Q-omics provides the consensus-scored RNY4 profile across patient tissues and cancer cell-line models. RNY4 expression is associated with patient survival in 11 of 34 cancer types, with the highest sampling consensus in CHOL. Among the 18 cancer types available for tumor–normal comparison, RNY4 is differentially expressed in 2, with the highest sampling consensus in STAD. Additionally, RNY4 RNA expression shows 5,694 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight CHOL, STAD, and ESCA as cancer lineages where RNY4 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 RNY4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RNY4 survival associations across molecular data types. RNY4 RNA expression shows survival associations in the most cancer types (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RNY4 RNA expression–survival associations across cancer types. High RNY4 expression shows unfavorable associations in CHOL, THCA, LUSC, KIRP and PCPG, but favorable associations in LUAD. The CHOL 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 CHOL as the clearest survival context for RNY4 RNA expression.
This table summarizes RNY4 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 STAD for RNA.
This table ranks reproducible tumor–normal expression differences for RNY4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RNY4 shows lower tumor expression in STAD and KICH. The STAD box plot shows higher RNY4 RNA expression in normal versus tumor tissue (log2 FC = −0.856, t-test p = .023).
This table shows molecular features associated with RNY4 in patient tissues and cancer cell lines. In patient samples, RNY4 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set.
