Q-omics provides the consensus-scored SATB2 profile across patient tissues and cancer cell-line models. SATB2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SATB2 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, SATB2 RNA expression shows 19,244 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where SATB2 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 SATB2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SATB2 survival associations across molecular data types. SATB2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SATB2 RNA expression–survival associations across cancer types. High SATB2 expression shows unfavorable associations in MESO, UVM, THCA and BLCA, but favorable associations in KIRC and KIRP. 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 SATB2 RNA expression.
This table summarizes SATB2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SATB2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SATB2 shows lower tumor expression in COAD and KICH and higher tumor expression in HNSC, STAD, KIRP and LIHC. The HNSC box plot shows higher SATB2 RNA expression in tumor versus normal tissue (log2 FC = +0.915, t-test p < 0.001).
This table shows molecular features associated with SATB2 in patient tissues and cancer cell lines. In patient samples, SATB2 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, SATB2 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 CNS and UPPER_AERODIGESTIVE_TRACT.
