Q-omics provides the consensus-scored BAALC profile across patient tissues and cancer cell-line models. BAALC expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, BAALC is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, BAALC RNA expression shows 16,977 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight BLCA, COAD, and UVM as cancer lineages where BAALC 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 BAALC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BAALC survival associations across molecular data types. BAALC RNA expression shows survival associations in the most cancer types (26), 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 BAALC RNA expression–survival associations across cancer types. High BAALC expression shows unfavorable associations in BLCA, UVM and UCS, but favorable associations in SKCM, LGG and THCA. The BLCA 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 BLCA as the clearest survival context for BAALC RNA expression.
This table summarizes BAALC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 2. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for BAALC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BAALC shows lower tumor expression in COAD, KIRP, LUAD and UCEC and higher tumor expression in HNSC and KICH. The COAD box plot shows higher BAALC RNA expression in normal versus tumor tissue (log2 FC = −0.976, t-test p < 0.001).
This table shows molecular features associated with BAALC in patient tissues and cancer cell lines. In patient samples, BAALC shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, BAALC 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 SKIN.
