To　identify　signature　genes　for　the　pathogenesis　of　cancer,　which　provides　a　theoretical　support　for　prevention　and　early　diagnosis　of　cancer.　The　pattern　recognition　method　was　used　to　analyze　the　genome-wide　gene　expression　data,　which　was　collected　from　the　The　Cancer　Genome　Atlas　(TCGA)　database.　For　the　transcription　of　invasive　breast　carcinoma,　lung　adenocarcinoma,　lung　squamous　cell　carcinoma,　colon　adenocarcinoma,　renal　clear-cell　carcinoma,　thyroid　carcinoma,　and　hepatocellular　carcinoma　of　the　seven　cancers,　the　signature　genes　were　selected　by　means　of　a　combination　of　statistical　methods,　such　as　correlation,　t-test,　confidence　interval,　etc.　Modeling　by　artificial　neural　network　model,　the　accuracy　can　be　as　high　as　98%　for　the　TCGA　data　and　as　high　as　92%　for　the　Gene　Expression　Omnibus　(GEO)　independent　data,　the　recognition　accuracy　of　stage　I　is　more　than　95%,　which　is　higher　compared　with　the　previous　study.　The　common　genes　emerging　in　five　cancers　were　obtained　from　the　signature　genes　of　seven　cancers,　PID1,　and　SPTBN2.　At　the　same　time,　we　obtain　three　common　pathways　of　cancer　by　using　Kyoto　Encyclopedia　of　Genes　and　Genomes＇　pathway　analysis.　A　functional　analysis　of　the　pathways　shows　their　close　relationship　at　the　level　of　gene　regulation,　which　indicted　that　the　identified　signature　genes　play　an　important　role　in　the　pathogenesis　of　cancer　and　is　very　important　for　understanding　the　pathogenesis　of　cancer　and　the　early　diagnosis.