Q-omics provides the consensus-scored ERRFI1 profile across patient tissues and cancer cell-line models. ERRFI1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ERRFI1 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, ERRFI1 protein abundance shows 26,143 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KICH, and GBM as cancer lineages where ERRFI1 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 ERRFI1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERRFI1 survival associations across molecular data types. ERRFI1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ERRFI1 RNA expression–survival associations across cancer types. High ERRFI1 expression shows unfavorable associations in HNSC, STAD, LGG, LUSC and CESC, but favorable associations in LIHC. The HNSC 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 HNSC as the clearest survival context for ERRFI1 RNA expression.
This table summarizes ERRFI1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 11. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ERRFI1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERRFI1 shows lower tumor expression in KICH, BRCA, KIRP and LIHC and higher tumor expression in LUAD and KIRC. The KICH box plot shows higher ERRFI1 RNA expression in normal versus tumor tissue (log2 FC = −3.903, t-test p < 0.001).
This table shows molecular features associated with ERRFI1 in patient tissues and cancer cell lines. In patient samples, ERRFI1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ERRFI1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BONE.
