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The investigation of topological properties of ovarian cancer network (OCN) and the roles of hubs involved in it by digging the network at various levels of organization are important to understand how OCN is organized to understand disease states. The OCN constructed from the experimentally verified genes exhibits fractal nature in the topological properties of the network and deeply rooted communities. Also, the network properties at all levels of organization obey one parameter scaling law which lacks centrality lethality rule. We then showed that $\langle k\rangle$ can be taken as a scaling parameter, where, power law exponent can be estimated from the ratio of network diameters, $\lambda=1+\rho\left[\frac{d_c}{d_k}\right]$. The betweenness centrality shows two distinct behaviors one shown by high degree hubs and the other by segregated low degree nodes. The $C_B$ distribution follows power law behavior with the exponent connected to exponents of distributions of high and low degree nodes by, $\theta\sim\left[1+\frac{1}{2}\left(\frac{1}{\epsilon_s}+\frac{1}{\epsilon_h}\right)(\lambda-1)\right]$. Absence of rich-club formation leads to the missing of a number of attractors in the network causing formation of weakly tied diverse functional modules to keep optimal network efficiency. The hubs knockout experiment shows that provincial hubs take major responsibility to keep network integrity and organization. The identified key regulators are found to be provincial and connector hubs. Further, two key regulators, EPCAM and CD44 are found to be maximally over expressed at various cancer stages (II-IV). They are also positively correlated with immune infiltrates (CD4+ T cells). Finally, few potential drugs are identified related to the key regulators.