Q-omics provides the consensus-scored FER1L6-AS2 profile across patient tissues and cancer cell-line models. FER1L6-AS2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, FER1L6-AS2 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, FER1L6-AS2 RNA expression shows 11,061 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, THCA, and GBM as cancer lineages where FER1L6-AS2 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-AS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FER1L6-AS2 survival associations across molecular data types. FER1L6-AS2 RNA expression shows survival associations in the most cancer types (23). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FER1L6-AS2 RNA expression–survival associations across cancer types. High FER1L6-AS2 expression shows unfavorable associations in LIHC, THYM, DLBC and LUAD, but favorable associations in READ and LGG. The LIHC 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 LIHC as the clearest survival context for FER1L6-AS2 RNA expression.
This table summarizes FER1L6-AS2 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 THCA for RNA.
This table ranks reproducible tumor–normal expression differences for FER1L6-AS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FER1L6-AS2 shows lower tumor expression in THCA, KIRP and COAD and higher tumor expression in LUSC, LIHC and HNSC. The THCA box plot shows higher FER1L6-AS2 RNA expression in normal versus tumor tissue (log2 FC = −0.179, t-test p < 0.001).
This table shows molecular features associated with FER1L6-AS2 in patient tissues and cancer cell lines. In patient samples, FER1L6-AS2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, FER1L6-AS2 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 LUNG_SCLC.
