Q-omics provides the consensus-scored FOXD4L6 profile across patient tissues and cancer cell-line models. FOXD4L6 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, FOXD4L6 is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, FOXD4L6 RNA expression shows 6,185 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight ACC, HNSC, and STAD as cancer lineages where FOXD4L6 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 FOXD4L6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FOXD4L6 survival associations across molecular data types. FOXD4L6 RNA expression shows survival associations in the most cancer types (16), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FOXD4L6 RNA expression–survival associations across cancer types. High FOXD4L6 expression shows unfavorable associations in ACC, THCA, UVM and PCPG, but favorable associations in OV and SCLC. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify ACC as the clearest survival context for FOXD4L6 RNA expression.
This table summarizes FOXD4L6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for FOXD4L6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FOXD4L6 shows lower tumor expression in KICH and higher tumor expression in HNSC, STAD, BRCA and ESCA. The HNSC box plot shows higher FOXD4L6 RNA expression in tumor versus normal tissue (log2 FC = +0.011, t-test p = .005).
This table shows molecular features associated with FOXD4L6 in patient tissues and cancer cell lines. In patient samples, FOXD4L6 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, FOXD4L6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and LIVER.
