Q-omics provides the consensus-scored ZC3H13 profile across patient tissues and cancer cell-line models. ZC3H13 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ZC3H13 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, ZC3H13 protein abundance shows 31,036 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where ZC3H13 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 ZC3H13 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZC3H13 survival associations across molecular data types. ZC3H13 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (9) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZC3H13 RNA expression–survival associations across cancer types. High ZC3H13 expression shows unfavorable associations in CESC, SKCM and LUSC, but favorable associations in KIRC, UCS and SCLC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for ZC3H13 RNA expression.
This table summarizes ZC3H13 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ZC3H13. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZC3H13 shows lower tumor expression in THCA, BRCA and KICH and higher tumor expression in HNSC, STAD and READ. The HNSC box plot shows higher ZC3H13 RNA expression in tumor versus normal tissue (log2 FC = +0.555, t-test p < 0.001).
This table shows molecular features associated with ZC3H13 in patient tissues and cancer cell lines. In patient samples, ZC3H13 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ZC3H13 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
