Q-omics provides the consensus-scored GSN profile across patient tissues and cancer cell-line models. GSN expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, GSN is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, GSN protein abundance shows 30,495 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight BLCA, and PDAC as cancer lineages where GSN 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 GSN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GSN survival associations across molecular data types. GSN RNA expression shows survival associations in the most cancer types (28), followed by mutation status (4) 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 GSN RNA expression–survival associations across cancer types. High GSN expression shows unfavorable associations in BLCA and LGG, but favorable associations in KIRC, UCEC, CESC and DLBC. The BLCA 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 BLCA as the clearest survival context for GSN RNA expression.
This table summarizes GSN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GSN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GSN shows lower tumor expression in BLCA, COAD, LUAD, READ and KIRP and higher tumor expression in LIHC. The BLCA box plot shows higher GSN RNA expression in normal versus tumor tissue (log2 FC = −3.378, t-test p < 0.001).
This table shows molecular features associated with GSN in patient tissues and cancer cell lines. In patient samples, GSN shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, GSN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BONE.
