Q-omics provides the consensus-scored GCG profile across patient tissues and cancer cell-line models. GCG expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GCG is differentially expressed in 4, with the highest sampling consensus in COAD. Additionally, GCG protein abundance shows 15,232 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, COAD, and GBM as cancer lineages where GCG 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 GCG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GCG survival associations across molecular data types. GCG RNA expression shows survival associations in the most cancer types (18), followed by mutation status (3) 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 GCG RNA expression–survival associations across cancer types. High GCG expression shows unfavorable associations in KIRC, KIRP, UCEC, UVM and OV, but favorable associations in SCLC. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .006). Together, the overview and detailed table identify KIRC as the clearest survival context for GCG RNA expression.
This table summarizes GCG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 4, while mass-spec protein shows differences in 6. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for GCG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GCG shows lower tumor expression in COAD, READ and STAD and higher tumor expression in LUAD. The COAD box plot shows higher GCG RNA expression in normal versus tumor tissue (log2 FC = −4.450, t-test p < 0.001).
This table shows molecular features associated with GCG in patient tissues and cancer cell lines. In patient samples, GCG 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, GCG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in OVARY and URINARY_TRACT.
