Q-omics provides the consensus-scored DLST profile across patient tissues and cancer cell-line models. DLST expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, DLST is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, DLST protein abundance shows 20,241 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where DLST 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 DLST — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DLST survival associations across molecular data types. DLST RNA expression shows survival associations in the most cancer types (20), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DLST RNA expression–survival associations across cancer types. High DLST expression shows unfavorable associations in UVM, HNSC and LUSC, but favorable associations in KIRC, UCS and KIRP. The UVM 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 UVM as the clearest survival context for DLST RNA expression.
This table summarizes DLST 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DLST. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DLST shows lower tumor expression in KIRC, BRCA, COAD and BLCA and higher tumor expression in HNSC and CHOL. The KIRC box plot shows higher DLST RNA expression in normal versus tumor tissue (log2 FC = −1.018, t-test p < 0.001).
This table shows molecular features associated with DLST in patient tissues and cancer cell lines. In patient samples, DLST 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, DLST RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
