Q-omics provides the consensus-scored DSEL profile across patient tissues and cancer cell-line models. DSEL 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, DSEL is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, DSEL RNA expression shows 18,578 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, COAD, and UVM as cancer lineages where DSEL 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 DSEL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DSEL survival associations across molecular data types. DSEL RNA expression shows survival associations in the most cancer types (23), followed by mutation status (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DSEL RNA expression–survival associations across cancer types. High DSEL expression shows unfavorable associations in BLCA, UCEC, THCA, LUSC and ACC, but favorable associations in KIRC. The KIRC 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 KIRC as the clearest survival context for DSEL RNA expression.
This table summarizes DSEL 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 1. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DSEL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DSEL shows lower tumor expression in COAD, THCA, UCEC, LUSC and BRCA and higher tumor expression in KIRC. The COAD box plot shows higher DSEL RNA expression in normal versus tumor tissue (log2 FC = −0.581, t-test p < 0.001).
This table shows molecular features associated with DSEL in patient tissues and cancer cell lines. In patient samples, DSEL 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, DSEL 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 LUNG_SCLC and CNS.
