Q-omics provides the consensus-scored DGKG profile across patient tissues and cancer cell-line models. DGKG expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, DGKG is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, DGKG RNA expression shows 16,781 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCEC, HNSC, and UVM as cancer lineages where DGKG 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 DGKG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DGKG survival associations across molecular data types. DGKG RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DGKG RNA expression–survival associations across cancer types. High DGKG expression shows unfavorable associations in UCEC, LIHC, HNSC, LUAD, KIRC and UVM. The UCEC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify UCEC as the clearest survival context for DGKG RNA expression.
This table summarizes DGKG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for DGKG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DGKG shows lower tumor expression in KICH, BLCA, THCA and UCEC and higher tumor expression in HNSC and KIRC. The HNSC box plot shows higher DGKG RNA expression in tumor versus normal tissue (log2 FC = +1.143, t-test p < 0.001).
This table shows molecular features associated with DGKG in patient tissues and cancer cell lines. In patient samples, DGKG 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, DGKG 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_NSCLC_LUAD and BLOOD_Leukemia.
