Q-omics provides the consensus-scored GGNBP2 profile across patient tissues and cancer cell-line models. GGNBP2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GGNBP2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, GGNBP2 RNA expression shows 20,829 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where GGNBP2 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 GGNBP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GGNBP2 survival associations across molecular data types. GGNBP2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GGNBP2 RNA expression–survival associations across cancer types. High GGNBP2 expression shows unfavorable associations in ACC, LIHC, KIRP, UVM and HNSC, but favorable associations in KIRC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for GGNBP2 RNA expression.
This table summarizes GGNBP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for GGNBP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GGNBP2 shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, LIHC, STAD and CHOL. The HNSC box plot shows higher GGNBP2 RNA expression in tumor versus normal tissue (log2 FC = +0.560, t-test p < 0.001).
This table shows molecular features associated with GGNBP2 in patient tissues and cancer cell lines. In patient samples, GGNBP2 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, GGNBP2 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 LARGE_INTESTINE.
