Q-omics provides the consensus-scored GBP4 profile across patient tissues and cancer cell-line models. GBP4 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, GBP4 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, GBP4 RNA expression shows 18,105 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, KIRC, and UVM as cancer lineages where GBP4 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 GBP4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GBP4 survival associations across molecular data types. GBP4 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (8) 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 GBP4 RNA expression–survival associations across cancer types. High GBP4 expression shows unfavorable associations in KIRP and UVM, but favorable associations in SKCM, KIRC, BRCA and OV. 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 GBP4 RNA expression.
This table summarizes GBP4 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GBP4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GBP4 shows lower tumor expression in LUAD, KICH, LUSC and KIRP and higher tumor expression in KIRC and STAD. The KIRC box plot shows higher GBP4 RNA expression in tumor versus normal tissue (log2 FC = +1.378, t-test p < 0.001).
This table shows molecular features associated with GBP4 in patient tissues and cancer cell lines. In patient samples, GBP4 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, GBP4 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 OESOPHAGUS and BLOOD_Lymphoma.
