).
The proof of Theorem 1.1 is complete.
The authors would like to express sincere thanks to the reviewers for their helpful comments and suggestions. This research was supported by National Natural Science Foundations of China (No.12061062, 11661071).
The authors declare that they have no competing interests.
[1] |
T. Rozario, D. W. DeSimone, The extracellular matrix in development and morphogenesis: a dynamic view, Dev. Biol., 341 (2010), 126–140. https://doi.org/10.1016/j.ydbio.2009.10.026 doi: 10.1016/j.ydbio.2009.10.026
![]() |
[2] |
B. Yue, Biology of the extracellular matrix: an overview, J. Galucoma, 23 (2015), S20–S23. https://doi.org/10.1097/IJG.0000000000000108 doi: 10.1097/IJG.0000000000000108
![]() |
[3] |
V. Gkretsi, T. Stylianopoulos, Cell adhesion and matrix stiffness: coordinating cancer cell invasion and metastasis, Front. Oncol., 8 (2018), 145. https://doi.org/10.3389/fonc.2018.00145 doi: 10.3389/fonc.2018.00145
![]() |
[4] | C. Fountzilas, S. Patel, D. Mahalingam, Review: oncolytic virotherapy, updates and future directions, Oncotarget, 8 (2017), 102617–102639. |
[5] |
H. L. Kaufman, F. J. Kohlhapp, A. Zloza, Oncolytic viruses: a new class of immunotherapy drugs, Nat. Rev. Drug Discov., 14 (2015), 642–662. https://doi.org/10.1038/nrd4663 doi: 10.1038/nrd4663
![]() |
[6] |
J. Pol, G. Kroemer, L. Galluzzi, First oncolytic virus approved for melanoma immunotherapy, Oncoimmunology, 5 (2016), e1115641. https://doi.org/10.1080/2162402X.2015.1115641 doi: 10.1080/2162402X.2015.1115641
![]() |
[7] |
S. J. Russell, K. W. Peng, J. C. Bell, Oncolytic virotherapy, Nat. Biotechnol., 30 (2012), 658–670. https://doi.org/10.1038/nbt.2287 doi: 10.1038/nbt.2287
![]() |
[8] |
J. Wojton, B. Kaur, Impact of tumor microenvironment on oncolytic viral therapy, Cytokine Growth Factor Rev., 21 (2010), 127–134. https://doi.org/10.1016/j.cytogfr.2010.02.014 doi: 10.1016/j.cytogfr.2010.02.014
![]() |
[9] |
N. J. Armstrong, K. J. Painter, J. A. Sherratt, A continuum approach to modelling cell-cell adhesion, J. Theor. Biol., 243 (2006), 98–113. https://doi.org/10.1016/j.jtbi.2006.05.030 doi: 10.1016/j.jtbi.2006.05.030
![]() |
[10] |
A. Gerisch, M. A. Chaplain, Mathematical modelling of cancer cell invasion of tissue: local and non-local models and the effect of adhesion, J. Theor. Biol., 250 (2008), 684–704. https://doi.org/10.1016/j.jtbi.2007.10.026 doi: 10.1016/j.jtbi.2007.10.026
![]() |
[11] |
P. Domschke, D. Trucu, A. Gerisch, M. A. J. Chaplain, Mathematical modelling of cancer invasion: implications of cell adhesion variability for tumour infiltrative growth patterns, J. Theor. Biol., 361 (2014), 41–60. https://doi.org/10.1016/j.jtbi.2014.07.010 doi: 10.1016/j.jtbi.2014.07.010
![]() |
[12] |
J. J. Crivelli, J. Földes, P. S. Kim, J. R. Wares, A mathematical model for cell cycle-specific cancer virotherapy, J. Biol. Dyn., 6 (2012), 104–120. https://doi.org/10.1080/17513758.2011.613486 doi: 10.1080/17513758.2011.613486
![]() |
[13] |
R. Eftimie, J. Dushoff, B. W. Bridle, J. L. Bramson, D. J. Earn, Multi-stability and multi-instability phenomena in a mathematical model of tumor-immune-virus interactions, Bull. Math. Biol., 73 (2011), 2932–2961. https://doi.org/10.1007/s11538-011-9653-5 doi: 10.1007/s11538-011-9653-5
