Q-omics provides the consensus-scored ZCCHC3 profile across patient tissues and cancer cell-line models. ZCCHC3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, ZCCHC3 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ZCCHC3 protein abundance shows 21,981 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight COAD, HNSC, and LSCC as cancer lineages where ZCCHC3 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 ZCCHC3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZCCHC3 survival associations across molecular data types. ZCCHC3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZCCHC3 RNA expression–survival associations across cancer types. High ZCCHC3 expression shows unfavorable associations in COAD, LIHC and LGG, but favorable associations in BRCA, KIRC and PAAD. The COAD 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 COAD as the clearest survival context for ZCCHC3 RNA expression.
This table summarizes ZCCHC3 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ZCCHC3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZCCHC3 shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRC, COAD, STAD and LIHC. The HNSC box plot shows higher ZCCHC3 RNA expression in tumor versus normal tissue (log2 FC = +1.093, t-test p < 0.001).
This table shows molecular features associated with ZCCHC3 in patient tissues and cancer cell lines. In patient samples, ZCCHC3 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ZCCHC3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SOFT_TISSUE.
