Q-omics provides the consensus-scored APOBEC3A profile across patient tissues and cancer cell-line models. APOBEC3A expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, APOBEC3A is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, APOBEC3A RNA expression shows 18,097 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight CESC, KIRC, and PDAC as cancer lineages where APOBEC3A 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 APOBEC3A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APOBEC3A survival associations across molecular data types. APOBEC3A RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible APOBEC3A RNA expression–survival associations across cancer types. High APOBEC3A expression shows unfavorable associations in UCEC, KIRP and LGG, but favorable associations in CESC, SKCM and ESCA. The CESC 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 CESC as the clearest survival context for APOBEC3A RNA expression.
This table summarizes APOBEC3A 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 2. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for APOBEC3A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APOBEC3A shows lower tumor expression in COAD, KICH, LUAD and BLCA and higher tumor expression in KIRC and BRCA. The KIRC box plot shows higher APOBEC3A RNA expression in tumor versus normal tissue (log2 FC = +0.564, t-test p < 0.001).
This table shows molecular features associated with APOBEC3A in patient tissues and cancer cell lines. In patient samples, APOBEC3A shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, APOBEC3A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
