Q-omics provides the consensus-scored GATA6 profile across patient tissues and cancer cell-line models. GATA6 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, GATA6 is differentially expressed in 13, with the highest sampling consensus in BLCA. Additionally, GATA6 RNA expression shows 17,879 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and BLCA as cancer lineages where GATA6 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 GATA6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GATA6 survival associations across molecular data types. GATA6 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GATA6 RNA expression–survival associations across cancer types. High GATA6 expression shows unfavorable associations in UVM, KIRP, HNSC, COAD and OV, but favorable associations in MESO. 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 GATA6 RNA expression.
This table summarizes GATA6 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 LUAD for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for GATA6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GATA6 shows lower tumor expression in BLCA, LUAD, KICH, LUSC and UCEC and higher tumor expression in HNSC. The BLCA box plot shows higher GATA6 RNA expression in normal versus tumor tissue (log2 FC = −3.757, t-test p < 0.001).
This table shows molecular features associated with GATA6 in patient tissues and cancer cell lines. In patient samples, GATA6 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, GATA6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BONE and SKIN.
