Q-omics provides the consensus-scored CGB2 profile across patient tissues and cancer cell-line models. CGB2 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, CGB2 is differentially expressed in 3, with the highest sampling consensus in UCEC. Additionally, CGB2 RNA expression shows 5,236 significant pathway-activity associations, with the highest sampling consensus in HNSC. Together, these results highlight LIHC, UCEC, and HNSC as cancer lineages where CGB2 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 CGB2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CGB2 survival associations across molecular data types. CGB2 RNA expression shows survival associations in the most cancer types (17), 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 CGB2 RNA expression–survival associations across cancer types. High CGB2 expression shows unfavorable associations in LIHC, KIRC, ACC, THCA, STAD and MESO. The LIHC 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 LIHC as the clearest survival context for CGB2 RNA expression.
This table summarizes CGB2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3, while mass-spec protein shows differences in 1. The strongest signals are observed in LUSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CGB2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CGB2 shows higher tumor expression in UCEC, LUSC and LUAD. The UCEC box plot shows higher CGB2 RNA expression in tumor versus normal tissue (log2 FC = +0.247, t-test p = .005).
This table shows molecular features associated with CGB2 in patient tissues and cancer cell lines. In patient samples, CGB2 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, CGB2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma.
