Q-omics provides the consensus-scored APOBEC4 profile across patient tissues and cancer cell-line models. APOBEC4 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, APOBEC4 is differentially expressed in 7, with the highest sampling consensus in LUSC. Additionally, APOBEC4 RNA expression shows 10,319 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KICH, LUSC, and HNSC as cancer lineages where APOBEC4 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 APOBEC4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APOBEC4 survival associations across molecular data types. APOBEC4 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible APOBEC4 RNA expression–survival associations across cancer types. High APOBEC4 expression shows unfavorable associations in KICH, KIRP and LIHC, but favorable associations in CESC, PAAD and BRCA. The KICH 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 KICH as the clearest survival context for APOBEC4 RNA expression.
This table summarizes APOBEC4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in LUSC for RNA.
This table ranks reproducible tumor–normal expression differences for APOBEC4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APOBEC4 shows lower tumor expression in LUSC, LUAD and THCA and higher tumor expression in BRCA, LIHC and STAD. The LUSC box plot shows higher APOBEC4 RNA expression in normal versus tumor tissue (log2 FC = −1.653, t-test p < 0.001).
This table shows molecular features associated with APOBEC4 in patient tissues and cancer cell lines. In patient samples, APOBEC4 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, APOBEC4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
