Q-omics provides the consensus-scored PDZD3 profile across patient tissues and cancer cell-line models. PDZD3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, PDZD3 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, PDZD3 RNA expression shows 14,775 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight READ, KICH, and TGCT as cancer lineages where PDZD3 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 PDZD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDZD3 survival associations across molecular data types. PDZD3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PDZD3 RNA expression–survival associations across cancer types. High PDZD3 expression shows unfavorable associations in LUAD and LGG, but favorable associations in READ, KIRP, BLCA and UCS. The READ Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .004). Together, the overview and detailed table identify READ as the clearest survival context for PDZD3 RNA expression.
This table summarizes PDZD3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 1. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PDZD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDZD3 shows lower tumor expression in KICH, COAD, LUSC, BRCA, READ and UCEC. The KICH box plot shows higher PDZD3 RNA expression in normal versus tumor tissue (log2 FC = −2.663, t-test p < 0.001).
This table shows molecular features associated with PDZD3 in patient tissues and cancer cell lines. In patient samples, PDZD3 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PDZD3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
