Q-omics provides the consensus-scored PRKD3 profile across patient tissues and cancer cell-line models. PRKD3 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PRKD3 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, PRKD3 RNA expression shows 20,305 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight ACC, HNSC, and KIRP as cancer lineages where PRKD3 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 PRKD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRKD3 survival associations across molecular data types. PRKD3 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRKD3 RNA expression–survival associations across cancer types. High PRKD3 expression shows unfavorable associations in ACC, LIHC, KICH and LGG, but favorable associations in KIRC and COAD. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for PRKD3 RNA expression.
This table summarizes PRKD3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PRKD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRKD3 shows lower tumor expression in KICH, THCA and BRCA and higher tumor expression in HNSC, LIHC and CHOL. The HNSC box plot shows higher PRKD3 RNA expression in tumor versus normal tissue (log2 FC = +0.644, t-test p < 0.001).
This table shows molecular features associated with PRKD3 in patient tissues and cancer cell lines. In patient samples, PRKD3 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, PRKD3 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 UPPER_AERODIGESTIVE_TRACT.
