eukaryotic translation initiation factor 3 subunit K pseudogene 2Genealiases: []
Q-omics provides the consensus-scored EIF3KP2 profile across patient tissues and cancer cell-line models. EIF3KP2 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in DLBC. Among the 18 cancer types available for tumor–normal comparison, EIF3KP2 is differentially expressed in 7, with the highest sampling consensus in KICH. Additionally, EIF3KP2 RNA expression shows 6,271 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight DLBC, KICH, and STAD as cancer lineages where EIF3KP2 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 EIF3KP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF3KP2 survival associations across molecular data types. EIF3KP2 RNA expression shows survival associations in the most cancer types (17). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EIF3KP2 RNA expression–survival associations across cancer types. High EIF3KP2 expression shows unfavorable associations in STAD, CESC and MESO, but favorable associations in DLBC, LUAD and ESCA. The DLBC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .007). Together, the overview and detailed table identify DLBC as the clearest survival context for EIF3KP2 RNA expression.
This table summarizes EIF3KP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for EIF3KP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF3KP2 shows lower tumor expression in LUAD, READ and LUSC and higher tumor expression in KICH, COAD and ESCA. The KICH box plot shows higher EIF3KP2 RNA expression in tumor versus normal tissue (log2 FC = +0.447, t-test p < 0.001).
This table shows molecular features associated with EIF3KP2 in patient tissues and cancer cell lines. In patient samples, EIF3KP2 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set.
