Q-omics provides the consensus-scored BATF profile across patient tissues and cancer cell-line models. BATF expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, BATF is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, BATF RNA expression shows 21,138 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRC, and GBM as cancer lineages where BATF 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 BATF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BATF survival associations across molecular data types. BATF RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) 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 BATF RNA expression–survival associations across cancer types. High BATF expression shows unfavorable associations in ACC and UVM, but favorable associations in HNSC, UCEC, BLCA and CESC. The HNSC 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 HNSC as the clearest survival context for BATF RNA expression.
This table summarizes BATF 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 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for BATF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BATF shows higher tumor expression in KIRC, COAD, STAD, KIRP, LUAD and BRCA. The KIRC box plot shows higher BATF RNA expression in tumor versus normal tissue (log2 FC = +2.625, t-test p < 0.001).
This table shows molecular features associated with BATF in patient tissues and cancer cell lines. In patient samples, BATF 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, BATF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Lymphoma.
