Q-omics provides the consensus-scored USF2 profile across patient tissues and cancer cell-line models. USF2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, USF2 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, USF2 protein abundance shows 18,932 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, KIRC, and HNSC as cancer lineages where USF2 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 USF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes USF2 survival associations across molecular data types. USF2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4) 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 USF2 RNA expression–survival associations across cancer types. High USF2 expression shows unfavorable associations in ACC, KIRC, CESC and LGG, but favorable associations in UVM and UCS. 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 USF2 RNA expression.
This table summarizes USF2 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 5. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for USF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. USF2 shows higher tumor expression in KIRC, HNSC, COAD, LIHC, LUSC and STAD. The KIRC box plot shows higher USF2 RNA expression in tumor versus normal tissue (log2 FC = +0.697, t-test p < 0.001).
This table shows molecular features associated with USF2 in patient tissues and cancer cell lines. In patient samples, USF2 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, USF2 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 KIDNEY and BLOOD_Leukemia.
