In　order　to　identify　the　signature　genes　of　tumorigenesis,　the　pattern-recognition　method　was　used　to　analyze　the　gene　methylation　(ME)　data　which　included　only　normal　and　cancer　samples　and　was　collected　from　the　TCGA　(The　Cancer　Genome　Atlas)　database.　Here,　we　analyzed　the　DNA　methylation　profiles　of　the　six　types　of　cancer　and　the　ME　signature　genes　for　each　cancer　were　selected　by　means　of　a　combination　of　correlation,　students　t-test　and　Elastic　Net.　Modeling　by　support　vector　machine,　the　accuracy　of　ME　signature　genes　can　be　as　high　as　98　%　for　training　set　and　as　high　as　97　%　for　the　independent　test　set,　the　recognition　accuracy　of　stage　I　is　more　than　97　%　for　training　set　and　more　than　98　%　for　test　set.　Then,　the　common　signature　genes　and　common　pathways　emerging　in　multiple　cancers　were　obtained.　A　functional　analysis　of　these　signature　genes　indicates　that　the　identified　signatures　have　direct　relationship　with　tumorigenesis　and　is　very　important　for　understanding　the　pathogenesis　of　cancer　and　the　early　therapy.