lncRNA negative regulator of fibroblast-like synoviocyte migration, SYNCRIP interactingGenealiases: []
Q-omics provides the consensus-scored LERFS profile across patient tissues and cancer cell-line models. LERFS expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, LERFS is differentially expressed in 2, with the highest sampling consensus in KICH. Additionally, LERFS RNA expression shows 4,590 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight LUAD, KICH, and STAD as cancer lineages where LERFS 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 LERFS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LERFS survival associations across molecular data types. LERFS RNA expression shows survival associations in the most cancer types (25). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LERFS RNA expression–survival associations across cancer types. High LERFS expression shows unfavorable associations in LUAD, ACC, UCS and PRAD, but favorable associations in PAAD and LIHC. The LUAD 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 LUAD as the clearest survival context for LERFS RNA expression.
This table summarizes LERFS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for LERFS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LERFS shows lower tumor expression in KICH and higher tumor expression in BLCA. The KICH box plot shows higher LERFS RNA expression in normal versus tumor tissue (log2 FC = −0.101, t-test p = .002).
This table shows molecular features associated with LERFS in patient tissues and cancer cell lines. In patient samples, LERFS shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set.
