Q-omics provides the consensus-scored GBX1 profile across patient tissues and cancer cell-line models. GBX1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in DLBC. Among the 18 cancer types available for tumor–normal comparison, GBX1 is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, GBX1 RNA expression shows 9,961 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight DLBC, KICH, and THYM as cancer lineages where GBX1 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 GBX1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GBX1 survival associations across molecular data types. GBX1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GBX1 RNA expression–survival associations across cancer types. High GBX1 expression shows unfavorable associations in DLBC, KICH, LGG, READ and ACC, but favorable associations in CESC. The DLBC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .006). Together, the overview and detailed table identify DLBC as the clearest survival context for GBX1 RNA expression.
This table summarizes GBX1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for GBX1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GBX1 shows lower tumor expression in LUSC and higher tumor expression in KICH, UCEC, BLCA, KIRC and LIHC. The KICH box plot shows higher GBX1 RNA expression in tumor versus normal tissue (log2 FC = +0.026, t-test p = .008).
This table shows molecular features associated with GBX1 in patient tissues and cancer cell lines. In patient samples, GBX1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, GBX1 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 LARGE_INTESTINE.
