Q-omics provides the consensus-scored ZC2HC1A profile across patient tissues and cancer cell-line models. ZC2HC1A expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, ZC2HC1A is differentially expressed in 10, with the highest sampling consensus in UCEC. Additionally, ZC2HC1A protein abundance shows 23,516 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, UCEC, and GBM as cancer lineages where ZC2HC1A 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 ZC2HC1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZC2HC1A survival associations across molecular data types. ZC2HC1A RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZC2HC1A RNA expression–survival associations across cancer types. High ZC2HC1A expression shows unfavorable associations in LIHC and UVM, but favorable associations in KIRC, UCS, BLCA and COAD. The LIHC 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 LIHC as the clearest survival context for ZC2HC1A RNA expression.
This table summarizes ZC2HC1A 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 7. The strongest signals are observed in UCEC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ZC2HC1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZC2HC1A shows lower tumor expression in UCEC, LUAD, LUSC and BRCA and higher tumor expression in KIRP and LIHC. The UCEC box plot shows higher ZC2HC1A RNA expression in normal versus tumor tissue (log2 FC = −1.270, t-test p < 0.001).
This table shows molecular features associated with ZC2HC1A in patient tissues and cancer cell lines. In patient samples, ZC2HC1A 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, ZC2HC1A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BONE.
