Q-omics provides the consensus-scored GBF1 profile across patient tissues and cancer cell-line models. GBF1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, GBF1 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, GBF1 RNA expression shows 19,952 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where GBF1 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 GBF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GBF1 survival associations across molecular data types. GBF1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GBF1 RNA expression–survival associations across cancer types. High GBF1 expression shows unfavorable associations in ACC, BLCA and OV, but favorable associations in SCLC, UCS and LGG. The ACC 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 ACC as the clearest survival context for GBF1 RNA expression.
This table summarizes GBF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for GBF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GBF1 shows lower tumor expression in KIRC and COAD and higher tumor expression in LIHC, HNSC, BRCA and STAD. The LIHC box plot shows higher GBF1 RNA expression in tumor versus normal tissue (log2 FC = +1.325, t-test p < 0.001).
This table shows molecular features associated with GBF1 in patient tissues and cancer cell lines. In patient samples, GBF1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, GBF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Lymphoma.
