Q-omics provides the consensus-scored BCL9L profile across patient tissues and cancer cell-line models. BCL9L expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, BCL9L is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, BCL9L RNA expression shows 20,167 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight BLCA, HNSC, and ACC as cancer lineages where BCL9L 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 BCL9L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BCL9L survival associations across molecular data types. BCL9L RNA expression shows survival associations in the most cancer types (30), followed by mutation status (6) 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 BCL9L RNA expression–survival associations across cancer types. High BCL9L expression shows unfavorable associations in BLCA, PAAD, UVM and LUAD, but favorable associations in UCS and KIRC. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify BLCA as the clearest survival context for BCL9L RNA expression.
This table summarizes BCL9L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for BCL9L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BCL9L shows higher tumor expression in HNSC, KIRC, LIHC, COAD, KIRP and STAD. The HNSC box plot shows higher BCL9L RNA expression in tumor versus normal tissue (log2 FC = +1.035, t-test p < 0.001).
This table shows molecular features associated with BCL9L in patient tissues and cancer cell lines. In patient samples, BCL9L 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, BCL9L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
