zinc finger CCCH-type and G-patch domain containingGenealiases: GPATC6 · GPATCH6 · KIAA1847 · ZC3H9 · ZC3HDC9 · ZIP
Q-omics provides the consensus-scored ZGPAT profile across patient tissues and cancer cell-line models. ZGPAT expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ZGPAT is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ZGPAT RNA expression shows 18,940 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, and ACC as cancer lineages where ZGPAT 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 ZGPAT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZGPAT survival associations across molecular data types. ZGPAT RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZGPAT RNA expression–survival associations across cancer types. High ZGPAT expression shows unfavorable associations in KIRC, KICH, LGG, LIHC and LUSC, but favorable associations in HNSC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify HNSC as the clearest survival context for ZGPAT RNA expression.
This table summarizes ZGPAT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ZGPAT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZGPAT shows lower tumor expression in KIRP and KICH and higher tumor expression in HNSC, COAD, STAD and BLCA. The HNSC box plot shows higher ZGPAT RNA expression in tumor versus normal tissue (log2 FC = +0.700, t-test p < 0.001).
This table shows molecular features associated with ZGPAT in patient tissues and cancer cell lines. In patient samples, ZGPAT shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ZGPAT 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 CNS and BLOOD_Leukemia.
