In this paper, random-site percolation thresholds for a simple cubic (SC) lattice with site neighborhoods containing next-next-next-nearest neighbors (4NN) are evaluated with Monte Carlo simulations. A recently proposed algorithm with low sampling for percolation thresholds estimation (Bastas et al., arXiv:1411.5834) is implemented for the studies of the top-bottom wrapping probability. The obtained percolation thresholds are p(C)(4NN)=0.31160(12),p(C)(4NN+NN)=0.15040(12),p(C)(4NN+2NN)=0.15950(12),p(C)(4NN+3NN)=0.20490(12),p(C)(4NN+2NN+NN)=0.11440(12),p(C)(4NN+3NN+NN)=0.11920(12),p(C)(4NN+3NN+2NN)=0.11330(12), and p(C)(4NN+3NN+2NN+NN)=0.10000(12), where 3NN, 2NN, and NN stand for next-next-nearest neighbors, next-nearest neighbors, and nearest neighbors, respectively. As an SC lattice with 4NN neighbors may be mapped onto two independent interpenetrated SC lattices but with a lattice constant that is twice as large, the percolation threshold p(C)(4NN) is exactly equal to p(C)(NN). The simplified method of Bastas et al. allows for uncertainty of the percolation threshold value p(C) to be reached, similar to that obtained with the classical method but ten times faster.