Q-omics provides the consensus-scored ADCY9 profile across patient tissues and cancer cell-line models. ADCY9 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ADCY9 is differentially expressed in 15, with the highest sampling consensus in LUAD. Additionally, ADCY9 protein abundance shows 22,115 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LUAD, and GBM as cancer lineages where ADCY9 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 ADCY9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADCY9 survival associations across molecular data types. ADCY9 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (8) 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 ADCY9 RNA expression–survival associations across cancer types. High ADCY9 expression shows unfavorable associations in UCEC and BLCA, but favorable associations in KIRC, HNSC, BRCA and LUAD. The KIRC 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 KIRC as the clearest survival context for ADCY9 RNA expression.
This table summarizes ADCY9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ADCY9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADCY9 shows lower tumor expression in LUAD, THCA, BLCA, COAD and UCEC and higher tumor expression in LIHC. The LUAD box plot shows higher ADCY9 RNA expression in normal versus tumor tissue (log2 FC = −1.316, t-test p < 0.001).
This table shows molecular features associated with ADCY9 in patient tissues and cancer cell lines. In patient samples, ADCY9 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, ADCY9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and OESOPHAGUS.
