Q-omics provides the consensus-scored RNY4P10 profile across patient tissues and cancer cell-line models. RNY4P10 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RNY4P10 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, RNY4P10 RNA expression shows 16,783 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, HNSC, and UVM as cancer lineages where RNY4P10 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 RNY4P10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RNY4P10 survival associations across molecular data types. RNY4P10 RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RNY4P10 RNA expression–survival associations across cancer types. High RNY4P10 expression shows unfavorable associations in ACC, UCEC and KIRC, but favorable associations in BLCA, READ and UCS. The ACC 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 ACC as the clearest survival context for RNY4P10 RNA expression.
This table summarizes RNY4P10 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 HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for RNY4P10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RNY4P10 shows lower tumor expression in BRCA and higher tumor expression in HNSC, KIRC, LIHC, BLCA and COAD. The HNSC box plot shows higher RNY4P10 RNA expression in tumor versus normal tissue (log2 FC = +0.742, t-test p < 0.001).
This table shows molecular features associated with RNY4P10 in patient tissues and cancer cell lines. In patient samples, RNY4P10 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set.
