Q-omics provides the consensus-scored GBP3 profile across patient tissues and cancer cell-line models. GBP3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, GBP3 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, GBP3 RNA expression shows 18,461 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, KICH, and UVM as cancer lineages where GBP3 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 GBP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GBP3 survival associations across molecular data types. GBP3 RNA expression shows survival associations in the most cancer types (22), 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 GBP3 RNA expression–survival associations across cancer types. High GBP3 expression shows unfavorable associations in LGG, LUSC, THYM and HNSC, but favorable associations in SKCM and KIRC. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for GBP3 RNA expression.
This table summarizes GBP3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GBP3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GBP3 shows lower tumor expression in KICH, LUSC and COAD and higher tumor expression in THCA, KIRC and BRCA. The KICH box plot shows higher GBP3 RNA expression in normal versus tumor tissue (log2 FC = −2.894, t-test p < 0.001).
This table shows molecular features associated with GBP3 in patient tissues and cancer cell lines. In patient samples, GBP3 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, GBP3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
