Q-omics provides the consensus-scored EIF3IP1 profile across patient tissues and cancer cell-line models. EIF3IP1 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, EIF3IP1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, EIF3IP1 RNA expression shows 5,767 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight LIHC, HNSC, and STAD as cancer lineages where EIF3IP1 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 EIF3IP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF3IP1 survival associations across molecular data types. EIF3IP1 RNA expression shows survival associations in the most cancer types (16), 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 EIF3IP1 RNA expression–survival associations across cancer types. High EIF3IP1 expression shows unfavorable associations in LIHC, CHOL, UVM, STAD and LUSC, but favorable associations in KIRC. The LIHC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify LIHC as the clearest survival context for EIF3IP1 RNA expression.
This table summarizes EIF3IP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for EIF3IP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF3IP1 shows higher tumor expression in HNSC, COAD, KIRC, UCEC, BRCA and READ. The HNSC box plot shows higher EIF3IP1 RNA expression in tumor versus normal tissue (log2 FC = +0.037, t-test p = .003).
This table shows molecular features associated with EIF3IP1 in patient tissues and cancer cell lines. In patient samples, EIF3IP1 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set.
