Q-omics provides the consensus-scored CGB1 profile across patient tissues and cancer cell-line models. CGB1 expression is associated with patient survival in 9 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CGB1 is differentially expressed in 1, with the highest sampling consensus in UCEC. Additionally, CGB1 RNA expression shows 3,150 significant pathway-activity associations, with the highest sampling consensus in UCEC. Together, these results highlight ACC, and UCEC as cancer lineages where CGB1 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 CGB1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CGB1 survival associations across molecular data types. CGB1 RNA expression shows survival associations in the most cancer types (9), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CGB1 RNA expression–survival associations across cancer types. High CGB1 expression shows unfavorable associations in ACC, HNSC, BRCA, MESO, GBM and BLCA. 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 CGB1 RNA expression.
This table summarizes CGB1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1. The strongest signals are observed in UCEC for RNA.
This table ranks reproducible tumor–normal expression differences for CGB1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CGB1 shows higher tumor expression in UCEC. The UCEC box plot shows higher CGB1 RNA expression in tumor versus normal tissue (log2 FC = +0.041, t-test p = .021).
This table shows molecular features associated with CGB1 in patient tissues and cancer cell lines. In patient samples, CGB1 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, CGB1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and LARGE_INTESTINE.
