Q-omics provides the consensus-scored EIF4HP1 profile across patient tissues and cancer cell-line models. EIF4HP1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, EIF4HP1 is differentially expressed in 8, with the highest sampling consensus in COAD. Additionally, EIF4HP1 RNA expression shows 18,389 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, COAD, and ACC as cancer lineages where EIF4HP1 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 EIF4HP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF4HP1 survival associations across molecular data types. EIF4HP1 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 EIF4HP1 RNA expression–survival associations across cancer types. High EIF4HP1 expression shows unfavorable associations in PAAD, UVM, LGG and MESO, but favorable associations in KIRC and UCS. The KIRC 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 KIRC as the clearest survival context for EIF4HP1 RNA expression.
This table summarizes EIF4HP1 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 COAD for RNA.
This table ranks reproducible tumor–normal expression differences for EIF4HP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF4HP1 shows lower tumor expression in THCA and higher tumor expression in COAD, LUSC, HNSC, CHOL and LIHC. The COAD box plot shows higher EIF4HP1 RNA expression in tumor versus normal tissue (log2 FC = +0.609, t-test p < 0.001).
This table shows molecular features associated with EIF4HP1 in patient tissues and cancer cell lines. In patient samples, EIF4HP1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set.
