Even though various molecules may serve as biomarkers, little is known concerning the mechanisms underlying the carcinogenesis of ESCC, particularly the transcriptional regulatory network. Thus, in the present study, paired ESCC and non-cancerous (NC) tissues were assayed by Affymetrix microarray assays. Passing Attributes between Networks for Data Assimilation (PANDA) was used to construct networks between transcription factors (TFs) and their targets. AnaPANDA program was applied to compare the regulatory networks. A hypergeometric distribution model-based target profile similarity analysis was utilized to find co-activation effects using both TF-target networks and differential expression data. There were 1,116 genes upregulated and 1,301 genes downregulated in ESCC compared with NC tissues. In TF-target networks, 16,970 ESCC-specific edges and 9,307 NC-specific edges were identified. Edge enrichment analysis by AnaPANDA indicated 17 transcription factors (NFE2L2, ELK4, PAX6, TLX1, ESR1, ZNF143, TP53, REL, ELF5, STAT1, TBP, NHLH1, FOXL1, SOX9, STAT3, ELK1, and HOXA5) suppressed in ESCC and 5 (SPIB, BRCA1, MZF1, MAFG and NFE2L1) activated in ESCC. For SPIB, MZF1, MAFG and NFE2L1, a strong and significant co-activation effect among them was detected in ESCC. In conclusion, the construction of transcriptional regulatory networks found SPIB, MZF1, MAFG and NFE2L1 co-activated in ESCC, which provides distinctive insight into the carcinogenesis mechanism of ESCC.