![]() |
[14] |
R. Eftimie, C. K. MacNamara, J. Dushoff, J. L. Bramson, D. J. Earn, Bifurcations and chaotic dynamics in a tumour-immune-virus system, Math. Model. Nat. Phenom., 11 (2016), 65–85. https://doi.org/10.1051/mmnp/201611505 doi: 10.1051/mmnp/201611505
![]() |
[15] |
J. L. Gevertz, J. R. Wares, Developing a minimally structured mathematical model of cancer treatment with oncolytic viruses and dendritic cell injections, Comput. Math. Methods Med., 2018 (2018), 1–14. https://doi.org/10.1155/2018/8760371 doi: 10.1155/2018/8760371
![]() |
[16] | J. P. W. Heidbuechel, D. Abate-Daga, C. E. Engeland, H. Enderling, Mathematical modeling of oncolytic virotherapy, in Oncolytic Viruses, Humana, New York, (2020), 307–320. https://doi.org/10.1007/978-1-4939-9794-7_21 |
[17] | M. A. Nowak, R. M. May, Virus Dynamics: Mathematical Principles of Immunology and Virology, Oxford University Press, Oxford, 2000. |
[18] |
D. Wodarz, Computational modeling approaches to the dynamics of oncolytic viruses, Wiley Interdiscip. Rev. Syst. Biol. Med., 8 (2016), 242–252. https://doi.org/10.1002/wsbm.1332 doi: 10.1002/wsbm.1332
![]() |
[19] |
D. R. Berg, C. P. Offord, I. Kemler, M. K. Ennis, L. Chang, G. Paulik, et al., In vitro and in silico multidimensional modeling of oncolytic tumor virotherapy dynamics, PLOS Comput. Biol., 15 (2019), e1006773. https://doi.org/10.1371/journal.pcbi.1006773 doi: 10.1371/journal.pcbi.1006773
![]() |
[20] |
K. Jacobsen, S. S. Pilyugin, Analysis of a mathematical model for tumor therapy with a fusogenic oncolytic virus, Math. Biosci., 270 (2015), 169–182. https://doi.org/10.1016/j.mbs.2015.02.009 doi: 10.1016/j.mbs.2015.02.009
![]() |
[21] |
J. Malinzi, P. Sibanda, H. Mambili-Mamboundou, Analysis of virotherapy in solid tumor invasion, Math. Biosci., 263 (2015), 102–110. https://doi.org/10.1016/j.mbs.2015.01.015 doi: 10.1016/j.mbs.2015.01.015
![]() |
[22] |
Y. Tao, M. Winkler, Global classical solutions to a doubly haptotactic cross-diffusion system modeling oncolytic virotherapy, J. Differ. Equation, 268 (2020), 4973–4997. https://doi.org/10.1016/j.jde.2019.10.046 doi: 10.1016/j.jde.2019.10.046
![]() |
[23] |
D. Wodarz, A. Hofacre, J. W. Lau, Z. Sun, H. Fan, N. L. Komarova, Complex spatial dynamics of oncolytic viruses in vitro: mathematical and experimental approaches, PLoS Comput. Biol., 8 (2012), e1002547. https://doi.org/10.1371/journal.pcbi.1002547 doi: 10.1371/journal.pcbi.1002547
![]() |
[24] |
A. Alsisi, R. Eftimie, D. Trucu, Non-local multiscale approaches for tumour-oncolytic viruses interactions, Math. Appl. Sci. Eng., 1 (2020), 249–273. https://doi.org/10.5206/mase/10773 doi: 10.5206/mase/10773
![]() |
[25] |
A. Alsisi, R. Eftimie, D. Trucu, Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions, Math. Biosci. Eng., 18 (2021), 5252–5284. https://doi.org/10.3934/mbe.2021267 doi: 10.3934/mbe.2021267
![]() |
[26] |
T. Alzahrani, R. Eftimie, D. Trucu, Multiscale modelling of cancer response to oncolytic viral therapy, Math. Biosci., 310 (2019), 76–95. https://doi.org/10.1016/j.mbs.2018.12.018 doi: 10.1016/j.mbs.2018.12.018
