Q-omics provides the consensus-scored BAG6 profile across patient tissues and cancer cell-line models. BAG6 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, BAG6 is differentially expressed in 14, with the highest sampling consensus in LIHC. Additionally, BAG6 RNA expression shows 19,032 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, LIHC, and ACC as cancer lineages where BAG6 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 BAG6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BAG6 survival associations across molecular data types. BAG6 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (10) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BAG6 RNA expression–survival associations across cancer types. High BAG6 expression shows unfavorable associations in LIHC, MESO, SARC, COAD and ACC, but favorable associations in KIRC. 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 BAG6 RNA expression.
This table summarizes BAG6 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 5. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for BAG6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BAG6 shows lower tumor expression in KICH and higher tumor expression in LIHC, KIRC, STAD, HNSC and BRCA. The LIHC box plot shows higher BAG6 RNA expression in tumor versus normal tissue (log2 FC = +1.352, t-test p < 0.001).
This table shows molecular features associated with BAG6 in patient tissues and cancer cell lines. In patient samples, BAG6 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, BAG6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
