Q-omics provides the consensus-scored SAG profile across patient tissues and cancer cell-line models. SAG 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, SAG is differentially expressed in 8, with the highest sampling consensus in COAD. Additionally, SAG RNA expression shows 6,943 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight KIRC, COAD, and STAD as cancer lineages where SAG 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 SAG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SAG survival associations across molecular data types. SAG RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SAG RNA expression–survival associations across cancer types. High SAG expression shows unfavorable associations in KIRC, ACC, COAD, LIHC and UVM, but favorable associations in BLCA. The KIRC 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 KIRC as the clearest survival context for SAG RNA expression.
This table summarizes SAG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 1. The strongest signals are observed in LUSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SAG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SAG shows lower tumor expression in COAD, LUSC, KICH and LUAD and higher tumor expression in KIRC and BRCA. The COAD box plot shows higher SAG RNA expression in normal versus tumor tissue (log2 FC = −0.020, t-test p < 0.001).
This table shows molecular features associated with SAG in patient tissues and cancer cell lines. In patient samples, SAG shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, SAG 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 BREAST and BONE.
