Q-omics provides the consensus-scored PDZK1P1 profile across patient tissues and cancer cell-line models. PDZK1P1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PDZK1P1 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, PDZK1P1 RNA expression shows 19,193 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, LIHC, and UVM as cancer lineages where PDZK1P1 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 PDZK1P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDZK1P1 survival associations across molecular data types. PDZK1P1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PDZK1P1 RNA expression–survival associations across cancer types. High PDZK1P1 expression shows unfavorable associations in ACC and KIRC, but favorable associations in HNSC, UCS, SKCM and BRCA. 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 PDZK1P1 RNA expression.
This table summarizes PDZK1P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for PDZK1P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDZK1P1 shows lower tumor expression in KICH and higher tumor expression in LIHC, HNSC, STAD, CHOL and COAD. The LIHC box plot shows higher PDZK1P1 RNA expression in tumor versus normal tissue (log2 FC = +0.160, t-test p < 0.001).
This table shows molecular features associated with PDZK1P1 in patient tissues and cancer cell lines. In patient samples, PDZK1P1 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, PDZK1P1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in CNS.
