Q-omics provides the consensus-scored ZCCHC12 profile across patient tissues and cancer cell-line models. ZCCHC12 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ZCCHC12 is differentially expressed in 14, with the highest sampling consensus in THCA. Additionally, ZCCHC12 RNA expression shows 16,018 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, THCA, and TGCT as cancer lineages where ZCCHC12 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 ZCCHC12 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZCCHC12 survival associations across molecular data types. ZCCHC12 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZCCHC12 RNA expression–survival associations across cancer types. High ZCCHC12 expression shows unfavorable associations in KIRP, KIRC, ACC and UVM, but favorable associations in THCA and SCLC. The KIRP 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 KIRP as the clearest survival context for ZCCHC12 RNA expression.
This table summarizes ZCCHC12 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 1. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ZCCHC12. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZCCHC12 shows lower tumor expression in KICH, UCEC, COAD and BRCA and higher tumor expression in THCA and HNSC. The THCA box plot shows higher ZCCHC12 RNA expression in tumor versus normal tissue (log2 FC = +6.725, t-test p < 0.001).
This table shows molecular features associated with ZCCHC12 in patient tissues and cancer cell lines. In patient samples, ZCCHC12 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, ZCCHC12 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SKIN.
