long intergenic non-protein coding RNA 474Genealiases: C9orf27 · EST-YD1
Q-omics provides the consensus-scored LINC00474 profile across patient tissues and cancer cell-line models. LINC00474 expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in ESCA. Additionally, LINC00474 RNA expression shows 6,023 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight ESCA, and STAD as cancer lineages where LINC00474 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 LINC00474 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LINC00474 survival associations across molecular data types. LINC00474 RNA expression shows survival associations in the most cancer types (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LINC00474 RNA expression–survival associations across cancer types. High LINC00474 expression shows unfavorable associations in ESCA, KIRC, LUAD, UCS, COAD and SKCM. The ESCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .008). Together, the overview and detailed table identify ESCA as the clearest survival context for LINC00474 RNA expression.
This table shows molecular features associated with LINC00474 in patient tissues and cancer cell lines. In patient samples, LINC00474 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, LINC00474 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and NCI60_ALL.
