Q-omics provides the consensus-scored PNN profile across patient tissues and cancer cell-line models. PNN expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PNN is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PNN protein abundance shows 36,696 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where PNN 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 PNN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PNN survival associations across molecular data types. PNN RNA expression shows survival associations in the most cancer types (27), followed by mutation status (6) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PNN RNA expression–survival associations across cancer types. High PNN expression shows unfavorable associations in ACC, LIHC, KICH and COAD, but favorable associations in BRCA and UCS. 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 PNN RNA expression.
This table summarizes PNN 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 10. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PNN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PNN shows lower tumor expression in THCA and higher tumor expression in HNSC, COAD, STAD, LUSC and LIHC. The HNSC box plot shows higher PNN RNA expression in tumor versus normal tissue (log2 FC = +0.853, t-test p < 0.001).
This table shows molecular features associated with PNN in patient tissues and cancer cell lines. In patient samples, PNN 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, PNN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
