Q-omics provides the consensus-scored YY1 profile across patient tissues and cancer cell-line models. YY1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, YY1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, YY1 protein abundance shows 27,124 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where YY1 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 YY1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YY1 survival associations across molecular data types. YY1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YY1 RNA expression–survival associations across cancer types. High YY1 expression shows unfavorable associations in ACC, KIRP, LIHC and UVM, but favorable associations in KIRC and THYM. 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 YY1 RNA expression.
This table summarizes YY1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for YY1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YY1 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, STAD, LUSC and BLCA. The HNSC box plot shows higher YY1 RNA expression in tumor versus normal tissue (log2 FC = +0.945, t-test p < 0.001).
This table shows molecular features associated with YY1 in patient tissues and cancer cell lines. In patient samples, YY1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, YY1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
