G protein subunit beta 2Genealiases: HG2C1 · NEDHYDF · SSS4 · SSS4; NEDHYDF
Q-omics provides the consensus-scored GNB2 profile across patient tissues and cancer cell-line models. GNB2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, GNB2 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, GNB2 protein abundance shows 30,326 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KICH, COAD, and PDAC as cancer lineages where GNB2 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 GNB2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GNB2 survival associations across molecular data types. GNB2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GNB2 RNA expression–survival associations across cancer types. High GNB2 expression shows unfavorable associations in KICH, ACC, LGG, UCS, READ and UVM. The KICH 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 KICH as the clearest survival context for GNB2 RNA expression.
This table summarizes GNB2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in COAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for GNB2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GNB2 shows higher tumor expression in COAD, KIRC, LIHC, THCA, HNSC and KIRP. The COAD box plot shows higher GNB2 RNA expression in tumor versus normal tissue (log2 FC = +0.761, t-test p < 0.001).
This table shows molecular features associated with GNB2 in patient tissues and cancer cell lines. In patient samples, GNB2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, GNB2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and CNS.
