Q-omics provides the consensus-scored ZDHHC16 profile across patient tissues and cancer cell-line models. ZDHHC16 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ZDHHC16 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ZDHHC16 RNA expression shows 19,057 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where ZDHHC16 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 ZDHHC16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZDHHC16 survival associations across molecular data types. ZDHHC16 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (5) 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 ZDHHC16 RNA expression–survival associations across cancer types. High ZDHHC16 expression shows unfavorable associations in ACC, LIHC, HNSC, KICH, KIRC and CESC. The ACC 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 ACC as the clearest survival context for ZDHHC16 RNA expression.
This table summarizes ZDHHC16 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 HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ZDHHC16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZDHHC16 shows lower tumor expression in KICH and higher tumor expression in HNSC, COAD, LIHC, KIRP and THCA. The HNSC box plot shows higher ZDHHC16 RNA expression in tumor versus normal tissue (log2 FC = +0.680, t-test p < 0.001).
This table shows molecular features associated with ZDHHC16 in patient tissues and cancer cell lines. In patient samples, ZDHHC16 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ZDHHC16 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 UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
