Q-omics provides the consensus-scored GCKR profile across patient tissues and cancer cell-line models. GCKR expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GCKR is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, GCKR RNA expression shows 11,786 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRC, LIHC, and ESCA as cancer lineages where GCKR 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 GCKR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GCKR survival associations across molecular data types. GCKR RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GCKR RNA expression–survival associations across cancer types. High GCKR expression shows unfavorable associations in KIRC, KIRP, CESC, GBM, LAML and SCLC. The KIRC 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 KIRC as the clearest survival context for GCKR RNA expression.
This table summarizes GCKR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 4. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for GCKR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GCKR shows lower tumor expression in LIHC and KICH and higher tumor expression in THCA, COAD, KIRP and LUAD. The LIHC box plot shows higher GCKR RNA expression in normal versus tumor tissue (log2 FC = −1.637, t-test p < 0.001).
This table shows molecular features associated with GCKR in patient tissues and cancer cell lines. In patient samples, GCKR shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, GCKR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
