Q-omics provides the consensus-scored DSP profile across patient tissues and cancer cell-line models. DSP expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, DSP is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, DSP protein abundance shows 24,514 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight BLCA, KIRC, and LSCC as cancer lineages where DSP 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 DSP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DSP survival associations across molecular data types. DSP RNA expression shows survival associations in the most cancer types (22), followed by mutation status (9) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DSP RNA expression–survival associations across cancer types. High DSP expression shows unfavorable associations in BLCA and ACC, but favorable associations in KIRC, LUSC, READ and PRAD. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify BLCA as the clearest survival context for DSP RNA expression.
This table summarizes DSP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for DSP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DSP shows lower tumor expression in KIRC and higher tumor expression in LUAD, BLCA, LUSC, LIHC and UCEC. The KIRC box plot shows higher DSP RNA expression in normal versus tumor tissue (log2 FC = −1.971, t-test p < 0.001).
This table shows molecular features associated with DSP in patient tissues and cancer cell lines. In patient samples, DSP shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, DSP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_SCLC.
