Q-omics provides the consensus-scored FERD3L profile across patient tissues and cancer cell-line models. FERD3L expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in UCEC. Additionally, FERD3L RNA expression shows 6,698 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UCEC, and THYM as cancer lineages where FERD3L 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 FERD3L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FERD3L survival associations across molecular data types. FERD3L RNA expression shows survival associations in the most cancer types (16), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FERD3L RNA expression–survival associations across cancer types. High FERD3L expression shows unfavorable associations in UCEC, THCA, KIRC, LUSC, READ and KIRP. The UCEC 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 UCEC as the clearest survival context for FERD3L RNA expression.
This table shows molecular features associated with FERD3L in patient tissues and cancer cell lines. In patient samples, FERD3L 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, FERD3L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and LUNG_SCLC.
