Q-omics provides the consensus-scored EFR3A profile across patient tissues and cancer cell-line models. EFR3A expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, EFR3A is differentially expressed in 7, with the highest sampling consensus in HNSC. Additionally, EFR3A protein abundance shows 20,505 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, HNSC, and PDAC as cancer lineages where EFR3A 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 EFR3A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EFR3A survival associations across molecular data types. EFR3A RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EFR3A RNA expression–survival associations across cancer types. High EFR3A expression shows unfavorable associations in UVM, CESC, BLCA and KICH, but favorable associations in KIRC and ESCA. The UVM 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 UVM as the clearest survival context for EFR3A RNA expression.
This table summarizes EFR3A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EFR3A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EFR3A shows lower tumor expression in UCEC and higher tumor expression in HNSC, LIHC, BRCA, LUAD and CHOL. The HNSC box plot shows higher EFR3A RNA expression in tumor versus normal tissue (log2 FC = +1.077, t-test p < 0.001).
This table shows molecular features associated with EFR3A in patient tissues and cancer cell lines. In patient samples, EFR3A 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, EFR3A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and SOFT_TISSUE.
