Q-omics provides the consensus-scored PYGM profile across patient tissues and cancer cell-line models. PYGM expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PYGM is differentially expressed in 17, with the highest sampling consensus in BLCA. Additionally, PYGM protein abundance shows 35,568 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRP, BLCA, and LUAD as cancer lineages where PYGM 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 PYGM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PYGM survival associations across molecular data types. PYGM RNA expression shows survival associations in the most cancer types (24), followed by mutation status (10) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PYGM RNA expression–survival associations across cancer types. High PYGM expression shows unfavorable associations in KIRP, UVM, COAD, LUSC and READ, but favorable associations in KIRC. The KIRP 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 KIRP as the clearest survival context for PYGM RNA expression.
This table summarizes PYGM tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 11. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PYGM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PYGM shows lower tumor expression in BLCA, THCA, COAD, LUAD, KIRP and KICH. The BLCA box plot shows higher PYGM RNA expression in normal versus tumor tissue (log2 FC = −5.080, t-test p < 0.001).
This table shows molecular features associated with PYGM in patient tissues and cancer cell lines. In patient samples, PYGM shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, PYGM RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_SCLC.
