protein phosphatase, Mg2+/Mn2+ dependent 1LGenealiases: PP2C-epsilon · PP2CE · PPM1-LIKE
Q-omics provides the consensus-scored PPM1L profile across patient tissues and cancer cell-line models. PPM1L expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PPM1L is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, PPM1L RNA expression shows 20,578 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, BLCA, and GBM as cancer lineages where PPM1L 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 PPM1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PPM1L survival associations across molecular data types. PPM1L RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PPM1L RNA expression–survival associations across cancer types. High PPM1L expression shows favorable associations in KIRC, ACC, LGG, LUSC, SCLC and HNSC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for PPM1L RNA expression.
This table summarizes PPM1L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PPM1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PPM1L shows lower tumor expression in BLCA, THCA, HNSC, READ and BRCA and higher tumor expression in LIHC. The BLCA box plot shows higher PPM1L RNA expression in normal versus tumor tissue (log2 FC = −2.178, t-test p < 0.001).
This table shows molecular features associated with PPM1L in patient tissues and cancer cell lines. In patient samples, PPM1L 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, PPM1L 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 BLOOD_Myeloma and BLOOD_Leukemia.