![]() |
[27] |
T. Alzahrani, R. Eftimie, D. Trucu, Multiscale moving boundary modelling of cancer interactions with a fusogenic oncolytic virus: the impact of syncytia dynamics, Math. Biosci., 323 (2020), 108296. https://doi.org/10.1016/j.mbs.2019.108296 doi: 10.1016/j.mbs.2019.108296
![]() |
[28] |
L. R. Paiva, C. Binny, S. C. Ferreira, M. L. Martins, A Multiscale mathematical model for oncolytic virotherapy, Cancer Res., 69 (2009), 1205–1211. https://doi.org/10.1158/0008-5472.CAN-08-2173 doi: 10.1158/0008-5472.CAN-08-2173
![]() |
[29] |
L. R. Paiva, H. S. Silva, S. C. Ferreira, M. L. Martins, Multiscale model for the effects of adaptive immunity suppression on the viral therapy of cancer, Phys. Biol., 10 (2013), 025005. https://doi.org/10.1088/1478-3975/10/2/025005 doi: 10.1088/1478-3975/10/2/025005
![]() |
[30] |
D. Trucu, P. Lin, M. A. J. Chaplain, Y. Wang, A multiscale moving boundary model arising in cancer invasion, Multiscale Model. Simul., 11 (2013), 309–335. https://doi.org/10.1137/110839011 doi: 10.1137/110839011
![]() |
[31] |
R. Shuttleworth, D. Trucu, Multiscale modelling of fibres dynamics and cell adhesion within moving boundary cancer invasion, Bull. Math. Biol., 81 (2019), 2176–2219. https://doi.org/10.1007/s11538-019-00598-w doi: 10.1007/s11538-019-00598-w
![]() |
[32] |
N. Bhagavathula, A. W. Hanosh, K. C. Nerusu, H. Appelman, S. Chakrabarty, J. Varani, Regulation of E-cadherin and β-catenin by Ca2+ in colon carcinoma is dependent on calcium-sensing receptor expression and function, Int. J. Cancer, 121 (2007), 1455–1462. https://doi.org/10.1002/ijc.22858 doi: 10.1002/ijc.22858
![]() |
[33] |
U. Cavallaro, G. Christofori, Cell adhesion in tumor invasion and metastasis: loss of the glue is not enough, Biochim. Biophys. Acta Rev. Cancer, 1552 (2001), 39–45. https://doi.org/10.1016/S0304-419X(01)00038-5 doi: 10.1016/S0304-419X(01)00038-5
![]() |
[34] |
J. D. Humphries, A. Byron, M. J. Humphries, Integrin ligands at a glance, J. Cell Sci., 119 (2006), 3901–3903. https://doi.org/10.1242/jcs.03098 doi: 10.1242/jcs.03098
![]() |
[35] |
K. S. Ko, P. D. Arora, V. Bhide, A. Chen, C. A. McCulloch, Cell-cell adhesion in human fibroblasts requires calcium signaling, J. Cell Sci., 114 (2001), 1155–1167. https://doi.org/10.1242/jcs.114.6.1155 doi: 10.1242/jcs.114.6.1155
![]() |
[36] |
B. P. L. Wijnhoven, W. N. M. Dinjens, M. Pignatelli, E-cadherin-catenin cell-cell adhesion complex and human cancer, Br. J. Surg., 87 (2000), 992–1005. https://doi.org/10.1046/j.1365-2168.2000.01513.x doi: 10.1046/j.1365-2168.2000.01513.x
![]() |
[37] |
M. Chaplain, G. Lolas, Mathematical modelling of cancer invasion of tissue: dynamic heterogeneity, Networks Heterog. Media, 1 (2006), 399–439. https://doi.org/10.3934/nhm.2006.1.399 doi: 10.3934/nhm.2006.1.399
![]() |
[38] |
Z. Gu, F. Liu, E. A. Tonkova, S. Y. Lee, D. J. Tschumperlin, M. B. Brenner, Soft matrix is a natural stimulator for cellular invasiveness, Mol. Biol. Cell, 25 (2014), 457–469. https://doi.org/10.1091/mbc.e13-05-0260 doi: 10.1091/mbc.e13-05-0260
![]() |
[39] |
