Q-omics provides the consensus-scored EBI3 profile across patient tissues and cancer cell-line models. EBI3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, EBI3 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, EBI3 RNA expression shows 17,829 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, KIRC, and GBM as cancer lineages where EBI3 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 EBI3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EBI3 survival associations across molecular data types. EBI3 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EBI3 RNA expression–survival associations across cancer types. High EBI3 expression shows unfavorable associations in UVM and LUSC, but favorable associations in SKCM, HNSC, SCLC and LUAD. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for EBI3 RNA expression.
This table summarizes EBI3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for EBI3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EBI3 shows lower tumor expression in COAD and higher tumor expression in KIRC, THCA, KIRP, STAD and ESCA. The KIRC box plot shows higher EBI3 RNA expression in tumor versus normal tissue (log2 FC = +2.280, t-test p < 0.001).
This table shows molecular features associated with EBI3 in patient tissues and cancer cell lines. In patient samples, EBI3 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, EBI3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
