Q-omics provides the consensus-scored PNPO profile across patient tissues and cancer cell-line models. PNPO expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PNPO is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, PNPO protein abundance shows 29,029 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight UVM, BLCA, and HNSC as cancer lineages where PNPO 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 PNPO — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PNPO survival associations across molecular data types. PNPO RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) 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 PNPO RNA expression–survival associations across cancer types. High PNPO expression shows unfavorable associations in UVM, LAML and LUSC, but favorable associations in KIRC, BRCA and LIHC. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify UVM as the clearest survival context for PNPO RNA expression.
This table summarizes PNPO 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 10. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PNPO. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PNPO shows lower tumor expression in THCA, KIRC and KICH and higher tumor expression in BLCA, COAD and LUAD. The BLCA box plot shows higher PNPO RNA expression in tumor versus normal tissue (log2 FC = +0.959, t-test p < 0.001).
This table shows molecular features associated with PNPO in patient tissues and cancer cell lines. In patient samples, PNPO 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, PNPO RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
