Q-omics provides the consensus-scored FBXO4 profile across patient tissues and cancer cell-line models. FBXO4 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, FBXO4 is differentially expressed in 14, with the highest sampling consensus in LIHC. Additionally, FBXO4 RNA expression shows 19,263 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and LIHC as cancer lineages where FBXO4 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 FBXO4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FBXO4 survival associations across molecular data types. FBXO4 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FBXO4 RNA expression–survival associations across cancer types. High FBXO4 expression shows unfavorable associations in UVM, KICH and LGG, but favorable associations in OV, KIRC and SKCM. The UVM 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 UVM as the clearest survival context for FBXO4 RNA expression.
This table summarizes FBXO4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for FBXO4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FBXO4 shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, KIRC, HNSC and STAD. The LIHC box plot shows higher FBXO4 RNA expression in tumor versus normal tissue (log2 FC = +0.880, t-test p < 0.001).
This table shows molecular features associated with FBXO4 in patient tissues and cancer cell lines. In patient samples, FBXO4 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, FBXO4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BONE and UPPER_AERODIGESTIVE_TRACT.
