Q-omics provides the consensus-scored FRA10AC1 profile across patient tissues and cancer cell-line models. FRA10AC1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, FRA10AC1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, FRA10AC1 RNA expression shows 20,586 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, KIRC, and UVM as cancer lineages where FRA10AC1 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 FRA10AC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FRA10AC1 survival associations across molecular data types. FRA10AC1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FRA10AC1 RNA expression–survival associations across cancer types. High FRA10AC1 expression shows unfavorable associations in ACC, UVM and LIHC, but favorable associations in BRCA, SKCM and LGG. The ACC 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 ACC as the clearest survival context for FRA10AC1 RNA expression.
This table summarizes FRA10AC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for FRA10AC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FRA10AC1 shows lower tumor expression in KICH, BRCA, BLCA and THCA and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher FRA10AC1 RNA expression in tumor versus normal tissue (log2 FC = +0.428, t-test p < 0.001).
This table shows molecular features associated with FRA10AC1 in patient tissues and cancer cell lines. In patient samples, FRA10AC1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, FRA10AC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
