Q-omics provides the consensus-scored ZEB2P1 profile across patient tissues and cancer cell-line models. ZEB2P1 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, ZEB2P1 is differentially expressed in 5, with the highest sampling consensus in LIHC. Additionally, ZEB2P1 RNA expression shows 11,128 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight STAD, LIHC, and UVM as cancer lineages where ZEB2P1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for ZEB2P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZEB2P1 survival associations across molecular data types. ZEB2P1 RNA expression shows survival associations in the most cancer types (17). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZEB2P1 RNA expression–survival associations across cancer types. High ZEB2P1 expression shows unfavorable associations in STAD, THCA, HNSC and KIRP, but favorable associations in ESCA and ACC. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify STAD as the clearest survival context for ZEB2P1 RNA expression.
This table summarizes ZEB2P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for ZEB2P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZEB2P1 shows lower tumor expression in KICH and THCA and higher tumor expression in LIHC, BRCA and PRAD. The LIHC box plot shows higher ZEB2P1 RNA expression in tumor versus normal tissue (log2 FC = +0.229, t-test p < 0.001).
This table shows molecular features associated with ZEB2P1 in patient tissues and cancer cell lines. In patient samples, ZEB2P1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set.
