Let $(\Omega,\mathcal{A},P)$ be a probability space and $X=(X_1,X_2,\cdots,X_n)$ a random vector on $(\Omega,\mathcal{A},P)$ such that $ X_k:(\Omega,\mathcal{A})\to({\Bbb R},{\mathcal B}_{\Bbb R}), k=1,2,\cdots, n $ are random variables, but not necessarily independent. What I need to show is that $ \phi_X(u)=\phi_{X_1}(u_1) $ where $u=(u_1,0,0,\cdots,0)\in{\Bbb R}^n$, and $\phi_X$ is the characteristic function of $X$: $ \phi_X(u)=\int_{\Bbb R^n}e^{it\langle u,x\rangle}dP^{X} $ where $P^X$ is the probability distribution measure of $X$. By simple calculation, $ \phi_X(u)=\int_{\Bbb R^n}e^{iu_1x_1}dP^X. $
My question is: How can I relate this integral with $ \phi_{X_1}(u_1)=\int_{\Bbb R}e^{iu_1x_1}dP^{X_1} ? $
Formally, what I tried is that (in the case $n=2$) $ \begin{align} \phi_{X_1}(u_1)&=\int_{\Bbb R}e^{iu_1x_1}dP^{X_1}\\ &=\int_{\Bbb R}e^{iu_1x_1}dP^{X_1}\int_{\Bbb R}dP^{X_2}\\ &=\int_{\Bbb R}\left(\int_{\Bbb R}e^{iu_1x_1}dP^{X_1}\right)dP^{X_2}\\ &=\int_{\Bbb R^2}e^{iu_1x_1}P^{X_1}\otimes P^{X_2} \end{align} $ But $X_1,X_2$ are not necessarily independent and I'm not able to get $ P^{(X_1,X_2)}=P^{X_1}\otimes P^{X_2}. $