Q-omics provides the consensus-scored EIF4G2 profile across patient tissues and cancer cell-line models. EIF4G2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, EIF4G2 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, EIF4G2 RNA expression shows 19,136 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, LIHC, and ACC as cancer lineages where EIF4G2 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 EIF4G2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF4G2 survival associations across molecular data types. EIF4G2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 EIF4G2 RNA expression–survival associations across cancer types. High EIF4G2 expression shows unfavorable associations in MESO, LIHC, BLCA, ACC and PAAD, but favorable associations in KIRC. The MESO 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 MESO as the clearest survival context for EIF4G2 RNA expression.
This table summarizes EIF4G2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 8. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for EIF4G2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF4G2 shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, HNSC, BRCA and CHOL. The LIHC box plot shows higher EIF4G2 RNA expression in tumor versus normal tissue (log2 FC = +0.861, t-test p < 0.001).
This table shows molecular features associated with EIF4G2 in patient tissues and cancer cell lines. In patient samples, EIF4G2 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, EIF4G2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
