Literature mining analysis associated it with the key hallmark events like apoptosis and cell-proliferation. CD70 was detected to be topologically AZD7687 evolved gene by dependency network analysis, which has a significant number of connections in cancer condition, but does not have any connection in control condition. CD70 is a clinical trial target for various cancers. LYN was identified in dependency network analysis as a topologically evolved gene, which has a significant number of connections in cancer condition, but does not have any connection in control condition. Literature mining analysis has associated it with apoptosis and cell-proliferation. It is also well connected in causal network, and was identified as one of the significant hypotheses. LYN has been reported in various studies to be an attractive therapeutic target for various cancers, including oral cancer. SKIL has been identified in our analysis as highly connected gene in the dependency network with marked topological difference under cancer and control condition. Literature mining analysis associated it with apoptosis, cell proliferation and metastasis. SKIL was reported to be a novel therapeutic target for ovarian cancer. The analytical approach presented in the current study shows the power of direct integration of dataset generated by different studies to derive statistically significant results. The novel literature mining approach presented in the current study can be used for Benzethonium Chloride functional annotation of a gene-list produced by high-throughput studies related with cancer. The literature mining based functional classification comprehensively reviews published data, and has an advantage over traditional functional classification methods based on pathways or gene-sets, which does not represent the current state of art information since they are generally not updated quite often. The current study has identified potential target genes for oral cancer. Some of the most potential therapeutic targets identified by our integrated analysis are adrenomedullin, TP53, CTGF, EGFR, CTLA4, LYN, SKI-like oncogene and CD70. The data presented here can also be used for identifying targets, which are specific to a particular cancer hallmark. The data presented could facilitate development of effective targeted therapies for oral cancer.