Q-omics provides the consensus-scored PENK profile across patient tissues and cancer cell-line models. PENK expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, PENK is differentially expressed in 12, with the highest sampling consensus in LUAD. Additionally, PENK protein abundance shows 10,850 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCS, LUAD, and GBM as cancer lineages where PENK 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 PENK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PENK survival associations across molecular data types. PENK RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PENK RNA expression–survival associations across cancer types. High PENK expression shows unfavorable associations in UVM and BLCA, but favorable associations in UCS, HNSC, KICH and LUAD. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify UCS as the clearest survival context for PENK RNA expression.
This table summarizes PENK tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 1. The strongest signals are observed in LUAD for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PENK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PENK shows lower tumor expression in LUAD, BRCA, UCEC, BLCA, HNSC and KIRP. The LUAD box plot shows higher PENK RNA expression in normal versus tumor tissue (log2 FC = −1.304, t-test p < 0.001).
This table shows molecular features associated with PENK in patient tissues and cancer cell lines. In patient samples, PENK 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, PENK RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BONE.
