Q-omics provides the consensus-scored GUCY2EP profile across patient tissues and cancer cell-line models. GUCY2EP expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, GUCY2EP is differentially expressed in 6, with the highest sampling consensus in KIRP. Additionally, GUCY2EP RNA expression shows 6,895 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight SKCM, KIRP, and STAD as cancer lineages where GUCY2EP 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 GUCY2EP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GUCY2EP survival associations across molecular data types. GUCY2EP RNA expression shows survival associations in the most cancer types (19). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GUCY2EP RNA expression–survival associations across cancer types. High GUCY2EP expression shows unfavorable associations in SKCM, BLCA, KIRC, KIRP, COAD and LAML. The SKCM 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 SKCM as the clearest survival context for GUCY2EP RNA expression.
This table summarizes GUCY2EP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in KIRP for RNA.
This table ranks reproducible tumor–normal expression differences for GUCY2EP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GUCY2EP shows higher tumor expression in KIRP, LIHC, HNSC, THCA, LUSC and LUAD. The KIRP box plot shows higher GUCY2EP RNA expression in tumor versus normal tissue (log2 FC = +0.838, t-test p < 0.001).
This table shows molecular features associated with GUCY2EP in patient tissues and cancer cell lines. In patient samples, GUCY2EP shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, GUCY2EP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BONE.
