Q-omics provides the consensus-scored RNF8 profile across patient tissues and cancer cell-line models. RNF8 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, RNF8 is differentially expressed in 17, with the highest sampling consensus in COAD. Additionally, RNF8 RNA expression shows 19,592 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, COAD, and ACC as cancer lineages where RNF8 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 RNF8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RNF8 survival associations across molecular data types. RNF8 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RNF8 RNA expression–survival associations across cancer types. High RNF8 expression shows unfavorable associations in LIHC, ACC, SARC and PRAD, but favorable associations in KIRC and LUSC. The LIHC 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 LIHC as the clearest survival context for RNF8 RNA expression.
This table summarizes RNF8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 1. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RNF8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RNF8 shows lower tumor expression in KICH and higher tumor expression in COAD, LIHC, HNSC, UCEC and BLCA. The COAD box plot shows higher RNF8 RNA expression in tumor versus normal tissue (log2 FC = +0.759, t-test p < 0.001).
This table shows molecular features associated with RNF8 in patient tissues and cancer cell lines. In patient samples, RNF8 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, RNF8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
