Q-omics provides the consensus-scored APOD profile across patient tissues and cancer cell-line models. APOD expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, APOD is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, APOD RNA expression shows 22,760 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight LUSC, KIRC, and HNSC as cancer lineages where APOD 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 APOD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APOD survival associations across molecular data types. APOD RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible APOD RNA expression–survival associations across cancer types. High APOD expression shows unfavorable associations in BLCA, ACC, STAD and UVM, but favorable associations in LUSC and CHOL. The LUSC 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 LUSC as the clearest survival context for APOD RNA expression.
This table summarizes APOD 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 7. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for APOD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APOD shows lower tumor expression in KIRC, KICH, THCA, KIRP, BLCA and HNSC. The KIRC box plot shows higher APOD RNA expression in normal versus tumor tissue (log2 FC = −1.938, t-test p < 0.001).
This table shows molecular features associated with APOD in patient tissues and cancer cell lines. In patient samples, APOD shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, APOD RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BREAST.
