Q-omics provides the consensus-scored FOXL1 profile across patient tissues and cancer cell-line models. FOXL1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, FOXL1 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, FOXL1 RNA expression shows 14,509 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UVM, HNSC, and TGCT as cancer lineages where FOXL1 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 FOXL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FOXL1 survival associations across molecular data types. FOXL1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FOXL1 RNA expression–survival associations across cancer types. High FOXL1 expression shows unfavorable associations in UVM, CESC, KIRP and PAAD, but favorable associations in UCEC and READ. 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 FOXL1 RNA expression.
This table summarizes FOXL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for FOXL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FOXL1 shows lower tumor expression in KICH and higher tumor expression in HNSC, STAD, KIRC, LIHC and CHOL. The HNSC box plot shows higher FOXL1 RNA expression in tumor versus normal tissue (log2 FC = +1.259, t-test p < 0.001).
This table shows molecular features associated with FOXL1 in patient tissues and cancer cell lines. In patient samples, FOXL1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, FOXL1 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 SOFT_TISSUE.
