Q-omics provides the consensus-scored ZDHHC9 profile across patient tissues and cancer cell-line models. ZDHHC9 expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ZDHHC9 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, ZDHHC9 RNA expression shows 20,069 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, and ACC as cancer lineages where ZDHHC9 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 ZDHHC9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZDHHC9 survival associations across molecular data types. ZDHHC9 RNA expression shows survival associations in the most cancer types (30), followed by mutation status (3) 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 ZDHHC9 RNA expression–survival associations across cancer types. High ZDHHC9 expression shows unfavorable associations in HNSC, BRCA, CESC, BLCA and ACC, but favorable associations in KIRC. The HNSC 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 HNSC as the clearest survival context for ZDHHC9 RNA expression.
This table summarizes ZDHHC9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for ZDHHC9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZDHHC9 shows higher tumor expression in HNSC, COAD, BLCA, KIRC, STAD and LUAD. The HNSC box plot shows higher ZDHHC9 RNA expression in tumor versus normal tissue (log2 FC = +1.414, t-test p < 0.001).
This table shows molecular features associated with ZDHHC9 in patient tissues and cancer cell lines. In patient samples, ZDHHC9 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, ZDHHC9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and UPPER_AERODIGESTIVE_TRACT.
