Q-omics provides the consensus-scored ZCCHC18 profile across patient tissues and cancer cell-line models. ZCCHC18 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, ZCCHC18 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, ZCCHC18 RNA expression shows 18,935 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight PAAD, KICH, and UVM as cancer lineages where ZCCHC18 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 ZCCHC18 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZCCHC18 survival associations across molecular data types. ZCCHC18 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZCCHC18 RNA expression–survival associations across cancer types. High ZCCHC18 expression shows unfavorable associations in KIRC, but favorable associations in PAAD, HNSC, LUAD, SKCM and BLCA. The PAAD 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 PAAD as the clearest survival context for ZCCHC18 RNA expression.
This table summarizes ZCCHC18 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for ZCCHC18. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZCCHC18 shows lower tumor expression in KICH and READ and higher tumor expression in HNSC, LIHC, CHOL and KIRP. The KICH box plot shows higher ZCCHC18 RNA expression in normal versus tumor tissue (log2 FC = −0.545, t-test p < 0.001).
This table shows molecular features associated with ZCCHC18 in patient tissues and cancer cell lines. In patient samples, ZCCHC18 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ZCCHC18 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
