Q-omics provides the consensus-scored FBXL22 profile across patient tissues and cancer cell-line models. FBXL22 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, FBXL22 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, FBXL22 RNA expression shows 19,587 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ESCA, KIRC, and UVM as cancer lineages where FBXL22 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 FBXL22 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FBXL22 survival associations across molecular data types. FBXL22 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FBXL22 RNA expression–survival associations across cancer types. High FBXL22 expression shows unfavorable associations in BLCA and UVM, but favorable associations in ESCA, UCS, KIRC and LUAD. The ESCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify ESCA as the clearest survival context for FBXL22 RNA expression.
This table summarizes FBXL22 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for FBXL22. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FBXL22 shows lower tumor expression in KIRC, BLCA, COAD, THCA and KIRP and higher tumor expression in LIHC. The KIRC box plot shows higher FBXL22 RNA expression in normal versus tumor tissue (log2 FC = −0.632, t-test p < 0.001).
This table shows molecular features associated with FBXL22 in patient tissues and cancer cell lines. In patient samples, FBXL22 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, FBXL22 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BREAST.
