Q-omics provides the consensus-scored YY2 profile across patient tissues and cancer cell-line models. YY2 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, YY2 is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, YY2 RNA expression shows 20,156 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LGG, COAD, and UVM as cancer lineages where YY2 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 YY2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YY2 survival associations across molecular data types. YY2 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YY2 RNA expression–survival associations across cancer types. High YY2 expression shows unfavorable associations in LGG, KICH, HNSC, LUSC and KIRP, but favorable associations in COAD. The LGG 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 LGG as the clearest survival context for YY2 RNA expression.
This table summarizes YY2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for YY2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YY2 shows higher tumor expression in COAD, KIRP, KIRC, LUAD, HNSC and BLCA. The COAD box plot shows higher YY2 RNA expression in tumor versus normal tissue (log2 FC = +0.511, t-test p < 0.001).
This table shows molecular features associated with YY2 in patient tissues and cancer cell lines. In patient samples, YY2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, YY2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Lymphoma.
