Q-omics provides the consensus-scored STIMATE profile across patient tissues and cancer cell-line models. STIMATE expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, STIMATE is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, STIMATE RNA expression shows 18,123 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, KIRC, and UVM as cancer lineages where STIMATE 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 STIMATE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes STIMATE survival associations across molecular data types. STIMATE RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible STIMATE RNA expression–survival associations across cancer types. High STIMATE expression shows unfavorable associations in ACC, KICH, LGG and LUSC, but favorable associations in LUAD and KIRC. 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 STIMATE RNA expression.
This table summarizes STIMATE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for STIMATE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. STIMATE shows lower tumor expression in KIRC, KIRP and LUAD and higher tumor expression in LIHC, COAD and HNSC. The KIRC box plot shows higher STIMATE RNA expression in normal versus tumor tissue (log2 FC = −0.385, t-test p < 0.001).
This table shows molecular features associated with STIMATE in patient tissues and cancer cell lines. In patient samples, STIMATE 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, STIMATE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
