Q-omics provides the consensus-scored DENND2D profile across patient tissues and cancer cell-line models. DENND2D expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, DENND2D is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, DENND2D protein abundance shows 20,941 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, BLCA, and LSCC as cancer lineages where DENND2D 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 DENND2D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DENND2D survival associations across molecular data types. DENND2D RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) 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 DENND2D RNA expression–survival associations across cancer types. High DENND2D expression shows unfavorable associations in LGG and GBM, but favorable associations in HNSC, BLCA, ESCA and SKCM. The HNSC 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 HNSC as the clearest survival context for DENND2D RNA expression.
This table summarizes DENND2D 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 LUSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for DENND2D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DENND2D shows lower tumor expression in LUSC and higher tumor expression in BLCA, BRCA, THCA, KIRC and CHOL. The BLCA box plot shows higher DENND2D RNA expression in tumor versus normal tissue (log2 FC = +1.478, t-test p = .008).
This table shows molecular features associated with DENND2D in patient tissues and cancer cell lines. In patient samples, DENND2D 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, DENND2D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BREAST.
