Q-omics provides the consensus-scored ADCY4 profile across patient tissues and cancer cell-line models. ADCY4 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ADCY4 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, ADCY4 RNA expression shows 18,910 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight HNSC, KICH, and CCRCC as cancer lineages where ADCY4 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 ADCY4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADCY4 survival associations across molecular data types. ADCY4 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) 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 ADCY4 RNA expression–survival associations across cancer types. High ADCY4 expression shows unfavorable associations in KIRP, UVM, MESO and COAD, but favorable associations in HNSC and UCEC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for ADCY4 RNA expression.
This table summarizes ADCY4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in LUAD for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ADCY4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADCY4 shows lower tumor expression in KICH, LUAD, KIRP, LUSC and BLCA and higher tumor expression in LIHC. The KICH box plot shows higher ADCY4 RNA expression in normal versus tumor tissue (log2 FC = −2.009, t-test p < 0.001).
This table shows molecular features associated with ADCY4 in patient tissues and cancer cell lines. In patient samples, ADCY4 shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ADCY4 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 OESOPHAGUS and BLOOD_Leukemia.