A. M. Hofer, S. Curci, M. A. Doble, E. M. Brown, D. I. Soybel, Intercellular communication mediated by the extracellular calcium-sensing receptor, Nat. Cell Biol., 2 (2000), 392–398. https://doi.org/10.1038/35017020 doi: 10.1038/35017020
![]() |
[40] |
D. Hanahan, R. A. Weinberg, Hallmarks of cancer: the next generation, Cell, 144 (2011), 646–674. https://doi.org/10.1016/j.cell.2011.02.013 doi: 10.1016/j.cell.2011.02.013
![]() |
[41] | R. A. Weinberg, The Biology of Cancer, Garland Science, New York, 2006. |
[42] | D. Trucu, P. Domschke, A. Gerisch. M. Chaplain, Multiscale computational modelling and analysis of cancer invasion, in Mathematical Models and Methods for Living Systems (eds. L. Preziosi, M. A. J. Chaplain and A. Pugliese), Springer, Cham, (2016), 275–321. https://doi.org/10.1007/978-3-319-42679-2_5 |
[43] |
F. Sabeh, R. Shimizu-Hirota, S. J. Weiss, Protease-dependent versus -independent cancer cell invasion programs: three-dimensional amoeboid movement revisited, J. Cell Biol., 185 (2009), 11–19. https://doi.org/10.1083/jcb.200807195 doi: 10.1083/jcb.200807195
![]() |
[44] |
K. Wolf, S. Alexander, V. Schacht, L. M. Coussens, U. H. von Andrian, J. van Rheenen, et al., Collagen-based cell migration models in vitro and in vivo, Semin. Cell Dev. Biol., 20 (2009), 931–941. https://doi.org/10.1016/j.semcdb.2009.08.005 doi: 10.1016/j.semcdb.2009.08.005
![]() |
[45] |
K. Wolf, Y. I. Wu, Y. Liu, J. Geiger, E. Tam, C. Overall, et al., Multi-step pericellular proteolysis controls the transition from individual to collective cancer cell invasion, Nat. Cell Biol., 9 (2007), 893–904. https://doi.org/10.1038/ncb1616 doi: 10.1038/ncb1616
![]() |
[46] |
B. I. Camara, H. Mokrani, E. Afenya, Mathematical modeling of glioma therapy using oncolytic viruses, Math. Biosci. Eng., 10 (2013), 565–578. https://doi.org/10.3934/mbe.2013.10.565 doi: 10.3934/mbe.2013.10.565
![]() |
[47] |
K. J. Painter, N. J. Armstrong, J. A. Sherratt, The impact of adhesion on cellular invasion processes in cancer and development, J. Theor. Biol., 264 (2010), 1057–1067. https://doi.org/10.1016/j.jtbi.2010.03.033 doi: 10.1016/j.jtbi.2010.03.033
![]() |
[48] |
R. Shuttleworth, D. Trucu, Multiscale dynamics of a heterotypic cancer cell population within a fibrous extracellular matrix, J. Theor. Biol., 486 (2020), 110040. https://doi.org/10.1016/j.jtbi.2019.110040 doi: 10.1016/j.jtbi.2019.110040
![]() |
[49] |
L. Peng, D. Trucu, P. Lin, A. Thompson, M. A. Chaplain, A multiscale mathematical model of tumour invasive growth, Bull. Math. Biol., 79 (2017), 389–429. https://doi.org/10.1007/s11538-016-0237-2 doi: 10.1007/s11538-016-0237-2
![]() |
1. | Bo Yang, Radially Symmetric Positive Solutions of the Dirichlet Problem for the p-Laplace Equation, 2024, 12, 2227-7390, 2351, 10.3390/math12152351 | |
2. | Yongxiang Li, Pengbo Li, Radial solutions of p-Laplace equations with nonlinear gradient terms on exterior domains, 2023, 2023, 1029-242X, 10.1186/s13660-023-03069-y | |
3. | 旭莹 唐, The Existence of Positive Solutions to Quasilinear Differential Equation on Infinite Intervals, 2023, 13, 2160-7583, 2103, 10.12677/PM.2023.137217 |