Q-omics provides the consensus-scored PDXP profile across patient tissues and cancer cell-line models. PDXP expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PDXP is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PDXP protein abundance shows 25,996 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where PDXP 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 PDXP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDXP survival associations across molecular data types. PDXP RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PDXP RNA expression–survival associations across cancer types. High PDXP expression shows unfavorable associations in ACC, KICH, CESC and KIRP, but favorable associations in UCS and STAD. 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 PDXP RNA expression.
This table summarizes PDXP 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 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PDXP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDXP shows higher tumor expression in HNSC, LUAD, LUSC, BRCA, BLCA and KIRC. The HNSC box plot shows higher PDXP RNA expression in tumor versus normal tissue (log2 FC = +0.713, t-test p < 0.001).
This table shows molecular features associated with PDXP in patient tissues and cancer cell lines. In patient samples, PDXP shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, PDXP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
