Q-omics provides the consensus-scored GPAM profile across patient tissues and cancer cell-line models. GPAM expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GPAM is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, GPAM RNA expression shows 20,198 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, and UVM as cancer lineages where GPAM 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 GPAM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GPAM survival associations across molecular data types. GPAM RNA expression shows survival associations in the most cancer types (22), 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 GPAM RNA expression–survival associations across cancer types. High GPAM expression shows unfavorable associations in CHOL, CESC and MESO, but favorable associations in KIRC, LUAD and UCS. The KIRC 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 KIRC as the clearest survival context for GPAM RNA expression.
This table summarizes GPAM tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for GPAM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GPAM shows lower tumor expression in KIRC, BRCA, THCA and CHOL and higher tumor expression in HNSC and BLCA. The KIRC box plot shows higher GPAM RNA expression in normal versus tumor tissue (log2 FC = −0.594, t-test p < 0.001).
This table shows molecular features associated with GPAM in patient tissues and cancer cell lines. In patient samples, GPAM 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, GPAM RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
