Q-omics provides the consensus-scored YY1AP1 profile across patient tissues and cancer cell-line models. YY1AP1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, YY1AP1 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, YY1AP1 RNA expression shows 20,176 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where YY1AP1 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 YY1AP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YY1AP1 survival associations across molecular data types. YY1AP1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (11) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YY1AP1 RNA expression–survival associations across cancer types. High YY1AP1 expression shows unfavorable associations in ACC, KICH, KIRP and LIHC, but favorable associations in UVM 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 YY1AP1 RNA expression.
This table summarizes YY1AP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 2. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for YY1AP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YY1AP1 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, BRCA and LUSC. The HNSC box plot shows higher YY1AP1 RNA expression in tumor versus normal tissue (log2 FC = +0.530, t-test p < 0.001).
This table shows molecular features associated with YY1AP1 in patient tissues and cancer cell lines. In patient samples, YY1AP1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, YY1AP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and SOFT_TISSUE.
