Q-omics provides the consensus-scored ZIC4 profile across patient tissues and cancer cell-line models. ZIC4 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ZIC4 is differentially expressed in 8, with the highest sampling consensus in UCEC. Additionally, ZIC4 RNA expression shows 9,671 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, UCEC, and TGCT as cancer lineages where ZIC4 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 ZIC4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZIC4 survival associations across molecular data types. ZIC4 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZIC4 RNA expression–survival associations across cancer types. High ZIC4 expression shows unfavorable associations in KIRC, ACC, MESO, THYM and KIRP, but favorable associations in HNSC. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for ZIC4 RNA expression.
This table summarizes ZIC4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for ZIC4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZIC4 shows higher tumor expression in UCEC, LIHC, LUSC, BRCA, LUAD and KIRC. The UCEC box plot shows higher ZIC4 RNA expression in tumor versus normal tissue (log2 FC = +0.980, t-test p < 0.001).
This table shows molecular features associated with ZIC4 in patient tissues and cancer cell lines. In patient samples, ZIC4 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, ZIC4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and CNS.
