Q-omics provides the consensus-scored HERC2 profile across patient tissues and cancer cell-line models. HERC2 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, HERC2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, HERC2 protein abundance shows 21,990 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, HNSC, and PDAC as cancer lineages where HERC2 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 HERC2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HERC2 survival associations across molecular data types. HERC2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (13) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HERC2 RNA expression–survival associations across cancer types. High HERC2 expression shows unfavorable associations in ACC, KICH and UVM, but favorable associations in SCLC, KIRC and HNSC. 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 HERC2 RNA expression.
This table summarizes HERC2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HERC2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HERC2 shows lower tumor expression in THCA and BRCA and higher tumor expression in HNSC, LIHC, LUSC and CHOL. The HNSC box plot shows higher HERC2 RNA expression in tumor versus normal tissue (log2 FC = +0.569, t-test p < 0.001).
This table shows molecular features associated with HERC2 in patient tissues and cancer cell lines. In patient samples, HERC2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, HERC2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Lymphoma.
