Q-omics provides the consensus-scored PDE9A profile across patient tissues and cancer cell-line models. PDE9A expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PDE9A is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, PDE9A RNA expression shows 17,953 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, COAD, and TGCT as cancer lineages where PDE9A 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 PDE9A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDE9A survival associations across molecular data types. PDE9A RNA expression shows survival associations in the most cancer types (20), followed by mutation status (9) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PDE9A RNA expression–survival associations across cancer types. High PDE9A expression shows unfavorable associations in ACC, CESC, STAD and UVM, but favorable associations in KIRC and ESCA. 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 PDE9A RNA expression.
This table summarizes PDE9A 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 COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PDE9A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDE9A shows lower tumor expression in COAD, KICH, KIRC, BRCA and READ and higher tumor expression in THCA. The COAD box plot shows higher PDE9A RNA expression in normal versus tumor tissue (log2 FC = −2.658, t-test p < 0.001).
This table shows molecular features associated with PDE9A in patient tissues and cancer cell lines. In patient samples, PDE9A shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PDE9A 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 BONE and LARGE_INTESTINE.
