Q-omics provides the consensus-scored GRID2IP profile across patient tissues and cancer cell-line models. GRID2IP expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, GRID2IP is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, GRID2IP RNA expression shows 19,806 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight COAD, KIRC, and THYM as cancer lineages where GRID2IP 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 GRID2IP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GRID2IP survival associations across molecular data types. GRID2IP RNA expression shows survival associations in the most cancer types (21), 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 GRID2IP RNA expression–survival associations across cancer types. High GRID2IP expression shows unfavorable associations in COAD, ACC and UCEC, but favorable associations in HNSC, SCLC and LUAD. The COAD 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 COAD as the clearest survival context for GRID2IP RNA expression.
This table summarizes GRID2IP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for GRID2IP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GRID2IP shows lower tumor expression in KIRC, KICH and HNSC and higher tumor expression in LUAD, COAD and CHOL. The KIRC box plot shows higher GRID2IP RNA expression in normal versus tumor tissue (log2 FC = −0.410, t-test p < 0.001).
This table shows molecular features associated with GRID2IP in patient tissues and cancer cell lines. In patient samples, GRID2IP shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, GRID2IP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
