G protein nucleolar 2Genealiases: HUMAUANTIG · NGP1 · Ngp-1 · Nog2 · Nug2
Q-omics provides the consensus-scored GNL2 profile across patient tissues and cancer cell-line models. GNL2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, GNL2 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, GNL2 protein abundance shows 27,558 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRP, KIRC, and LSCC as cancer lineages where GNL2 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 GNL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GNL2 survival associations across molecular data types. GNL2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GNL2 RNA expression–survival associations across cancer types. High GNL2 expression shows unfavorable associations in KIRP, ACC, LIHC, LGG, KICH and PAAD. The KIRP 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 KIRP as the clearest survival context for GNL2 RNA expression.
This table summarizes GNL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GNL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GNL2 shows higher tumor expression in KIRC, BLCA, STAD, LIHC, HNSC and COAD. The KIRC box plot shows higher GNL2 RNA expression in tumor versus normal tissue (log2 FC = +0.817, t-test p < 0.001).
This table shows molecular features associated with GNL2 in patient tissues and cancer cell lines. In patient samples, GNL2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, GNL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
