Q-omics provides the consensus-scored ARF4 profile across patient tissues and cancer cell-line models. ARF4 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ARF4 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, ARF4 protein abundance shows 29,177 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, THCA, and LSCC as cancer lineages where ARF4 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 ARF4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARF4 survival associations across molecular data types. ARF4 RNA expression shows survival associations in the most cancer types (19), 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 ARF4 RNA expression–survival associations across cancer types. High ARF4 expression shows unfavorable associations in ACC, KIRP, LIHC, KICH, LGG and HNSC. 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 ARF4 RNA expression.
This table summarizes ARF4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ARF4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARF4 shows lower tumor expression in THCA and KICH and higher tumor expression in LUAD, LIHC, BRCA and STAD. The THCA box plot shows higher ARF4 RNA expression in normal versus tumor tissue (log2 FC = −0.864, t-test p < 0.001).
This table shows molecular features associated with ARF4 in patient tissues and cancer cell lines. In patient samples, ARF4 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ARF4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
