Q-omics provides the consensus-scored APMAP profile across patient tissues and cancer cell-line models. APMAP expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, APMAP is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, APMAP RNA expression shows 19,866 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight MESO, HNSC, and UVM as cancer lineages where APMAP 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 APMAP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APMAP survival associations across molecular data types. APMAP RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible APMAP RNA expression–survival associations across cancer types. High APMAP expression shows unfavorable associations in MESO, OV, CHOL, HNSC and BLCA, but favorable associations in LUAD. The MESO 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 MESO as the clearest survival context for APMAP RNA expression.
This table summarizes APMAP 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 5. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for APMAP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APMAP shows lower tumor expression in THCA and higher tumor expression in HNSC, BLCA, STAD, KIRP and COAD. The HNSC box plot shows higher APMAP RNA expression in tumor versus normal tissue (log2 FC = +1.466, t-test p < 0.001).
This table shows molecular features associated with APMAP in patient tissues and cancer cell lines. In patient samples, APMAP shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, APMAP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and UPPER_AERODIGESTIVE_TRACT.
