Q-omics provides the consensus-scored PPM1E profile across patient tissues and cancer cell-line models. PPM1E expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PPM1E is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, PPM1E RNA expression shows 19,496 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and KIRC as cancer lineages where PPM1E 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 PPM1E — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPM1E survival associations across molecular data types. PPM1E RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) 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 PPM1E RNA expression–survival associations across cancer types. High PPM1E expression shows unfavorable associations in UVM, ACC, STAD, THCA and KIRP, but favorable associations in PAAD. The UVM 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 UVM as the clearest survival context for PPM1E RNA expression.
This table summarizes PPM1E tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PPM1E. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPM1E shows lower tumor expression in KIRC, COAD, READ and LUSC and higher tumor expression in BRCA and PRAD. The KIRC box plot shows higher PPM1E RNA expression in normal versus tumor tissue (log2 FC = −1.278, t-test p < 0.001).
This table shows molecular features associated with PPM1E in patient tissues and cancer cell lines. In patient samples, PPM1E shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, PPM1E RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
