Q-omics provides the consensus-scored SCAP profile across patient tissues and cancer cell-line models. SCAP expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SCAP is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, SCAP RNA expression shows 19,674 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, KIRC, and ACC as cancer lineages where SCAP 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 SCAP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCAP survival associations across molecular data types. SCAP RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCAP RNA expression–survival associations across cancer types. High SCAP expression shows unfavorable associations in ACC, KICH and LUAD, but favorable associations in UVM, THYM and COAD. The UVM 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 UVM as the clearest survival context for SCAP RNA expression.
This table summarizes SCAP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for SCAP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCAP shows lower tumor expression in KIRC and BRCA and higher tumor expression in LIHC, STAD, CHOL and BLCA. The KIRC box plot shows higher SCAP RNA expression in normal versus tumor tissue (log2 FC = −0.882, t-test p < 0.001).
This table shows molecular features associated with SCAP in patient tissues and cancer cell lines. In patient samples, SCAP 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, SCAP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
