Q-omics provides the consensus-scored GSR profile across patient tissues and cancer cell-line models. GSR expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, GSR is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, GSR protein abundance shows 22,380 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, and GBM as cancer lineages where GSR 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 GSR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GSR survival associations across molecular data types. GSR RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GSR RNA expression–survival associations across cancer types. High GSR expression shows unfavorable associations in LIHC, KICH, LGG and UCS, but favorable associations in SCLC and COAD. The LIHC 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 LIHC as the clearest survival context for GSR RNA expression.
This table summarizes GSR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 7. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for GSR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GSR shows lower tumor expression in KIRC and higher tumor expression in LIHC, UCEC, BRCA, KIRP and CHOL. The LIHC box plot shows higher GSR RNA expression in tumor versus normal tissue (log2 FC = +0.646, t-test p < 0.001).
This table shows molecular features associated with GSR in patient tissues and cancer cell lines. In patient samples, GSR 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, GSR 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 BLOOD_Lymphoma and BONE.
