F-box and leucine rich repeat protein 4Genealiases: FBL4 · FBL5 · MTDPS13
Q-omics provides the consensus-scored FBXL4 profile across patient tissues and cancer cell-line models. FBXL4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, FBXL4 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, FBXL4 RNA expression shows 20,599 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, HNSC, and THYM as cancer lineages where FBXL4 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 FBXL4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FBXL4 survival associations across molecular data types. FBXL4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) 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 FBXL4 RNA expression–survival associations across cancer types. High FBXL4 expression shows unfavorable associations in CESC and KIRP, but favorable associations in KIRC, READ, SKCM and ACC. 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 FBXL4 RNA expression.
This table summarizes FBXL4 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 2. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for FBXL4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FBXL4 shows lower tumor expression in THCA, KIRC, KICH and KIRP and higher tumor expression in HNSC and COAD. The HNSC box plot shows higher FBXL4 RNA expression in tumor versus normal tissue (log2 FC = +0.742, t-test p < 0.001).
This table shows molecular features associated with FBXL4 in patient tissues and cancer cell lines. In patient samples, FBXL4 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, FBXL4 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 BREAST and UPPER_AERODIGESTIVE_TRACT.
