Q-omics provides the consensus-scored HERC2P3 profile across patient tissues and cancer cell-line models. HERC2P3 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, HERC2P3 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, HERC2P3 RNA expression shows 14,031 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ESCA, KIRC, and UVM as cancer lineages where HERC2P3 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 HERC2P3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HERC2P3 survival associations across molecular data types. HERC2P3 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HERC2P3 RNA expression–survival associations across cancer types. High HERC2P3 expression shows unfavorable associations in LUSC, THCA, STAD and CESC, but favorable associations in ESCA and SKCM. The ESCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify ESCA as the clearest survival context for HERC2P3 RNA expression.
This table summarizes HERC2P3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for HERC2P3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HERC2P3 shows lower tumor expression in KIRC, LUAD, BRCA and LUSC and higher tumor expression in LIHC and CHOL. The KIRC box plot shows higher HERC2P3 RNA expression in normal versus tumor tissue (log2 FC = −0.351, t-test p < 0.001).
This table shows molecular features associated with HERC2P3 in patient tissues and cancer cell lines. In patient samples, HERC2P3 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, HERC2P3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in CNS.
