Q-omics provides the consensus-scored CADPS profile across patient tissues and cancer cell-line models. CADPS expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, CADPS is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, CADPS protein abundance shows 16,173 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SCLC, COAD, and GBM as cancer lineages where CADPS 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 CADPS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CADPS survival associations across molecular data types. CADPS RNA expression shows survival associations in the most cancer types (27), followed by mutation status (8) 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 CADPS RNA expression–survival associations across cancer types. High CADPS expression shows unfavorable associations in BLCA, THCA, MESO and STAD, but favorable associations in SCLC and CESC. The SCLC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify SCLC as the clearest survival context for CADPS RNA expression.
This table summarizes CADPS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in COAD for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for CADPS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CADPS shows lower tumor expression in LUSC and higher tumor expression in COAD, BRCA, KIRP, CHOL and READ. The COAD box plot shows higher CADPS RNA expression in tumor versus normal tissue (log2 FC = +1.443, t-test p < 0.001).
This table shows molecular features associated with CADPS in patient tissues and cancer cell lines. In patient samples, CADPS shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CADPS 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 LUNG_NSCLC_LUAD and BLOOD_Lymphoma.
