Q-omics provides the consensus-scored APOA2 profile across patient tissues and cancer cell-line models. APOA2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, APOA2 is differentially expressed in 10, with the highest sampling consensus in KIRP. Additionally, APOA2 protein abundance shows 23,977 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight ESCA, KIRP, and CCRCC as cancer lineages where APOA2 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 APOA2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APOA2 survival associations across molecular data types. APOA2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) 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 APOA2 RNA expression–survival associations across cancer types. High APOA2 expression shows unfavorable associations in ESCA, CHOL, UCEC, STAD, UVM and UCS. The ESCA 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 ESCA as the clearest survival context for APOA2 RNA expression.
This table summarizes APOA2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for APOA2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APOA2 shows lower tumor expression in KIRP, KIRC and KICH and higher tumor expression in THCA, STAD and BRCA. The KIRP box plot shows higher APOA2 RNA expression in normal versus tumor tissue (log2 FC = −0.585, t-test p = .003).
This table shows molecular features associated with APOA2 in patient tissues and cancer cell lines. In patient samples, APOA2 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, APOA2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and LIVER.
