Q-omics provides the consensus-scored ERBIN profile across patient tissues and cancer cell-line models. ERBIN expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ERBIN is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, ERBIN RNA expression shows 21,196 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, LIHC, and ACC as cancer lineages where ERBIN 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 ERBIN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERBIN survival associations across molecular data types. ERBIN RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) 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 ERBIN RNA expression–survival associations across cancer types. High ERBIN expression shows unfavorable associations in MESO, LGG and PAAD, but favorable associations in KIRC, HNSC and SCLC. The KIRC 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 KIRC as the clearest survival context for ERBIN RNA expression.
This table summarizes ERBIN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 9. The strongest signals are observed in LIHC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ERBIN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERBIN shows lower tumor expression in COAD and READ and higher tumor expression in LIHC, BRCA, LUAD and CHOL. The LIHC box plot shows higher ERBIN RNA expression in tumor versus normal tissue (log2 FC = +0.687, t-test p < 0.001).
This table shows molecular features associated with ERBIN in patient tissues and cancer cell lines. In patient samples, ERBIN shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ERBIN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and SOFT_TISSUE.
