Q-omics provides the consensus-scored APOC3 profile across patient tissues and cancer cell-line models. APOC3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, APOC3 is differentially expressed in 8, with the highest sampling consensus in KIRP. Additionally, APOC3 protein abundance shows 20,081 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight STAD, KIRP, and BRCA as cancer lineages where APOC3 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 APOC3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APOC3 survival associations across molecular data types. APOC3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible APOC3 RNA expression–survival associations across cancer types. High APOC3 expression shows unfavorable associations in STAD, UVM, ACC, HNSC and CHOL, but favorable associations in LIHC. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify STAD as the clearest survival context for APOC3 RNA expression.
This table summarizes APOC3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRP for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for APOC3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APOC3 shows lower tumor expression in KIRP, KICH, LIHC, KIRC, CHOL and LUAD. The KIRP box plot shows higher APOC3 RNA expression in normal versus tumor tissue (log2 FC = −3.402, t-test p < 0.001).
This table shows molecular features associated with APOC3 in patient tissues and cancer cell lines. In patient samples, APOC3 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, APOC3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Lymphoma.
