Q-omics provides the consensus-scored GATAD2B profile across patient tissues and cancer cell-line models. GATAD2B expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, GATAD2B is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, GATAD2B protein abundance shows 28,689 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where GATAD2B 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 GATAD2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GATAD2B survival associations across molecular data types. GATAD2B RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) 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 GATAD2B RNA expression–survival associations across cancer types. High GATAD2B expression shows unfavorable associations in ACC and KIRP, but favorable associations in HNSC, GBM, KIRC and LUAD. The ACC 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 ACC as the clearest survival context for GATAD2B RNA expression.
This table summarizes GATAD2B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for GATAD2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GATAD2B shows higher tumor expression in HNSC, LIHC, COAD, BRCA, LUSC and CHOL. The HNSC box plot shows higher GATAD2B RNA expression in tumor versus normal tissue (log2 FC = +0.858, t-test p < 0.001).
This table shows molecular features associated with GATAD2B in patient tissues and cancer cell lines. In patient samples, GATAD2B shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, GATAD2B 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 CNS and BLOOD_Leukemia.
