Q-omics provides the consensus-scored EFNB3 profile across patient tissues and cancer cell-line models. EFNB3 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EFNB3 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, EFNB3 RNA expression shows 17,716 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, KIRC, and TGCT as cancer lineages where EFNB3 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 EFNB3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EFNB3 survival associations across molecular data types. EFNB3 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EFNB3 RNA expression–survival associations across cancer types. High EFNB3 expression shows unfavorable associations in ACC, STAD and UCEC, but favorable associations in LAML, BRCA and SCLC. The ACC 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 ACC as the clearest survival context for EFNB3 RNA expression.
This table summarizes EFNB3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for EFNB3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EFNB3 shows lower tumor expression in KIRC, KICH, LIHC, BRCA and COAD and higher tumor expression in LUSC. The KIRC box plot shows higher EFNB3 RNA expression in normal versus tumor tissue (log2 FC = −1.110, t-test p < 0.001).
This table shows molecular features associated with EFNB3 in patient tissues and cancer cell lines. In patient samples, EFNB3 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, EFNB3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SKIN and SOFT_TISSUE.
