Q-omics provides the consensus-scored PNP profile across patient tissues and cancer cell-line models. PNP expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PNP is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, PNP protein abundance shows 24,141 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, KIRC, and HNSC as cancer lineages where PNP 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 PNP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PNP survival associations across molecular data types. PNP RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PNP RNA expression–survival associations across cancer types. High PNP expression shows unfavorable associations in ACC, UVM, LIHC, UCS, HNSC and MESO. 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 PNP RNA expression.
This table summarizes PNP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PNP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PNP shows lower tumor expression in KIRC, KICH and KIRP and higher tumor expression in THCA, HNSC and COAD. The KIRC box plot shows higher PNP RNA expression in normal versus tumor tissue (log2 FC = −1.444, t-test p < 0.001).
This table shows molecular features associated with PNP in patient tissues and cancer cell lines. In patient samples, PNP shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, PNP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in BONE and UPPER_AERODIGESTIVE_TRACT.
