Q-omics provides the consensus-scored HERC2P8 profile across patient tissues and cancer cell-line models. HERC2P8 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, HERC2P8 is differentially expressed in 5, with the highest sampling consensus in LIHC. Additionally, HERC2P8 RNA expression shows 12,616 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UVM, LIHC, and TGCT as cancer lineages where HERC2P8 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 HERC2P8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HERC2P8 survival associations across molecular data types. HERC2P8 RNA expression shows survival associations in the most cancer types (19). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HERC2P8 RNA expression–survival associations across cancer types. High HERC2P8 expression shows unfavorable associations in UVM, COAD, ACC, CHOL and KICH, but favorable associations in READ. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify UVM as the clearest survival context for HERC2P8 RNA expression.
This table summarizes HERC2P8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for HERC2P8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HERC2P8 shows lower tumor expression in UCEC and higher tumor expression in LIHC, READ, KIRP and HNSC. The LIHC box plot shows higher HERC2P8 RNA expression in tumor versus normal tissue (log2 FC = +0.012, t-test p = .001).
This table shows molecular features associated with HERC2P8 in patient tissues and cancer cell lines. In patient samples, HERC2P8 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set.
