Q-omics provides the consensus-scored FER1L6 profile across patient tissues and cancer cell-line models. FER1L6 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, FER1L6 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, FER1L6 RNA expression shows 16,088 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and KIRC as cancer lineages where FER1L6 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 FER1L6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FER1L6 survival associations across molecular data types. FER1L6 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FER1L6 RNA expression–survival associations across cancer types. High FER1L6 expression shows unfavorable associations in UVM, ACC, CESC and ESCA, but favorable associations in COAD and SCLC. 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 FER1L6 RNA expression.
This table summarizes FER1L6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for FER1L6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FER1L6 shows lower tumor expression in KIRC, KIRP, THCA and COAD and higher tumor expression in LIHC and LUSC. The KIRC box plot shows higher FER1L6 RNA expression in normal versus tumor tissue (log2 FC = −1.652, t-test p < 0.001).
This table shows molecular features associated with FER1L6 in patient tissues and cancer cell lines. In patient samples, FER1L6 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, FER1L6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and LARGE_INTESTINE.
