Q-omics provides the consensus-scored EIF4HP2 profile across patient tissues and cancer cell-line models. EIF4HP2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, EIF4HP2 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, EIF4HP2 RNA expression shows 16,645 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight BLCA, KIRC, and UVM as cancer lineages where EIF4HP2 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 EIF4HP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF4HP2 survival associations across molecular data types. EIF4HP2 RNA expression shows survival associations in the most cancer types (26). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EIF4HP2 RNA expression–survival associations across cancer types. High EIF4HP2 expression shows unfavorable associations in LIHC, COAD, KIRC and LUAD, but favorable associations in BLCA and UCS. The BLCA 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 BLCA as the clearest survival context for EIF4HP2 RNA expression.
This table summarizes EIF4HP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for EIF4HP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF4HP2 shows lower tumor expression in KIRC and higher tumor expression in COAD, LIHC, HNSC, LUAD and UCEC. The KIRC box plot shows higher EIF4HP2 RNA expression in normal versus tumor tissue (log2 FC = −0.450, t-test p < 0.001).
This table shows molecular features associated with EIF4HP2 in patient tissues and cancer cell lines. In patient samples, EIF4HP2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set.
