Q-omics provides the consensus-scored ERCC8 profile across patient tissues and cancer cell-line models. ERCC8 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, ERCC8 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, ERCC8 protein abundance shows 27,467 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight MESO, HNSC, and LUAD as cancer lineages where ERCC8 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 ERCC8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERCC8 survival associations across molecular data types. ERCC8 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ERCC8 RNA expression–survival associations across cancer types. High ERCC8 expression shows unfavorable associations in MESO, KICH, LIHC, STAD and UVM, but favorable associations in KIRC. The MESO 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 MESO as the clearest survival context for ERCC8 RNA expression.
This table summarizes ERCC8 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 11. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ERCC8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERCC8 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, LUAD, COAD and BLCA. The HNSC box plot shows higher ERCC8 RNA expression in tumor versus normal tissue (log2 FC = +0.544, t-test p < 0.001).
This table shows molecular features associated with ERCC8 in patient tissues and cancer cell lines. In patient samples, ERCC8 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, ERCC8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
