Q-omics provides the consensus-scored BATF3 profile across patient tissues and cancer cell-line models. BATF3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, BATF3 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, BATF3 RNA expression shows 16,722 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and KIRC as cancer lineages where BATF3 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 BATF3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BATF3 survival associations across molecular data types. BATF3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) 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 BATF3 RNA expression–survival associations across cancer types. High BATF3 expression shows unfavorable associations in UVM, KIRP, KIRC, MESO and LGG, but favorable associations in SKCM. The UVM 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 UVM as the clearest survival context for BATF3 RNA expression.
This table summarizes BATF3 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 COAD for protein.
This table ranks reproducible tumor–normal expression differences for BATF3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BATF3 shows lower tumor expression in KICH, LUSC and BRCA and higher tumor expression in KIRC, THCA and HNSC. The KIRC box plot shows higher BATF3 RNA expression in tumor versus normal tissue (log2 FC = +1.246, t-test p < 0.001).
This table shows molecular features associated with BATF3 in patient tissues and cancer cell lines. In patient samples, BATF3 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, BATF3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and STOMACH.
