Q-omics provides the consensus-scored ZG16B profile across patient tissues and cancer cell-line models. ZG16B expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, ZG16B is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, ZG16B RNA expression shows 15,144 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UCEC, HNSC, and THYM as cancer lineages where ZG16B 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 ZG16B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZG16B survival associations across molecular data types. ZG16B RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZG16B RNA expression–survival associations across cancer types. High ZG16B expression shows unfavorable associations in KIRP and LUAD, but favorable associations in UCEC, HNSC, COAD and OV. The UCEC 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 UCEC as the clearest survival context for ZG16B RNA expression.
This table summarizes ZG16B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ZG16B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZG16B shows lower tumor expression in HNSC and higher tumor expression in COAD, KIRC, THCA, BRCA and LUAD. The HNSC box plot shows higher ZG16B RNA expression in normal versus tumor tissue (log2 FC = −4.706, t-test p < 0.001).
This table shows molecular features associated with ZG16B in patient tissues and cancer cell lines. In patient samples, ZG16B shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, ZG16B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BREAST.
