Mounting evidence links cancers possessing stem-like properties with worse prognosis. Network biology with signal processing mechanics was explored here using expression profiles of a panel of tumor stem-like cells (TSLCs). The profiles were compared to their parental tumor cells (PTCs) and the human embryonic stem cells (hESCs), for the identification of gene chromobox homolog 5, CBX5, as a potential target for lung cancer. CBX5 was found to regulate the stem-like properties of lung TSLCs and was predictive of lung cancer prognosis. The investigation was facilitated by finding target genes based on modeling epistatic signaling mechanics via a predictive and scalable network-based survival model. Topologically-weighted measurements of CBX5 were synchronized with those of BIRC5, DNMT1, E2F1, ESR1, MLH1, MSH2, RB1, SMAD1 and TAF5. We validated our findings in another Taiwanese lung cancer cohort, as well as in knockdown experiments using sh-CBX5 RNAi both in vitro and in vivo.