Q-omics provides the consensus-scored HERC2P9 profile across patient tissues and cancer cell-line models. HERC2P9 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, HERC2P9 is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, HERC2P9 RNA expression shows 20,203 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, THCA, and UVM as cancer lineages where HERC2P9 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 HERC2P9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HERC2P9 survival associations across molecular data types. HERC2P9 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HERC2P9 RNA expression–survival associations across cancer types. High HERC2P9 expression shows unfavorable associations in KIRC, ACC, UVM and KICH, but favorable associations in HNSC and SKCM. The KIRC 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 KIRC as the clearest survival context for HERC2P9 RNA expression.
This table summarizes HERC2P9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for HERC2P9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HERC2P9 shows lower tumor expression in THCA, BRCA, KICH and LUAD and higher tumor expression in LIHC and COAD. The THCA box plot shows higher HERC2P9 RNA expression in normal versus tumor tissue (log2 FC = −0.309, t-test p < 0.001).
This table shows molecular features associated with HERC2P9 in patient tissues and cancer cell lines. In patient samples, HERC2P9 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, HERC2P9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST.
