Q-omics provides the consensus-scored GNS profile across patient tissues and cancer cell-line models. GNS expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, GNS is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, GNS RNA expression shows 19,752 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight MESO, HNSC, and THYM as cancer lineages where GNS 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 GNS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GNS survival associations across molecular data types. GNS RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) 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 GNS RNA expression–survival associations across cancer types. High GNS expression shows unfavorable associations in MESO, LUSC, LGG, LIHC, KICH and UVM. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify MESO as the clearest survival context for GNS RNA expression.
This table summarizes GNS 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 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GNS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GNS shows lower tumor expression in THCA, KICH and LUSC and higher tumor expression in HNSC, LIHC and STAD. The HNSC box plot shows higher GNS RNA expression in tumor versus normal tissue (log2 FC = +1.314, t-test p < 0.001).
This table shows molecular features associated with GNS in patient tissues and cancer cell lines. In patient samples, GNS shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, GNS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
