Q-omics provides the consensus-scored A1CF profile across patient tissues and cancer cell-line models. A1CF expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, A1CF is differentially expressed in 7, with the highest sampling consensus in KICH. Additionally, A1CF RNA expression shows 15,841 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, KICH, and TGCT as cancer lineages where A1CF 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 A1CF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes A1CF survival associations across molecular data types. A1CF RNA expression shows survival associations in the most cancer types (27), followed by mutation status (8) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible A1CF RNA expression–survival associations across cancer types. High A1CF expression shows unfavorable associations in LUAD, THCA, HNSC, UVM and UCEC, but favorable associations in KIRC. The KIRC 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 KIRC as the clearest survival context for A1CF RNA expression.
This table summarizes A1CF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 3. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for A1CF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. A1CF shows lower tumor expression in KICH, COAD, KIRP and CHOL and higher tumor expression in KIRC and LUSC. The KICH box plot shows higher A1CF RNA expression in normal versus tumor tissue (log2 FC = −2.312, t-test p < 0.001).
This table shows molecular features associated with A1CF in patient tissues and cancer cell lines. In patient samples, A1CF shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, A1CF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in OVARY and LIVER.
