Q-omics provides the consensus-scored PYGL profile across patient tissues and cancer cell-line models. PYGL expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PYGL is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, PYGL protein abundance shows 25,722 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRC, and GBM as cancer lineages where PYGL 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 PYGL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PYGL survival associations across molecular data types. PYGL RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PYGL RNA expression–survival associations across cancer types. High PYGL expression shows unfavorable associations in HNSC, LGG, PAAD, UCS, LUAD and STAD. The HNSC 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 HNSC as the clearest survival context for PYGL RNA expression.
This table summarizes PYGL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PYGL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PYGL shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, BLCA, KIRP and LUSC. The KIRC box plot shows higher PYGL RNA expression in tumor versus normal tissue (log2 FC = +2.328, t-test p < 0.001).
This table shows molecular features associated with PYGL in patient tissues and cancer cell lines. In patient samples, PYGL 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, PYGL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
