Q-omics provides the consensus-scored APOBEC3C profile across patient tissues and cancer cell-line models. APOBEC3C expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, APOBEC3C is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, APOBEC3C protein abundance shows 21,473 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LGG, KIRC, and GBM as cancer lineages where APOBEC3C 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 APOBEC3C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APOBEC3C survival associations across molecular data types. APOBEC3C RNA expression shows survival associations in the most cancer types (28), 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 APOBEC3C RNA expression–survival associations across cancer types. High APOBEC3C expression shows unfavorable associations in LGG and LAML, but favorable associations in CESC, BLCA, LUSC and BRCA. The LGG 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 LGG as the clearest survival context for APOBEC3C RNA expression.
This table summarizes APOBEC3C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for APOBEC3C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APOBEC3C shows lower tumor expression in UCEC, BRCA and KICH and higher tumor expression in KIRC, KIRP and HNSC. The KIRC box plot shows higher APOBEC3C RNA expression in tumor versus normal tissue (log2 FC = +2.514, t-test p < 0.001).
This table shows molecular features associated with APOBEC3C in patient tissues and cancer cell lines. In patient samples, APOBEC3C shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, APOBEC3C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in OVARY and UPPER_AERODIGESTIVE_TRACT.
